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The Half-Life of MOOC Knowledge : A Randomized Trial Evaluating the Testing Effect in MOOCs. / Davis, Dan; Kizilcec, René F.; Hauff, Claudia; Houben, Geert-Jan.

LAK'18 Proceedings of the 8th International Conference on Learning Analytics and Knowledge. New York : Association for Computing Machinery (ACM), 2018. p. 1-10.

Research output: Scientific - peer-reviewConference contribution

Harvard

Davis, D, Kizilcec, RF, Hauff, C & Houben, G-J 2018, The Half-Life of MOOC Knowledge: A Randomized Trial Evaluating the Testing Effect in MOOCs. in LAK'18 Proceedings of the 8th International Conference on Learning Analytics and Knowledge. Association for Computing Machinery (ACM), New York, pp. 1-10, LAK 2018 , Sydney, Australia, 7/03/18. DOI: 10.1145/3170358.3170383

APA

Davis, D., Kizilcec, R. F., Hauff, C., & Houben, G-J. (2018). The Half-Life of MOOC Knowledge: A Randomized Trial Evaluating the Testing Effect in MOOCs. In LAK'18 Proceedings of the 8th International Conference on Learning Analytics and Knowledge (pp. 1-10). New York: Association for Computing Machinery (ACM). DOI: 10.1145/3170358.3170383

Vancouver

Davis D, Kizilcec RF, Hauff C, Houben G-J. The Half-Life of MOOC Knowledge: A Randomized Trial Evaluating the Testing Effect in MOOCs. In LAK'18 Proceedings of the 8th International Conference on Learning Analytics and Knowledge. New York: Association for Computing Machinery (ACM). 2018. p. 1-10. Available from, DOI: 10.1145/3170358.3170383

Author

Davis, Dan ; Kizilcec, René F. ; Hauff, Claudia ; Houben, Geert-Jan. / The Half-Life of MOOC Knowledge : A Randomized Trial Evaluating the Testing Effect in MOOCs. LAK'18 Proceedings of the 8th International Conference on Learning Analytics and Knowledge. New York : Association for Computing Machinery (ACM), 2018. pp. 1-10

BibTeX

@inbook{2a955b98f01a41658de6d3b747be05f3,
title = "The Half-Life of MOOC Knowledge: A Randomized Trial Evaluating the Testing Effect in MOOCs",
abstract = "Retrieval practice has been established in the learning sciences as one of the most effective strategies to facilitate robust learning in traditional classroom contexts. The cognitive theory underpinning the {"}testing effect{"} states that actively recalling information is more effective than passively revisiting materials for storing information in long-term memory. We document the design, deployment, and evaluation of an Adaptive Retrieval Practice System (ARPS) in a MOOC. This push-based system leverages the testing effect to promote learner engagement and achievement by intelligently delivering quiz questions from prior course units to learners throughout the course. We conducted an experiment in which learners were randomized to receive ARPS in a MOOC to track their performance and behavior compared to a control group. In contrast to prior literature, we find no significant effect of retrieval practice in this MOOC environment. In the treatment condition, passing learners engaged more with ARPS but exhibited similar levels of knowledge retention as non-passing learners.",
keywords = "Retrieval Practice, Testing Effect, Experiment, Knowledge Retention",
author = "Dan Davis and Kizilcec, {René F.} and Claudia Hauff and Geert-Jan Houben",
year = "2018",
doi = "10.1145/3170358.3170383",
isbn = "978-1-4503-6400-3",
pages = "1--10",
booktitle = "LAK'18 Proceedings of the 8th International Conference on Learning Analytics and Knowledge",
publisher = "Association for Computing Machinery (ACM)",
address = "United States",

}

RIS

TY - CHAP

T1 - The Half-Life of MOOC Knowledge

T2 - A Randomized Trial Evaluating the Testing Effect in MOOCs

AU - Davis,Dan

AU - Kizilcec,René F.

AU - Hauff,Claudia

AU - Houben,Geert-Jan

PY - 2018

Y1 - 2018

N2 - Retrieval practice has been established in the learning sciences as one of the most effective strategies to facilitate robust learning in traditional classroom contexts. The cognitive theory underpinning the "testing effect" states that actively recalling information is more effective than passively revisiting materials for storing information in long-term memory. We document the design, deployment, and evaluation of an Adaptive Retrieval Practice System (ARPS) in a MOOC. This push-based system leverages the testing effect to promote learner engagement and achievement by intelligently delivering quiz questions from prior course units to learners throughout the course. We conducted an experiment in which learners were randomized to receive ARPS in a MOOC to track their performance and behavior compared to a control group. In contrast to prior literature, we find no significant effect of retrieval practice in this MOOC environment. In the treatment condition, passing learners engaged more with ARPS but exhibited similar levels of knowledge retention as non-passing learners.

AB - Retrieval practice has been established in the learning sciences as one of the most effective strategies to facilitate robust learning in traditional classroom contexts. The cognitive theory underpinning the "testing effect" states that actively recalling information is more effective than passively revisiting materials for storing information in long-term memory. We document the design, deployment, and evaluation of an Adaptive Retrieval Practice System (ARPS) in a MOOC. This push-based system leverages the testing effect to promote learner engagement and achievement by intelligently delivering quiz questions from prior course units to learners throughout the course. We conducted an experiment in which learners were randomized to receive ARPS in a MOOC to track their performance and behavior compared to a control group. In contrast to prior literature, we find no significant effect of retrieval practice in this MOOC environment. In the treatment condition, passing learners engaged more with ARPS but exhibited similar levels of knowledge retention as non-passing learners.

KW - Retrieval Practice

KW - Testing Effect

KW - Experiment

KW - Knowledge Retention

U2 - 10.1145/3170358.3170383

DO - 10.1145/3170358.3170383

M3 - Conference contribution

SN - 978-1-4503-6400-3

SP - 1

EP - 10

BT - LAK'18 Proceedings of the 8th International Conference on Learning Analytics and Knowledge

PB - Association for Computing Machinery (ACM)

ER -

ID: 36754547