定义ST数学中的生产性斗争:在数字学习环境中制定学习行为和策略指标的意义

Andrew E. Krumm, Andrew Coulson, J. Neisler
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引用次数: 2

摘要

本文描述了在广泛使用的称为ST Math的数字学习环境中操作定义生产性斗争的过程。制定一个可操作定义的过程涉及到研究人员先前在数字学习环境中量化生产斗争的方法的现有文献。使用先前的研究,我们将生产性斗争定义为学生在保持未来成功可能性的同时坚持数字化学习任务。为了开发一个机器可执行的生产性挣扎定义,我们确定了学习者完成ST Math中的一个关卡所需的典型尝试次数,并应用改进的性能因素分析算法来估计学习者在一个关卡中随后的谜题尝试中成功的概率。使用不同的重新尝试和预测概率的定义,我们检查了可以被新分类为生产性斗争实例的关卡尝试的比例。本文中描述的实用主义方法旨在为其他寻求制定生产性斗争指标的数字学习环境提供范例。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Defining Productive Struggle in ST Math: Implications for Developing Indicators of Learning Behaviors and Strategies in Digital Learning Environments
This paper describes a process for operationally defining productive struggle in a widely used digital learning environment called ST Math. The process for developing an operational definition involved examining the existing literature for ways in which researchers have previously quantified productive struggle in digital learning environments. Using prior research, we defined productive struggle as a student persisting in a digital learning task while maintaining a likelihood of future success. To develop a machine-executable definition of productive struggle, we identified the typical number of attempts learners needed to complete a level in ST Math and applied a modified Performance Factors Analysis algorithm to estimate learners’ probability of success on a subsequent puzzle attempt within a level. Using definitions that differentially combined re-attempts and predicted probabilities, we examined the proportion of level attempts that could be newly classified as instances of productive struggle. The pragmatic approach described in this paper is intended to serve as an example for other digital learning environments seeking to develop indicators of productive struggle.
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