Didactic requirements of learning environments: the web didactics approach of L 3

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1.1

Didactic requirements of learning environments: the web didactics approach of L3 Norbert Meder

1.1.1 Introduction This chapter outlines the web didactics approach developed for L3 and uses this as a basis to discuss quality aspects of web-based learning environments. They have been formulated, on one hand, from didactic traditions and, on the other, from experiences gained in the L3 project (cf. Meder, 2000a). They all refer to learning material, whereby this term also encompasses information, learning tasks and scenarios. The criteria are: media-compatible modularisation and granularity, decontextuality and coherence, fulfilling of SCORM standards, the explication of fundamental hypertext in metadata for the network nodes and boundaries (matching key words), adaptivity according to competence, cognitive and media learning style, individualisation of learning and the suitability of cooperative learning scenarios (storyboard). Of course, it can be said that all the quality criteria are requirements of learning environments, in terms of the L3 web didactics approach. If we begin to theorise about didactic ontology, then we must first identify the problems for which we are attempting to find theoretical solutions. These theoretical, but practically implementable, efforts form the core of the L3 didactic concept.

1.1.2 The problem The lighthouse project asks the question, to what extent can globally-available knowledge be used for further training. The fundamental technological platform for globally-available knowledge already exists: the WWW – and is increasingly used as a platform for providing global knowledge. In this sense, the WWW has developed into the basis for the globalisation of knowledge, into a universal, globally-accessible library. This is certainly advantageous, but gives rise to two problems. Firstly, the problem of the validity of the available knowledge, especially in terms of the imputability of an author or authority and, secondly, the problem of allocating available knowledge to further training tasks, to a problem in the workplace which is frequently characterised as a search problem and becomes ‘lost in hyperspace’. L3 tackles this last problem which incidentally is not just a problem for further training but for any search. It is, therefore, no wonder that a general solution to this problem is cur-

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rently being sought all over the world. The strategy of problem-solving has already been discovered or determined: metadata must be inserted into web sites or knowledge items to simplify and make searches more selective in finding information and, thereby, increasing knowledge bases. Metadata are information about resources and should characterise knowledge items so that more accurate ‘hits’ can be found in the respective further training context. As a result, the World Wide Web Consortium ( W 3C ), the IMS Global Learning Consortium ( IMS ), the Institute of Electrical and Electronics Engineers ( IEEE ), Ariadne, EML (Open University Niederlande and other EML approaches) are attempting to develop one standard in this regard. The framework architecture, the so-called Resource Description Framework ( RDF ) is designed to depict various forms of metadata and to integrate them into a uniform (technological) architectural framework. The IEEE has taken a similar approach with its Learning Object Metadata Working Group ( IEEE LTSC ), which is attempting to develop a special standard ( LOM ) for the preparatory work of the IMS for ‘educationally relevant’ material (‘learning objects’). There are other approaches to developing metadata sets for learning or educationally relevant material for the education sector. These approaches are primarily based on a metadata model developed as part of the ‘Dublin Core Metadata Initiative’, the so-called ‘Dublin Core’ ( DC ). Another task of L3 is to find a didactic and theoretical basis for a solution approach, which actually answers questions and meets requirements set in the standardisation committees. It should be noted that in the run up to the L3 project, work has been going on since 1990 to develop a metadata concept corresponding to Merril’s basic vision (Merril 1990a, 1990b, 1992a, 1992b), that learning material can be individually categorised and these individual categorisations can be supported by software and technology. We identify these individualisations in L3 learning strategies. We have resolved this problem within the realms of possibility: when the learner chooses a learning strategy, the hypertext is dynamically linked and on-demand learning paths are possible, such as deductive or inductive learning, exemplary or task-oriented learning and many other variations. The gravest misunderstanding of the metadata problematic is that it is simply the matching of keywords in learning material so that it can be deployed in traditional, mostly trainer-oriented learning structures. In truth, the WWW and its vibrancy stipulates something else: surfing in lexical information environments, in which information can be found inadvertently or in which we can become quickly lost – in short: learning as a form of natural discovery – just as unintentional and unnoticed as in everyday action environments. It is this main feature of the hypertext-based WWW, it being an environment for this type of approach to knowledge. If we were to view it as just a collection of material to be classified for slide shows and whole-class teaching, we would almost be thinking and acting against the medium. Of course, it is a question of organising, classifying and authorising the swathes of material on the WWW – not to print out teaching material for whole-class lessons but for surfing to discover learning, which allows me to self-direct my individual training processes through the professional organisation of knowledge. The aim must be a kind of autodidactic knowledge management.

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Here, we deliberately avoid talking about ‘learning’. This appears to contradict the guiding principle of the L3 project. But this is not the case. L3 = LifeLong Learning, returns learning to where it was before its institutionalisation: facing a world of problems to solve, in which the solution process was and should be improved by making the information and expertise required to solve the problem available at the suitable time and location. When this problem is solved, the required information can certainly be forgotten again, as long as it is stored somewhere so that it can be accessed again whenever it is needed. On this basis, an integrated teaching and learning environment was conceived in the L3 project, whose core forms a didactic ontology and supports authors in their efforts to develop optimal teaching and learning methods and also learners in their efforts to process self-organised knowledge. L3 always strives to provide both didactic and autodidactic support. No other international project has been able to produce what the results of L3 have: a metadata system, a didactic ontology, which is so fine that it really can make concrete learning processes describable, and which is so concrete that it ca model learning processes. As exceptional as EML , for example, is, it has no answer to the question of how learning can be concretely structured. However, the L3 didactic concept can. The option of using metadata to structure learning and training processes is self-evident in the L3 project and underlies the unique position of the L3 project. As a result, compatibility with the various standardisation attempts is no problem for L3 because the project responds to questions which other concepts leave unanswered.

1.1.3 Modularisation of the learning environment Modularisation is traditionally an educationally-didactic task based on the questions, in what time period, what content, with what tasks and in what social form the learning should take place. That is, learning units are traditionally differentiated in terms of how knowledge is medially conveyed in representation media (content/material), interactive media (tasks) or communication media (social forms).

An online learning environment must be measured against this degree of differentiation, which is already fulfilled by traditional teaching, especially since this medium optimally supports these types of learning unit – that is, through the presentation of media in multimedia mode, through interactive media, in particular in simulation mode (Meder 1995a) and through communication media for divided and distanced cooperation. This fundamental classification of training media forms a dimension in the differentiation of sub-

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ontology in the web didactics approach, as shown in fig. 1.1-1 (page 58). In addition to its media characteristics, it is a dimension which clearly shows the increase in the learners’ level of activity.

1.1.3.1 Granularity of the course and/or the size of learning material units An important issue in the modularisation process is the question of granularity, i. e. the size of the learning items. In order to answer this question and to determine the quality of the granulisation we use the following traditional and practical criteria: 1. Media compatibility, where the main practical questions are as follows: does the graphic fit on an A4 page? Can I get all the results on the board? Do images and text fit on the screen? Is this training film too long, will people be able to continue concentrating? Is the learning task still clear? Are communication channels for the task suitable for their purpose? 2. Reusability, where the main practical questions are as follows: can I use the text again next year or in another series of lessons? Is the image suitable in a different context? Is the example or learning task suitable for a different theory/explanation? 3. Researchability, where the main practical questions are as follows: can I store the material so that I can find it again for other teaching/learning tasks? Can I store it clearly under the correct matching keywords so that I can find it again for the relevant teaching/learning task? 4. Adaptivity, where the main practical questions are as follows: can the learning material on a topic or subject be used in such a way that it meets the learning needs of individual learners? Are the individual media suitably applied ad hoc? Can ad hoc and individualised learning processes be controlled by the learning materials? These main practical questions are deliberately formulated so that they are important for web-based learning, they are intended to show that traditional, professional didactics experts already ask these questions and think in terms of these categories. But examples clearly show that questions about the Internet as a medium and the dramaturgy of selfdirected learning are transferable.

1.1.3.2 Decontextuality of learning material units The issue of learning material granularity is closely linked to the issue of context-dependency. If learning content is to be used in the different contexts of teaching and learning, then it must be independent of the respective contexts. The best example of this situation is an encyclopaedia and its entries. These can be used in all corresponding life situations. But the same also applies to the dramaturgy of group learning, i. e. to scenarios in which

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learning is cooperative and divided. Brainstorming, the future conference or the open space conference and the fishbowl are context-independent so they can be used for different content.

1.1.3.3 Coherency of learning material units Decontextualised learning material must be intrinsically and extrinsically comprehensible. But this comprehensibility and intelligibility can only be relative, since too many possible references are excluded. This situation can be clarified: there’s a word in an encyclopaedia entry and after the word there’s usually a word which is explained in the encyclopaedia, with an arrow pointing diagonally upwards in brackets to indicate further reading if desired. That means a loss of reference or context is clearly shown by references, which then retrieve this loss. This technology is known as recontextualisation, it is well known in encyclopaedic logic. In web-based learning environments, recontextualisation follows the logic of the hypertext. Since this hypertext logic is fundamental for the Web, decontextualisation and recontextualisation, whilst taking account of coherence, is seen as one of the most significant quality standards for web-based learning platforms.

1.1.4 The application of metadata on learning material units The international debate about learning on the Internet reflects the issue of how educationally relevant material can be found on the Web, with all the information available. The solution to this issue is comparatively trivial: we need to view the Internet as a library and organise the available – and not yet available – information, just as the information in a library is organised. We have known about this for centuries, we simply need to transfer this system to the Internet. The core means of knowledge organisation in a library is matching keywords in documents. One keyword is a piece of meta information about a document. Consequently, in today’s IT language, keywords are known as metadata. In this context, keyword systems are referred to as ontologies which are in tune with the tradition of classification dating back to the Middle Ages. The international debate has since progressed so far that initial standards have been developed: the LOM and SCORM standards. LOM stands for Learning Object Metadata and SCORM stands for Shareable Content (formerly Courseware) Object Reference Model. In these terms, achieving a quality learning platform means fulfilling these rather low standards. LOM standards are primarily oriented towards bibliographic data, such as the title of a learning object, content of the learning object, producer/author, creation date, version etc. The required data on education/didactics is still very unclear. In SCORM , interfaces are fixed which allow learning content to be transported from one platform to another. The L3 web didactics approach is the only international attempt to standardise didactics-structured knowledge. It steps into the breach, left empty by LOM in the category of pedagogic metadata. Ariadne and EML proposals in this sector also lack the respective

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didactics concepts, with which the training process can be adaptively directed both at micro level in a didactics transaction (3 – 5 min.) and at micro level in a course or part of a course (approximately 3 hours learning time). As a result there are no references to international literature on the concepts developed here – with the exception of references to Merrill, who came up with the idea of this instructional design but found no solution, and the work of Fleschig and Haller, from whom the fundamental concepts (metadata) of knowledge organisation were taken and developed further.

1.1.4.1 Metadata according to L3 The didactically relevant data can be specified in terms of the following metadata, as developed during the L3 project, by refining the LOM standards (Meder 2000b, Meder 2001). They are subdivided according to the dimension of media differences already outlined in the context of modularisation: Metadata with regard to receptive media types (see fig. 1.1-3) Metadata with regard to interactive media types (see fig. 1.1-3) Metadata with regard to communicative media types (see fig. 1.1-3) Parallel to these types of media, different forms of knowledge can also be determined: types of knowledge as answers to learners’ questions, assignments as interactive forms of knowledge and scenarios for group work as forms of communicative knowledge: Metadata with regard to types of knowledge (knowledge type) (see fig. 1.1-4) Metadata with regard to types of assignments (assignment type) (see fig. 1.1-5) Metadata with regard to forms of cooperation (cooperation type) Irrespective of these intuitively comprehendible differences, the learning aim dimension or target competence should be characterised by metadata. Metadata with regard to target competence This full differentiation conforms to the above-mentioned, traditional, didactic standards, as can be found implicitly or explicitly in almost every didactics teaching book. Data on the target competence are also required. A differentiation of largely formalised competence levels – from 1 to 7, as became apparent – and of yet to be defined qualitative competence types, is appropriate here. In the vocational training sector, a workplace skills list, role description or group of functions could be considered.

The question arises, in which systematic are the metadata for a learning object located. Traditional didactics answers this question using 5 categories (these are the matrix lines in fig. 1.1-1).

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A learning object must be defined 1. in the subject category, i. e. there is a thematically-formulated problem, under which the learning object can be classified; (semantic category, the ‘stuff’) 2. in the target category, i. e. there is an ability (a competence), which correlates to the learning object; (pragmatic category) 3. in the category of knowledge type, i. e. there are answers to special questions and problems: know what, know why, know how, know where and others in learning material, assignments and group learning scenarios; (knowledge organisation category) 4. in the category of media presentation forms, i. e. there is at least one media in which the knowledge content can be shown and conveyed so that it can captivate in sensory terms; (media category/vividness) 5. in the category of progressive forms of teaching and learning, i. e. there are methods – in definite terms – of defining the sequence of knowledge appropriation via relations between the learning materials; (relational category). While the first two categories largely define the results of the appropriation process (in facts and ability), the last three categories directly or indirectly define the progressive form of the appropriation process and, consequently, the core problem of teaching and learning as a representation of the factual structure during the appropriation period. This representation is defined threefold: via the knowledge type as an answer to questions, via the media presentation of the answer and via the logical structure of the answer sequence (i. e. the methods in a narrower sense). On this basis, it ensues that a learning object is defined fivefold: in terms of problem-oriented topics (1), competence-oriented pragmatism (2), knowledge-oriented pragmatism (3), media presentation (4) and methodical operation (5).

This fivefold categorical defining of knowledge items in the context of learning can and must be viewed again in another dimension, mentioned many times previously. It is defined through the learner’s activity form: does the learner only intend to learn receptively, does the learner want to interact with a machine (relatively anonymously) or does the learner want to communicate and work with other people via the Internet. 3 + 2 ≈ 3 = 9 metadata sets (according to multi-field technology) result from a combination of the two dimensions (see fig. 1.1-1), making the didactic action correlation fully describable.

If we understand2 ontologies to be theories, which can be formalised individually – as is currently being observed in practical computer science – then the ‘existence’ of learning objects is defined by their predicates through metadata in nine categories and can be classified in two dimensions. The entities (knowledge items) are not explicitly defined by this and also cannot be individually defined3 within the ontology, from a theoretical point of view. We can only define them through classification from a meta-theoretical point of view. This is what we intend to do in the following.

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Definition: We understand a didactic entity to be a knowledge item, which, on one hand, is defined fivefold according to pedagogic categories and, on the other, is differentiated from knowledge items in three social forms. This second dimension is arranged according to: receptive items corresponding to the size of an on-screen page intrinsically interactive items corresponding to the duration of the smallest interactive training sequences, in person-to-machine mode (up to 3 min.) person-to-person cooperative items which are defined by the item of communicative tasks and problems (over an undetermined period) This second dimension of differentiation is not only pragmatically motivated and systematically defined by a general differentiation in terms of dramaturgy and the degree of activity (see above), but is also defined according to the media differentiation of presentation media, interactive media and communication media. These three types of knowledge items must be defined in ontology as learning objects in semantic terms, according to competency, according to the type of knowledge, according to media and its factual operation. This produces the systematic shown as a table in fig. 1.1-1, which represents the entire framework of a didactic ontology. The relational linking of learning objects is outlined in the LOM standards under the category of ‘Relations to other materials’. In contrast to L3, the learning material is not precisely defined: this could be a course, a learning environment, a learning unit or knowledge item. In L3, these terms are clearly outlined. A learning unit represents a number of knowledge items on one subject (semantic keyword). A course is an organised number of learning units or parts of courses, a learning environment is the technically, socially and semantically structured setting for training processes which can be individualised. Here are the definitions in detail: Fig. 1.1.-1: Metadata dimensions in L3 Receptive knowledge items Subject category

Competence category

Interactive knowledge items

Cooperative knowledge items

Three or multi-stage thesaurus

Degree of difficulty and description of activity or role

Media category

Presentation media

Interactive media

Communication media

Knowledge category

Type of knowledge (answers to questions)

Type of assignment (filling in gaps)

Forms of cooperation (knowledge communication)

Relational category

Subject relations between the learning units and didactic relations between the knowledge items

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1.1.4.2 Definitions of a learning object Definition: A learning environment is a media and socially communicative content environment for adaptive learning and training processes. Definition: A learning platform is the technical or technological part of a learning environment. Definition: A learning arrangement is the entire complex, institutional and application-oriented embedding of a learning environment. A learning arrangement can also be defined as the circumstances of a learning environment.

Definition: A didactic learning object is a knowledge item or a collection of knowledge items (learning units), which, on one hand, are defined fivefold according pedagogic categories (see. fig. 1.1-1) and, on the other hand, are different from knowledge items in three media activity forms.

Definitions: 1. On a subject-oriented level, we talk of learning units being defined by topics and their corresponding keywords or classification and the associated competence. 2. Under the learning units, i. e. classified below the topic, on a didactic level so to speak, we talk of knowledge items which define ‘appropriated’ access to the subject by the type of question (knowledge type) and by the type of visualisation and media (media type). 3. In terms of this double-level viewpoint, we call this thematic, i. e. subject and competence-oriented level, the macro level. 4. The knowledge and media type level, through which the differential access is structured, is known as the micro level. 5. The structure and organisation of the learning units is known as the macro structure (coarse structure) of the learning environment. 6. The structure and organisation of the knowledge items within a learning unit is called the micro structure of the learning environment. 7. Sub-courses subsume learning units and other sub-courses into larger structures, i. e. sub-courses can be nested. 8. A course is the transitive cover with respect to the nesting of sub-courses. This differentiation of terms, as laid out in the above definitions, forms part of didactic tradition, as outlined above, and forms the basis of the didactic ontology. If this differentia-

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tion of terms is not adhered to, a positive quality assessment will not be achieved. If printed course texts are sent online in ‘ PDF ’ format only or CBT s are provided in web technology, the quality requirements will not be met against a background of hypertext options – however well didactically the PDF file or CBT is internally designed.

1.1.4.3 Metadata in the subject category Metadata in the subject category is established largely pragmatically in work with the material it appropriates. An index of matching keywords from the learning material (websites) is created. This kind of index is also known as a postindex because it will be created from work with the content. In contrast, there is also the preindex work principle. This is predetermined before working on the content, and the creation of content as well as work on the material must be oriented towards the preindex. The latter assumes expert and profession-specific thesauri; these are systematically organised keyword systems. They prove themselves for knowledge sub-sectors, but the preindex form of structuring appears to be impossible for overall global knowledge. In any case, attempts at universal classification, universal thesauri or so-called encyclopaedia have, up to now, either failed or been unsatisfactory. As a result we prefer to work with a postindex in the subject category of learning environments, so that the metadata is established pragmatically in line with the creation of online learning material. This can also occur in orientation towards predetermined, didactic keyword systems so that a mix of preindex and postindex ensues. As a result of all these problems, L3 provides no predetermined metadata system for the subject category. The metadata must be specifically configured by didactics specialists according to a default training problem.

1.1.4.4 Metadata in the competence category As with metadata in the subject category, no metadata system can be predetermined in the competence category. In further training, the competence profiles required in the workplaces of different companies are all very different. Consequently, it is the task of the individual company to configure the metadata in question, according to their knowledge requirements, as part of their knowledge management systems. A competence level could be predetermined and oriented towards cultural and maybe even intercultural educational achievements. The latter is being attempted as part of international standardisation with the concordance of international educational achievements. Whether or not this is successful remains to be seen.

1.1.4.5 Metadata in the media category In the media category for the distribution of learning material or content of educational processes, the fundaments are already in the body of the text. The following fig. 1.1-3 specifies the main divisions of currently-known forms of media presentation: presentation, interaction and communication media. The details are primarily self-evident, further knowledge of these details is not important for the rest of this book.

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Fig. 1.1-2: Metadata in the media category

text dynamic table table static table knowledge map diagram graphical model picture animated picture single image image non-animated slides slides animated slides stopped movie non-stopped movie speech music sound

interaction media

simulation programmed instruction form interactive video

presentation media

movie

media

audio

communication media

synchronous

chat snap chat application sharing audio conference video conference

asynchronous

e-mail mailing list black board

1.1.4.6 Metadata in the knowledge category Learning and education processes always have something to do with, or are even central to, knowledge development, if the term knowledge is to have such a broad meaning, as it does in cognition theories (cf. Meder 1994). Knowledge then encompasses declarative, explicit knowledge as well as operative and cooperative implicit knowledge. As a result, the classification of knowledge items should be especially cultivated in a web didactics approach. Against this background, in L3 the sub-ontologies for the receptive types of knowledge, for interactive knowledge in learning assignments and tests and for communicative knowledge, were developed in teams and partnerships. Receptive knowledge items give answers to posed questions. The knowledge type is defined according to the type of question posed, for example: ‘What is there, anyway?’ or ‘Is there anything?’ ‘Why is something the way it is?’ or ‘What happens when something’s wrong?’ ‘How is it applicable?’ ‘Where can I find more information?’ The 4 main categories of knowledge types derived from these questions are: 1. Orientation knowledge helps learners to find their way around a subject while attaching no importance to acting in a subject-specific manner. Orientation knowledge provides the corresponding facts, but the learner may not know what to do with them. Orientation knowledge provides, for example, an overview or a summary; it supplies pure facts or presents subject-specific scenarios. 2. Explanation knowledge provides learners with arguments to explain why something is the way it is (‘know why’), i. e. arguments with which claims and recommendations are supported. In western cultures, scientific explanations play a special role, in particular when models are used to combine the causes with effects and aims. Explana-

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tion knowledge encompasses scientific explanations as well as humanistic comprehension. 3. Action knowledge helps learners to appropriate subject-specific practices, methods, techniques or strategies. It refers to real action by people (‘know how’). Sometimes the terms ‘abilities’ or ‘skills’ are used. Action knowledge encompasses knowledge about reasonable aims and targets, about conditions in which human action is appropriate, about procedural methods and operations, about aids, control procedures and quality criteria as well as sources of danger. 4. Source knowledge shows learners where they can find additional/more detailed information on a specific subject (‘know where’). These four fundamental knowledge types can be refined even further, as shown in fig. 1.1-3. Fig. 1.1-3: Knowledge types statistics report protocol doc. reference dictionary entry manual reference on communication

history scenario archive reference reference

appendix glossary conclusion proof

orientiation

cross reference

explanation why

description

facts summary overview

knowledge type

proposition/theorem mathematical def. item def.

hypothetical situation story virtual world

rule explanation what

definition

procedure

example counter example

explanation

action

administrative direction operating instructions

case study

argument(ation) assumption hypothesis reflexion comment interpretation

check list principle strategy law regulation law annotation

As interactive knowledge forms, learning and test assignments should always be viewed in such a way that incomplete, declarative knowledge is presented and must be completed by learners. Supporting the construction of learning tasks is not the intention of the L3 project. However, we have depicted the developed ontology in fig. 1.1-4 as we suggest it be introduced into the standardisation process.

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Fig. 1.1-4: Task types

sequencing exercise ordering exercise

construction exercise

sentence construction technical construction document construction

association exercise multiple choice test single choice test yes-or-no question

formal aspect design aspect subject-matter aspect

choice test

tests or exercises answer test locate errors find the difference problem solving

quiz long answer execise instructional game spelling exercise fill in the blank

discovery exercise without limitation double negation distinction exercise with limitation

by meaning by comprehension

Cooperations are learning and test assignments with even less declarative knowledge than traditional learning and test tasks, which occur in human-to-machine interaction. This increased incompleteness – as is the experience and hope of the didactics experts – can only be overcome and made compete if more learners input more individual ‘distributed knowledge’ into the group’s ‘shared knowledge’ when fulfilling group tasks. In this chapter, we will not go into cooperation forms in more detail; they are dealt with in chapter 1.2.

1.1.4.7 Metadata in the relational category: Outlining relational importances during the learning period The technology of making learning material relational solves the core didactics problem, and more still, the problem of the relational correlation of learning material has been the central question posed in the theory of didactics. Since each correlation of learning material occurs either at learning unit level, i. e. at thesaurus level, purely factual, better: factual rules or at knowledge item level with purely problem-oriented and media rules for presentation. Whatever level we look at, in both cases there is a high degree of complexity in terms of relational networking, in particular, of multidimensional networking. So a reduction in complexity is required for possible learning and education routes. This is not just for quantitative reasons but also for structural reasons. At learning unit level, there is a semantic network structure (semantic spatial structure). This network is multidimensional but learning is one-dimensional, it follows the linear period of experience. So, in structural terms, a multidimensional configuration must be portrayed in the one-dimen-

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sionality of time (Meder 1997). This is precisely the didactics problem, i. e. every didactics theory must adhere to this principle: Didactic action is the depiction of relational importances (semantic networks) in the (linear) period of material acquisition. All the theoretical details of a structural didactic must be derived from this basic principle or gained through analysis. Old didactic conflicts between material didactics and theoretical learning methods are attributed to this theoretical basis, since the overall task of didactics is to convey this; to portray the material during the acquisition period, i. e. during the methodically structured period oriented towards learning. It is clear that work on the learning material dominates against a background of self-organised acquisition in web-based environments, since all we know about learning sequences must be edited into the structure of the material because, as didactics experts, we are not present in the learning process, so we are not able to intervene at the time. This means that we have to incorporate possible learning routes into the structure of the material. In L3, the technology that makes this possible has been implemented through software. Here, the semantic area for metadata has been described so as to allow representations to be oriented towards learning demand during the period of acquisition.

1.1.3.7.1 The representation of relational importances during the learning period: deductive and inductive learning Definition: We call the route a learner takes through the semantic network (through the material) learning navigation or just navigation. We call the leading navigational viewpoint, its orientation to a principle, a learning strategy. Fig. 1.1-5: Metadata in the relational category generalizes is sub-process of is aspect of is part of is similar to is alternative to is analogous to

has part

hierarchical relations (asymmetric)

side by side is opposite of is function of

subject-matter relations symmetric

relations association relations

determines is means of is before is context of is process of is evalution of/for

asymmetric

didactic relations

didactically before (asymmetric) is prerequisite of (asymmetric) belongs to (symmetric)

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Navigation through the material can occur according to subject-related stipulations (the subject dimension in the tabular system), then the orientation is called a macro learning strategy because it describes the route through the learning units, i. e. operating at macro level. The necessary correlations are shown by typified links between the learning units or sub-courses, i. e. by references, which can be explicated as subject-related relations, as defined by German industry standards (see fig. 1.1-7). This type of macro learning strategy may proceed along hierarchical relations: ‘from generalities to specifics’ or ‘from the whole to a part’, then they are known as deductive, top-down or holistic. But they can also function inversely, in which case navigation occurs ‘from specifics to generalities’, bottom-up or elementaristically, and we call the macro learning strategy inductive. This is the most trivial didactics example we know. Of course, it can be modelled with software, if we only consider the metadata for the relations between the different, subject-related learning material. The same applies to other learning strategies, such as ‘constructive’ or ‘reconstructive’ learning or for contextual or spiral learning and others. Macro learning strategies for the acquisition of material following a subject-related ductus After everything we have detailed up to now, only the following quality requirements can be set: the subject-related ductus should contain several variations, the subject-related ductus should open up a new area of operation, in which the learner can operate as freely as possible, i. e. only restricted by the subject. The subject-related ductus should be variably and adaptively directed through the restrictions of the operation area. Operative navigation should facilitate strategic thinking, creativity and heuristic operations, it should allow potential, problem-oriented learning to proceed, just in person, just in situation – just in working.

1.1.4.7.1 The representation of relational importances during the learning period: the employment of didactic relations In the micro sector of learning, i. e. in the core of a learning unit, we differentiate between different questions in terms of learning material (knowledge types), different presentation media with respect to the material, different learning assignments (interactive media) and different scenarios for cooperative, distributed learning. Since all these forms of acquisition are unspecific to the subject, the appropriation of correlated learning material cannot be structured in a subject-related manner either. We need didactic relations, such as ‘is a prerequisite of’ as an obligating sequence, ‘prior to didactics’ as a recommended sequence for guided tours and ‘belongs to’ for classifying learning material, e. g. from action knowledge (know how) to explanation knowledge (know what). The didactic dramaturgy of the learning material must be arranged in the social dimension, we must be able to present the logic of media and knowledge types (space-time-dimension). We refer to the associated organisational criteria as micro learning strategies. For the micro learning strategies defined in L3, the ‘is a prerequisite of’, the ‘prior to didactics’ relations and ‘belongs to’, as a symmetrical relation, suffice as targeted relations.

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How the micro sector of learning is structured with the aid of these relations cannot be shown in detailed here. It should merely be mentioned that approximately 50 different micro learning strategies can be modelled with these relations and the characterisation of knowledge items via their metadata. This includes action-oriented, task-oriented, example-oriented learning and, equally, instructional design (see fig. 1.1-6). Fig. 1.1-6: Instructional Design as an example of a micro learning strategy

explanation

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Variations in the dramaturgy of the learning process have not been considered in detail for the portrayal of facts with so-called intended Points of Cooperation (iPoC) in social areas, as explained in chapter 1.2 Storyboards or staged scenarios, the dramaturgy of question/ answer, the dramaturgy of brainstorming, the dramaturgy of problem and solution, the framework story (narrative knowledge elements), the sequence of stories, the excitement element in narratives and the surprise effects have not been calculated. The role of storyboard or staged scenario, the information content of the stories for learners, background knowledge, orientation knowledge, meta cognitions, realistic versus fictitious (framework), learning through assignments, problem-solving in simulations and in virtual worlds – all these are further viewpoints for the quality of the learning material or the learning of such material, which is accessed in L3 through sub-ontologies. Navigation of the learning process via assignments deserves particular attention. In quality assessment, it is a question of considering the degree of activity, the complexity, the preciseness (adequateness) and the appropriateness of the (didactics) reductions in terms of their variability, intensity, congruence or realism towards task-oriented learning. In the micro sector of learning, navigation of the learning process via media play a crucial role. It is important to consider criteria which comprise the information density (semantic per period), the coding density (semiotic per area and period), the preciseness (adequateness/grammar), sociality per area and period, clear focussing on (didactic) reduction, acceleration and slowing down of the presentation of information, the compactness and equalisation (retention) as well as emphasis and expansion.

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1.1.5 Quality criteria for web-based learning environments Here is a summary of the vital quality criteria for web-based learning environments: Differentiation in learning units, i. e. the number of different knowledge items on one subject, which is an indicator for learning access to the material to be acquired (see following example), the plurality of knowledge types as well as the multimedia composition (Meder 1995b) in the visualisation of learning material, which is also an indicator for the differentiation of learning access to material to be acquired, the subject-related structure of the metadata in learning units (thesaurus/competence) and the relations of learning units within course units (correct and complete), which lead to organised amounts of subjects. These main quality criteria are more comprehensible with the following example. Let’s take an online course on constructing a rainwater re-processing unit, which provides a web-based learning environment for an installer of sanitary, heating and air-conditioning units and can use it to keep himself up-to-date with the latest technology. In this kind of learning environment, the word ‘water filter’ will occur. In the L3 web didactics approach, this subject forms a learning unit. What knowledge would the user expect to find on this subject, what knowledge items must the web didactics expert provide? We would certainly expect a knowledge item to provide an initial orientation on the subject. This might look like this: Orientation knowledge/ text: under water filters in rainwater re-processing units, there are the following alternatives …, whereby the following should be noted … etc. Orientation knowledge/ image sequence: the different filters used in a rainwater re processing unit are displayed in a kind of slide show. Of course, we would need explanation knowledge on the water filter. Explanation knowledge/ text&image/ level: trainee: explains how a water filter is constructed and how it functions using a construction diagram. Explanation knowledge/ text/ level: expert: deals with the specific characteristics of different construction and function types. In general, an image is no longer necessary. Explanation knowledge/ text&image/ level: tradesman: … The most important information could be the action knowledge. Instructions/ video/ level: tradesman: a video shows how the water filter is installed. Installation rules/ image&text/ level: expert: tips and tricks are explained, for example, when so and so is the case, then do this or that! Etc. Checklist/ text/ level: tradesman: check and tick off the following points for assembly control and quality assurance (signed at the bottom) ... Example/ text&sound/ level: trainee: using a rainwater re-processing unit in a detach-

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ed house as an example, the problems of choosing, installing and controlling quality of water filters are clarified and explained. Example/ text&sound/ level: tradesman: using a rainwater re-processing unit in a block of flats as an example, the problems of choosing, installing and controlling quality of water filters are clarified and explained. Example/ text&sound/ level: expert: using a rainwater re-processing unit in a factory as an example, the problems of choosing, installing and controlling quality of water filters are clarified and explained. Learning task/ text&graphic/ level: tradesman: in a problem-oriented practical situation, a decision needs to be made about the most appropriate water filter and its installation etc. Test/ text&graphic/ level: tradesman: in a problem-oriented practical situation, a decision needs to be made about the most appropriate water filter and its installation etc. Test scores will be awarded. Multiple choice test/ text&graphic/ level: tradesman: knowledge of the learning unit is examined in a practical multiple-choice test. Test scores will be awarded. Tutorial discussion/ video conference/ level: any: providing advice on the rainwater reprocessing unit and/or linking the problems of choice, of installation and quality control of water filters. Learning project/ chat&application sharing/ level: trainee: in separate trainee groups, use of the filter in a large rainwater re-processing unit is planned and documented. Source knowledge/ text/ level: any: tips on other areas in lists, on the Internet, from manufacturers, wherever information about water filters can be found. This examples clearly shows how quickly micro sectors within the learning unit can become very diverse and complex, when web didactics experts constantly bear in mind that different target groups need different levels, and that different problems and issues need to be addressed. For traditional didactics designers, this will certainly be strange and new because they are used to working according to standards for particular target groups, particular problems and at particular levels. It means a fundamental paradigm change in didactics design and that, in a web-based learning environment, all the parameters of didactics design are varied and the variations are made available as individualised access to the subject. This creates a micro learning environment, which, on one hand, anyone can find his or her way through or can achieve access to, and, on the other, one which is so complex that the user must be given more support to reduce this complexity. But as educators and didactics experts, we are used to that. First of all, we assemble the entire complex range of possible access points to particular information so that everyone can see what’s what, and are then ready to help, if needed, to further reduce the individual complexity. One of the core issues of web-based learning environments is whether this reduction in didactic complexity can be supported with user-related software, i. e. algorithmically. In L3 this occurs using micro learning strategies. Points c) and d) refer to the macro learning sector. In these cases, the learning units form modules that need to be classified according to subject. It is not a question of the

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plurality of the knowledge types, nor of the differences in media presentation, interaction or communication, or even of the different levels of competence, but of the factual relations between the various subjects, of the relation between key words (metadata) in a thesaurus. In this context, quality means linking as much and as complexly as possible so that there are as many routes through this semantically occurring network as possible. The individual relations (cf. fig. 1.1-7) are selected so that they also have a didactic importance. This cannot be detailed in full here. But at least one or two examples should clarify this. If you want to facilitate constructive, modular navigation through the material, then the learning units (content pages) must be linked with the criteria, ‘a builds on b’, ‘a determines b’ or ‘b forms the basis of a’. If you want to facilitate a kind of spiral didactic navigation, then you need learning material which is linked with contextual relations – with ‘enlargement’ and ‘narrowing’. Deductive and inductive navigation is explained in section 1.1.4.7.1.

1.1.6 Conclusions on didactic knowledge organisation The main quality demands on web-based learning environments are: information must be pre-processed for learners in terms of Internet logic. This logic is hypertext logic, which is a special logic for the lexicon. In adapting this for learners, i. e. in order to individualise acquisition, metadata can and should be used which is compatible with current international standards. The learning environments can then be dynamically created via the metadata so that they meet the demands of learners. If the learner is more of a holist then he or she can learn deductively; if the learner tends more towards theory, then he or she can choose the theory-driven instructional design. The knowledge basis, which can also be transferred to the knowledge management system in a company or organisation, can be adapted to various learner types, where the respective learner type can be represented by the metadata logic. This is not always the case, as with socratic-discursive learning, but predominantly, as shown in examinations of the Bielefeld-Duisburg web-didactics approach.

Footnotes 1 Compare also with ‘Interaction Analysis’, ‘Operations Analysis’. In: Grzesik, J./P. Fleischhauer./N. Meder, Interaktions- und Leistungstypen im Literaturunterricht. Eine handlungstheoretische Feldstudie unterrichtlicher Komplexität. Opladen 1982, p. 37–165 and p. 439–504 2 In his transcendental philosophical approach, Kant called these metaphysical rudiments, i. e. sector-specific metaphysics. 3 For example, where set theory is not able to determine the terms ‘set’ and ‘element’.

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