Distance Learning Articles 1. Adding Up the Distance

2

2. Bridging the Gap: A Community College and Area High Schools Collaborate To Improve

Student Success in College 3. Is the Sky Still Falling?

6 23

4. Student Preferences, Satisfaction, and Perceived Learning in an Online Mathematics

Class

29

5. New Directions for Dual Enrollment: Creating Stronger Pathways from High School

through College

43

League for Innovation in the Community College

 

PLATO Learning Releases Results of Major Distance Learning Study

   

'Adding Up the Distance' study completed in conjunction with the League for Innovation in the Community College BLOOMINGTON, MINN. (June 26, 2000) - It is no secret that many students who enroll in college are unprepared for the academic rigors of college work. The overwhelming numbers indicate that nearly one-half, or 44 percent, of students entering 2-year colleges each year require some form of remediation. The number of students underprepared for college level work is amplified by the variety of developmental learners' needs. The needs and academic plans are clearly not the same for a 40-year-old woman returning to college for job development skills after being out of school for 22 years and an 18-year old high school student who goofed off in math class. Nor are they the same for a student who graduated from an inner-city high school that did not offer advanced algebra classes and a highly skilled math student whose native language is not English. Internet-based learning is increasingly utilized to help these students quickly get up to speed in their courses. In the spring of 1999, the League for Innovation in the Community College and PLATO Learning initiated a joint research project exploring the questions and challenges of implementing successful distance learning developmental math programs for community colleges across the country. Eight colleges participated in the study and the findings will be released at the Conference on Information Technology, Nov. 15-18 in Anaheim, Calif., as "Adding up the Distance: Critical Success Factors for Internet-based Learning in Developmental Mathematics." Each year, more than $1 billion is spent to provide remedial services to incoming community college students," said Dr. Rob Foshay, Vice President of Instructional Design and Cognitive Learning at PLATO Learning. "This research project focused on identifying how the Internet, distance learning techniques, and PLATO Learning can work together to more effectively serve the developmental needs of students. This is a significant step in PLATO's ongoing commitment to expand our Internet offerings. Our project partners are national leaders in postsecondary education and we are excited to have had the opportunity to work with them in this effort." According to Edward Leach, Vice President-Technology Programs at the League for Innovation: "The Internet has opened powerful new doors to education. The League is pleased to have participated in this project to further define the best practices for using online technologies to enhance student success in developmental mathematics." The project explored "critical success factors" for computer-based distance learning in developmental math programs during a summer trial implementation session and a full fall semester term. Mathematics was chosen because it is the

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League for Innovation in the Community College

subject area of perhaps widest need in developmental studies, and because its content and measures are relatively well defined. College participants, League research team members, and PLATO service teams worked together in four principal areas of investigation: Development of effective, individualized, open entry/open exit programs for developmental students via distance education. Cultivation of learners' motivation through the use of technology in developmental studies programs using distance education. Exploration of successful developmental student profiles using distance learning technology. Effective combinations of campus-based support service and distance learning delivery systems as models of success for developmental learners.

  The project began by exploring college administration, instructors, and students as independent variables of distance learning developmental math programs and continued with an investigation of best distance learning practices. Extensive data analysis allowed PLATO and League researchers to draw some conclusions about the interdependent relationship of college resources, instructors, and learners in successful distance learning models. The colleges that were most successful with students created a systemic and connected balance in their distance learning developmental math programs. According to the preliminary project results, the 10 factors that appeared to be most critical to success of these programs are summarized below and will be explained in greater detail within the final "Adding Up the Distance" report. Development of individualized, open entry/open exit, effective programs for developmental students via distance education. Beyond the traditional functions of student services and development of course objectives, distance learning services and curriculum should be enhanced to include a more comprehensive plan with the following variables. 1. Easy Access to Internet and Easy Navigational Courseware - Although the majority of students who enrolled in distance learning courses expressed high levels of comfort and expertise with computer-based applications, courseware that makes logon/logout functions and transition from lesson to lesson as smooth as possible was cited as a recognized benefit to successful students. 2. Technical Support - Over and over again technical support (via college helpdesk or program contact) reigned as the most important factor cited by both students and faculty to program success. 3. Alignment of Online Courseware and Course Objectives - Those programs that correlated course objectives with Internet courseware lessons in a meaningful way (whether as supplemental or primary content) and connected assignments and class activities had more successful outcomes than those programs who used the Internet courseware as a drill-and-practice exercise. 4. Individualized Instructional Format - Faculty who used the computeradaptive components of the Internet courseware management system and offered individualized and targeted assignments for students were recognized more favorably by students. Students and faculty noted the self-paced, individualized, any-time/any-place functions of distance learning as the best features of the project. Development of successful student profiles using distance learning

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League for Innovation in the Community College

technology. 5. Student Recruitment and Counseling - Proactive selection, preparation, and counseling with students entering distance learning programs were noted as key variables for success and course completion. Students who demonstrated a sense of motivation, time management, and program/academic goal were more successful in the project. 6. Orientation - Students who attended mandatory group orientations had few technical problems, experienced greater ease of navigation, and had successful program outcomes. Cultivation of learners' motivation through the use of technology in developmental studies programs using distance education. 7. Student Connections - Interactive and frequent contact was an important condition for success. Although many students appreciated the self-paced and individualized format of the Internet courseware, they were quick to note that when questions or issues were resolved via a Web page contact, email, or phone call, there were higher levels of satisfaction with the course and comfort level with technology. The successful programs in the study had structured assignment schedules with student contact requirements as part of course activities. Combination of campus-based support service and distance learning delivery systems as models of success for developmental learners. 8. Faculty Development - Faculty participants had varying levels of experience with technology and computer-based applications. Those colleges who offered more than five professional development opportunities correlated with faculty who were active in attending workshops and conferences. The faculty from these colleges created successful programs in this project. 9. High Standards of Quality and Content Development - As might be expected, faculty who had experience with distance learning had successful program outcomes, however in a few instances, faculty who were using distance learning as a developmental math option for the first time were also very successful. From the research data gathered, it is concluded that the "first-time successful faculty" showed great interest in computer-based applications and selfinitiated the learning curve of teaching with technology. Rather than tag on a few lessons with existing course assignments, they closely reviewed Internet courseware content and were actively involved in new curriculum development and content upgrade for their courses. They were also very active in seeking technical support and assistance from the PLATO helpdesk and their assigned PLATO educational consultant. 10. College Leadership & Program Support - Participating colleges that designated priority, support, and commitment of resources for technical investments to this project clearly saw successful responses from faculty and students. Although transparent in some instances, administrative support was recognized as clearing the way for successful implementation, program development, and student access leading to high quality services and learning opportunities for students. "Behind these critical success factors is the hard work, dedication to innovation, and commitment to learning shared by administrators, faculty, and student participants," said Dr. Foshay. "Although the project traced the ideas, progress, and outcomes of students over two short semesters, the need to expand and lead further research efforts in distance learning for developmental education should be part of the investment in our college, community, and country's future. If community colleges are to journey from the place-bound world of classrooms and

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League for Innovation in the Community College

computer-labs within campus walls to the anytime/anyplace expanse of distance learning, it is imperative that studies like these chart our course and guide our actions towards a destination of knowing," Dr. Foshay concluded. Participating Colleges The participating colleges included a considerable diversity of program structure and size. While all participating colleges had well-established campus-based developmental math programs, they had varying degrees of history and experience with technology in their developmental studies programs. The participants included: Central Florida Community College, Ocala, Florida Delta College, University Center, Michigan Kapiolani Community College, Honolulu, Hawaii Kirkwood Community College, Cedar Rapids, Iowa Moraine Valley Community College, Palos Hills, Illinois Miami-Dade Community College, Miami, Florida Santa Fe College, Gainesville, Florida Sinclair Community College, Dayton, Ohio League for Innovation in the Community College The League for Innovation in the Community College, as a nonprofit educational consortium of resourceful community colleges, stimulates experimentation and innovation in all areas of community college development and serves as a catalyst, project incubator, and experimental laboratory for all community colleges. The League for Innovation in the Community College headquarters are located at 4505 East Chandler Boulevard, Suite 250, Phoenix, Arizona 850487690. The telephone is (480) 705-8200. For more information, visit www.league.org. PLATO Learning With revenues of over $44 million, PLATO Learning, Inc. is a publicly held company traded as TUTR on the NASDAQ-NMS. Offering more than 2,000 hours and 10,000 learning objectives of comprehensive academic and applied skills courseware designed for adolescents and adults, PLATO Learning Systems are marketed to middle and high schools, colleges, job training programs, correctional institutions, military education programs, corporations, and consumers. PLATO is delivered via networks, CD-ROM, private intranets, and the Internet. An international training and education company, PLATO Learning's headquarters are located at 10801 Nesbitt Avenue South, Bloomington, Minnesota, 55437. Phone (952) 832-1000 or (800) 869-2000. PLATO Learning has domestic offices located throughout the United States, and international offices in the United Kingdom and throughout Canada. PLATO Learning has international distributors located in Puerto Rico, Singapore, South Africa, and the United Arab Emirates. The company's Web site address on the Internet's World Wide Web is www.plato.com. 

    HOME | SEARCH | SITE MAP | iStream | LEAGUE STORE | WEBMASTER League for Innovation in the Community College 4505 East Chandler Boulevard, Suite 250 · Phoenix, Arizona 85048 · Voice: (480) 705-8200 · Fax: (480) 705-8201 Copyright © 1995 - 2011 League for Innovation in the Community College. All rights reserved.

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This article was downloaded by: [University of Texas San Antonio] On: 06 December 2011, At: 09:23 Publisher: Routledge Informa Ltd Registered in England and Wales Registered Number: 1072954 Registered office: Mortimer House, 37-41 Mortimer Street, London W1T 3JH, UK

Community College Journal of Research and Practice Publication details, including instructions for authors and subscription information: http://www.tandfonline.com/loi/ucjc20

BRIDGING THE GAP: A COMMUNITY COLLEGE AND AREA HIGH SCHOOLS COLLABORATE TO IMPROVE STUDENT SUCCESS IN COLLEGE Laura Berry a

a

North Arkansas College, Harrison, Arkansas, USA

Available online: 15 Dec 2010

To cite this article: Laura Berry (2003): BRIDGING THE GAP: A COMMUNITY COLLEGE AND AREA HIGH SCHOOLS COLLABORATE TO IMPROVE STUDENT SUCCESS IN COLLEGE, Community College Journal of Research and Practice, 27:5, 393-407 To link to this article: http://dx.doi.org/10.1080/713838157

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for any loss, actions, claims, proceedings, demand, or costs or damages whatsoever or howsoever caused arising directly or indirectly in connection with or arising out of the use of this material.

Community College Journal of Research and Practice, 27: 393–407, 2003 Copyright # 2003 Taylor & Francis 1066-8926/03 $12.00 +.00 DOI: 10.1080/10668920390129004

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BRIDGING THE GAP: A COMMUNITY COLLEGE AND AREA HIGH SCHOOLS COLLABORATE TO IMPROVE STUDENT SUCCESS IN COLLEGE Laura Berry North Arkansas College, Harrison, Arkansas, USA

The Institutional Research Officer and Vice President of Student Services from North Arkansas College, and the Mathematics Facilitator at the local educational cooperative have initiated a tracking study to determine (1) if area students who take college preparatory math courses in high school place into, and succeed in, subsequent college-level math courses at North Arkansas College and (2) if area students who come to college for a degree have taken sufficient college preparatory coursework in high school. The study disclosed that (1) students who take a high school course more rigorous than Algebra 2 place into, and succeed in, College Algebra at a high rate, and (2) most students have not taken sufficient college preparatory coursework in math. The second, and more important part of the project, has been to bring college and high school personnel together to work on solutions.

College may not be for everyone, but it should be attainable for students who complete high school and have a view toward progressing to the next educational level. Instead, students with the ink barely dry on their high school diplomas enroll in college but find themselves back in high school level (or lower) remediation courses. What has gone wrong? National and regional studies help explain what is wrong by reminding us of what we knew all along — that rigorous high school curricula prepare students for college. Or as Jago (2000) states, ‘‘it’s the curriculum, stupid.’’ Studies consistently show that the quality of high school education overrides other factors in college success. Answers in the Toolbox (Adelman, 1999), a 15-year longitudinal study of the factors which affect college success, found that: Address correspondence to Laura Berry, Director of Institutional Research & Assessment, North Arkansas College, 1515 Pioneer Drive, Harrison, AR 72601. E-mail: [email protected]

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The association between degree completion and academic resources (high school curricula, test scores, and class rank) is much greater than the association between degree completion and socioeconomic status.
High school curriculum is consistently a better predictor of bachelor’s degree attainment than test scores or class rank=GPA.
Of all pre-college curricula, the highest level of mathematics one completes in secondary school has the strongest association with bachelor’s degree completion. For those who enter postsecondary education, having completed a course beyond the level of Algebra 2 more than doubles the odds of completing a bachelor’s degree.

The authors of The Condition of Education 2000 (U.S. Department of Education, 2000) have concluded that students with certain risk factors, such as low income or parents without postsecondary education, were less likely to persist in four-year college programs. But these risk factors only affected persistence for students who had not completed rigorous high school curricula. In an earlier report, Adelman (1996) concluded that ‘‘the extent of a student’s need for remediation is inversely related to his or her eventual completion of a degree.’’ Again, it’s the curriculum.

WHY DO WE CARE? Educational level is positively correlated with higher incomes (‘‘Family Income,’’ 2000), and educators in Arkansas are well aware of the economic consequences of low college attendance and lack of completion. As a low-income, low-education state with remediation rates hovering around 50%, Arkansas is tied for last among the states in bachelor’s degree completion (Chronicle of Higher Education, 2001, August) and has lost ground relative to the rest of the country during the 1990s (Johnston & Hardin, 2001). Measuring Up 2000 (2000) has awarded Arkansas a grade of D for its preparation for higher education, a D7 for participation in higher education, and a Dþ for higher education completion. The Arkansas Department of Higher Education estimates that if Arkansans had the average education and associated income of the U.S., state revenues and the budget could be from $2 to $7 billion more each year (Johnston & Hardin, 2001). Mortenson, a policy analyst with Postsecondary Education Opportunity, suggests that ‘‘the only thing more expensive than going to college is not going to college’’ (Mortenson, 2002).

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The statement applies to individuals, but states also suffer the consequences of a poorly educated populace. College-bound students are not the only ones who need remediation. The National Commission on the High School Senior Year (2001) concluded that ‘‘freshly minted high school graduates are equally unprepared for the literacy, computation, and problem-solving demands of the modern high performance workplace.’’ The Commission recommends that high schools stop functioning as ‘‘sorting machines’’ for college- and workforce-bound students.

REMEDIATION IN ARKANSAS Almost 60% of first-time freshmen who entered Arkansas public education in Fall 2001 were placed into remediation in at least one area, and 34% needed remediation in all three areas: math, English, and reading (Harrell, 2001, April). Two-year colleges bear a larger portion of the remedial load than do four-year institutions—in Fall 2001 69% of the cohort who entered two-year schools placed into math remediation, 50% placed into English remediation, and 39% into reading remediation (Harrell, 2001).

HISTORY OF THE STUDY North Arkansas College (Northark) is a comprehensive community college serving a five-county area in northwest Arkansas. Fall enrollment is typically 1,800 credit students, and about half of the first-time freshmen declare a transfer major. The Ozarks Unlimited Resources Cooperative (OUR Co-op) assists public school districts in roughly the same five-county area by providing them with shared educational programs and services. Both institutions reside in Harrison, population 12,000, one of the ‘‘100 Best Small Towns in America’’ (Crampton, 1993). In the Fall of 1999 the Director of Institutional Research at Northark, the Vice President of Student Services at Northark, and the Math Facilitator from the OUR Co-op began work on a plan to provide feedback to public school teachers about performance of their graduates in college. Specifically, they hoped to share information with local teachers about the success of recent high school graduates in math courses at Northark. Queried about their interest in such feedback, high school administrators and, especially, teachers responded enthusiastically to the project. That Fall the Northark Institutional Research Office (IR Office) analyzed high school transcript data for all May 1999 graduates of local schools who were enrolled at Northark.

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The transcript analysis focused on math courses taken in high school, primarily on factors such as the highest course completed, grades earned, and presence or absence of math during the senior year. Two questions were of primary concern: (1) Do students who take college preparatory math courses in high school place into, and succeed in, college math courses at Northark? Stated differently, do students place into remediation because they didn’t take the ‘‘right’’ courses in high school, or did they take the college preparatory courses yet still need remediation?; and, (2) Do students who come to college for a degree take sufficient college preparatory coursework in high school? The IR Office prepared summary reports for each school, carefully ensuring the anonymity of students, and shared the information with teachers and counselors during a late Fall Co-op meeting. The same office prepared a second report after the college recorded Fall grades and students began classes for the Spring semester. The IR Office continued to track this cohort of students through the summer and mailed a third report to counselors and teachers near the end of Summer 2000. Northark and the public school teachers continued to share information and hold discussions during the next two years. Northark math faculty reviewed the information released to high school personnel during the first two years and began meeting with high school faculty during the third year.

SAMPLE Each Fall’s sample consisted of first-time freshmen students at Northark who had graduated from any of the OUR Co-op secondary schools during the previous academic year. During the first three years of the study, transcript data were analyzed for 623 students from 22 high schools, 186 students in year one, 210 in year two, and 227 in year three. Each year a few students entered Northark as non-degree seekers and were not required to take a placement examination. These students were included in summary statistics of high school courses taken but were omitted from college follow-up.

STUDY VARIABLES The highest math course completed in high school was the primary independent variable in our research. The three values of this variable were above Algebra 2, Algebra 2, or below Algebra 2. The study

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considers Geometry of lower level than Algebra 2, and courses such as Advanced Math of higher level than Algebra 2. Assignment of math courses listed on the transcript was usually straightforward but occasionally required assistance from high school counselors or teachers or the OUR Co-op’s math facilitator. Table 1 shows math courses, as they appeared on high school transcripts, for the three years of the study. Courses shown in bold type were considered more advanced than Algebra 2. The study also considered students’ grades in the highest math course they completed. Because most high school courses are two semesters long, the IR Office averaged grades for both semesters using these conversions: A ¼ 4, B ¼ 3, C ¼ 2, D ¼ 1, and F ¼ 0. For example, a student who earned an A in semester one and B in semester two of high school Geometry would show a grade of 3.5 for the course. If a student completed only one semester of a course, the study used that grade. The dependent variables in the study were college math placement and college math success. Placement refers to placement into a ‘‘college-level’’ or ‘‘remedial’’ math course based on math ACT or Compass test scores. Northark requires all first-time degree seeking students to take one of these placement tests prior to enrollment. College Algebra is the first in the sequence of college level math courses. Although some certificate or Associate of Applied Science (A.A.S.) programs require math only as high as Intermediate Algebra, College Algebra is a requirement for Northark Associate of Arts (A.A.) and Associate of Science (A.S.) degrees. Therefore, this study assumes courses at a level lower than College Algebra to be remedial. From lowest to highest the

TABLE 1 High School Courses A-School Math Advanced Math Algebra A Algebra A-B Algebra B Algebra C-D Algebra Connections Algebra I Algebra II Algebra III Algebra Interact A DSC Algebra

Integrated Algebra A Integrated Algebra B Integrated Algebra I Intro. to Int. Algebra Business=Computer Math Calculus Applied Geometry College Prep Geometry Geometry Geometry A Geometry B Integrated Geometry Investigative Geometry

LC Math Math I Math Study Skills Math Technology I Math Technology II Math þ Pace Math Practical Math Resource Math SS Algebra I SS Algebra II Trigonometry

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sequence of Northark math courses is: Basic Math, Beginning Algebra, Intermediate Algebra, and College Algebra. Since progression to the next math class in the sequence requires a grade of at least C, as does transfer of the course, the study defined success in a college math course as a grade of A, B, or C. Other possible grades included D, F, or W (withdrew). A few students audited a math course; these students were omitted from computations of success versus failure.

ANALYSIS OF DATA The IR Office manually entered high school transcript data for each student and added placement data and other demographic data from the college’s student record system during the Fall semester and college math courses and grades at the beginning of the Spring semester. Analysis of data was to determine overall math placement of students, placement by highest high school math, and success in college math by highest math course. Another variable considered in the analysis was the grade earned in the highest high school math class. As a reminder, the intent of this project was to share information about high school coursework completed and subsequent placement and success at Northark. Northark and the OUR Co-op used this information to begin dialogue between high school and college faculties, not to develop a predictive model of college success.

FINDINGS Student Intent and Courses Over the three years of the study, 623 students entered Northark from local schools as first time freshmen. Fifty-seven percent of these students declared a transfer major (A.A. or A.S.), 21% pursued a two-year A.A.S. degree, and 15% were certificate seekers; the remainder did not declare a major (Table 2). Over half of the students (53%) completed Algebra 2 as their highest high school math course. Only 25% had completed a course more advanced than Algebra 2 (Table 3). It is reasonable to assume that transfer students, those intending to earn an A.A. or A.S., would have completed a more rigorous program of study in high school and so have better placement into college courses. There was some truth to this, although the percentage of transfer students who placed into college level math was still low. Table 4 shows that 33% of transfer students took a course more

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TABLE 2 Degree Intent of Entering Students Frequency

Percent

356 130 95 26 16 623

57.1 20.9 15.2 4.2 2.6 100.0

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AA or AS AAS Certificate Degree — undeclared Undeclared Total

TABLE 3 Highest High School Math Course of Entering Students

Above alg2 Alg2 Below alg2 Total

Frequency

Percent

158 329 136 623

25.4 52.8 21.8 100.0

advanced than Algebra 2, compared to 25% of A.A.S. students and only 4% of certificate-seeking students.

Placement Only 34% of students in the study placed into college level math (College Algebra) upon entering Northark. The good news is that 73% of students who completed a course higher than Algebra 2 placed into

TABLE 4 Highest High School Class by Degree Intent Highest high school class

Degree intent

AA or AS AAS Certificate Undeclared

Total

Above alg2

Alg2

Below alg2

Total

116 32.6% 33 25.4% 4 4.2% 5 11.9% 158 25.4%

206 57.9% 69 53.1% 33 34.7% 21 50.0% 329 52.8%

34 9.6% 28 21.5% 58 61.1% 16 38.1% 136 21.8%

356 100.0% 130 100.0% 95 100.0% 42 100.0% 623 100.0%

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TABLE 5 Math Placement by Highest High School Math Math placement

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Highest high school class

Above alg2 Alg2 Below alg2

Total

Placed in college level

Placed in remedial course

Total

114 73.1% 94 28.9% 1 .8% 209 34.3%

42 26.9% 231 71.1% 128 99.2% 401 65.7%

156 100.0% 325 100.0% 129 100.0% 610 100.0%

college-level math; in contrast, only 29% of those whose highest course was Algebra 2 placed into college level math (Table 5). Transfer students were more likely to place into college-level math (44%) than were A.A.S. (30%) or certificate students (8%), but the difference seems to result from the highest class taken rather than degree intent. There was no significant difference in placement of transfer students and A.A.S. students after controlling for the highest high school courses. Placement into college math is, however, only the first step. Success is the real goal. Over the three year period students who completed a course more advanced than Algebra 2 were much more likely than others to pass their first Northark math course, even when taking a remedial course. Table 6 shows success or failure of students who enrolled in a math course during their first semester. For example, 156 students completed a course higher than Algebra 2, and 114 of these placed into a college level math course. Eighty-six of the 114 enrolled in a math course during the fall, and 66 of these (77%) passed the course with an A, B, or C. Note that 78% of students who completed a course higher than Algebra 2 and then enrolled in a Northark math course during the first Fall successfully completed the course, whether remedial or college level; this means less time and money spent to repeat courses, and a higher likelihood of achieving their goal in college. In contrast, only 54% of students with an Algebra 2 background and 27% of students with less than an Algebra 2 background passed the math course they enrolled in the first Fall. These students started their college math

401

Table total

Highest high school class

Below alg2

Alg2

Above alg2

Group total

Group total Math placement

Math placement

Group total

Math placement

Placed in college level Placed in remedial course

Placed in college level Placed in remedial course

Placed in college level Placed in remedial course

241

21

21

55.3%

26.9%

27.3%

53.7%

51.4%

90 130

59.7%

40

77.6%

80.0%

24 90

76.7%

Row %

66

Count

Passed

193

55

54

1

112

85

27

26

6

20

Count

44.3%

70.5%

70.1%

100.0%

46.3%

48.6%

40.3%

22.4%

20.0%

23.3%

Row %

Did not pass

Semester 1 pass fail

TABLE 6 College Math Success by Highest High School Class and Placement

2

2

2

Count

.5%

2.6

2.6%

Row %

Audit

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436

78

77

1

242

175

67

116

30

86

Count

Group total

610

129

128

1

325

231

94

156

42

114

Count

Table total

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L. Berry

career from one to three semesters behind, and they have stayed behind. The opportunity gap between these students and others continues to widen.

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Grades This study focused on the relationship between curriculum and College Algebra placement and success, not on the impact of high school grades. Students who did what was necessary to earn a high grade in high school, whether in Algebra 2 or in a more advanced course, might be more likely to do what it takes to perform well in college. It is difficult to separate the effect of course grade from the effect of the work ethic of students, especially with 22 diverse high school grading policies. Still, grades provide some information about the likely success of students in college. The study found that: 1. High grades accompanied more advanced high school courses. Students who completed a course more advanced than Algebra 2 earned an average of 2.9 on a 4.0 scale in the class, while students who completed only as high as Algebra 2 averaged a course grade of 2.4. 2. High school grades seemed to make a difference in college placement for students whose highest high school class was Algebra 2 (Table 7). Students who placed into College Algebra from Algebra 2 had an average Algebra 2 grade of 2.9 on a 4.0 scale, well above average for the group of all Algebra 2 students. Students from the same group who placed into remediation averaged 2.3. The difference was significant at the alpha ¼ 0.05 level. Students who completed a class more advanced than Algebra 2 had little difference in grade average.

TABLE 7 Grades in Highest High School Class by Math Placement

Highest high school class

Above alg2

Math placement

Count

Mean

Placed in college level Placed in remedial course

114 41 155

2.9 2.7 2.9

Placed in college level Placed in remedial course

93 229 322

2.9 2.3 2.4

Group total Alg2

Math placement Group total

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TABLE 8 Grades in Highest High School Class by College Algebra Success

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Highest high school class

Count

Mean

Above alg2

Semester 1 pass fail Group total

Passed Did not pass

66 20 86

3.1 2.3 2.9

Alg2

Semester 1 pass fail Group total

Passed Did not pass

40 26 66

3.3 2.3 2.9

3. Regardless of the highest high school math taken, students who passed College Algebra the first semester had earned a higher average grade in high school math than those who did not pass (Table 8). A successful transition to college algebra seems to require more than just good high school grades. Seventy-nine percent of students who earned a 3.1 or higher (on a 4.0 scale) in an advanced math course placed into College Algebra, compared to only 51% of Algebra 2 students who earned a similar grade. The curriculum matters.

RESULTS OF COLLABORATION Pulling together faculty from the college and high schools proved more difficult than anticipated. The problems stemmed from logistics, not lack of interest. During the first two years of the project, the Director of Institutional Research, accompanied by the Vice President of Student Services, provided regular updates to the public school teachers during math workshops at the OUR Co-op. They planned a formal meeting between the two faculties, hosted by Northark, for the end of year two, but had to cancel due to scheduling conflicts and other complications. Because formal gatherings proved so difficult to arrange, college math faculty began attending the Co-op meetings in year three. At the end of the third year of the study, the IR Director met with the combined faculties to summarize results and offer answers to the two research questions. During these meetings high school teachers viewed College Algebra textbooks and course syllabi, and instructors with experience in secondary and college-level instruction described their perception of the obstacles students faced as they made the

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transition to college. In a meeting near the end of academic year 20012002, faculty discussed two main topics:

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1. measures that would encourage high school students to take a more rigorous math course curriculum, and 2. changes to create better articulation between Algebra 2 and college-level math. Some issues that affect these topics surfaced during the meeting and they, along with a summary of the discussion, follow: Issue 1: High school and college courses often use different grading criteria. For example, test grades constitute the majority of the College Algebra grade at Northark, while homework makes up most of the grade for many high school classes. Related to this issue, some high school teachers felt pressure from their administration to ‘‘pass’’ students. Discussion: Although some teachers felt pressured to pass students, many others had already fought this battle, and apparently had won. Most of these felt that administrators would support their grading criteria as long as course grades were, in general, a good reflection of standardized test scores. The OUR Co-op Math Facilitator proposed that the group develop a statement that suggests a more uniform grading standard with less weight given to homework; the statement would allow the group to speak with a united voice to area administrators. Issue 2: High school and college courses often use different criteria for ‘‘success.’’ Students can pass a high school course with a grade of D, but need a C in college level math to progress to the next course. Discussion: The group did not discuss changing the definition of a ‘‘passing’’ grade, but the study indicates that students who earned a D in their highest high school math course are ill-prepared for college math. Issue 3: Arkansas still requires only three years of high school math; many students have completed Algebra 2 by their junior year or earlier, and see no need for an additional math course during their senior year. Discussion: High school and college faculty agreed that students need a reason to take more math, and more rigorous math, during their senior year. Northark already offers dual credit courses such as College Algebra to high school students via a well-used distance education program. Some high schools, however, prefer to offer dual credit courses from their campus using qualified high school teachers. This option was discontinued because of problems with on-site dual credit

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courses in the past, but Northark is now working with area high schools to redevelop the program. Northark personnel suggested giving the Compass test during the sophomore or junior year so students will know if they are on track to enroll in college-level math. Also, many participants felt that the state should require students to complete four years of high school math. While this is a logical step, if schools continue to split a one-year course such as Algebra 1 into two one-year courses (Algebra A and B), then the change will be pointless. Issue 4: The senior year. Math is not the only problem during senior year, in which high school students may be in class only a few hours daily. Discussion: A required fourth year of math and enhanced dual credit opportunities may give students reasons to stay in the classroom. Schools can begin to implement recommendations such as those from the National Commission on the High School Senior Year to help students remain engaged with school. More problems were identified than were solved during the meeting. The OUR Co-op Math Facilitator hopes to develop a policy statement from the combined faculties to be given to administrators, and has asked the IR Director to present a summary of this project to high school administrators and superintendents. Northark hopes to provide at least one College Algebra textbook for each high school math teacher, and to allow high school faculty to take the math portion of the Compass test to gain a better idea of problems students face with placement tests.

CONCLUSIONS 1. Do students who take college preparatory math courses in high school place into and succeed in college math courses at Northark? Yes, as long as ‘‘college preparatory’’ is defined as a course more advanced than Algebra 2. 2. Do students who come to college for a degree take sufficient college preparatory coursework in high school? No. Only 25% of students tracked during the three years of this study had completed courses more advanced than Algebra 2.

Recommendations There is no easy solution to the problem of high remediation and low achievement as students make the transition to college math; these recommendations are offered as a starting point.

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Just offering more rigorous math courses won’t solve the problem — students must actually take the courses!
Data such as these should be publicized to teachers, counselors, parents, school boards, and public school administrators. It is possible these interested parties do not realize the consequences of such a broad, but weak, math curriculum.
High school administrators, counselors, and teachers should start talking to students (and parents) in early grades about college. Many students will plan to attend college, and prepare for it, if we encourage them early on.
High schools should find an alternative to tracking —less rigorous math courses, at least in our area, do not prepare students for anything except to receive a high school diploma.
High school students should receive placement testing during their sophomore or junior year; this can provide concrete evidence to students that they need more math.
High schools must find ways to keep students in relevant classes during the senior year.
Colleges and public schools must communicate and work together. Although we are distinct, we depend on each other.

Summary The data indicate that a fourth year of rigorous high school math, something more advanced than Algebra 2, greatly increased the likelihood that a student would place into college level math. Perhaps as important, students who completed a post-Algebra 2 course were more likely than others to succeed in college math, even if they placed into a remedial course. Students who took a rigorous math curriculum in high school were more likely to enter college at the appropriate level or to progress to college level after a semester in remediation. Students who lacked a rigorous high school math course often started college one to three math courses (thus semesters) behind and then stayed behind because of their high failure rate in the remedial courses. Remediation rates for college-going students continue to soar, yet national studies show that a high quality high school curriculum can eliminate much of the need for remediation. The trouble with national or regional studies is that the results, even if they filter down to the local level, often have little effect on what happens to individual students in individual schools. The purpose of this project was to bring high school and college math faculty together to observe closely what

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happens as local students make the transition from secondary to higher education. Although we are only beginning the dialogue, collaboration between the two groups might be the catalyst that brings needed change to our area of Arkansas, then to the entire state.

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REFERENCES Adelman, C. (1996, October 4). The truth about remedial work. The Chronicle of Higher Education, p. A56. Adelman, C. (1999). Answers in the tool box: Academic intensity, attendance patterns, and bachelor’s degree attainment. Washington, DC: U.S. Government Printing Office. Chronicle of Higher Education. (2001, August). Almanac Issue. Crampton, N. (1993). The 100 best small towns in America. New York: Prentice Hall. Family income by educational attainment of householder, 1956 to 1999 (2000, December). Postsecondary Education Opportunity, 102, 14. Harrell, R. (2001, April). Annual report on first-year student remediation. Student success: Graduation & retention in Arkansas. Paper presented at the meeting of the Arkansas Higher Education Coordinating Board, Little Rock, AR. Harrell, R. (2001). Student enrollment fall 2001. Retrieved March 3, 2003 from Arkansas Department of Higher Education website: http:==www.arkansashighered. com=enrollment-2001.html Jago, C. (2000). It’s the curriculum, stupid. American School Board Journal, 187(4), 66, 68. Johnston, R., & Hardin, L. (2001). Student success: Graduation & retention in Arkansas. Little Rock, AR: Arkansas Dept of Higher Education. Measuring up 2000: The state by state report card for higher education. (2000). The National Center for Public Policy and Higher Education. [On-line]. Available: http:==measuringup2000.highereducation.org=reporthome.htm Mortenson, T. (2002, February). Higher education as a private and social investment. Paper presented at the meeting of the Key Bank Financing Conference 2002, Orlando, FL. The lost opportunity of senior year: Finding a better way. Summary of results, retrieved March 3, 2003 from National Commission on the High School Senior Year website: http:==www.commissiononthesenioryear.org=Report=CommissionSummary2.pdf U.S. Department of Education, National Center for Education Statistics. (2000). The condition of education 2000 (NCES Publication No. 2000-602). Washington, DC: U.S. Government Printing Office.

Is the Sky Still Falling? David M. Bressoud

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n the 1998 Notices article “The Sky is Falling” [4], Garfunkel and Young drew attention to the alarming decrease in the number of students who study mathematics in college. In their words, “Our profession is in desperate trouble—immediate and present danger [. ​ .​ . ] If something is not done soon, we will see mathematics department faculties decimated and an already dismal job market completely collapse.” In the past ten years the situation seems to have reversed. The mathematical community is not in the desperate straits that Garfunkel and Young predicted. Yet, as this article will show, the situation is far from healthy, and in many respects we are worse off now than we were in 1995. Today we teach a smaller percentage of the total enrollment than ever before. The growth that has occurred has been entirely within our research universities, and there it can be explained by a short-term increase in the number of engineering students. This article concludes with three action items that the mathematical community needs to undertake if we are to reverse this decline. Garfunkel and Young’s argument rested on data from the Conference Board of the Mathematical Sciences (CBMS) showing a drop in enrollments from 1985 to 1995. As Table 1 shows, the situation in 1995 looked far worse than it does today. Enrollment in precollege (remedial) mathematics has continued to decline at 4-year colleges.1 For all other categories of courses,2 enrollments are up David M. Bressoud is DeWitt Wallace Professor of Mathematics at Macalester College and president elect of the Mathematical Association of America. His email address is [email protected]. Most precollege or remedial mathematics is taught at ​ 2-year colleges where it now accounts for 61% of all mathematics taught at these colleges. 1

Introductory level includes College Algebra, Precalculus, ​ and Math for Liberal Arts. Calculus level is Calculus I through Differential Equations, Linear Algebra, and Discrete Math. Advanced is everything above calculus level including Introduction to Proofs. Statistics courses are not included in these numbers. 2

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over the 1995 numbers by between 9% and 17%. While we are still well below the 1985 numbers for courses at the level of calculus and above, whatever was going wrong in the early 1990s seems to have been corrected. But if we compare the number of students studying mathematics to the number of students enrolled in our 4-year undergraduate programs, we see that mathematics has been accounting for an ever-decreasing slice of the pie. The figures for 1995 were bad, but the percentages for 2005 are considerably worse (see Table 2). These percentages should be alarming. The true situation is revealed to be even more discouraging once we unpack these numbers and look at what is happening in individual courses and at specific types of institutions. Because of its central role in the undergraduate curriculum, I will focus on calculus.

Calculus in High School In the spring of 1985, 46,000 students took the Advanced Placement Calculus exam. In spring 2008, the number was 292,000. By 2009, it will be well over 300,000. In fact, the number of AP Calculus exams given each year has grown steadily over the past decade at an average rate of over 7% per year with no sign yet that it is approaching its inflection point (see Figure 1). AP Calculus exam takers are only a piece of the broader population of students who study calculus while in high school, a population that includes those who take an AP Calculus course but not the exam as well as those in the International Baccalaureate program, dual enrollment programs, registration in 2- or 4-year college calculus classes, and the many students who are given a soft introduction to calculus while in high school in the hope of easing the transition to college calculus. Based on the NELS study from spring 2004 [3], the NAEP transcript study from 2005 [12], and the growth of AP Calculus since then, it is safe to conclude that we have reached the point where each year over half a million high school students study calculus. AMS

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precollege level introductory level calculus level advanced

1985 251 593 637 138

1990 261 592 647 119

1995 222 613 538 96

2000 219 723 570 102

2005 201 706 587 112

Table 1. Mathematics enrollments (thousands) for fall term at 4-year colleges and universities in the United States. Sources: [1, 5–7]. precollege level introductory level calculus level advanced

1985 3.25% 7.69% 8.26% 1.79%

1990 3.04% 6.90% 7.54% 1.39%

1995 2.53% 6.99% 6.14% 1.09%

2000 2.34% 7.72% 6.09% 1.09%

2005 1.83% 6.42% 5.34% 1.02%

Table 2. Mathematics enrollments at 4-year colleges as a percentage of total number of students enrolled in fall term. Sources: [1, 5–7, 13].

Calculus I Calculus II Calculus III & IV

1985* 217 95 90

1990 201 88 84

1995 192 83 62

2000 192 87 73

2005 201 85 74

Table 3. Mainstream calculus enrollments (thousands for fall term in 4-year colleges). *1985 breakdown is estimate based on total number of students in all mainstream calculus classes. Sources: [1, 5–7, 13].

At least we have seen some increase in the Calculus I, III, and IV enrollments over the period 2000–05. In fact, even that is less robust than it seems. When we break down calculus enrollments

by type of institution,3 we see that the growth is occurring entirely at the research universities (see Figures 2–4). For all levels of college calculus, the increase since 1995 is entirely within the research universities. Everywhere else, enrollment has declined. There is a distinctive pattern of enrollments across all levels of calculus that occurred at the research universities and at no other type of institution: a five-year decline from 1990 to 1995 followed by steady growth. This pattern can be explained by the fact that most large research universities have large engineering programs. If we consider the number of incoming freshmen who intend to major in engineering (Figure 5 and Table 4), we see that it also decreased from 1990 to 1995, then grew. The scatterplot in Figure 6 shows a high correlation (correlation coefficient of 0.99) between the number of entering freshmen who intend to major in engineering and the total number of students in research universities each fall who enroll in any level of calculus. The downturn at the end of the graph in Figure 5 suggests that the 2005 CBMS numbers may be overly optimistic. As Table 4 shows, the number of students who intend to major in engineering began a steady decrease following a record large number in 2004. It is interesting to compare the number of intended majors in engineering with those in the other STEM (science, technology, engineering,

The CBMS categories of 4-year institutions are based on ​ the highest degree offered in mathematics: Ph.D., M.A., or B.A. The labels “research university”, “comprehensive

university”, and “undergraduate college” are substituted as descriptive of the general type of institution and to clarify that the categorization is by type of institution.

Most of the students who study calculus in high school do not receive college credit for this course. Morgan [8] estimates that about half of the students who take the AP Calculus exam are entitled to and choose to use credit for Calculus I. Perhaps another 30,000 receive college credit via dual enrollment, IB, or enrollment in a college class. A reasonable estimate is that between 150,000 and 200,000 students arrive at college each fall bringing with them credit for calculus. That suggests that we should be seeing dramatically increasing numbers of students taking Calculus II in the fall term. As Table 3 shows, this is not the case. In fact, Calculus II enrollments in the fall term actually dropped over the period 2000–05. What about the other 300,000–350,000 students who took calculus but not for college credit? One would hope that the increasing numbers of these students would translate into increasing numbers of students taking calculus in college. But combining all mainstream Calculus I classes in all 2- and 4year colleges in the United States, fall enrollments have been stuck at very close to 250,000 over the past quarter century.

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Figure 1. Fall enrollments in mainstream Calculus I and number of AP Calculus exams (thousands). Sources [1, 2, 5–7, 11].

Figure 2. Fall enrollments in mainstream Calculus I by type of institution (thousands). Sources: [1, 5–7]. mathematics) disciplines: the biological sciences in Figure 7 and the physical sciences (including mathematics4) in Figure 8.

Conclusions We have seen growth in enrollments in mathematics courses over the past ten years, but that growth is well below the rate of increase in total enrollments. The only place where it has been robust has been where it is tied to the increase in engineering The number of freshmen intending to major in math​ ematics dropped from 1.1% in 1985 to 0.5% in 2000. It has since grown to 0.8%, approximately the current percentage of graduates who earn majors in mathematics. 4

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majors, a phenomenon that appears to be cyclical and has now entered a downturn. The mathematical community needs to look at what it can do to strengthen enrollments. One solution is to get a lot more high school students to plan careers in engineering. It would be interesting to know what caused the reversal in engineering enrollments in the mid-1990s. These projections of intent to major in engineering were measured during freshman orientation, and thus the increase after 1995 was the result of something that happened in high school. What role did the introduction and widespread acceptance of graphing calculators and reform teaching methods within high schools have on the increased interest in and willingness to pursue highly technical majors? What is causing the current downturn in interest in engineering? Engineering has served us well, but there is no reason why the fate of mathematics should be so dependent on just this discipline. The key to getting students into our advanced courses is to first get them into firstyear courses that teach solid mathematics and pique their interest to continue in mathematics. This does not have to be a course tied to the engineering curriculum. Nevertheless, calculus is at the heart of the mathematics curriculum, and we must begin by taking a serious look at what is happening in college calculus and how well it articulates with the experiences that today’s students have in high school. This is the basis for my first two recommendations. Recommendation 1: We need to understand what happens in college to students who study calculus in high

school. The half million students who study calculus in high school are a reasonable approximation of the top 15% of all high school graduates. They should be swelling the ranks of the students taking calculus- and advanced-level mathematics. We need a better understanding of what happens to these students after they enter college. For the 150,000 to 200,000 who arrive with and use credit for calculus taken in high school, how many continue to pursue mathematics and how well do they succeed? What happens to the other 300,000 to 350,000? For all of these students, what are the programs that most AMS

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effectively engage them, preparing and encouraging them into the further study of mathematics? Recommendation 2: We need to know more about the preparation of the students who take calculus in college and what they need in order to succeed once they get to our classes. We must have a better sense of who these students are who sit in our college calculus classes. What is the preparation that has gotten them to this point? How can we modify our courses so as to capitalize on the strengths and correct the weaknesses that these students bring? The answers to these questions will necessarily be local, highly dependent on the nature of a given college or university, but the entire mathematical community should be able to identify commonalities among similar types of institutions. The entire community should also promote programmatic and course structures that are particularly effective for each of the different populations we encounter.

Figure 3. Fall enrollments in mainstream Calculus II and number of AP Calculus exams (thousands). Sources: [1, 2, 5–7].

Recommendation 3: Mainstream calculus should not be the only entry to good college-level mathematics. The department of mathematics should be at the core of its college or university, interacting with every other department and working collaboratively to develop courses that meet the needs of each group of students. These should be courses that involve real mathematics and that open the way to the further, deeper study of mathematics. This conviction should be part of the vision of every department of mathematics. I look with longing at those 120,000 prospective biological science majors coming in each year. We need courses that are attractive to them, courses Figure 4. Fall enrollments in mainstream Calculus III & IV and number of AP that give them the tools from lin- Calculus exams (thousands). Sources: [1, 2, 5–7]. ear algebra that they will need for sophisticated statistical modeling, up in collaboration with biologists. Many colleges courses that enable them to read and write differential equations and turn them into and universities have begun this process. See, for computer simulations. We are not going to example, Math & Bio: 2010 [14]. Doing this for biolbe able to convince the biologists that their ogy is just the beginning of what should be a broad students need to take more of the courses program of outreach and development. that we have created for the engineers, nor is The surge in engineering enrollments since it enough to take an engineering course and 1995 coupled with the growth in physical science throw in some biological examples. These enrollments over the past five years has given us courses must be designed from the ground January 2009

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Figure 7. Number of freshmen in 4-year undergraduate programs who intend to major in biological sciences. Sources: [9, 10].

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Figure 5. Number of freshmen in 4-year undergraduate programs who intend to major in engineering. Sources: [9, 10].

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Figure 8. Number of freshmen in 4-year undergraduate programs who intend to major in physical sciences. Sources: [9, 10].

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# of Prospective Engineers against Total Fall Calculus Enrollments in Research Universities

Figure 6. Number of prospective engineering majors against total fall calculus enrollment at research universities. Sources: [1, 5–7, 9, 10].

total fall calculus enrollment (thousands)

a reprieve. Yet, unless we address fundamental weaknesses, the long-term prognosis for the health of undergraduate mathematics is not good. I am still optimistic. Many talented people are working hard to improve the undergraduate program in mathematics. With a better of sense of where we are and widespread dissemination of what works, we can build a foundation for the future.

year 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007

References [1] Donald J. Albers, Don O. Loftsgaarden, Donald C. Rung, and Ann E. Watkins, Statistical Abstract of Undergraduate Programs in the Mathematical Sciences and Computer Science in the United States: 1990–91 CBMS Survey, Number 23 in MAA Notes, Mathematical Association of America, Washington, DC, 1992. http://www.ams.org/cbms/cbms1990. html. [2] College Board, AP report to the nation, New York, NY, 2004–2007. http://professionals. collegeboard.com/data-reports-research/ap/ nation. [3] Ben Dalton, Steven J. Ingels, Jane Downing, Robert Bozick, and Jeffrey Owings, Advanced Mathematics and Science Coursetaking in the Spring High School Senior Classes of 1982, 1992, and 2004: Statistical Analysis Report, Number 2007-312, National Center for Education Statistics, U.S. Department of Education, Washington, DC, 2007. http://nces.ed.gov/ pubsearch/pubsinfo.asp?pubid=2007312. [4] Solomon A. Garfunkel and Gail S. Young, The sky is falling, Notices of the AMS, 45 (1998), 256–257. [5] Don O. Loftsgaarden, Donald C. Rung, and Ann E. Watkins, Statistical Abstract of Undergraduate Programs in the Mathematical Sciences in the United States: Fall 1995 CBMS Survey, Number 2 in MAA Reports, Mathematical Association of America, Washington, DC, 1997. http://www.ams.org/cbms/ cbms1995.html. [6] David J. Lutzer, James W. Maxwell, and Stephen B. Rodi, Statistical Abstract of Undergraduate Programs in the Mathematical Sciences in the United States: Fall 2000 CBMS Survey, American Mathematical Society, Providence, RI, 2002. http://www.ams.org/cbms/ cbms2000.html. [7] David J. Lutzer, Stephen B. Rodi, Ellen E. Kirkman, and James W. Maxwell, Statistical Abstract of Undergraduate Programs in the Mathematical Sciences in the United States: Fall 2005 CBMS Survey, American Mathematical Society, Providence, RI, 2007. http:// www.ams.org/cbms/cbms2005.html. [8] Karen Christman Morgan, The use of AP examination grades by students in college, preprint. [9] John H. Pryor, The American freshman: Forty year trends, ACE Research Reports, Higher Education Research Institute, UCLA, Los Angeles, CA, 2007. [10] John H. Pryor, Sylvia Hurtado, Jessica Sharkness, and William S. Korn, The American freshman: National norms for 2007, ACE Research Reports, Higher Education Research Institute, UCLA, Los Angeles, CA, 2007. [11] Larry Riddle, personal communication of record maintained by AP Calculus Chief Readers of the total number of exams taken each year.

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4-year freshman enrollment 1,067,928 1,023,762 1,031,968 1,076,036 1,028,143 1,010,548 1,024,976 1,060,087 996,690 1,017,725 1,024,550 1,076,035 1,054,500 1,066,679 1,098,833 1,101,817 1,204,240 1,234,968 1,196,089 1,258,333 1,298,093 1,320,824 1,354,958

% engineering 11.0% 10.2% 9.4% 8.7% 9.9% 9.7% 10.8% 10.0% 10.0% 8.8% 8.1% 9.7% 9.7% 8.2% 9.0% 8.7% 9.1% 9.5% 9.3% 9.6% 8.4% 8.0% 7.5%

# prospective engineers 117,000 104,000 97,000 94,000 102,000 98,000 111,000 106,000 100,000 90,000 83,000 104,000 102,000 87,000 99,000 96,000 110,000 117,000 111,000 121,000 109,000 106,000 102,000

% biological sciences 4.6% 4.6% 4.4% 4.4% 4.5% 4.8% 5.7% 6.5% 7.1% 7.9% 8.3% 8.2% 8.0% 7.1% 7.2% 6.8% 6.9% 7.2% 7.3% 7.7% 7.6% 8.3% 8.6%

Table 4. Number of freshmen in 4-year undergraduate programs who intend to major in engineering. Sources: [9, 10]. [ 12] Carolyn Shettle, Shep Roey, Joy Mordica, Robert Perkins, Christine Nord, Jelena Teodorovic, Janis Brown, Marsha Lyons, Chris Averett, and David Kastberg, America’s High School Graduates: Results from the 2005 NAEP High School Transcript Study, Number 2007-467, National Center for Education Statistics, U.S. Department of Education, Washington, DC, 2007. http://nces.ed.gov/ nationsreportcard/pubs/studies/2007467. asp. [13] Thomas D. Snyder, Sally A. Dillow, and Charlene M. Hoffman, Digest of Education Statistics: 2007, Number 2008-022, National Center for Education Statistics, U.S. Department of Education, Washington, DC, 2008. http://nces.ed.gov/ programs/digest/. [14] Lynn Arthur Steen, editor, Math & Bio 2010: Linking Undergraduate Disciplines, Mathematical Association of America, Washington, DC, 2005.

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MERLOT Journal of Online Learning and Teaching

Vol. 4, No. 3, September 2008

Student Preferences, Satisfaction, and Perceived Learning in an Online Mathematics Class Julie Glass Department of Mathematics and Computer Science California State University, East Bay Hayward, CA 94542 USA [email protected]

Valerie Sue California State University, East Bay Hayward, CA 94542 USA [email protected] Abstract This study analyzes student preference, satisfaction and perceived learning in an online college mathematics course for business majors. Using a combination of active and passive learning objects, the online course was developed to investigate the instructional strategies students use the most, prefer and believe impact their learning. Students answered weekly surveys about the course. They were asked to report their usage of the learning objects and to reflect on their interactions with the material and with each other. They were also asked to assess the impact that various learning objects had on their learning and on their satisfaction with the course and with the material. Of the learning objects investigated, homework emerged as the factor students preferred and used the most, and that they felt had the greatest impact on their learning. Participation in online discussions did not surface as a favored or significant factor in the students’ learning. This work is aimed at informing best practices for increasing student engagement, and thus learning, in online mathematics and other similar courses. Keywords: Online learning, Learning Objects, Active Learning, Mathematics, Survey Research Introduction The Internet has brought about a paradigm shift in the way professors teach and students learn. Online courses, an experimental concept less than a decade ago, have become de rigueur for postsecondary institutions wishing to maintain a presence at the forefront of educational innovation. Research about online teaching and learning has, however, struggled to keep pace with the rapid development of the field. Recently, the focus has shifted from questions surrounding whether online education is effective to how best to achieve important student learning outcomes in online environments. This study analyzes student preference, satisfaction and perceived learning in an online mathematics course. Students answered weekly surveys about the course. They were asked to reflect on their interactions with the material, each other and the professor as well as on the impact that various learning objects had on their learning and on their engagement in the course. This work is aimed at informing best practices for organizing and presenting course material in online mathematics and related courses. Literature Survey The Internet has provided a new mechanism for connecting teachers and students; however, distance education is hardly a new concept. Saba (2005) notes that distance learning can be traced back to the 1800s; technological developments, including radio in the 1920s, television in the 1950s, and the use of the Internet by civilian organizations in the mid-1980s, have contributed to moving distance education from a fringe activity to a central focus in American higher education. Whether the method is termed

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distance education, distributed learning, e-learning or online education, one consistent goal in the study of these methods of bringing instructors and learners together has been to determine optimal strategies for enhancing the student learning experience. One avenue of research activity that has received attention across disciplinary boundaries is focused on the notion of active learning. Active learning is fostered when instructional methods engage students in the learning process (Bonwell & Eison, 1991). Active learning takes place when instructors ask students to reflect on what students are doing and participate in meaningful learning activities. In an online learning context, this may take the form of journal entries or discussion board postings as well as traditional homework assignments or simulation exercises. In an extensive review of the literature surrounding active learning, Prince (2004) discovered substantial empirical support for the assertion that active learning can significantly improve recall of information and substantially contributes to student engagement. Active learning strategies have been shown to lead not only to greater retention of course material but also to increased satisfaction in online courses (Sahin, 2007). The literature regarding student satisfaction in online courses is less clear cut than the active learning line of studies. While some researchers have found that learner-centered activities are central to student satisfaction in online courses (Ellis & Cohen, 2005), Cuthrell and Lyon’s (2007) recent investigation discovered that students preferred a mix of instructional strategies that incorporated active and passive modes of instruction. Other factors that have been shown to be related to student satisfaction in online courses are presence (social, cognitive and teaching) (Pelz, 2004), community (Sahin, 2007) and frequent feedback and assessment (Swan, 2003). In a study of non-posting (i.e., lurking) discussion board behavior among students in online classes, Dennen (2008) found that about half of the students felt that they learned through online discussions (both posting and reading messages); students who reported that they participated in discussion only to meet course requirements and those who focused more on posting rather than reading messages had less positive impressions of the discussions’ impact on their learning. The nomenclature of learning objects (LOs) provides a useful framework for discussing the Web-based multimedia systems used to deliver instructional content in online courses. Learning objects have engendered considerable debate as of late (Bennett & McGee, 2005; Friesen, 2003; Parrish, 2004) and definitions vary widely (Liber, 2005), however, the fervor with which supporters and detractors continue to engage in debate over both the explication of the concept and its utility for higher education is an indication of the resilience of the concept. As defined by Hodgins (2000), LOs are small, reusable instructional components designed to achieve specific learning objectives that are delivered via the Internet. Hodgins (2000) compared LOs to LEGO building blocks; that is, individual course components that can be easily added, removed or replaced, making course content highly adaptable. Wiley (2002) broadened the concept by defining LOs as any digital resource that can be reused to support learning. The definition of LOs used in the present research follows loosely from Hodgins’ (2000) original definition. With the literature concerning student preferences, satisfaction and perceived learning as a base (with particular attention being given to active learning strategies), and with the taxonomy of learning objects as a framework, this research endeavored to investigate the LOs that students preferred, used the most and were the most satisfied with as well as the LOs that they believed had the most impact on their learning. The course and the university The vehicle for this study was a quarter-long (ten weeks) online mathematics course for Business and Social Science students at California State University, East Bay (CSUEB). CSUEB is a mid-sized comprehensive, public urban university in the San Francisco Bay Area. The student population is highly varied in age, ethnicity and socioeconomic status (see participants section). The course has a prerequisite of college algebra and is required for all business majors and for entry into the MBA program. The course consisted of ten learning modules consisting of two lectures and a series of online assignments. Students were required to complete one module each week for which all material was made available at midnight on the first day of the week. The course material included: functions and graphs; exponential and logarithmic functions; mathematics of accounting and finance; matrices and

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systems of equations; linear programming (a geometric approach); and an introduction to differential and integral calculus with applications to business and social sciences. Grades were based on a total of 1000 points as shown in Table 1 below and the grades were assigned based upon a standard points-togrades scheme as shown in Table 2.

Table 1: Point distribution for Learning Objects LO

Points

Homework

240 (12 points each)

Discussion

60

Quizzes

200 (20 points each)

Midterm

200

Final Exam

300

Total Possible

1000

Table 2: Points to Grade Scheme Total Pts Earned

Grade Assigned

Total Pts Earned

Grade Assigned

930 – 1000

A

770 – 799

C+

900 – 929

A-

730 – 769

C

870 – 899

B+

700 – 729

C-

830 – 869

B

670 – 699

D+

800 – 829

B-

600 – 669

D

< 600

F

The course was delivered via the Blackboard (Bb) Course Management System (CMS). All homework, quizzes and examinations were completed on a publisher-supported course shell, Course Compass, utilizing an online homework service, My Math Lab (CC/MML). All course requirements were completed totally online except the final exam which students were required to take in person. The instructor was present at the final exam, however all other content was completed without a proctor present. A detailed table of activities and deadlines was provided to students at the beginning of the quarter. The course was structured so as to require students to work regularly on the material. The instructor was available to answer questions online and in person via online and face-to-face office hours as well as discussion boards and via e-mail. Learning Objects The primary focus for this study was usage and perceived impact on learning of the LOs as described in Table 3. Figure 1 illustrates the connections between each of the LOs and satisfaction and learning. The course included the following required components: weekly homework, discussion, quizzes, one midterm examination and a final examination. It should be noted that there was some overlap between the LOs (Table 3) and the required components of the course. This is an obvious result of the fact that some LOs are needed to simply convey information while others involve active participation on the part of the student (e.g. homework, quizzes, etc.) Moreover, in any valid course design, one would expect required components to be a mode of content delivery, i.e. an integral part of the learning experience

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Table 3: Description of Learning Objects Learning Object

Active/Passive

PowerPoint

Passive

Required/Optional

Optional Text

Passive Optional

Video Lectures

Passive

Homework

Active

Optional

Required

Discussions

Active Required & Optional

Quizzes

Description

Active Required

Two weekly sets of PowerPoint slides which were also embedded in the video lectures and were available for printing and review on the course Bb site. Students were able to purchase a hard copy text or view an e-text on the CC/MML course site. Specific examples, “matched problems,” and “look in the book” exercises were referenced in the video lectures. Note that the text is classified as passive because that is generally the manner in which students utilize the text. The authors acknowledge that active utilization of the text is possible and desirable. Two weekly media-enhanced lectures created using Microsoft Acustudio. Lectures included head and shoulder video of the instructor, audio, PowerPoint slides and a white board feature (“examples by hand”). See Figure 2. Two required homework assignments each week. All homework was done on the publisher supported site CC/MML. While doing homework, extensive worked examples (generated by MML) and “hints” are available. See Figure 3. Students were required to respond weekly to instructorprovided prompts designed to encourage higher level thinking about the weekly content. Optional discussion boards were available for general and mathematical questions and comments. Required weekly quizzes which were completed on the CC/MML site.

Methods The data for this project were collected via a series of online surveys. The first survey of the quarter gathered general demographic information, data related to learning styles and information about math attitudes. The weekly surveys, beginning in Week 2 of the course, were brief and focused on the students’ activity during the week, related to each of the LOs. Students were asked whether they used each of the LOs and how much they felt that each one contributed to their learning of the week’s course material. The longer, final survey of the term allowed the students to rate each LO and to evaluate the course overall. This data collection process was designed to place non-grade-related data and assessments outside the domain of the course. The survey data were supplemented with student grades and course component utilization statistics collected from Course Compass.

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Figure 1. LO Interaction with Student Satisfaction and Perceived Impact on Learning

Figure 2. Screenshot of Lecture Participants Table 4 provides participant demographics for the course. A total of 55 students consented to participate in the research. Women were the majority of the sample, accounting for three-quarters of the participants; most were juniors or seniors and about a third were graduate students. The wide age range

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(19 to 47-years-old) and somewhat high mean age of 27.8 is typical for this university, where the campus-wide mean age is 30-years-old.

Figure 3. Screenshot of Homework Module

Table 4. Demographic Profile of Research Participants Characteristic

Frequency (percent)

Gender Male Female

14 (25.5%) 41 (74.5%)

Class level Freshman/Sophomore Junior Senior Graduate student

2 (3.6%) 21 (38.2%) 15 (27.3%) 17 (30.9%)

Major Undergraduate Business MBA Other

42 (76.4%) 10 (18.2%) 3 (5.5%)

Age Range Mean Median Mode Standard deviation

19 – 47 27.8 20 7.0

The students reported working an average of 31.7 hours per week at a job or internship and 82% had taken at least one other online class. When asked why they signed up for this particular online course, “flexibility” and “to accommodate work schedules” were the two most popular reasons.

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Results Preferences. To establish a baseline measure of preferences for various LOs, students were asked at the beginning of the quarter to report how much they liked or disliked a variety of teaching methods. The results are presented in Table 5. The clear preference for practice exercises and low rating of online discussions among these online students foretells the usage and satisfaction results that were subsequently discovered. Table 5. Student Learning Preferences Method

N

Mean (1=dislike very much, 5=like very much)

SD

Practice exercises

55

4.20

.78

Video lectures

55

4.00

.97

One-on-one w/instructor (online)

55

3.71

.81

Online discussions

55

3.36

1.16

Utilization. Every week, the students were asked to report whether they had used each LO and then to indicate how much each LO contributed to their learning of the week’s course material. Figure 4 provides a percent summary of utilization feedback. Percent utilization was calculated as (# utilizing LO / total respondents) x 100. All survey questions were optional; therefore, sample sizes for each question and across surveys varied. For example, the smallest sample size represented by the data in Figure 4 is 47 and the largest is 55. Week 6 was midterm week; therefore, there was no quiz. Also during Week 6, the discussion question, rather than addressing specific course content, asked that each student reflect on the course so far, resulting in a spike in participation.

No quiz week

Figure 4. Learning Object Utilization During the Course It should be noted that the overlap between required components of the course such as homework, quizzes and discussion participation, and those LOs that are non-participatory and optional such as text,

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PowerPoint slides, and lectures, should have an impact on reported usage. Homework emerged as the LO that students reported using most; this was remarkably consistent throughout the quarter. The low utilization was in Week 5 when 96% of the students surveyed said that they did the homework; the highest utilization was in Week 9 when 100% of the respondents said they did the homework. Participation in the required weekly quizzes was consistently quite high (range = 88% - 96%, overall mean = 89%). Fewer students reported reading the text (range = 65% - 78%, overall mean = 70%) and PowerPoint slides (range = 53% - 65%, overall mean = 58%) but utilization of these LOs was fairly stable over time as well. There was more variation in reports of watching the video lectures (range = 46% 73%, overall mean = 56%), and participating in Blackboard discussions (range = 53% - 90%, overall mean= 68%) Course Compass afforded the opportunity to track the amount of time that students spent on homework. Figure 5 shows the mean time spent doing homework on Course Compass throughout the course. The first homework assignment of the course required students to simply report that they had successfully logged in to the Course Compass site (which they had to do to have access to the homework assignment) thus resulting in an average of 43 seconds spent on that homework assignment. As the course progressed and the homework became more challenging, time spent on homework increased dramatically; homework 8 had the highest mean time of almost two-and-a-half hours. It should be noted that this data represents the amount of time that students were logged on to the homework site; clearly, it is not possible to know whether they were actively working homework problems during the entire time that they were on the Web site. In addition, students were encouraged to print out the homework assignments, work offline, and then log in to enter their responses. Thus, the time spent-data from CC/MML could, in fact, be higher or lower than actual time spent working with the material. Course Compass also recorded how much time students spent on quizzes; since the quizzes were timed, however, the “time spent” data was deemed not relevant for this study.

2:52:48 2:25:52

2:24:00

2:20:30

Mean time spent

2:08:26

2:04:33

2:01:11 1:59:36

1:55:12

1:53:04 1:47:09

1:44:26

1:49:28

1:31:43 1:37:29

1:26:24

1:22:26

1:20:15

1:15:15

1:12:45

1:15:28

1:10:32

0:57:36

0:55:09

0:28:48 0:00:43

0:00:00 1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

Homework #

Figure 5. Mean “Time Spent” on Homework

Contribution to Learning. Along with reporting whether they had used each of the LOs, students indicated how much they felt that each one had contributed to their learning of the week’s course material. These questions were measured on a 1-to-5 point scale where 1 meant that the LO made no contribution to learning and 5 meant that the LO contributed a lot to the learning of that week’s material. Figures 6 and 7 present the mean weekly ratings for each LO; Figure 6 shows the averages for the passive LOs: lecture, text and PowerPoint slides; Figure 7 displays the averages for the active LOs: homework, quizzes and discussions. When presented this way, it is clear to see that students perceived the passive LOs to have varying contributions to their learning during the course; in week 2, for example, the PowerPoint had the greatest mean and this value then declines, spikes, and dips again near the end

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of the quarter. The lecture shows the opposite pattern, and the means for all three passive LOs converge in week 6.

Figure 6. Contribution of Passive LOs to Perceived Learning

No quiz week

Figure 7. Contribution of Active LOs to Perceived Learning. The active LOs, on the other hand, are stable throughout the 10 weeks of the course. Homework was consistently reported to have the greatest contribution to the learning, quizzes were also said to have had an impact on learning and, according to the students, Blackboard discussions consistently contributed less to their learning of the material. As previously noted, these active LOs also correspond to the required components of the course. Although the students were given opportunities throughout the quarter to rate the contribution of each LO to their learning, they were asked to do so again on the final survey. The question on the final survey asked them to reflect globally on the contribution of each LO to their overall learning of the course material. The mean overall ratings are in Table 6. The students reported that the homework assignments contributed the most to their overall learning of the material. This is consistent with responses from the weekly surveys where homework was reported to be the LO having the greatest contribution to learning every week.

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Table 6. Contribution of LOs to Overall Learning Learning Object

N

Mean

SD

(1=not at all, 5=a lot) Homework

45

4.71

.66

Quizzes

45

4.31

1.02

PowerPoint slides

45

4.02

1.25

Lectures

45

3.91

1.46

Text

45

3.33

1.38

Blackboard discussions

45

3.02

1.37

To validate the rating data, students were presented with five LOs (quizzes were not included in this ranking question) and asked to rank them based on which they believed had the greatest overall impact on them; the results of those rankings are in Table 7. In this ranking exercise, it was impossible to assign the same rank to more than one item; therefore, students who might have rated, homework and lectures, for example, as both having a lot of impact on their learning were forced to choose which had the most impact, which had the second most impact, and so on. As with the quality and learning contribution ratings previously presented, homework emerged as the most important LO, ranking #1. Without this impact ranking data, one might conclude that the required LOs would always come out “on top” of the pile in terms of impact on learning; however, note that this is not the case. Homework came out on top for usage and impact on learning, but the 2nd, 3rd, and 4th LOs (lectures, PowerPoint and text) ranked in terms of overall impact were not required LOs and did not rank high in terms of usage (see Figure 4). This is additional evidence of the importance and value of the homework support provided by the CC/MML site. Table 7. Impact on learning of LOs—Overall Rankings LO

Rank

Homework

1st

Lectures

2nd

PowerPoint slides

3rd

Text

4th

Blackboard discussions

5th

Quality. In the final survey of the quarter, students were asked to rate the quality of each of the LOs. Table 8 presents the mean ratings (on a 1-to-4 point scale) of each LO. Homework, the LO that students consistently used the most, and that they felt contributed the most to their learning, was rated highest quality; the text, which was used moderately, received the lowest rating.

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Table 8. Overall Quality Ratings of LOs LO

N

Mean

SD

(1=poor, 4=excellent) Homework

45

3.58

.54

Quizzes

45

3.22

.67

PowerPoint slides

45

3.11

.91

Lectures

45

3.02

.81

Blackboard discussions

44

2.59

.84

Text

45

2.58

.92

Satisfaction. Two measures were used to determine overall student satisfaction with this online course: a standardized question on the general student course evaluation form distributed to all students at the end of every class and a question on the final online survey of the quarter that asked students whether they would recommend this particular online course. Table 9 shows the frequencies of responses to both items: 58 students completed the course evaluation administered by the University; of those, 86.2% said that the course was outstanding or good. About the same percentage of students who answered the recommend question on the final course survey (86.7%) said that they would recommend the course. Together, these two questions provide compelling evidence to support the claim that students in this online course were overwhelmingly satisfied. Table 9. Overall Rating and Likelihood to Recommend Evaluation item

Frequency (percent)

Overall course rating Outstanding Good Fair Poor

26 (44.8%) 24 (41.4%) 5 (8.6%) 3 (5.2%)

Would recommend the course Yes No

39 (86.7%) 6 (13.3%)

Discussion Because of the challenges of notation and intricacy of content, mathematics is one of the most challenging disciplines to offer online. However, the availability of rich, publisher-supported online homework sites such as CC/MML and software such as Acustudio has made the creation of LOs for teaching mathematics relatively easy. Acustudio makes possible the creation of rich online lectures that, in the past, would have required extensive instructional technology design support. The ability to show hand-worked examples using the “whiteboard” feature was key to the successful implementation of this software. Students reported that the “examples by hand” created utilizing the whiteboard were an especially useful component of the lectures. However, far and away the most highly utilized and consistently preferred LO was the homework. As shown in the screenshot in Figure 3, the CC/MML site offers a variety of tools for students completing homework assignments. Students are able to view examples, request help solving a problem and link directly to relevant pages in the e-text. In addition,

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students are given immediate feedback on their solutions. This instant feedback speaks also to student preferences as described by Swan (2003). If an incorrect solution is entered, students are able to solve a similar problem (generated by MML) for credit. This rewards persistence and helps students become familiar with procedures and patterns found in solving certain types of problems. CC/MML allows students to interact with the material in a manner that exemplifies the notion of active learning. There is evidence (Bonwell & Eison, 1991; Sahin, 2007) that active participation in content leads to greater and longer lasting understanding of material. Thus, in this online environment, the fact that students engaged with, perceived the values of, and spent a majority of their time doing homework is a positive outcome in terms of student learning online. It would be interesting to compare student performance and preferences to that of a face-to-face class with the same credit structure that offers all the mentioned support mechanisms (including videos) and regular (in terms of time as well as delivery mode) class meetings. This is an area of great interest and may be pursued for verification in future studies. Another area of interest is the lack of value that students placed on the discussion portion of the class. There were, in fact, two aspects of the discussion: a required component and an optional component. The students were only asked to comment on the required component, which consisted of students responding to an instructor “prompt” (a question, problem or statement). The 60 points total for discussion participation were distributed as follows: 3 responses (chosen by the student) were graded for quality (content and communication skills) by the instructor for a total of 30 points (10 points each). The remaining 30 points were given based upon timely and consistent responses to the prompts throughout the quarter. The prompts were designed to encourage students to think more deeply about the material and its applications. Some sample prompts are: “We know that two points determine a unique line. What if you have 3 points? How many distinct lines pass through at least 2 of the given points? Is the answer always the same? How do the various transformations (shifts, stretches and shrinks) affect the equation of a line and the graph of that line (think about the slope and y-intercept)?” and “Find two examples in the newspaper or online of automobile loan offers that require periodic payments and compare the offers.” Thus we see that “discussion” is somewhat of a misnomer for this portion of the course that does not fit the traditional definition of “discussion.” Students were encouraged to respond to each other’s postings but did not often do so. On the other hand, there were optional discussion boards where students could post questions and comments about the course. Because open discussion boards had only optional participation, it was not included in the weekly survey questions. However, in the final survey, “Instructor responses to your discussion postings” was among the course components rated for quality and contribution to overall learning. It is of note that for this final survey, the optional and required discussion boards were not distinguished. In terms of quality, these instructor responses were rated 2nd only to the homework with a mean score of 3.25 (1 = poor, 4 = excellent, SD = .78) while the Blackboard discussions had a rating of 2.59 (SD = .84). In terms of contribution to overall learning, Instructor responses were rated 5th (out of 7) for a mean of 3.64 (with 1 = not at all, 5 = a lot, SD = 1.46) while the Blackboard discussions ranked last overall with a mean score of 3.02 (SD = 1.37). Features of a face-to-face class that were lost in this online course were useful office hour interactions between student and faculty and partial credit on students’ solutions. While office hours were offered both online and face-to-face, students rarely took advantage of this availability. The online office hours were offered in chat format, limiting the ability to use the required notation for useful interaction, and students generally could not travel to campus to attend face-to-face office hours. It is certainly a difficult mode of communication for mathematics. However, students did interact with the instructor and each other on discussion boards. A potential solution to this problem is offered by a very promising communication software package titled enVision. This software allows for anonymous online communication between students and faculty with rich notational availability. One study (Hooper, et. al., 2006) reports that enVision sessions are more effective than traditional office hours. The software (freeware) allows any number of students to “attend” an online office hour and participate, or lurk, as they choose. Several strengths of the software are described as “Anonymity”, “Engagement and multiway dialog” and “Passive participation.” Incorporation of enVision into future offerings of the course here are being considered. Students’ open-ended comments about their online learning experience revealed that there was a great deal of disappointment over the lack of partial credit in the online homework. This will be addressed in future offerings of the course by requiring the final exam to be a traditional “paper and pencil” exam, graded by the instructor. There is also impressive work being done on creating and incorporating partial

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credit in computer-aided homework grading (Ahton, et. al., 2006) and (Livne, et. al., 2007). If these processes were to come to fruition, it would greatly enhance the online homework services currently offered. Conclusions The preference, satisfaction, and perceived impact on learning reported by students in this online class are encouraging for students and instructors of online mathematics courses. Students clearly felt that the course was demanding though time consuming. A large majority of the students rated the class as good or outstanding (50 out of 58) and an even greater majority found the class to be intellectually challenging (54 out of 58). This demonstrates that the course, while requiring a lot of work, was perceived as successful by most students. The strong preference for the active learning LO homework coupled with the perceived impact on learning of the lectures lead to the overall impression that the online environment offered these students an extensive, flexible and rich learning experience. While there are some areas of concern, the rate at which tools for instruction online are being developed leads the authors to believe that many will be addressed in due time. The findings in this paper point to a best practices model for online mathematics that strongly utilizes practice problems with fast feedback and integrates tools for content delivery such as media-enhanced lectures. This combination of LOs will provide students with the tools that they need to succeed online. Acknowledgements Both authors are grateful for funding from the Faculty Support Grants Program at CSUEB. The first author also thanks the members of the FLC for Best Practices in Online Teaching and Learning and the members of the FLC for the Scholarship of Teaching and Learning. The authors appreciated the reviewers’ comments and have incorporated their suggestions. We feel this has made a stronger paper. References Ahton, H., Beevers, C., Korabinski, A. & Youngson, M. (2006) Incorporating partial credit in computeraided assessment of Mathematics in secondary education. British Journal of Educational Technology, 37(1), 93-119. Bennett, K. & McGee, P. (2005). Transformative power of the learning object debate. Open Learning, 20(1), 15-30. Bonwell, C. & Eison, J. (1991). Active learning: Creating excitement in the classroom. ASHEERIC Higher Education Report No. 1, George Washington University, Washington, D.C. Cuthrell, K. & Lyon, A. (2007). Instructional strategies: What do online students prefer? MERLOT Journal of Online Learning and Teaching, 3(4), 357-362 (http://jolt.merlot.org/documents/cuthrell.pdf) Dennen, V. (2008). Pedagogical lurking: Student engagement in non-posting discussion behavior Computers in Human Behavior, 24(4), 1624-1633. Ellis, T. & Cohen, M. (2005). Building the better asynchronous computer mediated communication system for use in distributed education. Proceedings of the 35th Frontiers in Education Conference (pp T3E15-T3E20). Piscataway, NJ: IEEE. Friesen, N. (2003). Three objections to learning objects. Available online at: phenom.edu.ualberta.ca/˜nfriesen (accessed May 2008). Hodgins, W. (2000). Into the future. Available at: http://www.learnactivity.com/download/MP7.PDF, p27. Hooper, J., Pollanen, M. & Teismann, H. (2006). Effective Online Office Hours in the Mathematical Sciences. MERLOT Journal of Online Learning and Teaching, 2(3), 187-194 (http://jolt.merlot.org/vol2no3/hooper.pdf)

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Liber, O. (2005). Learning objects: Conditions for viability. Journal of Computer Assisted Learning, 21, 366-373. Livne, N., Livne, O. & Wight, C. (2007). Can Automated Scoring Surpass Hand Grading of Students’ Constructed Responses and Error Patterns in Mathematics? MERLOT Journal of Online Learning and Teaching, 3(3), 295-306 (http://jolt.merlot.org/vol3no3/livne.pdf) Parish, P. (2004). The trouble with learning objects. Educational Technology Research and Development, 52(1), 49-61. Pelz, B. (2004). Three principles of effective online pedagogy. JALN 8(3), retrieved May 2008 from http://www.sloan-c.org/publications/JALN/v8n3/v8n3_pelz.asp Prince, M. (2004). Does active learning work? A review of the research. Journal of Engineering Education, 93(3), 223-231. Saba, F. (2005). Critical issues in distance education: A report from the United States. Distance Education, 26(2), 255-272. Sahin, I. (2007). Predicting student satisfaction in distance education and learning environments. (ERIC Document Reproduction Service No. ED 496541). Swan, K. (2003). Learning effectiveness: What the research tells us. In J. Bourne & J. Moore (Eds.) Elements of Quality Online Education, Practice and Directions. Needham, MA: Sloan Center for Online Education, 13-45. Wiley, D. (2002). Connecting learning objects to instructional design theory: A definition, a metaphor, and a taxonomy. In D. Wiley (Ed.) The Instructional Use of Learning Objects. The Agency for Instructional Technology, Bloomington, IN, 4.

Manuscript received 30 May 2008; revision received 18 Aug 2008.

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This chapter provides a national picture of innovative learning options, such as dual enrollment and early college high schools. These options prepare high school students for college-level course work by providing supported early immersion in college. The chapter also discusses how such programs can help a wide range of students and highlights the importance of state policy in encouraging these efforts to create stronger connections among high schools, postsecondary institutions, and the workforce.

New Directions for Dual Enrollment: Creating Stronger Pathways from High School Through College Nancy Hoffman, Joel Vargas, Janet Santos There are a number of ways to increase high school graduation rates and put more students on the path to and through college. Most states are trying to do so by increasing the academic rigor of all their high schools. A first line of attack is to boost the academic requirements for high school graduation. Fifteen states are instituting a core curriculum that ensures that the default pathway through high school is a college preparatory sequence (American Diploma Project, 2007). Moreover, a substantial number of states are aligning high school graduation standards with the standards required to advance directly into nonremedial, college-level work. For example, thirty states are at work on such alignment through Achieve’s American Diploma Project Network (2007), and other states are engaged in aligning standards themselves. Some states use tenth- or eleventh-grade assessments to provide students with information about their readiness for college. And some states and school districts are mounting programs to recover high school dropouts and students who fall behind in earning credits: these students too need intensive academic work to meet the more rigorous standards required to complete high school and succeed in a community college. An emerging body of research and practice suggests that providing college-level work in high school is one promising way to better prepare a wide range of young people for college success, including those who do

NEW DIRECTIONS FOR COMMUNITY COLLEGES, no. 145, Spring 2009 © 2009 Wiley Periodicals, Inc. Published online in Wiley InterScience (www.interscience.wiley.com) • DOI: 10.1002/cc.354

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not envision themselves as college material. Increasing numbers of young people are taking advantage of such opportunities. In some states, such as Florida and Rhode Island, as many as 17 percent of high school students graduate with college credit (Vargas and Hoffman, 2006; Fletcher, 2006). If designed well, this college-level work in high school can: • Increase the pool of historically underserved students who are ready for college. • Provide realistic information to high school students about the knowledge and skills they will need to succeed in postsecondary education. • Improve motivation through high expectations and the promise of free courses. • Decrease the cost of postsecondary education by compressing the years of financial support needed. • Create a feedback loop between K–12 and postsecondary systems around issues of standards, assessments, curriculum, and transitions from high school to college. Across the country, increasing numbers and more varied students are taking part in accelerated learning options that provide college-level credit during high school. These options increase the likelihood that students currently underrepresented in higher education will enroll in postsecondary education. Data from the U.S. Department of Education (Adelman, 1999, 2006) indicate that the accumulation of twenty college credits by the end of the first calendar year of college is a strong predictor that a student will successfully earn a college credential. If the accelerated high school program is intensive—that is, if students gain twenty or more credits—it is our estimation that such credit attainment should also be highly correlated with the student’s likelihood of earning a postsecondary credential. In addition, such credit attainment is a strong indicator that the student is college ready—the goal increasingly set by states as the only sufficient outcome of high school. Some accelerated options also have the potential to better link secondary and postsecondary institutions and to point to better ways to integrate financing, data systems, and accountability mechanisms across K–16. Community colleges lead the way in making accelerated learning options available. First, their missions include outreach to high schools and service to their immediate neighborhoods and regions. Second, in many of the forty-two states with dual-enrollment policies, public community colleges, not four-year institutions, provide such opportunities. When they are not mandated to do so, community colleges are encouraged and supported in doing so. Ninety-eight percent of public two-year institutions had high school students taking courses for college credit, compared to 77 percent of public four-year institutions, 40 percent of private four-year institutions, and 17 percent of private two-year institutions (Kleiner and Lewis, 2005). NEW DIRECTIONS FOR COMMUNITY COLLEGES • DOI: 10.1002/cc

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In this chapter, we describe three such options: traditional dual enrollment, dual-enrollment pathways, and early college high schools. We then present cases of states and community colleges that have particularly interesting models for these options and review the evidence that such options can do what they claim: increase college success. Our organization, Jobs for the Future ( JFF), has worked over the past five years with several states and intermediary organizations that are implementing early college schools and strengthening their dual-enrollment policies. Based on this experience and national research, we discuss the lessons learned about practice as well as policy barriers and opportunities posed by the options. In each section, we highlight the key role played by community colleges as the leaders in facilitating these options. One final note is that dual enrollment is also called dual credit, concurrent enrollment, college in the high school, and joint enrollment. Dual enrollment, joint enrollment, or concurrent enrollment typically refer to high school students taking postsecondary courses, no matter what credit they receive. Dual credit refers to dual-enrollment course taking that results in both high school and college credit. College in the high school usually refers to college courses that are offered on the campus of a high school. Any of these program variations can fall under the umbrella of what some states call postsecondary, or accelerated, learning options.

Accelerated Learning Options: Definitions and Prevalence The term accelerated learning options covers a continuum of designs and approaches. Another common name for these options is credit-based transition programs (Bailey and Karp, 2003). The most intensive of these, early college schools, move students through at least the critical first year of postsecondary education and often through the second year. Dual-enrollment programs, although not as intensive, also provide exposure and access to college-level work to a large number of high school students. The most familiar of these accelerated learning options is dual or concurrent enrollment. These programs allow high school students to enroll in college-level course work and earn credit for it while they are still in high school. Students typically enroll in college courses in their junior and senior years. In most programs, courses result in dual credit: the college course replaces a required high school course, and the student earns credit for both. In some programs, however, students must choose between high school or college credit. Most dual-enrollment programs offer free or discounted tuition, providing some savings for families who otherwise might not afford to send their children to college. In 2006, the National Center for Education Statistics (NCES) published the first national study to attempt to capture the number of students participating in exam- and course-based college-level learning in high school. NEW DIRECTIONS FOR COMMUNITY COLLEGES • DOI: 10.1002/cc

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According to key NCES findings (Kleiner and Lewis, 2005) for the 2002–2003 school year, there were an estimated 1.2 million enrollments in courses for dual credit. If a student took multiple courses, schools counted the student for each course in which he or she was enrolled. Thus, enrollments may include duplicated counts of students. Overall, approximately 813,000 high school students took college-level courses through postsecondary institutions, either within or outside dual-enrollment programs. Using Kleiner and Lewis’s figures (2005), over 15 million students were enrolled in public and private high schools in the United States in fall 2001 (the last year for which data are available). Thus, dual enrollees represent about 5 percent of all high school students. If we assume most course takers are juniors or seniors, the percentage of dual enrollees among these students rises to approximately 13 percent. The NCES data are not state specific and therefore do not capture growth in dual enrollment in states that have a history of providing such opportunities and keeping dual enrollment data. In Florida, for example, participation has increased 100 percent between 1995 and 2003 (Florida Board of Education, n.d.). Although participation in community college dual-enrollment programs has existed for several decades, some states and community colleges have made changes in their purpose, structure, and visibility—previously they had existed as an escape from high school for advanced students—and reconceiving them as a path to college and technical education for a wide range of students. In this new configuration, dual enrollment becomes a central strategy for increasing college-going rates of local high school students. The expectation is that students will receive help in course selection and academic support as needed. In some community colleges, dual enrollees do not have to reapply once they finish their high school requirements. This sends a strong signal to students that if they succeed in their first course, they can go right on in the host community college. Dual enrollment has another advantage in making college access more equitable. In rural and low-income areas where advanced courses may not be available to high school students, accelerated learning options may be provided virtually or by high school teachers or adjuncts certified by a community college. For these reasons, a number of states are making the opportunity to earn college credit in high school available to every high school student in the state. A second structure for dual enrollment, and one for which there is not yet settled terminology, is what we call here dual-enrollment pathways. Within a traditional high school, students participate in a preselected sequence of two to four college courses, sometimes preceded by a “college 101” introduction to study skills. The pathway includes opportunities for those not likely to qualify for college courses before graduation—students who are at risk of graduating with weak preparation for college. In addition, such enhanced programs often reach out to middle school students, offerNEW DIRECTIONS FOR COMMUNITY COLLEGES • DOI: 10.1002/cc

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ing them programs that familiarize them with the demands of postsecondary education and the adventure of visiting a college campus. In dual-enrollment pathways, courses are carefully chosen to meet postsecondary career certificate or general education requirements in two-year institutions and to be transferable. For example, high school students might be required to enroll in foundation or gatekeeper courses, such as the first college-level math or English courses, which when successfully completed are highly predictive of earning a credential. The expectation is that students will require and receive substantial academic support and that taxpayers will receive a return on this investment as more young people enter the labor market with a credential, contribute to the state’s economy, and pay taxes. In terms of scale, dual-enrollment pathways are not as prevalent as traditional dual enrollment. To qualify as a true dual-enrollment pathway, students would graduate from high school with anywhere from one to four semesters worth of college credit. These programs are in very early stages of development and thus not yet widely known. Nonetheless, visible models exist. With over twenty thousand enrollments in college courses by high school students in 2004–2005, the City University of New York’s College Now program is the largest and most developed example of which we are aware (Meade and Hofmann, 2007). Middle colleges similarly build pathways, as do some tech prep programs. While also relatively small in scale, the third accelerated option, early college high schools, is proliferating quickly and garnering considerable attention nationally. Early college high schools currently serve over fifteen thousand underrepresented students in integrated pathways and will eventually reach over ninety-five thousand students. Like dual-enrollment pathways, they align and integrate course sequences across the sectors with the goal of promoting postsecondary completion. But unlike dual-enrollment pathways, early colleges are small, autonomous schools. They are designed so that students underrepresented in postsecondary education (low-income students, student of color, and first-generation college students) can simultaneously earn a high school diploma and an associate degree or one to two years of credit toward a bachelor’s degree tuition free. Each school is developed in partnership with a postsecondary institution whose courses make up the college portion of the student’s education. Students begin college-level work as early as ninth grade. Beginning in 2001, the Bill and Melinda Gates Foundation, in cooperation with state and local education departments, philanthropies, and nonprofit partners (including JFF, which coordinates the national initiative), have supported the growth of a national network of over 160 early college high schools in twenty-four states. Sixty-four percent of these schools are partnered with a community college and are on or near a community college campus; another 7 percent have both community college and four-year partners ( Jobs for the Future, 2009). In addition, a number of states are creating additional early colleges without external funding, largely in partnership with NEW DIRECTIONS FOR COMMUNITY COLLEGES • DOI: 10.1002/cc

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their community colleges; several states are using the early college model to reinvent career and technical education. Early colleges have three designs: grade 6 to 12 schools that incorporate two years of college within the same time as a student would complete a high school diploma; four-year programs that incorporate up to thirty college credits by the end of twelfth grade; and five-year programs that start in ninth grade and incorporate up to sixty college credits by the end of the fifth year, which takes place entirely on a community college campus.

Community Colleges and Accelerated Learning Options: Cases To demonstrate the variety of ways that community colleges are leaders in enabling the growth of accelerated learning options, we describe how two states and one system have implemented accelerated learning options. For dual enrollment, we turn to one of the most extensive statewide programs: Florida’s comprehensive articulated acceleration array of choices for high school students. For dual-enrollment pathways, we turn to CUNY’s College Now program with an emphasis on its implementation in the six community colleges among the twenty-three CUNY institutions. For the most extensive network of early college high schools within a state and one encompassing both transfer and career preparation, we look at the forty-two currently open Learn and Earn schools in North Carolina, thirty-seven of which are partnered with a North Carolina community college. Traditional Dual Enrollment: Florida. Florida has one of the most highly articulated and centralized public education systems in the country. In terms of accelerated learning options, Florida provides multiple means for secondary school students to accumulate college credit—Advanced Placement (AP), International Baccalaureate (IB), and dual enrollment. However, dual enrollment is perceived as a path to a postsecondary degree or credential not just for gifted students, but for those considered middle achievers or on a career or technical track. Dual enrollment grew from 27,689 students in 1988–1989 to 34,273 in 2002–2003. The growth in participation for African American and Latino students was especially high during this period (Florida Board of Education, n.d.). Florida legislation mandates that all twenty-eight community colleges and specific four-year institutions offer dual-credit courses (Florida Statutes, Chapter 1007.27, 2002). Approximately 80 percent of all dual-credit courses take place at the community college (P. Cisek to Janet Santos, pers. communication, November 2007). Students may attend courses during the school day, before or after school, or during the summer, thereby relieving overcrowding in high schools and maximizing flexibility to participate. Students can access Web-based information that provides guidance in choosing college courses. In some community colleges, dual enrollees do not have to NEW DIRECTIONS FOR COMMUNITY COLLEGES • DOI: 10.1002/cc

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reapply once they finish their high school requirements, a strong signal to students that if they succeed in their first course, they can go directly on in the host community college. The state provides incentives for postsecondary degree completion through its lottery-funded Bright Futures Scholarship Program (Florida Department of Education, n.d.). The Bright Scholars Program is a merit-based academic scholarship awarded to students based on high school transcript and standardized test scores (SAT or ACT). The program consists of three scholarship awards: the Academic Top Scholars Award, the Florida Medallion Scholars Award, and the Florida Gold Seal Vocational Scholars Award. Participation in dual enrollment receives the same weight as participation in AP and IB for the purposes of evaluating a candidate’s scholarship application. Dual enrollment is open to all public, private, and home-schooled students. The state has established eligibility guidelines recommending that general education students have a 3.0 grade point average (GPA) and that students pursuing a career certificate have a 2.0 GPA in order to qualify for dual enrollment. Florida also provides dual-enrollment funding for high school students enrolling in college-level English or math if they have passed the College Entry Level Placement Test (CPT), the math and English admissions exam for the state’s college system (Florida Statutes, Chapter 1011, 2002). Additional admission criteria are included in the articulation agreement between the community college and the local school district. Florida’s only restriction on course taking is that courses count simultaneously for college and high school graduation. The state’s Articulation Coordinating Committee (ACC), whose members are appointed by and report to the commissioner of education, is responsible for ensuring a smooth transfer of credit from high school to college. The ACC comprises representatives from all levels of public and private education: the state university system, the community college system, independent postsecondary institutions, public schools, and applied technology education. It also includes a student member and a member at large. It meets regularly to coordinate the movement of students from institution to institution and from one level of education to the next by evaluating high school courses, including AP, and assigns them equivalency prefixes and numbers that match comparable college courses. Standing committees are charged with such issues as postsecondary transitions and course numbering. Despite the prescriptiveness of Florida’s legislation, the implementation of dual enrollment varies by institution: some provide college in the high school, and others bring large numbers of high school students onto college campuses. Dual-enrollment students are exempted from paying tuition, matriculation, and laboratory fees (Florida Statutes, Chapter 1009, 2002). Each district and its community college partner negotiate how they will share the cost of dual enrollment (transportation, faculty salary, advising, and student support) through their articulation agreement. The state subsidizes the NEW DIRECTIONS FOR COMMUNITY COLLEGES • DOI: 10.1002/cc

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purchase of textbooks and other instructional materials only for public high school students, not for private or home-schooled students. Florida’s comprehensive K–20 education data warehouse is the nation’s leader in the linking of student-level data across K–12 and postsecondary institutions. The gathering of such information allows the state to generate reports analyzing the effectiveness of its dual-enrollment policy (and its implementation) in helping students meet set educational goals. For example, a 2004 descriptive analysis conducted by the Florida Department of Education found that high school students who participate in dual enrollment were enrolling in colleges and universities at rates significantly higher than students who did not participate. In addition, Hispanic and African American students who took dual-enrollment courses were enrolling in higher education at higher rates than whites or any other ethnic group (Florida Department of Education, 2004a, 2004b). The news is encouraging considering previous findings reporting that only 32 percent of this population of students go on to college within four years of ninth grade (Ewell, Jones, and Kelly, 2003). Such encouraging results led to a much more extensive study published in 2007 (Karp and others, 2007). Dual-Enrollment Pathways: College Now. New York State has no dual-enrollment legislation. But the City University of New York, the largest urban postsecondary system in the country, and the New York Department of Education, the largest urban school district in the country, have established a high school–postsecondary partnership that rivals in size those of entire states. CUNY’s College Now, widely recognized as a national model for an integrated K–16 system, is the country’s most extensive dualenrollment partnership (College Now, n.d.). Between the 2001–2002 and 2006–2007 academic years, enrollment for high school students seeking college credit at City University of New York’s College Now program increased by 109 percent, from 7,084 to 14,380 students. In 2006–2007, high school students completed 20,650 credit courses, and 68 percent of total college credit enrollments took place at the community colleges (T. Meade to Nancy Hoffman, pers. communication, January 2005; S. Cochron to Nancy Hoffman, various communications between October 2004 and March 2005). The CUNY colleges have long opened their doors to students prior to their completion of high school diplomas—sometimes to help them complete the diploma or GED program. CUNY’s Collaborative Programs comprise a continuum of college preparation approaches serving students at different developmental stages and with different needs: early college high schools, university-affiliated high schools (there are fifteen on or near CUNY campuses), and Gear Up serving cohorts in single schools. College Now is another example and offers a range of programs: summer arts and theater activities that acquaint students with college faculty, college culture, and college campuses, and, of course, dual enrollment. College Now’s mission is to help students meet high school graduation and college entrance requirements without remediation and to be retained NEW DIRECTIONS FOR COMMUNITY COLLEGES • DOI: 10.1002/cc

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through a degree. Begun in 1984 at Kingsborough Community College, College Now expanded in 1999 when the CUNY board voted to end remediation at CUNY’s senior colleges. The program was designed specifically to serve students who might not otherwise be able to attend postsecondary institutions and who receive inadequate college preparation in the city’s high schools. Most CUNY students are poor (average family income is $28,000), and retention and graduation rates are low even at six years from college entry. The centerpiece of College Now is its free, credit-bearing college courses. College Now differs from most other dual-enrollment options in that courses are not offered at random but are provided in a structured sequence with academic supports as needed. All credits are transferable within the CUNY system, but college courses do not necessarily replace high school courses. In 2006–2007, 29,040 students participated in the program, with 46,888 course and activity enrollments. (Activities include noncredit prerequisites to specific college courses and content-rich workshops, such as an English language learners history course, to aid in the statewide Regents exam preparation.) College Now models vary, but the largest, at Kingsborough Community College with 7,699 college credit enrollments in 2006–2007, teaches almost all its courses in high schools. Other College Now programs taught courses on college campuses. Student eligibility for credit courses is based on Regents exam scores, high school records, and other measures, including substantial personal advising. While the College Now philosophy is to be stringent about admission to credit courses, the rigor of courses, and the standards of exit assessments, the program provides multiple and widespread opportunities for students to prepare for these courses. Some College Now programs also help prepare students for English and mathematics Regents exams and offer noncredit developmental college preparatory courses. Early College High Schools: North Carolina Learn and Earn. North Carolina’s leaders are making dramatic changes to the state’s education system. A major thrust of these efforts is to prepare more young people for high-skills jobs by encouraging them to complete some college before high school graduation. This is a response to the decline of the state’s long-time economic engines—tobacco, textile, and manufacturing jobs—that used to provide family-sustaining wages for workers without postsecondary training or education. As the state tries to reinvent its economy and attract innovative, knowledge-intensive industries, it must strengthen the educational attainment of its workforce. To meet the challenge, the state has invested in early education, raised high school graduation standards, and increased K–12 accountability. It is also aggressively starting new high schools, creating or redesigning 150 schools designed to produce more graduates—and graduates who are on a path to complete college. Early colleges, most of them on community colleges campuses, are central to this effort. NEW DIRECTIONS FOR COMMUNITY COLLEGES • DOI: 10.1002/cc

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Since 2004, North Carolina has opened forty-two early college schools, known in the state as Learn and Earn schools. These currently serve about fifty-one hundred students, and the state plans to open thirty-three more (G. Coltrane to Joel Vargas, pers. communication, January 2008). Learn and Earn schools enable students to earn up to two years of college credit or an associate degree (A.A. or A.A.S. in some cases), along with a high school diploma, within five years. Students are reflective of local school district populations, and Learn and Earn targets students not normally found on a college path. In 2007–2008, the state invested $15.2 million in Learn and Earn. Starting in 2007, it also made college courses available at no cost to any North Carolina high school student using the Internet through Learn and Earn On-Line. Thirty-seven Learn and Earn schools are partnerships between community colleges and local K–12 districts; four work with fouryear institutions (G. Coltrane to Joel Vargas, pers. communication, January 2008). Given Learn and Earn’s extensive reach into the public college system, it represents both a large-scale high school redesign initiative and a significant investment by the higher education sector in preparing a world-class workforce ion North Carolina. North Carolina has long permitted dual enrollment through community college courses offered exclusively to high school students, and through a concurrent enrollment policy allowing juniors and seniors to take college courses with other college students. (These dual-enrollment courses are known as Huskins classes, named after the North Carolina Huskins bill that provided the enabling legislation.) These programs were designed to provide supplemental educational opportunities, particularly for students from rural communities. Without altering those programs, the state took steps that allowed Learn and Earn to design dual enrollment as an improved pathway from grades 9 to 14. For example, the state created the Innovative Education Initiatives Act in 2003, which authorized state support of cooperative education programming between high schools and colleges, including for accelerated programs such as early college and dual enrollment. This laid the groundwork for state approval of several policy exemptions for Learn and Earn schools. Thus, Learn and Earn schools have avoided policy barriers confronted by early colleges in other states that stem from uncoordinated secondary and postsecondary education policies. For example, Learn and Earn schools have received a waiver from a state restriction, sometimes found in other states, on dual-crediting college courses toward nonelective high school course requirements. North Carolina is also supporting the capacity of its early college schools to build and sustain strong partnerships vital to their design. Learn and Earn schools must use some state funds to support a liaison between the high school and college partners. The New Schools Project, funded with private and public funds, supports Learn and Earn school implementation NEW DIRECTIONS FOR COMMUNITY COLLEGES • DOI: 10.1002/cc

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and sustainability through leadership trainings, instructional coaches, crosssite peer learning, and other services. The project also facilitates data collection, advises on research efforts, and reports to policymakers about the progress of the initiative. Given the size of North Carolina’s effort, Learn and Earn will hold instructive lessons for other accelerated learning options nationally.

Research About the Benefits of Accelerated Learning Options What is the evidence that accelerated learning options are a means of improving college success? It is promising but still nascent. Many states and programs do not track or report dual-enrollment outcomes. Fewer have unit-record longitudinal data systems that are capable of telling whether dual enrollees have better education outcomes compared to nonparticipants who are otherwise similar in social and academic background. However, some studies that use longitudinal data are available, including recent research on each of the three accelerated options discussed here. The research strongly suggests that dual enrollment can prepare high school students for college and give them momentum in completing a degree or credential. Moreover, it shows that these benefits extend to groups who are typically underrepresented in college. Traditional Dual Enrollment. Researchers from the Community College Research Center studied Florida’s large statewide program (Karp and others, 2007). The state’s P-20 data system allowed the researchers to examine the postsecondary outcomes of 36,214 dual-enrollment participants from the high school graduating classes of 2000–2001 and 2001–2002 and compare them to similar students who did not participate. Dual enrollees who entered college were more likely to continue for a second semester and be enrolled two years after high school. At both milestones, former dual enrollees had higher GPAs than classmates with no dualenrollment experience. Dual enrollees also had earned 15.1 more college credits on average than nonparticipants three years after high school. Although it stands to reason that some of these credits were earned through dual enrollment, the researchers deduced that “it is also likely that some were earned after matriculation into postsecondary education” (Karp and others, 2007, p. 7). The Florida data shed light on the benefits of dual enrollment for underrepresented students because the program serves a wide range of students. Although participants must meet some academic requirements, they vary in their academic and social backgrounds. This variation enabled researchers to look at dual-enrollment outcomes for subgroups such as lowsocioeconomic-status (SES) students, African American and Latino students, and students with lower academic achievement. In terms of positive effects on first-year and cumulative college GPA, low-income students and those with the lowest high school GPAs benefited NEW DIRECTIONS FOR COMMUNITY COLLEGES • DOI: 10.1002/cc

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to a “greater extent than their dual enrollment peers who enter[ed] college courses with more social, economic, and educational advantages” (Karp and others 2007, p. 63). Low-income students also seemed to benefit more in terms of greater college credit accumulation. Dual-Enrollment Pathways. There are similarly positive outcomes from CUNY’s College Now. CUNY cooperates closely with the New York City Department of Education, including sharing data across the two systems. Using these data, CUNY’s office of Collaborative Programs Research and Evaluation has studied the postsecondary outcomes of College Now students who became first-time freshmen at a CUNY college during the fall of 2002 or 2003. The research compares participants to nonparticipants who otherwise had similar academic achievements when starting college (Michalowski, 2006). The evidence suggests that College Now puts students on a path toward college completion. Among first-time freshmen, participants were more likely on average to enroll for a third semester and had higher GPAs on average than their classmates with no College Now experience. They also earned more credit on average than nonparticipants by the end of their first year. First-time freshmen in 2002 and 2003 with College Now experience earned an average of 1.08 credits more at the end of their first year versus nonparticipants. These figures do not include credits acquired through precollege dual enrollment or AP programs, which conceivably would have increased the number of college credits reported for the participants of College Now. Most of these positive effects held for College Now students across achievement levels among those admitted to a CUNY campus. Other findings are notable from the Community College Research Center’s study, which included both data from Florida and CUNY. In addition to positive effects on retention and GPA, dual enrollment was positively related to enrollment in college for Florida students and was positively related to enrollment in a four-year institution for CTE students in CUNY College Now. Early College High Schools. JFF and the intermediary organizations supporting early colleges have been collecting data about early college students, but as the newest of the accelerated options, early college schools still have limited longitudinal data. These efforts include JFF’s development of a Student Information System for the Early College High School Initiative and the national evaluation of the initiative being conducted by AIR (American Institutes for Research) and SRI International. The oldest schools have just graduated their first classes of students (about nine hundred in all), permitting a glimpse at early outcomes. The data suggest that the schools reach underrepresented student populations and graduate them with considerable momentum toward a postsecondary degree. Early college schools overall serve students who are representative in race and SES of their local communities. National figures show that low-income students comprise at least 60 percent of all early college students, based on free and reduced-price lunch eligibility—a conserNEW DIRECTIONS FOR COMMUNITY COLLEGES • DOI: 10.1002/cc

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vative estimate of the number of students from low-income families since they rely on self-reporting by students and their families. If credit accumulation is indicative of eventual degree attainment, then early college schools have put many graduates on a promising path toward a degree. The vast majority (85 percent) accumulated between a semester and two years of college credit by graduation. The Middle College National Consortium, which supports some of the longest-running early colleges in the nation, reports that its students accumulate an average of thirty-one credits by twelfth grade and pass their college courses at rates of 92 percent with an average GPA of 2.78 (Middle College National Consortium, 2008).

Lessons Learned and Looking Ahead: Policy and Practice Beyond the benefits to the students themselves, accelerated learning options point the way to practices and state policies that can improve the alignment of the secondary and postsecondary sectors. The options are most likely to be supported and spread in states with certain policies and by the same token exemplify practices for improving college readiness and success that states may choose to expand through policy changes. Policies that are supportive of all accelerated learning options—early college schools, dual-enrollment pathways, and traditional dual enrollment— are guided by the recommendations of a state-level P–16 council, roundtable, or other body representative of secondary and postsecondary education. An essential starting point for policymaking is agreement on the purpose of these programs: ideally, to serve as a bridge to college for underrepresented students as well as a head start on college for those already on their way. A clearer purpose gives guidance to local partnerships and lends coherence to other policy decisions. Other policies that support local accelerated learning options include: • Encouraging dual crediting and the smooth transfer of college credits to other institutions of higher education • Ensuring tuition is not an obstacle for dual enrollees • Holding colleges and high schools harmless in financing dual enrollment so that they can provide joint support of dual enrollees, including through special efforts that recruit and prepare academically underprepared students for dual enrollment • Setting eligibility criteria that are agreed on by the secondary and postsecondary sectors and allow students to take college courses in subject areas for which they have demonstrated readiness based on a variety of measures • Promoting quality through policies that set minimum instructor qualifications and support teacher training NEW DIRECTIONS FOR COMMUNITY COLLEGES • DOI: 10.1002/cc

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• Collecting and reporting data on dual-enrollment participation and outcomes—best done with longitudinal, student-level data across high school and college At the level of practice, strong accelerated learning programs require several key elements to create feedback mechanisms and structures for collaboration across K–12 and higher education: • Formal structures that link a high school and a partner college such as a renewable partnership agreement; a person serving as liaison between high school and college; and a decision-making body to design, monitor, and collect data about the program • A feedback loop to high schools from postsecondary on student success: high school and college transcripts include college course grades and call attention to how well courses are sequenced between high school and college and how well high schools are preparing students for college work • Shared responsibility (financial and otherwise) by leaders in secondary and postsecondary education institutions for the continued collaboration From a narrow perspective, these practices and policies support promising accelerated programs that use dual enrollment. To be more speculative, if research continues to show that these programs have positive effects, they might be seen as indicative of broad-scale changes needed in practice and policy to build a more seamless P–16 education system for all students. Would not all local high schools and colleges benefit from regular collaboration to review and improve the efficacy of course sequences in preparing students for postsecondary? How could state finance and accountability systems be more integrated and engender joint responsibility for the successful transition of all students, especially underrepresented youth, through high school and college? That said, dual enrollment is no panacea and is not necessarily easy to implement. Dual-enrollment pathways and early college schools require that high schools and colleges work in close partnership, negotiating financing across the two systems and using dual enrollment as a laboratory for aligning standards across secondary and postsecondary education. These partnerships are challenging to build and sustain precisely because the country’s secondary and postsecondary systems are, by design, disconnected and uncoordinated. Their differing academic calendars, course schedules, crediting systems, and organizational norms can make partnership difficult. Accelerated learning programs have the potential to reconcile these divisions but are also constrained by them. These strategies also entail unique costs. Districts, colleges, or states must cover tuition and fees for college courses if dual enrollment is to be made accessible to lower-income students. There are also costs associated NEW DIRECTIONS FOR COMMUNITY COLLEGES • DOI: 10.1002/cc

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with maintaining the high school–college partnership such as employing a liaison who coordinates the alignment of curriculum, supports, and professional development across grades 9 to 14. Another challenge is that college courses offered through dual enrollment are only as good as regular courses offered by the college. Because there are no common content or learning standards across postsecondary institutions nationally or statewide, course quality takes special effort to monitor in accelerated programs. Despite these challenges, accelerated learning options are an important strategy for increasing the nation’s high school and college success rates because of their potential for bridging the secondary-postsecondary divide. Given their support of such programs, community colleges are well positioned to remain at the forefront of these efforts. References Adelman, C. Answers in the Tool Box: Academic Intensity, Attendance Patterns, and Bachelor’s Degree Attainment. Washington, D.C.: U.S. Department of Education, 1999. Adelman, C. The Toolbox Revisited: Paths to Degree Completion from High School Through College. Washington, D.C.: U.S. Department of Education, 2006. American Diploma Project. Aligning High School Graduation Requirements with the Real World: A Road Map for States. Washington, D.C.: Achieve, 2007. Bailey, T., and Karp, M. M. Promoting College Access and Success: A Review of Credit-Based Transition Programs. Washington, D.C.: U.S. Department of Education, Office of Adult and Vocational Education, 2003. “Early College Overview.” Middle College National Consortium. Retrieved Oct. 15, 2008, from http://www.mcnc.us/earlycollege_overview.htm. Ewell, P. T., Jones, D. P., and Kelly, P. J. Conceptualizing and Researching the Educational Pipeline. National Information Center for Higher Education, 2003. Retrieved February 25, 2009, from http://www.higheredinfo.org/suppinfo/Pipeline%20Article.pdf. Fletcher, J. “Dual Enrollment.” Presentation to the Florida House of Representatives, Jan. 11, 2006. Florida Legislature Office of Program Policy Analysis and Government Accountability, 2006. Retrieved February 25, 2009, from www.oppaga.state.fl.us/ reports/pdf/1–11–06_Dual_Enrollment_House.pdf, 2006. Florida Board of Education. Florida Dual Enrollment Participation Data. N.d. Retrieved Dec. 26, 2007, from http://www.flboe.org/news/2004/2004_03_10/DualEnrollment_ Pres.pdf. Florida Department of Education. Dual Enrollment Students Are More Likely to Enroll in Postsecondary Education. Tallahassee: Florida Department of Education, Mar. 2004a. Florida Department of Education. Impact of Dual Enrollment on High Performing Students. Tallahassee: Florida Department of Education, Mar. 2004b. Florida Department of Education. “2008–09 Florida Bright Futures Scholarship Program Fact Sheet.” Office of Student Financial Assistance, N.d. Retrieved Oct. 15, 2008, from http://www.floridastudentfinancialaid.org/SSFAD/factsheets/BF.htm. Florida Statutes, Title XLVIII, K–20 Code, Chapter 1007, sec. 1007.27. 2008. Retrieved Oct. 15, 2008, from http://www.flsenate.gov/Statutes/index.cfm?StatuteYear=2004& Tab=statutes&Submenu=1. n.d. Florida Statutes, Title K–20 Code, Chapter 1009, sec. 1009.25. N.d. Retrieved Oct. 15, 2008, from http://www.flsenate.gov/Statutes/index.cfm?StatuteYear=2004&Tab= statutes&Submenu=1. NEW DIRECTIONS FOR COMMUNITY COLLEGES • DOI: 10.1002/cc

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Florida Statutes. Title XLVIII, K–20 Code, Chapter 1011, sec. 1011.62. 2008. Retrieved online from http://www.flsenate.gov/Statutes/index.cfm?StatuteYear=2004&Tab= statutes&Submenu=1. Jobs for the Future. “A Portrait in Numbers.” In Early College High School News. Boston: Jobs for the Future, 2009. Karp, M. M., and others. The Postsecondary Achievement of Participants in Dual Enrollment: An Analysis of Student Outcomes in Two States. New York: Community College Research Center, Teacher College, Columbia University, Oct. 2007. Kleiner, B., and Lewis, L. Dual Enrollment of High School Students at Postsecondary Institutions: 2002–03. Washington, D.C: U.S. Department of Education, National Center for Education Statistics, 2005. Retrieved February 25, 2009, from http://nces.ed. gov/pubsearch/pubsinfo.asp?pubid=2005008. Meade, T., and Hofmann, E. “CUNY College Now: Extending the Reach of Dual Enrollment.” In N. Hoffman, J. Vargas, A. Venezia, and M. Miller (eds.), Minding the Gap: Why Integrating High School with College Makes Sense and How to Do It. Cambridge, Mass.: Harvard Education Press, 2007. Michalowski, S. Preliminary Interpretation of Regression Analysis on the College Now Program Conducted in Conjunction with Jobs for the Future. New York: City University of New York, Office of Academic Affairs, 2006. Vargas, J., and Hoffman, N. Dual Enrollment in Rhode Island: Opportunities for State Policy. Boston: Jobs for the Future, 2006.

NANCY HOFFMAN is vice president of Youth Transitions and director of the Early College High School Initiative at Jobs for the Future. JOEL VARGAS is program director at Jobs for the Future. JANET SANTOS is program manager of district, state, and national policy at Jobs for the Future. NEW DIRECTIONS FOR COMMUNITY COLLEGES • DOI: 10.1002/cc