A Re-Analysis and Synthesis of Data on Affect Dynamics in Learning
A Re-Analysis and Synthesis of Data on Affect Dynamics in Learning
复制标题
学习情感动态数据的重新分析和综合
DOI:
10.1109/taffc.2021.3086118
复制
发表时间:
2023
影响因子:
11.2
通讯作者:
J. Andres
中科院分区:
文献类型:
--
作者:
Shamya Karumbaiah;R. Baker;Jaclyn L. Ocumpaugh;J. Andres
Affect dynamics, the study of how affect develops and manifests over time, has become a popular area of research in affective computing for learning. In this article, we first provide a detailed analysis of prior affect dynamics studies, elaborating both their findings and the contextual and methodological differences between these studies. We then address methodological concerns that have not been previously addressed in the literature, discussing how various edge cases should be treated. Next, we present mathematical evidence that several past studies applied the transition metric (L) incorrectly - leading to invalid conclusions of statistical significance - and provide a corrected method. Using this corrected analysis method, we reanalyze ten past affect datasets collected in diverse contexts and synthesize the results, determining that the findings do not match the most popular theoretical model of affect dynamics. Instead, our results highlight the need to focus on cultural factors in future affect dynamics research.
DOI:
--
发表时间:
2018
期刊:
Proceedings of the 11th International Conference on Educational Data Mining
影响因子:
--
作者:
Botelho, A. F.;Baker, R. S.;Ocumpaugh, J.;Heffernan, N. T.
通讯作者:
Heffernan, N. T.
DOI:
10.1145/3448139.3448154
发表时间:
2021
期刊:
LAK21: 11th International Learning Analytics and Knowledge Conference
影响因子:
--
作者:
Karumbaiah, Shamya;Lan, Andrew;Nagpal, Sachit;Baker, Ryan S.;Botelho, Anthony;Heffernan, Neil
通讯作者:
Heffernan, Neil
影响因子:
3.7
作者:
Gross, JJ;Carstensen, LL;Hsu, AYC
通讯作者:
Hsu, AYC