The focus of the DaMiT project is the development of a computer-based tutor system to support ... which form the adaptive interface of the user. .... [DuT01] A. Düsterhöft, B. Thalheim: Conceptual modeling of internet sites, Proc. ER'2001,.
LOGISTICS FOR LEARNING OBJECTS Bernd Tschiedel, Aleksander Binemann-Zdanowicz, Bernhard Thalheim BTU Cottbus, LS Datenbanken Informationssysteme
{bernd.tschiedel | binemann | thalheim}@informatik.tu-cottbus.de Abstract
An auspicious technology in the area of e-Learning is the assignment of learning objects. Nowadays, learning object is a common vocabulary in the meaning of content that has to work up to small independent content units which are connected with some semantic signification. A postulating advantage of learning objects is to improve the information quality of service, the provision of content. The aspects of information quality are described in the three main principles of information logistics. The correct content in the right place to the right time. This we have realized in the DaMiT Project. Rationale was the utilization of SiteLang, a methodology originally developed for specifying entire websites and enhanced for designing web-based learning systems.
Keywords:
SiteLang, e-Learning websites, adaptive e-Learning, information logistics
1.
Introduction
In many scientific papers and working group specifications the fundamental insight was outlined, that a high granularity of learning units leads to higher useradaptive systems. One guideline is to deal with a lot of different types of units from the same topic. Users, in our case learners, just want best-suited content delivered just in time and to the right place and device. They should not be confronted with wasteful content. Therefore, some services are needed to fulfill the learner’s needs. In the information logistics one finds acceptable strategies which satisfy the requirements of a delivery of the right unit of information. The goals of information logistics are well-adoptable for the e-Learning challenge.
1.1
Types of Learning
A new hope is born, since e-Learning profits from the new technologies related to the internet and permanently increasing bandwidth. A hope with high demands on human and technical resources, which are involved in making the dream true to let everybody learn at any time, everywhere and whatever. But if we simply say "learn", we face a lot of problems and solutions coming from classroom learning, which are not easy adoptable for a computer-based learning system. Let us look at only one methodical aspect of learning and
2 teaching, the social aspect. In [Ott01]one can find organizational types which determine the interaction and communication possibilities. Frontal teaching: a teacher presents a learning unit and works on it together with the pupils, students. Single working place: every pupil, student is self-responsible for planning, solving, checking problem solutions. Classmate working: exactly two pupils, students are responsible for their product of actions. Cooperative, collaborative working: a group (3-6, autonomous) works on the instructions and creates an own product of actions. It is to divide into common group tasks and separated group tasks. Not only the obvious difficulty to model these social environments but also the classical problems like adaptivity, multi-usage of content, the necessary underlayer of developing social aspects are still in the scope of research. These natural characteristics of interactive working are controlled by a teacher, who evaluates and analyzes the needs and learning history of the pupils and basing on this knowledge he generates a learning scenario, which can be adapted at learn-time according to pupils’ progress and evolving needs.
1.2
Information logistics
Information logistics serves for providing optimized information to users [Lie01]. Optimized means that textually correct and needed information will be served at the right time and place. The information should always be transformed depending of user preferences and communication facilities. Derived from this definition [Lie01]explains some basic principles in information logistics which also concern e-Learning. Several information sources: The use of several content sources, in dependence of the actual user needs. The user looks for additional or extended information in distributed, correlated content bases. At the moment we restrict this to one database of one domain. Information on the tick: Information at the right time depends on the value of the information and the user context. The value depends on the deliverable content in the knowledge bases. High value demands a detailed description of the content. Users of an e-Learning system may interact with the system in different roles with special characteristics. This is the primary context for the user. Thus, on these conditions the system has to choose on demand or on click what the preferred content for the user is at this moment. Consideration of user preferences: Applications of information logistics must be able to satisfy individual needs of the users. User needs must be specified for optimal operation. This must be implemented in an explicit and an implicit way. Explicit data, like preferred presentation style or difficulty, must be treated as granularly as possible. Implicit data are the user’s history, current and recorded interaction and utilization behavior. Flexibility of presentation: Users have (depending on their working place and working context) different communication devices and channels. The system automatically recognizes the user’s system, his network connection and application. In any case, the presentation style must be adapted with respect to the individual working context.
The working place and context are features of information logistics. They do not belong to a web-based e-Learning environment, as they depend on the internet access. The described particularities are related to the challenges our department faced during the development of the SiteLang approach.
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1.3
Challenges in e-Learning
While creating a computer-based learning application you face certain challenges which have already been investigated and used in some prototypes. We also have to restrict the mentioned aspects of information logistics from above. in the following aspects. Full flexibility: E-learning services require full flexibility of learning scenarios. The set of scenarios necessary to be supported looks graphically similar to a complete graph. It is possible in such cases to use any menu point and to jump to any other dialogue step [Cau00]. The usage of a proven scenario theory for the application development is a basic assumption to realize full flexibility. Multiple usage of content: Authors of content must be able to index, research, reselect, recombine and update existing content. There is the need of a flexible data structure in order to comply with these demands. Thus, in the area of e-learning we use the approach of learning objects, based on the Reusable Learning Object Strategy [Cis01]. Adaptivity: Learners want to get content depending on their specific information requirements and demand. There are some general user profiles in the area of content format like text or formula-oriented learners. These can be used as pre-made scenarios with already associated learning objects. To realize user adaptation fully, learning objects should be enhanced at run-time with specific user information from the current user profile.
1.4
Overview of the Paper
This paper gives a short overview of the SiteLang methodology which is being used to develop parts of the DaMiT e-Learning system. Principles of information logistics are part of this design concept. The language has an operational semantics based on entity-relationship structuring and Abstract State Machines [Gur95]. It allows to specify entire websites by means of their structuring, behavior, information support, interaction and story space. The theoretical background of this work generalizes the approaches [FOS00]and [Tha00].
2.
The SiteLang Methodology
SiteLang has been developed to enable developing interactive web services in a systematic way, allowing to verify the behavior of an information service before its actual implementation. SiteLang supports the stepwise development of a website according to the CoDesign abstraction layer model [FOS00]. It allows to specify database behavior and user interaction of the system in parallel. The major goals achieved with SiteLang are the refineability of obtained SiteLang specifications and the possibility to execute and validate an abstract specification on any abstraction level. This has been achieved thanks to the operational semantics of Abstract State Machines [Gur95]SiteLang is based on. The development of analysis methods in the SiteLang methodology is also supported by the developments in the ASM community. The SiteLang language comprises constructs for specifying database functionality (database schema, database operations, transaction management, integrity constraints, database content), as well as user interaction (event-driven interaction model, multiple users and devices, scenes, dialogue steps with trans-
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action semantics, dialogues, media objects) [DuT01]in parallel. It allows to specify distributed system architectures. The user interaction model of SiteLang is event-driven; the event frame differs from the classical ECA model and comprises well-founded transaction semantics. SiteLang has been successfully used for specifying interactive services of a set-top-box-based tv platform which has been developed by an industrial consortium in cooperation with our database group. The positive experience of SiteLang has proven its suitability for specifying data-intensive applications. It is also suitable for specifying and validating systems in which the interaction flow is reciprocally influenced by semantic content structures.
3.
The Data Mining Tutor Project
The focus of the DaMiT project is the development of a computer-based tutor system to support learning and teaching in the area of Knowledge Discovery and Data Mining. Another important focus is put on the creation of content. The main goal of DaMiT is to realize user adaptivity. Derived sub-goals are: content generation, creating coherent and consistent content, generating a semantic network using the domain Data Mining, integrating applications for on-line data mining, keeping an architecture open for extensibility and updating, as well as obtaining a knowledge basket adoptable to other projects.
4.
SiteLang Usage in the Project
A SiteLang specification of DaMiT is obtained stepwise, starting with the Motivation Layer and the Requirements Acquisition Layer. The next step is the Business User Layer. It is the basis of further modeling and is then refined onto Conceptual Layer and the Implementation Layer. As an example we briefly present the user model and then focus on content modeling.
4.1
Modeling the User
For user adaptivity it is essential to analyze the most typical characteristics, operations and expectations of users who are to work and interact with the planned web service. Some of the characteristics are attributes and operations which form the adaptive interface of the user. This concerns the area of rights, educational classification and utilization behavior. So we defined at the BUL roles (Content Provider, Teacher, Administrator, Tutor, Learner with the subroles Anonymous, Pseudonymous, Standard, Manager), metadata and added
5 functionality, e.g. Payment, Rights Management (of courses, with respect to learner groups), as well as user-role-dependent interface and system functions. The transformation process towards the Conceptual Layer led us, through the (partially depicted) ER schema, to an appropriate relational database schema.
4.2
Modeling Content
Content and content-related user interaction is modeled in SiteLang on various abstraction levels. Content can be seen as a semantic structure with associated metadata. This semantic structure is modeled in SiteLang on the Business User Layer (BUL). In the stepwise refinement process of SiteLang, the BUL is mapped onto the Conceptual Layer, the semantic structure is mapped to an appropriate relational schema. On this layer, a more thorough validation of the system behavior is possible, as we deal with well-defined database structures and a ripe story specification. The Conceptual Layer itself can be then refined to the Implementation Layer, on which implementation-related details are added, e.g. architecture, information containers exchange etc. 4.2.1 Modeling on Business User Layer. The semantic structure of content is modeled on BUL by means of a content graph G = (V, E, tv , te , vv , ve , p, Σ), with E ⊆ V × V , vv : V → Γ, ve : E → 2Γ , p : V → 2P roperties . The sets V and E represent vertices and edges. The functions vv , ve determine version numbers of a node or a set of version numbers to an edge, respectively. Γ is just a set of consecutive version numbers. The function p assigns a set of properties to a node. The type functions tv , te , the constraint set Σ and the set P roperties are application-dependent. A content graph is valid if all constraints from Σ are fulfilled. For modeling e-learning content we define: tv : V → {content, unit, topic} te : E × Γ → {deleted, requires, is required by, see also,, has part, is part of, ...} P roperties = {lecture, course, unit group, mmedia obj, text obj, applet obj}.
The set Σ contains restrictions on the content graph:
α0 := ∀(e, γ) ∈ dom(te ) : γ ∈ ve (e) α1 := ∀v1 , v2 ∈ V : (v1 , v2 ) ∈ E ⇒ (tv (v1 ) = topic ∧ tv (v2 ) = topic) ∨(tv (v1 ) = topic ∧ tv (v2 ) = unit) ∨ (tv (v1 ) = unit ∧ tv (v2 ) = content)) α2 := ∀e ∈ E : [∃γ ∈ Γ : te (e, γ) = deleted ⇒ ∃γ ∈ ve (e) : γ > γ] α3 := ∀v ∈ V : (course ∈ p(v) ⇒ (∀v ∈ V : E ∗ (v, v ) ⇒ course ∈ p(v )))
The content graph is similar to the concept of semantic networks. It is, however, particularly suitable for modeling content on BUL. 4.2.2 Modeling on Conceptual and Implementation Layers. The BUL is essential for modeling semantic structures of e-Learning content. It allows to validate system behavior before the actual database schema has been modeled. In order to simulate both database behavior and user interaction, BUL needs to be refined to Conceptual Layer. For this purpose, the content graph is mapped to a database schema. Classes of objects of the same type in the content graph are mapped to relationship types,
6 es UnitGroup={TRUE}
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Figure 2.
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links between objects are mapped to relationship types of a higher order. The resulting schema depends on the types of links between nodes on the BUL and of their semantics with respect to learning scenarios, as well as on e-learning content type and paramount manipulation operations performed on the content. As a result we get a complete relational database schema with the corresponding metadata and the user information. User interaction is specified explicitly on Conceptual Layer. As learning scenarios are generated along links between content objects, topic and unit nodes from the BUL are transformed to scenes and dialogue steps. The navigation structure (dialogue step specification) results from the link structure of the respective node and of its parent nodes (topics). Navigation through content is realized as an execution of a series of scenes; navigation steps through a single unit by means of dialogue steps of a single scene. Content graph modifications at run-time result in scene changes on Conceptual Layer. Having obtained the Conceptual Layer specification, we can refine it onto Implementation Layer, e.g. by including further implementation details and by adding constructs describing system distribution. 4.2.3 Modeling Metadata. Metadata in DaMiT is modeled according to commonly known concepts like in [IMS01]. It is modeled in SiteLang on the BUL directly by means of the HERM model [DuT01]. On Conceptual Layer, the metadata schema is then transformed to a corresponding relational schema.
4.3
Content Generation
E-Learning content in DaMiT is generated according to the user’s needs and is closely related to content adaptivity. The generation is done in twofold ways. Content-to-Profile Matching: the existing content structure is matched with the user’s preferences and history. The generated content is assembled from the matching topics and units, chosen from the content graph and is presented to the user as a lesson. It is being realized in our prototype by means of parameterized views, mappings of profile-dependent generation rules. Semantic Content Evolving: the content structure is enriched by new subgraphs built on the basis of common learning objects. The new lessons can be more valuable to the learner, as they have new semantic relationships previously not present in the content graph; they are also reusable for later usage.
7 Representing content generation rules on BUL is subject to further research, so that SiteLang can support specifying the rules for both generation methods mentioned above.
4.4
Content Versioning with SiteLang
In the learning process, it is essential to provide every user with the a content version corresponding to his needs. The following needs to be considered: Content Stability: After the user has begun a course, any changes on the course content must not be released to the user as long as he has not completed it. This intuitive condition cannot be realized in a trivial manner, i.e. just by freezing the course version, as it would cause an overhead when dealing with massive amounts of users. History Continuance: It may be necessary to keep older content versions for later usage. Therefore, it must be possible to recall any older content version at any time. Similarity Versioning: Depending on the user’s knowledge and usage history, it may be necessary to use parallely different versions of the same content, which are assigned to the same unit. For instance, there may exist different difficulty versions of the same content, e.g. "basic", "intermediate", "advanced". Such parallel versions may also be subject to "classical" versioning in terms of updating content, e.g. for improvement purposes.
4.4.1 Content Modification Versioning. Course modifications, i.e. content modifications, are realized on the Business User Layer by integrating a new subgraph into the existing content graph, by deleting a subgraph or by updating a node. When a course modification is performed, it must not affect yet not completed interactions related to the respective course, in order to preserve Content Stability. Also, new interactions related to that course may be started after the modification: the new version should be applied to them. The following rules define how e-Learning content versioning is realized with SiteLang by means of BUL. Course Versioning: Each course is versioned separately from the other ones. Extending courses: Adding a subgraph into a course (into the content graph) increases the course version number. All vertices and edges of the subgraph also get the increased version number. The new edge leading from the existing graph into the added subgraph also receives the new version number. Removing course parts: Removing a subgraph from a course increases the course version number and adds another edge of type deleted from the subgraph’s father to the subgraph. Updating courses: Updating a node in a course (a topic, a unit or a content node) increases the version number of the course and creates a new node of the same type. This new node is connected with the same nodes and by new edges of the same type as the original node; the version number of the new edges is the increased version number.
4.4.2 Maintaining Parallel Unit Versions. Similarity Versioning is an important aspect of user adaptivity on e-Learning content, as it is necessary to provide users with content of appropriate difficulty level. Therefore, multiple units with similar content of varying difficulty are grouped in a topic which is specially marked with the property unit group. In this way, a group of units on the BUL can be identified as "similar units". The transformation into the Conceptual Layer is analogous to the one of the entire content graph.
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5.
Summary
In our work we have presented a methodology for specifying information logistics for e-learning applications. It is based on the operational semantics of Abstract State Machines and has proven suitable for specifying content adaptivity in the DaMiT project. Our further research will be focused on deeper aspects of adaptive content generation. Applying and enhancing the SiteLang methodology for an enhanced modeling of content structures and navigation rules - the new challenges that arose during the development - will be subject to further development as well. Actually it is playtime with the DaMiT prototype. Users can login as learners, switching their educational preferences for adaptive content navigation to different levels of difficulty or presentation. The system is accessible to the public under http://neumann.dfki.uni-sb.de/damit.
Acknowledgments The authors wish to thank the active participants of the DaMiT-Project Oleg Rostanin, Martin Memmel and Klaus P. Jantke for their encouragement and support, as well as other colleagues not mentioned here by name. This research was partially supported by the DFG, Berlin-Brandenburg Graduate School in Distributed Information Systems (DFG grant no. GRK 316).
References [Ott01] B. Ott: Grundlagen des beruflichen Lernens und Lehrens. Ganzheitliches Lernen in der beruflichen Bildung., Cornelsen Verlag, 2000 [Lie01] C. Lienemann: Informationlogistik-Qualität im Fokus, Symposion Publishing, 2001 Institute of Computer Science, Cottbus, 2000 [Cau00] J. Caumanns: Automatisierte Komposition von wissensvermittelnden Dokumenten für das World Wide Web, PhD thesis, BTU Cottbus, Cottbus, 2000 [Cis01] Cisco Systems Inc.: Reusable Learning Object Strategy, Nov. 2001, Ver. 4.0 [Bin01] A. Binemann-Zdanowicz: Towards Information System Modeling on the Basis of ASM Semantics, Computer Science Report 12/01, BTU Cottbus, CS dept., Cottbus, 2001 [DuT01] A. D¨usterh¨oft, B. Thalheim: Conceptual modeling of internet sites, Proc. ER’2001, LNCS 2224, Springer, Berlin, 2001, pp. 179-192 [FST98] T. Feyer, K.-D. Schewe, B. Thalheim: Conceptual design and development of information services, Proc. ER’98, LNCS 1507, Springer, 1998, pp. 7-20 [FOS00] T. Feyer, K. Odey, K.-D. Schewe, B. Thalheim: Design of data-intensive web-based information services, Proc. WISE’2000, IEEE, 2000 [Gur95] Y. Gurevich: Evolving Algebras 1993: Lipari Guide, Specification and Validation Methods, Oxford University Press, 1995, pp. 9-36 [IMS01] Global Learning Construction Inc.: Meta Data Specifications, http://www.imsglobal.org/metadata/index.cfm [LST99] J. Lewerenz, K.-D. Schewe, B. Thalheim: Modeling data warehouses and OLAP applications by means of dialogue objects, ER’99, LNCS 1728, Springer, 1999, pp. 354-369 [ScT00] K.-D. Schewe, B. Thalheim: Conceptual development of internet sites, Full-day tutorial, Conf. ER’2000, Salt Lake City, 2000 [Tha00] B. Thalheim: Entity-Relationship Modeling - Fundamentals of Database Technology, Springer, Berlin, 2000
