An Evaluation of Open Source E-Learning Platforms Stressing - - PowerPoint PPT Presentation

An Evaluation of Open Source E-Learning Platforms Stressing Adaptation Issues

Sabine Graf & Beate List Vienna University of Technology Women‘s Postgraduate College for Internet Technologies graf@wit.tuwien.ac.at

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Motivation and Aims

E-Learning platforms become very successful Adaptivity become more and more important How much adaptivity is supported in today‘s e- learning

platforms?

Which platform is most suitable for extending it to an

adaptive one?

General functionalities and capabilities Adaptation issues

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Evaluation Approach

Applying four minimum criteria to 36 platforms Installing and testing the remaining 9 platforms Applying the Qualitative Weight and Sum Approach

Weight: using symbols (e.g., * , # , + , | , 0) Performance: weight represents the maximum performance value

(e.g., + implies + , | , 0)

Result: summarizing all performance values per symbol

(e.g., Platform A: 3* , 4# , 2+ Platform B: 4* , 3# , 2+ Platform C: 4* , 2# , 3+ ) One very good criterion and one very poor criterion are not equal to two moderate criteria

Ranking: Maybe further analysis is necessary

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Categories, Subcategories & Attributes

Adaptation:

• Adaptability (* )
• Personalization (# )
• Extensibility (* )
• Adaptivity (* )

8 Categories:

• Communication tools
• Learning objects
• Management of user data
• Usability
• Adaptation
• Technical aspects
• Administration
• Course management

8 Categories:

• Communication tools
• Learning objects
• Management of user data
• Usability
• Adaptation
• Technical aspects
• Administration
• Course management

Adaptation:

• Adaptability (* )
• Personalization (# )
• Extensibility (* )
• Adaptivity (* )

Adaptivity (* ):

• Annotations of learning objects
• Annotations of communication objects
• Static adaptation of course content
• Dynamic adaptation of course content

* : Annotations and dynamic adaptation # : Dynamic adaptation + : Two attributes available | : One attribute available 0: No attribute available

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Results of the Adaptation Category

Legend: * … very good # … good + … moderate | …. poor 0 … very poor / not available

Adaptability Personalization Extensibility Adaptivity Ranking Maximum values * # * * ATutor | # # | 3 Dokeos | * + 2 dotLRN + + * 2 ILIAS + # * 2 LON-CAPA + # # | 2 Moodle # + * | 1 OpenUSS # # # 2 Sakai * 3 Spaghettilearning + # + 3

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Results of the Evaluation

2 7 8 6 8 9 11 8 7 7 13 9 10 6 7 7 11 10 10 7 9 10 9 5 11 5 3 3 4 5 6 3 8 7 6 4 3 4 2 6 12 13 2 1 2

5 10 15 20 25 30

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l e I L I A S D

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A T u t

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A P A S p a g h e t t i l e a r n i n g O p e n U S S S a k a i d

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L R N

very good (*) good (#) moderate (+) poor (|) not available / very poor (0) Legend:

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Conclusion & Ongoing Work

Evaluation of open-source e-learning platforms Using the Qualitative Weight & Sum Approach Moodle obtained best values Adaptivity is included very rarely but extensibility

is supported well

Ongoing Work

Meta model for adaptive courses Extend Moodle with adaptive features as proof of

concept prototype