Personalization Challenges in E-Learning
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The document discusses the challenges of personalization in e-learning, focusing on user profiles that include interests, skills, and educational goals, which evolve over time with user interaction. It highlights the importance of aligning learning resources with user objectives and the limitations of traditional rating systems in understanding user preferences. The document concludes that effective personalization relies on comprehensively understanding user profiles and adapting to their changing needs.
Personalization Challenges in E-Learning
- 1. Personaliza+on Challenges in E-Learning Roberto Turrin 29th Aug 2017
- 2. About us Roberto Turrin Head of Technology, PhD @robytur cloudacademy.com/
- 4. Personalized Thema4c path Search/explore CTR CONSUM. DRIVER CCR
- 5. Intent-based User task - standard Roberto Turrin Personaliza0on Challenges in E-Learning Watching a movie Listening to a song Planning a travel I know what I want to achieve I don’t know what to do Explora0on level Discovery Goal-driven Search Watching a movie with my partner Planning a travel with my family I know how I want to get sth Watching the last movie of TaranPno Finding the Pmetable of flights to Madrid Standard Enjoyment
- 6. Intent-based User task - educaPon Roberto Turrin Personaliza0on Challenges in E-Learning Studying something I know what I want to achieve I don’t know what to do Explora0on level Discovery Goal-driven Search Learning Python Preparing for a cerPficaPon TesPng the level of knowledge Mastering BBQ cooking Becoming a data scienPst I know how I want to get sth Doing an advanced course about deep learning Educa4on Learning
- 7. User profile - interests Standard Roberto Turrin Personaliza0on Challenges in E-Learning Interests/tastes Educa4on Interests/tastes Comedy vs drama movies Rock vs pop songs Statues vs painPngs Sea vs mountain vacaPon Astrology Machine Learning What I am interested in What I prefer What I am interested in What I prefer Enjoyment Learning
- 8. User profile - interests Roberto Turrin Personaliza0on Challenges in E-Learning Educa4on Interests/tastes Astrology Machine LearningWhat I am interested in What I prefer Learning ?
- 9. User profile - educaPon-specific Standard Roberto Turrin Personaliza0on Challenges in E-Learning Interests/tastes Educa4on Interests/tastes Comedy vs drama movies Rock vs pop songs Statues vs painPngs Sea vs mountain vacaPon Astrology Machine Learning Skills/knowledge Java Excel Novice in ML Expert of astrology NLP What I am interested in What I prefer What I am interested in What I prefer What I know Enjoyment Learning
- 10. User profile - signals Roberto Turrin Personaliza0on Challenges in E-Learning What I know What I am interested in Consuming a resource What I am interested in Educa4onStandard The activities done by the user affect his skills. In fact, as I study a change my knowledge, I learn more about a topic, I increase my understanding, I enable myself to learn something more complex on the same topic. Since skills are part of my profile, I practically change my profile. We can so say that use profile in education really changes over time Watching/discovering a new kind of movie might modify my interests
- 11. User profile & User task Roberto Turrin Personaliza0on Challenges in E-Learning Educa4on User profile Java Excel Novice in ML Expert of astrology NLP Learning Python Preparing for a cerPficaPon TesPng the level of knowledge Mastering BBQ cooking Becoming a data scienPst User task “Changing what I know” What I want to achieve/know What I know
- 12. Heterogeneity - resources Roberto Turrin Personaliza0on Challenges in E-Learning Learning Tes0ng Video lectures Hands-on Quizzes
- 13. Time evoluPon Roberto Turrin Personaliza0on Challenges in E-Learning S3 BigQuery 0me Learning Tes0ngLearning Learning Recommender goal: • “providing learning resources to make the user profile close to the user goal” • “providing training resources to improve the confidence of user profile representa+on”
- 14. Heterogeneity - connecPons Roberto Turrin Personaliza0on Challenges in E-Learning Video lectures Hands-on Quizzes
- 15. Heterogeneity - bundles and paths Roberto Turrin Personaliza0on Challenges in E-Learning Video lectures Hands-on Quizzes Learning paths Exams
- 16. User raPngs Roberto Turrin Personaliza0on Challenges in E-Learning User ra+ngs not par+cularly useful for the recommender: • They are rare. Most of user signals are implicit. • They are more related to the quality of the resource than to the interest of the user or to their uPlity for the user goal. • They are more useful for the content producer than for the user as they represent a feedback for the content. In fact, there is a high correlaPon between the raPng mean and the number of negaPve and posiPve comments.
- 17. Algorithms User profile transparency is o^en a requirement: • the user profile represents the current user skills • the user is curious about “himself” Roberto Turrin Personaliza0on Challenges in E-Learning Experiments with pure collabora0ve did not succeed • not aligned with the user learning task • a lot of new content ? • Currently, a hybrid is being used • Working on embedding learning tasks through an ontology.
- 18. Other peculiariPes of on-line training: open points Lack of a physical class: • social features • forum • pair-tasks Roberto Turrin Personaliza0on Challenges in E-Learning User recommendaPons Time constraints: • user learning pace • user deadlines • resource Pming • resource Pme availability Planning
- 19. Conclusions Roberto Turrin Personaliza0on Challenges in E-Learning • Learning goals drive most of user consumpPons. • User profile also represents skills. • The main user goal can be translated into “changing my skills”, i.e., changing my profile. • Consequently, • profile conPnuously changes over Pme. • profile is something the user is interested into. • Use carefully raPngs and collaboraPve filtering
- 20. Thank you! Roberto Turrin roberto.turrin@cloudacademy.com 29th Aug 2017 cloudacademy.com/