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Increasing MOOC completion rates through social interactions
A recommendation system
Hugues Labarthe, Rémi Bachelet, François Bouchet & Kalina Yacef
Download this slideshow : http://goo.gl/lkba7HFebruary 22nd, 2016, Graz, Austria
MOOC completion rates are notoriously low
• What we know:
– MOOC students interacting with each other have better odds to get certified (Yang, Wen & Rose, 2014)
• Problem:
– How to improve user-centered experience and facilitate user’s involvement with peers?
2
Questions & data
Research questions:
1. Impact of social interactions between students?
2. Best way to foster peer interaction?
3 data sets:
– Session 2 to 5: Impact of social interactions? Longitudinal Study
– Session5: Students groups. Experiment.
– Session6: Chat & contact recommendation module. Experiment
3
Context: MOOC GdP
4
GdP2 GdP3 GdP4 GdP5 GdP6
Date Fall 2013 Spring 2014 Fall 2014 Spring 2015 Fall 2015
Duration 5 weeks
+ 1 week for
final exam
5 weeks including
1 elective course
+ 1 week for final
exam
6 weeks including
2 elective course
+ 1 week of exams
6 weeks including
2 elective course
+ 1 week of exams
6 weeks including
2 elective course
+ 1 week of exams
Attendance:
- Enrolled
- > 1 quiz in basic
track
- > 1 deliverable in
adv. track
10848
5711
1011
11827
5899
705
19171
8120
1197
17579
4842
725
22300
7305
970
Track success:
- Basic
- Advanced61%
78%
38%
67%
41%
73%
47%
69%
53%
71%
• French MOOC on project management
• Platform: Canvas Engineering: Unow
• 2 sessions/year: enhanced content
• 3 tracks: basic, advanced, team
• Barcamp"richer learning activities for MOOCs : 14+ ideas " EMOOCs2015
5
“Funnel of participation” (Clow, 2013)Attrition rate increasing, “September effect” (in-cursus students = less drop out in these sessions)
Study #1 (Longitudinal): attrition & interactions in 5 sessions (1/3)
6
“Participation funnel” (Clow, 2013)Attrition rate increasing, “September effect” (in-cursus students = less drop out in these sessions)
Study #1 (Longitudinal): attrition & interactions in 5 sessions (1/3)
7
> 50,000 posts & PM - Social networks not included+8k contributors (13.5%), only 3.5% used both posts & PM 3 functions: socializing, learning reinforcement, experience sharing
Longitudinal study : attrition & interactions (2/3)
Longitudinal study : attrition & interactions (3/3)
8
Longitudinal study : attrition & interactions (3/3)
9
The drop in exam pass rate for 5+post comes mostly from the high forum activity of our teaching assistant staff. In our newly published papers, this bias is controlled, as well as involvement in the technical help thread
Longitudinal study : Findings
Interacting is a strong predictor of success
+35% exam pass on average
10
Increase social interactions: Recommendations
– « Introduce yourself » thread• Trigger contributions (“must read” in week zero)
• Boost visibility of this thread: pre-MOOC announcement
– Geolocalization • « where are you ? » map
– Facebook, Google+, Twitter…• Capitalize on existing social networks
• Foster them : news, answers…
– “Question of the week”• starting point for the weekly live Q&A
– Strategies• Reward active posters: Animator badge
• TA team : Do not answer questions too fast, leave this to the other students
11
Study #2: students group to increase interactions –methodology
• Session 5 : Canvas groups features (private forums, wiki, list of group members with link to profile)
• Experiment : 34 groups of variable size:– 4 groups of 50 students– 10 groups of 10 students– 20 groups of 4 students
• 5 grouping by similarity criteria (data from initial research questionnaire)– Geographical proximity (Country)– Study level– Age– Family status– Previous experience with MOOCs
12
Study #2: findings & recommendations
Not many interactions, yet much to be learned!
In groups of 4 & 10, no more than 1 post/person = no real interaction, not many visits after first attempt
13
Criteria Observation Recommendation
Teammates visibility Group page quicklyignored
Make the list of other group membersmore visible
Contact visibility No visit to checkreplies to one’s post
Improve notification system
Sample size Many students do not interact
Larger sample size next time
# of recommended contacts
Low activity even in large groups
More contact recommendations increase the chances of finding other students willing to interact
Individualizedinteraction
Similar interface prevented students from seeing what more it brought
Allow students to create small groups of their own
Study #3: contact recommendation & chat modules
14
A contact recommendation widget in every page of the platform below the navigation column
Advanced ID card with: - profile info,- ways to contact (PM and instant message)- adding to favorites/ignoredAvailable with a simple mouse-over
A permanent chat widget
Notification (+ sound) when a message arrives!
Contact manager, to initiate conversation with favorite(s) contact(s)
Chat manager, to start or pick up a conversation
GdP6: preliminary findings
15
Findings:- Strong curiosity for students’ profiles
- Asynchronous chat interactions- Impact on attrition and performance: currently under review
GdP6:- 22,300 enrolled- 16,127 connected once- 8,053 active
Experiment: 8,674 students- 1792 in control group (no
recommendation, no chat)- 2025 accepted the terms of use- 271 interacted with others
through chat
Conclusion
• Interactions are correlated w/ success, and are key to reducing attrition. Need to find:
• The right combination of factors to recommend students to their peers
• The right interface for them to interact with one another
Can only be achieved through experiments (work in progress)
• Perspectives:– Technology course –interaction design
– Identify students who want to interact = maximize chances of response
16
Thanks for listening!
• Twitter : @R_Bachelet, Googleplus : +Rémi Bachelet
Read the paper online : https://hal.archives-ouvertes.fr/view/index/docid/1277664
Does peer grading work? How to implement and improve it?
Comparing instructor and peer assessment in MOOC GdP
Rémi Bachelet, Drissa Zongo, Aline Bourelle
Download this slideshow : http://goo.gl/GiFvXb