Identifying Learning Activity Sequences that Are Associated with High Intention-Fulfillment in MOOCs

Eyal Rabin*, Vered Silber-Varod, Yoram Kalman, M. Kalz

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingAcademicpeer-review

Abstract

Learners join MOOCs (Massive Open Online Courses) with a variety of intentions. The fulfillment of these initial intentions is an important success criterion in self-paced and open courses. Using post course self-reported data enabled us to divide the participants to those who fulfilled the initial intentions (high-IF) and those who did not fulfill their initial intentions (low-IF). We used methods adapted from natural language processing (NLP) to analyze the learning paths of 462 MOOC participants and to identify activities and activity sequences of participants in the two groups. Specifically, we used n-gram analysis to identify learning activity sequences and keyness analysis to identify prominent learning activities. These measures enable us to identify the differences between the two groups. Differences can be seen at the level of single activities, but major differences were found when longer n-grams were used. The high-IF group showed more consistency and less divergent learning behavior. High-IF was associated, among other things, with study patterns of sequentially watching video lectures. Theoretical and practical suggestions are introduced in order to help MOOC developers and participants to fulfill the participants’ learning intentions.
Original languageEnglish
Title of host publicationTransforming Learning with Meaningful Technologies
Subtitle of host publication14th European Conference on Technology Enhanced Learning, EC-TEL 2019, Delft, The Netherlands, September 16–19, 2019, Proceedings
EditorsMaren Scheffel, Julien Broisin, Viktoria Pammer-Schindler, Andrea Ioannou, Jan Schneider
Place of PublicationCham
PublisherSpringer
Chapter17
Pages224-235
Number of pages11
ISBN (Electronic)9783030297367
ISBN (Print)9783030297350
DOIs
Publication statusPublished - 9 Sep 2019
Event14th European Conference on Technology Enhanced Learning: Transforming Learning With Meaningful Technologies - The Leiden-Delft-Erasmus Center for Education and Learning , Delft, Netherlands
Duration: 16 Sep 201919 Sep 2019
Conference number: 2019
http://www.ec-tel.eu
http://www.ec-tel.eu/index.php?id=918

Publication series

SeriesLecture Notes in Computer Science
Volume11722
ISSN0302-9743

Conference

Conference14th European Conference on Technology Enhanced Learning
Abbreviated titleEC-TEL 2019
CountryNetherlands
CityDelft
Period16/09/1919/09/19
Internet address

Fingerprint

learning
learning behavior
Group
video
language

Keywords

  • MOOCs
  • massive open online courses
  • Intention-fulfilment
  • Keyness
  • N-gram
  • Learning activity sequences

Cite this

Rabin, E., Silber-Varod, V., Kalman, Y., & Kalz, M. (2019). Identifying Learning Activity Sequences that Are Associated with High Intention-Fulfillment in MOOCs. In M. Scheffel, J. Broisin, V. Pammer-Schindler, A. Ioannou, & J. Schneider (Eds.), Transforming Learning with Meaningful Technologies: 14th European Conference on Technology Enhanced Learning, EC-TEL 2019, Delft, The Netherlands, September 16–19, 2019, Proceedings (pp. 224-235). Cham: Springer. Lecture Notes in Computer Science, Vol.. 11722 https://doi.org/10.1007/978-3-030-29736-7_17
Rabin, Eyal ; Silber-Varod, Vered ; Kalman, Yoram ; Kalz, M. / Identifying Learning Activity Sequences that Are Associated with High Intention-Fulfillment in MOOCs. Transforming Learning with Meaningful Technologies: 14th European Conference on Technology Enhanced Learning, EC-TEL 2019, Delft, The Netherlands, September 16–19, 2019, Proceedings. editor / Maren Scheffel ; Julien Broisin ; Viktoria Pammer-Schindler ; Andrea Ioannou ; Jan Schneider. Cham : Springer, 2019. pp. 224-235 (Lecture Notes in Computer Science, Vol. 11722).
@inproceedings{489829cec5184453a70e22ed7cd62bee,
title = "Identifying Learning Activity Sequences that Are Associated with High Intention-Fulfillment in MOOCs",
abstract = "Learners join MOOCs (Massive Open Online Courses) with a variety of intentions. The fulfillment of these initial intentions is an important success criterion in self-paced and open courses. Using post course self-reported data enabled us to divide the participants to those who fulfilled the initial intentions (high-IF) and those who did not fulfill their initial intentions (low-IF). We used methods adapted from natural language processing (NLP) to analyze the learning paths of 462 MOOC participants and to identify activities and activity sequences of participants in the two groups. Specifically, we used n-gram analysis to identify learning activity sequences and keyness analysis to identify prominent learning activities. These measures enable us to identify the differences between the two groups. Differences can be seen at the level of single activities, but major differences were found when longer n-grams were used. The high-IF group showed more consistency and less divergent learning behavior. High-IF was associated, among other things, with study patterns of sequentially watching video lectures. Theoretical and practical suggestions are introduced in order to help MOOC developers and participants to fulfill the participants’ learning intentions.",
keywords = "MOOCs, massive open online courses, Intention-fulfilment, Keyness, N-gram, Learning activity sequences",
author = "Eyal Rabin and Vered Silber-Varod and Yoram Kalman and M. Kalz",
year = "2019",
month = "9",
day = "9",
doi = "10.1007/978-3-030-29736-7_17",
language = "English",
isbn = "9783030297350",
series = "Lecture Notes in Computer Science",
publisher = "Springer",
pages = "224--235",
editor = "Maren Scheffel and Julien Broisin and Viktoria Pammer-Schindler and Andrea Ioannou and Jan Schneider",
booktitle = "Transforming Learning with Meaningful Technologies",

}

Rabin, E, Silber-Varod, V, Kalman, Y & Kalz, M 2019, Identifying Learning Activity Sequences that Are Associated with High Intention-Fulfillment in MOOCs. in M Scheffel, J Broisin, V Pammer-Schindler, A Ioannou & J Schneider (eds), Transforming Learning with Meaningful Technologies: 14th European Conference on Technology Enhanced Learning, EC-TEL 2019, Delft, The Netherlands, September 16–19, 2019, Proceedings. Springer, Cham, Lecture Notes in Computer Science, vol. 11722, pp. 224-235, 14th European Conference on Technology Enhanced Learning, Delft, Netherlands, 16/09/19. https://doi.org/10.1007/978-3-030-29736-7_17

Identifying Learning Activity Sequences that Are Associated with High Intention-Fulfillment in MOOCs. / Rabin, Eyal; Silber-Varod, Vered; Kalman, Yoram; Kalz, M.

Transforming Learning with Meaningful Technologies: 14th European Conference on Technology Enhanced Learning, EC-TEL 2019, Delft, The Netherlands, September 16–19, 2019, Proceedings. ed. / Maren Scheffel; Julien Broisin; Viktoria Pammer-Schindler; Andrea Ioannou; Jan Schneider. Cham : Springer, 2019. p. 224-235 (Lecture Notes in Computer Science, Vol. 11722).

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingAcademicpeer-review

TY - GEN

T1 - Identifying Learning Activity Sequences that Are Associated with High Intention-Fulfillment in MOOCs

AU - Rabin, Eyal

AU - Silber-Varod, Vered

AU - Kalman, Yoram

AU - Kalz, M.

PY - 2019/9/9

Y1 - 2019/9/9

N2 - Learners join MOOCs (Massive Open Online Courses) with a variety of intentions. The fulfillment of these initial intentions is an important success criterion in self-paced and open courses. Using post course self-reported data enabled us to divide the participants to those who fulfilled the initial intentions (high-IF) and those who did not fulfill their initial intentions (low-IF). We used methods adapted from natural language processing (NLP) to analyze the learning paths of 462 MOOC participants and to identify activities and activity sequences of participants in the two groups. Specifically, we used n-gram analysis to identify learning activity sequences and keyness analysis to identify prominent learning activities. These measures enable us to identify the differences between the two groups. Differences can be seen at the level of single activities, but major differences were found when longer n-grams were used. The high-IF group showed more consistency and less divergent learning behavior. High-IF was associated, among other things, with study patterns of sequentially watching video lectures. Theoretical and practical suggestions are introduced in order to help MOOC developers and participants to fulfill the participants’ learning intentions.

AB - Learners join MOOCs (Massive Open Online Courses) with a variety of intentions. The fulfillment of these initial intentions is an important success criterion in self-paced and open courses. Using post course self-reported data enabled us to divide the participants to those who fulfilled the initial intentions (high-IF) and those who did not fulfill their initial intentions (low-IF). We used methods adapted from natural language processing (NLP) to analyze the learning paths of 462 MOOC participants and to identify activities and activity sequences of participants in the two groups. Specifically, we used n-gram analysis to identify learning activity sequences and keyness analysis to identify prominent learning activities. These measures enable us to identify the differences between the two groups. Differences can be seen at the level of single activities, but major differences were found when longer n-grams were used. The high-IF group showed more consistency and less divergent learning behavior. High-IF was associated, among other things, with study patterns of sequentially watching video lectures. Theoretical and practical suggestions are introduced in order to help MOOC developers and participants to fulfill the participants’ learning intentions.

KW - MOOCs

KW - massive open online courses

KW - Intention-fulfilment

KW - Keyness

KW - N-gram

KW - Learning activity sequences

U2 - 10.1007/978-3-030-29736-7_17

DO - 10.1007/978-3-030-29736-7_17

M3 - Conference article in proceeding

SN - 9783030297350

T3 - Lecture Notes in Computer Science

SP - 224

EP - 235

BT - Transforming Learning with Meaningful Technologies

A2 - Scheffel, Maren

A2 - Broisin, Julien

A2 - Pammer-Schindler, Viktoria

A2 - Ioannou, Andrea

A2 - Schneider, Jan

PB - Springer

CY - Cham

ER -

Rabin E, Silber-Varod V, Kalman Y, Kalz M. Identifying Learning Activity Sequences that Are Associated with High Intention-Fulfillment in MOOCs. In Scheffel M, Broisin J, Pammer-Schindler V, Ioannou A, Schneider J, editors, Transforming Learning with Meaningful Technologies: 14th European Conference on Technology Enhanced Learning, EC-TEL 2019, Delft, The Netherlands, September 16–19, 2019, Proceedings. Cham: Springer. 2019. p. 224-235. (Lecture Notes in Computer Science, Vol. 11722). https://doi.org/10.1007/978-3-030-29736-7_17