Browsing by Author "Weng, JF"

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A new approach for constructing the concept map
(2004)
Sue, PC
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Weng, JF
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Su, JM
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Tseng, SS
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資訊工程學系
For achieving the adaptive learning, a predefined concept map of a course is often used to provide adaptive learning guidance for learners. However, it is difficult and time consuming to create the concept map of a course. Thus, how to automatically create a concept map of a course becomes an interesting issue. In this paper, we propose a Two-Phase Concept Map Construction (TP-CMC) approach to automatically construct the concept map by learners' historical testing records. Phase I is used to preprocess the testing records. We apply Fuzzy Set Theory to transform the numeric testing records of learners into symbolic, apply Education Theory (Item Analysis for Norm-Referencing) to further refine it, and apply Data Mining approach to find its grade fuzzy association rules. Then, in Phase 2, based upon our observation in real learning situation, we use multiple rule types to further analyze the mined rules and then propose a heuristic algorithm to automatically construct the concept map. Finally, the Redundancy and Circularity of the concept map constructed are also evaluated.
An object based authoring tool for creating SCORM compliant course
(2005)
Su, JM
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Tseng, SS
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Weng, JF
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Chen, KT
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Liu, YL
In recent years, how to reuse and share the teaching materials and instructional experiences among e-learning systems become more and more important. Sharable Content Object Reference Model (SCORM), the most popular international teaching materials standard, uses the metadata to specify the structure of every teaming object and proposes the content aggregation scheme to package these objects with XML language format. In 2004, the Sequencing and Navigation (SN) in SCORM 2004 also define the sequencing rules which can be used to control the sequencing, selecting and delivering of teaming activity for the desired, sequencing behavior. Learning contents in SN is organized into a hierarchical structure, namely Activity Tree (AT). However, for teachers/instructional designers, it is hard to understand the complicated sequencing rules in SN much less using it to construct a SCORM course with desired teaming guidance. Therefore, how to provide a user-friendly authoring tool to efficiently construct SCORM compliant course becomes an important issue. Therefore, in this paper, based upon the concept of Object Oriented Methodology (OOM), the complicated sequencing rules can be modularized into several basic components with corresponding sequencing rules in SN, called Sequencing Object (SO). Each SO is like a middleware, which represents a basic sequencing building block as a cluster in activity tree (AT) with some corresponding sequencing rules on the SCORM view and represents a basic sequencing graph on the users' view. By appropriately combining these SOs, users can easily construct a complex structure of course with desired teaming guidance. Then, a transformation algorithm is also proposed to firstly transform the created graph based course structure into Activity Tree (AT) with related sequencing rules, and then package the transformed activity tree and related physical teaming resources into a SCORM compliant course file. Moreover, the authoring tool can be easily upgraded by importing a new SO instead of redesigning the tool only for new SCORM version. Finally, a SCORM compliant course built by the object based authoring tool is executed on the SCORM RTE system. The results show that our approach is workable and efficient.
Constructing SCORM compliant course based on high-level Petri nets
(2006-01-01)
Su, JM
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Tseng, SS
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Chen, CY
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Weng, JF
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Tsai, WN
With rapid development of the Internet, e-learning system has become more and more popular. Currently, to solve the issue of sharing and reusing of teaching materials in different e-learning system, Sharable Content Object Reference Model (SCORM) is the most popular standard among existing international standards. In SCORM standard, the Sequencing and Navigation (SN) defines the course sequencing behavior, which controls the sequencing, selecting and delivering of a course, and organizes the content into a hierarchical structure, namely Activity Tree (AT). However, the structures with complicated sequencing rules of Activity Tree (AT) in SCORM make the design and creation of course sequences hard. Therefore, how to provide a user-friendly authoring tool to efficiently construct SCORM compliant course becomes an important issue. However, before developing the authoring tool, how to provide a systematic approach to analyze the sequencing rules and to transform the created course into SCORM compliant are our concerns. Therefore, in this paper, based upon the concept of Object Oriented Methodology (OOM), we propose a systematic approach, called Object Oriented Course Modeling (OOCM), to construct the SCORM compliant course. High-Level Petri Nets (HLPN), which is a powerful language for system modeling and validation, are applied to model the basic sequencing components, called Object-Oriented Activity Tree (OOAT), for constructing the SCORM course with complex sequencing behaviors. Every OOAT as a middleware represents a specific sequencing behavior in teaming activity and corresponding structure with associated sequencing rules of AT in SCORM. Thus, these OOATs can be efficiently used to model and construct the course with complex sequencing behaviors for different teaming guidance. Moreover, two algorithms, called PN2AT and AT2CP, are also proposed to transform HLPN modeled by OOATs into a tree-like structure with related sequencing rules in Activity Tree (AT) and package the AT and related physical teaming resources into a SCORM compliant course file described by XML language, respectively. Finally, based upon the OOCM scheme, a prototypical authoring tool with graphical user interface (GUI) is developed. For evaluating the efficiency of the OOCM approach compared with existing authoring tools, an experiment has been done. The experimental results show that the OOCM approach is workable and beneficial for teachers/ instructional designers. (c) 2005 Elsevier B.V. All rights reserved.
Learning portfolio analysis and mining for SCORM compliant environment
(2006)
Su, JM
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Tseng, SS
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Wang, W
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Weng, JF
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Yang, JTD
With vigorous development of the Internet, e-learning system has become more and more popular. Sharable Content Object Reference Model (SCORM) 2004 provides the Sequencing and Navigation (SN) Specification to define the course sequencing behavior, control the sequencing, selecting and delivering of course, and organize the content into a hierarchical structure, namely Activity Tree. Therefore, how to provide customized course according to individual learning characteristics and capabilities, and how to create, represent and maintain the activity tree with appropriate associated sequencing definition for different learners become two important issues. However, it is almost impossible to design personalized learning activities trees for each learner manually. The information of learning behavior, called learning portfolio, can help teacher understand the reason why a learner got high or low grade. Thus, in this paper, we propose a Learning Portfolio Mining (LPM) Approach including four phases: 1. User Model Definition Phase: define the learner profile based upon existing articles and pedagogical theory. 2. Learning Pattern Extraction Phase: apply sequential pattern mining technique to extract the maximal frequent learning patterns from the learning sequence, transform original learning sequence into a bit vector, and then use distance based clustering approach to group learners with good learning performance into several clusters. 3. Decision Tree Construction Phase: use two third of the learner profiles with corresponding cluster labels as training data to create a decision tree, and the remainings are the testing data. 4. Activity Tree Generation Phase: use each created cluster including several learning patterns as sequencing rules to generate personalized activity tree with associated sequencing rules of SN. Finally, for evaluating our proposed approach of learning portfolio analysis, an experiment has been done and the results show that generated personalized activity trees with sequencing rules are workable and beneficial for learners.