Imperial College London
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DrMichaelYeomans

Business School

Assistant Professor in Strategy and Organisational Behaviour
 
 
 
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Contact

 

m.yeomans

 
 
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Location

 

Business School BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@inproceedings{Cho:2024:10.1145/3636555.3636891,
author = {Cho, JY and Tao, Y and Yeomans, M and Tingley, D and Kizilcec, RF},
doi = {10.1145/3636555.3636891},
pages = {360--370},
publisher = {ACM},
title = {Which planning tactics predict online course completion?},
url = {http://dx.doi.org/10.1145/3636555.3636891},
year = {2024}
}
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RIS format (EndNote, RefMan)

TY  - CPAPER
AB  - Planning is a self-regulated learning strategy and widely used behavior change technique that can help learners achieve academic goals (e.g., pass an exam, apply to college, or complete an online course). Numerous studies have tested the effects of planning interventions, but few have examined the content of learners’ plans and how it relates to their academic outcomes. Building on a large-scale intervention study, we conducted a qualitative content analysis of 650 learner plans sampled from 15 massive open online courses (MOOCs). We identified a number of planning tactics, compared their prevalence, and examined which ones significantly predict course progress and completion using regression analyses. We found that learners whose plans specify a time of day (e.g., morning, afternoon, night) are significantly more likely to complete a MOOC, but only 25% of the learners in our sample used this tactic. The high degree of variation in the effectiveness of planning tactics may contribute to mixed intervention findings in scale-up studies. Models of plan effectiveness can be used to provide feedback on the quality of learners’ plans and encourage them to use effective tactics to achieve their learning goals.
AU  - Cho,JY
AU  - Tao,Y
AU  - Yeomans,M
AU  - Tingley,D
AU  - Kizilcec,RF
DO  - 10.1145/3636555.3636891
EP  - 370
PB  - ACM
PY  - 2024///
SP  - 360
TI  - Which planning tactics predict online course completion?
UR  - http://dx.doi.org/10.1145/3636555.3636891
UR  - https://dl.acm.org/doi/10.1145/3636555.3636891
UR  - http://hdl.handle.net/10044/1/108919
ER  -
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