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ANALYZING STUDENTS’ BEHAVIOR IN UNED-COMA
MOOCS
Ll.Tobarra, S. Ros, R. Hernández,A. Robles-Gómez,
R. Pastor,A. C. Caminero...
UNED COMA
 UNED, has started the UNED-COMA (Curso Online Masivo Abierto; in English, UNEDMOOC) project for
managing massi...
EXISTING DATA
 OpenMooc has three databases:
 Database PostgreSQL related towards the structure of the courses and users...
EVOLUTION OF STUDENT REGISTRATION
ACTIVITY OF THE STUDENTS
POSTGRESQL: STRUCTURAL CONCEPT
Course Users Groups
Badges
Modules
Pills (videos)
Attachements
(PDFs)
Quizzes
Peer reviews
...
POOR STUDENT PROFILE INFORMATION
 Detect the sex of the students using an
automated function that uses public name
lists ...
INITIAL ANALYSIS OF KNOWLEDGE PILLS
YOUTUBE ANALYTICS
YOUTUBE ANALYTICS
• Evaluation related videos have
a high number of views and
retention.
• Rest of the videos have a
lower...
ANALYSIS
 Hypothesis 1: shorter videos are better for the students’ outcomes.
 Hypothesis 2: courses with fewer videos a...
FORUMS INITIAL ANALYSIS
FORUM:ASKBOT
FORUM SCHEMA
Users
tags, reputation
Posts
score, vote_up_count
Three types: coments,
questions and answears
Threads
tags, ...
FORUM ACTIVITY
POSTS INSIDE THE COURSES
EXAMPLE OF FORUM BEHAVIOUR
 Activity evolution
USER BEHAVIOUR
 Statistics and histogram:
 Only 2240 students participate in
the forum (reading or writing):
around a 10...
FORUM
 Textual analysis.
 Words are not very
significative.
ANALYSIS
 Hypothesis 3: a elevated number of activities in the forums of the course is related to the student success wit...
CONCLUSIONS
 Lack of the activities data has an impact in the outcomes of our analysis.
 A set of hypothesis have also b...
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VII Jornadas eMadrid "Education in exponential times". Llanos Tobarra: "Studying Students' Behavior in UNED-COMA MOOCs". 05/07/2017.

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VII Jornadas eMadrid "Education in exponential times". Llanos Tobarra: "Studying Students' Behavior in UNED-COMA MOOCs". 05/07/2017.

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VII Jornadas eMadrid "Education in exponential times". Llanos Tobarra: "Studying Students' Behavior in UNED-COMA MOOCs". 05/07/2017.

  1. 1. ANALYZING STUDENTS’ BEHAVIOR IN UNED-COMA MOOCS Ll.Tobarra, S. Ros, R. Hernández,A. Robles-Gómez, R. Pastor,A. C. Caminero, J. Cano, and J. Claramonte
  2. 2. UNED COMA  UNED, has started the UNED-COMA (Curso Online Masivo Abierto; in English, UNEDMOOC) project for managing massive courses with multimedia videos and social interaction tools (like forums).  38 courses.  Several editions.  xMOOCs.  Certificates:  On-line badge.  Face-to-face exam.  In particular, UNED-COMA is an open initiative created in the 2012 year.  The OpenMOOC platform is employed for this purpose.  The main objective of this initiative has been the exploration of the rich experience with the distance educational methodology employed at UNED.  Not oriented towards learning analytics.  Nowadays this platform has been replaced by OpenEDX  URL: https://unedabierta.uned.es/wp/
  3. 3. EXISTING DATA  OpenMooc has three databases:  Database PostgreSQL related towards the structure of the courses and users profile data.  Database MySQL, a database for each forum:  OpenMOOC is based on AskBoot for handling forums (https://askbot.com/).  Database NoSQL MongoDB, oriented towards activities interactions  this database was not available.  Youtube analytics from 2015:  Fundación CSEV (https://www.youtube.com/user/FundacionCSEV).  UNED Abierta (https://www.youtube.com/user/UNEDcursoscoma).
  4. 4. EVOLUTION OF STUDENT REGISTRATION
  5. 5. ACTIVITY OF THE STUDENTS
  6. 6. POSTGRESQL: STRUCTURAL CONCEPT Course Users Groups Badges Modules Pills (videos) Attachements (PDFs) Quizzes Peer reviews Internal Mail
  7. 7. POOR STUDENT PROFILE INFORMATION  Detect the sex of the students using an automated function that uses public name lists such as Spanish Government Statistics popular names lists and the usernames.  Not always is possible.  Almost a 10% is not classified.
  8. 8. INITIAL ANALYSIS OF KNOWLEDGE PILLS
  9. 9. YOUTUBE ANALYTICS
  10. 10. YOUTUBE ANALYTICS • Evaluation related videos have a high number of views and retention. • Rest of the videos have a lower number of views.
  11. 11. ANALYSIS  Hypothesis 1: shorter videos are better for the students’ outcomes.  Hypothesis 2: courses with fewer videos are more successful that those ones with a great number of videos.  Features:  Number of videos per course.  Mean duration of videos per course.  Mean amount of visits per video in the course.  Mean amount of likes per video in the course.
  12. 12. FORUMS INITIAL ANALYSIS
  13. 13. FORUM:ASKBOT
  14. 14. FORUM SCHEMA Users tags, reputation Posts score, vote_up_count Three types: coments, questions and answears Threads tags, views, favorites Reviews Activity Content_type Type of activities: voting, answering,… Vote award badges
  15. 15. FORUM ACTIVITY
  16. 16. POSTS INSIDE THE COURSES
  17. 17. EXAMPLE OF FORUM BEHAVIOUR  Activity evolution
  18. 18. USER BEHAVIOUR  Statistics and histogram:  Only 2240 students participate in the forum (reading or writing): around a 10% of the students in the course.
  19. 19. FORUM  Textual analysis.  Words are not very significative.
  20. 20. ANALYSIS  Hypothesis 3: a elevated number of activities in the forums of the course is related to the student success within the course.  Features:  Number of activities.  Number of questions.  Number of answers.  Number of comments.  Percentage of the number of students.  Average number of activities per user.  Average number of activities per day.
  21. 21. CONCLUSIONS  Lack of the activities data has an impact in the outcomes of our analysis.  A set of hypothesis have also been proposed and discussed from the detected candidate variables (indicators) from datasets.  This indicators are about students’ behavior in MOOCs given both from the point of view of videos and debate forums.  A clear need to improve the platform with further learning analytics.

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