TY - GEN
T1 - Can Feedback based on Predictive Data Improve Learners' Passing Rates in MOOCs? A Preliminary Analysis
AU - Perez-Sanagustin, Mar
AU - Pérez-Álvarez, Ronald
AU - Maldonado-Mahauad, Jorge
AU - Villalobos, Esteban
AU - Hilliger, Isabel
AU - Hernández, Josefina
AU - Sapunar, Diego
AU - Moreno-Marcos, Pedro Manuel
AU - Muñoz-Merino, Pedro J.
AU - Delgado Kloos, Carlos
AU - Imaz, Jon
N1 - Publisher Copyright:
© 2021 Owner/Author.
PY - 2021/6/8
Y1 - 2021/6/8
N2 - This work in progress paper investigates if timely feedback increases learners' passing rate in a MOOC. An experiment conducted with 2,421 learners in the Coursera platform tests if weekly messages sent to groups of learners with the same probability of dropping out the course can improve retention. These messages can contain information about: (1) the average time spent in the course, or (2) the average time per learning session, or (3) the exercises performed, or (4) the video-lectures completed. Preliminary results show that the completion rate increased 12% with the intervention compared with data from 1,445 learners that participated in the same course in a previous session without the intervention. We discuss the limitations of these preliminary results and the future research derived from them.
AB - This work in progress paper investigates if timely feedback increases learners' passing rate in a MOOC. An experiment conducted with 2,421 learners in the Coursera platform tests if weekly messages sent to groups of learners with the same probability of dropping out the course can improve retention. These messages can contain information about: (1) the average time spent in the course, or (2) the average time per learning session, or (3) the exercises performed, or (4) the video-lectures completed. Preliminary results show that the completion rate increased 12% with the intervention compared with data from 1,445 learners that participated in the same course in a previous session without the intervention. We discuss the limitations of these preliminary results and the future research derived from them.
KW - MOOC
KW - feedback
KW - prediction
KW - self-regulated learning
UR - https://www.scopus.com/pages/publications/85108120489
U2 - 10.1145/3430895.3460991
DO - 10.1145/3430895.3460991
M3 - Contribución a la conferencia
AN - SCOPUS:85108120489
T3 - L@S 2021 - Proceedings of the 8th ACM Conference on Learning @ Scale
SP - 339
EP - 342
BT - L@S 2021 - Proceedings of the 8th ACM Conference on Learning @ Scale
PB - Association for Computing Machinery, Inc
T2 - 8th Annual ACM Conference on Learning at Scale, L@S 2021
Y2 - 22 June 2021 through 25 June 2021
ER -