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Personaliza+on Challenges in E-Learning
Roberto Turrin29th Aug 2017
About us
Roberto TurrinHead of Technology, PhD
@robytur cloudacademy.com/
Personalized Thema4c path Search/explore
CTR
CO
NSU
M.
DRI
VER
CCR
Inte
nt-b
ased
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
StandardEnjoyment
Inte
nt-b
ased
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 aboutdeep learning
Educa4onLearning
User profile - interests
Standard
Roberto Turrin
Personaliza0on Challenges in E-Learning
Interests/tastes
Educa4on Interests/tastes
Comedy vs drama movies Rock vs pop songsStatues vs painPngs Sea vs mountain vacaPon
Astrology Machine Learning
What I am interested inWhat I prefer
What I am interested inWhat I prefer
Enjoyment
Learning
User profile - interests
Roberto Turrin
Personaliza0on Challenges in E-Learning
Educa4on Interests/tastes Astrology Machine LearningWhat I am interested in
What I preferLearning
?
User profile - educaPon-specific
Standard
Roberto Turrin
Personaliza0on Challenges in E-Learning
Interests/tastes
Educa4on Interests/tastes
Comedy vs drama movies Rock vs pop songsStatues vs painPngs Sea vs mountain vacaPon
Astrology Machine Learning
Skills/knowledge Java Excel Novice in ML Expert of astrology NLP
What I am interested inWhat I prefer
What I am interested inWhat I prefer
What I know
Enjoyment
Learning
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 moviemight modify my interests
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
Heterogeneity - resources
Roberto Turrin
Personaliza0on Challenges in E-Learning
Learning
Tes0ng
Video lectures Hands-on Quizzes
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”
Heterogeneity - connecPons
Roberto Turrin
Personaliza0on Challenges in E-Learning
Video lectures Hands-on Quizzes
Heterogeneity - bundles and paths
Roberto Turrin
Personaliza0on Challenges in E-Learning
Video lectures Hands-on Quizzes
Learning paths Exams
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.
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.
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 recommendaPonsTime constraints: • user learning pace
• user deadlines
• resource Pming
• resource Pme availabilityPlanning
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
