A component to carry out the Logical Framework Approach in dotLRN

1. A component to carry out the Logical Framework Approach in dotLRN Alberto Bayón Olga C. Santos Jesús G. Boticario

2. A component to carry out the LFA in dotLRN Outline of the Presentation Objectives LFA: Logical Framework Approach Designing and Architecture Conclusion

3. Objective • Collaborative Learning Environment • Web-Based Context • Real Collaboration Among Students • Intelligence Learning Management System (iLMS) SERVICES ADAPTATION • Forums • Surveys • Storage Area • Email • . . . • Interaction Analysis • Suggestions Facility • Improve Effectiveness • Adapting to Student’ Needs • Logical Framework Approach • Collaborative Extension of LFA

4. LFA: Logical Framework Approach Objective Oriented Planning Methodology WHAT? International Development Agencies and NGOs WHO? Development Cooperation and International Aid Projects WHY? • Stakeholder Analysis • Problem Analysis • Objectives Analysis • Alternative Analysis • Project Planning Matrix HOW?

5. CLF Architecture Collaborative Logical Framework OpenACS/dotLRN package CLF • INTERACTION MODULE (I.M.) • Environment to Execute the Course • Sequence of LFA Phases • Collaborative Extension of LFA • MACHINE LEARNING MODULE (M.L.M.) • User Model Definition (u.m.) • Students Activity Monitoring • Learners Performance Classification • Machine Learning Algorithms • ADAPTIVE MODULE (A.M.) • Adapted Recommendations for All Users • Encourage to Collaborate • Help the Students in their Tasks I.M. M.L.M. u.m. A.M.

6. COLLABORATIVELY IN AGREEMENT Interaction Module • IM Implements the Collaborative Extension of LFA • Defined by aDeNu to Achieve Real Collaboration • Students Arranged in Small Groups • Working in Three Ways in All LFA Phases INDIVIDUALLY • Work Alone • Answer the Questions • Reveal the Answer • New Thread in Forum • Access to Other Solutions • Rate Colleagues’ Answers • Post Comments in Forums • Create Versions • Moderator Selection • Create Consensus • Moderator Works Individually • Colleagues Work Collaboratively

7. CLF Interaction Module FUNCIONALITY CLF package Parties, Groups, Permissions Workflow Content Repository (Revisions) Forums Ratings Survey Cronjob

8. M.L.M. User Model Active Data I.M. .LRN Active Indicators OpenAcs TAM Passive Data Passive Indicators Machine Learning Module - User Model • Data Mining Techniques for Forums, Versions & Ratings • Active Data: Taken from .LRN/OpenACS Database • Passive Data: Use of TAM, Web Track Auditing Management Tool • Indicators Define the Learners’ Profiles • Active Indicators: Participative, Insightful, Useful, Non-collaborative, With-Initiative, Communicative • Passive Indicators: Thinker-out, Unsecure, Gossip, Inspirable, Inspirator, Thorough

9. M.L.M. Recommendations User Model CLASSIFICATION Active Indicators Passive Indicators Adaptive Module – Recommender System A.M. • Periodic Calculation of Learners’ Profiles Using Machine Learning • Weka Data Mining Provides Classification Algorithms • A.M. Generates Suggestions (Recommender System Package) • Recommendations Help the Students to Enhance their Performance • Suggest rating or reading other answers • Suggest the communication with a colleague • Suggest using a specific tool

10. A component to carry out the LFA in dotLRN CONCLUSION • Achievements • Implementing All Kind of Collaborative Activities • Learners Monitoring • GPL Licence • Contribution to OpenACS/dotLRN Community • Future Work • Integrating TAM, Weka and RecommenderSystem Packages • Validation Planning Using CLF in a Pilot Course at UNED • Taking Part in other iLMS aDeNu Projects: Eu4all, Adaptaplan, aTODOS …

11. Screenshots

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14. Questions

15. A component to carry out the LFA in dotLRN abayval@yahoo.es ocsantos@dia.uned.es jgb@dia.uned.es

16. States of Answers & Workflow

17. CLF Class Diagram