通过分析思维-陈述协议中的自我调节学习来理解系统游戏
Understanding Gaming the System by Analyzing Self-Regulated Learning in Think-Aloud Protocols
AI总结：
本研究通过分析思维-陈述协议中的自我调节学习，发现系统游戏可能代表一种不适应的自我调节学习形式，并提出通过设计针对性系统来改善学习。
摘要：
在数字学习系统中，'系统游戏'指的是学生通过系统性地利用系统功能来完成教育任务，而不是有意义地参与内容的情况。通常被视为一种行为脱节，系统游戏与短期和长期的学习成果呈负相关。然而，很少有研究超越其行为表现来探讨这一现象，留下诸如学生是否认知脱节，或在游戏期间是否采用不同的自我调节学习（SRL）策略等问题未被回答。本研究采用混合方法方法，通过学生与智能教学系统互动时收集的思维-陈述协议，分析学生在游戏和非游戏期间的认知参与和SRL过程。我们发现，游戏并不单纯反映认知努力的缺乏；在游戏期间，学生经常产生更长的陈述，更可能参与信息处理和识别错误，但更少参与规划，并表现出反应而非主动的自我调节策略。这些发现提供了实证证据，支持系统游戏可能代表一种不适应的SRL形式的解释。有了这种理解，未来的工作可以通过设计针对不适应自我调节的系统来解决系统游戏及其负面影响。
英文摘要：
In digital learning systems, gaming the system refers to occasions when students attempt to succeed in an educational task by systematically taking advantage of system features rather than engaging meaningfully with the content. Often viewed as a form of behavioral disengagement, gaming the system is negatively associated with short- and long-term learning outcomes. However, little research has explored this phenomenon beyond its behavioral representation, leaving questions such as whether students are cognitively disengaged or whether they engage in different self-regulated learning (SRL) strategies when gaming largely unanswered. This study employs a mixed-methods approach to examine students' cognitive engagement and SRL processes during gaming versus non-gaming periods, using utterance length and SRL codes inferred from think-aloud protocols collected while students interacted with an intelligent tutoring system for chemistry. We found that gaming does not simply reflect a lack of cognitive effort; during gaming, students often produced longer utterances, were more likely to engage in processing information and realizing errors, but less likely to engage in planning, and exhibited reactive rather than proactive self-regulatory strategies. These findings provide empirical evidence supporting the interpretation that gaming may represent a maladaptive form of SRL. With this understanding, future work can address gaming and its negative impacts by designing systems that target maladaptive self-regulation to promote better learning.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
