Hong Kong Polytechnic University “ Towards a personalized open learning ecology”

1. Hong Kong Polytechnic University“Towards a personalized open learning ecology” Author: Herbert Lee [1/June/2010]

2. Towards a personalized Open Learning Ecology Table of Content • Introduction and objectives • The SocialLMS 2.1 Brief description 2.2 Issues to overcome 2.3 The ontological engine 2.4 Demonstration • Deployment considerations 3.1 How to start 3.2 How to sustain 3.3 Future possibilites • Conclusion

3. Summary This project proposes SocialLMS which is an e-learning portal that can provide personalized learning materials to learners in a one-to-one manner; while maintaining the cost per student to only a fraction of classroom teaching. The main obstacle is how the tutors can effortlessly produce personalized courses in minutes instead of weeks.

4. Introduction • Personalized one-to-one education delivery system is way beyond any educational institutes can afford. • Traditional courses do have several limitations that make them impractical to apply in all learning circumstances.

5. Introduction • Traditional courses do have several limitations that make them impractical to apply in all learning circumstances: • It doesn’t match today’s environment in terms of speed of change, flexibility of learning, and dynamics of content. • Life of knowledge changes too quickly (e.g.. IT courses). • Courses are not designed for a vast diversity of learners. • Knowledge is intertwined. Traditional course contents are presented in isolation. • After the course is finished (usually within 12 weeks), there is no environment to support the learners subsequently for what has been learnt.

6. Objective • To create a personalized open e-learning ecology to cater for a vast diversity of learners who commit to a self motivated life-long learning behavior. • Characteristics of the open e-learning environment: • Learners can choose their own tutor • Courses are designed based on the student’s profile • Courses can be constructed on-demand in very short time • Courses are built from reusable learning objects • Learning objects and courses are ranked by both tutors and learners • The running cost is much less than classroom teaching in term of cost/student

7. Introducing the SocialLMS • The personalized open e-learning SocialLMS consists of: • The learning objects Platform • The Mentor Platform • The Learner Platform • The ontological engine • Rapid course builder • Community based evaluation system

8. Introducing the SocialLMS

9. Issues to overcome • How to rapidly design a course that is suitable to a particular learner? • The ontological engine can automatically categorize tens of thousands of LOs in every domain of knowledge. • Tutors can easily find the right LOs through the built-in semantic search engine. • Courses are “composed” using LOs in the Rapid Course Builder. • The specifics of the courses are designed according to the learners’ profiles and requests which are posted in the Learner Platform.

10. Issues to overcome • How do each learner knows which tutor is best for him? • The tutors’ profiles are posted on the tutor platform. • Learners are required to rank his tutor after taking a course. • How do tutors know the subtle attributes of tens of thousands of LOs such as the correctness, comprehensibility, and level of difficulty? • The LOs are ranked by both learners & tutors in their respective attributes. • Low ranking LOs are gradually “filtered” out.

11. Issues to overcome • Who contributes these LOs? • Free learning materials are everywhere in the WWW. • Each page in Wikipedia is a LO. • Thousands of teaching videos are in Youtube. • Tutors can contribute LOs. • The composed courses are ranked, stored and reused. • Low quality LOs are gradually “filtered” out through community ranking.

12. The ontological engine • SocialLMS is powered by an ontological engine – ANTOM: Automated Ontology Manager. • ANTOM can automatically categorized tens of thousands of learning objects: text documents, audio clips, and video files. • Tutors need only input a topic or a key-phrase and a list of LOs will be retrieved and ranked according to their relevancy. • Alternatively, tutors can navigate through the concept map to locate LOs. • ANTOM knows EVERY domain of knowledge.

13. Demonstration Provide exploratory search • Navigate the concept map • Concept drill down • Concept explanation • Document retrieval • Explore concept cloud Provide semantic search • Semantic search of LOs by key-phrase • Related document search • ANTOM

14. Screenshots of ANTOM

15. Search for a concept and results are sorted by relevancy ranking

16. LOs are automatically categorized and associated with each related concepts. Clicking on the concept will retrieve a list of related LOs. Ontology map of the concept “knowledge management”

17. Concept in context Learning object that is related to the concept in context Each LO is automatically categorized into related concepts

18. Concept Cloud Determined by the collection of learning objects

19. Deployment considerationsHow to sustain? • A well set of central policies: • Initial community directors of each knowledge community are chosen by the central committee • All content contributors and mentors must have a verified identity and verified credentials [accountability] • The “open concept” must be maintained • Premium mentors can have the right to delete a learning object or a course if they think that the content is not accurately represented, highly controversial, unethical, or no education value [maintain a minimum quality] • Track learners’ usage behavior and suggest relevant courses (like Amazon.com)

20. Deployment considerationsHow to sustain? • Promote trust and identity: • Promote mentors & learners interactions, e.g. face-to-face supplementary workshops and seminars, live scheduled WebCast with interactive dialogue • Learners can promote to mentors so as to motivate long-term participation and sense of belonging • Ensure an open, transparent and righteous voting / ranking system • Certification & qualification through assessment to obtain academic recognition

21. Towards a global open e-learning ecology: Future possibility • When network effect does take effect in a global setting, an open e-learning ecology has evolved. What possible implication will that be? • A whole new way of pedagogy will emerge: • “Learning on demand” is possible such that learners post their requirements (learning demands) on the platform and the mentors assemble the courses or even curricula “on-the-fly” using ANTOM on the millions of learning objects. • A huge knowledge transfer e-marketplace is formed such that knowledge supply will try to meet knowledge demand.

22. Conclusion • The open e-learning platform can be complementary to cater for the deficiency in the traditional way of pedagogy. • The underlining technology is ANTOM which is an ontological engine that can automatically categorize millions of learning objects in everydomain of knowledge and subsequently retrieve using a semantic browser. • The open system concept leverages the collective intelligence to maintain a dynamic and vibrant learning content for every type of learners.

23. Thank You Q & A