"A Time and Phase for Everything" - Towards A Self Regulated Learning Perspective on Computational Support for Esports-Reference-Cited by-同舟云学术

"A Time and Phase for Everything" - Towards A Self Regulated Learning Perspective on Computational Support for Esports

Published:2022-10-25 Issue:CHI PLAY Volume:6 Page:1-27
ISSN:2573-0142
Container-title:Proceedings of the ACM on Human-Computer Interaction
language:en
Short-container-title:Proc. ACM Hum.-Comput. Interact.

Author:

Kleinman Erica¹,Habibi Reza¹,Yao Yichen¹,Gayle Christian¹,Seif El-Nasr Magy²

Affiliation:

1. University of California, Santa Cruz, Santa Cruz, CA, USA

2. University of California, Santa Cruz, Santa Clara, CA, USA

Abstract

Computational support for learning in the domain of esports has seen a great deal of attention in recent years as an effective means of helping players learn and reap the benefits of play. However, previous work has not examined the tools from a learning theory perspective to assess if learning is prompted and supported in the right place and time. As a first step towards addressing this gap, this paper presents the results of two studies: a review of existing computational tools, and an online survey of esports' players' learning needs supplemented with qualitative interviews. Using Zimmerman's Cyclical Phase Model of Self-Regulated Learning as a lens, we identify patterns in the types of support offered by existing tools and players' support interests during different learning phases. We identify 11 opportunities for future research and development to better support self-regulated learning in esports.

Funder

National Science Foundation

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Networks and Communications,Human-Computer Interaction,Social Sciences (miscellaneous)

Link

https://dl.acm.org/doi/pdf/10.1145/3549481

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