用智能提醒工具高效捕捉学生学习关键瞬间。
The Quick Red Fox gets the best Data Driven Classroom Interviews: A manual for an interview app and its associated methodology
- 通过预设行为触发,自动定位学生学习中的关键事件。
- 支持与已有学习分析技术集成,实时提醒研究者介入时机。
- 适合教育研究者快速开展精准学习访谈,节省时间成本。
数据驱动的课堂访谈(DDCIs)是一种借助学习分析技术发展起来的访谈方法。它通过短时、有针对性的访谈,使研究者能够在不干扰学生数字学习体验的前提下,聚焦于最值得关注的学习事件。该方法依赖于名为「快速红狐」(Quick Red Fox, QRF)的开源客户端-服务器安卓应用,该工具能根据研究团队预先设定的行为模式,自动识别并引导研究者访问刚表现出特定兴趣行为的学生。QRF可与现有学生建模技术(如行为感知、情绪感知、自我调节学习检测)集成,实现对学习过程关键节点的及时提醒。本文档详细介绍了QRF的技术架构,并提供触发规则设计、访谈流程培训及数据分析方法指导。
原文摘要 · Abstract (English)
Data Driven Classroom Interviews (DDCIs) are an interviewing technique that is facilitated by recent technological developments in the learning analytics community. DDCIs are short, targeted interviews that allow researchers to contextualize students' interactions with a digital learning environment (e.g., intelligent tutoring systems or educational games) while minimizing the amount of time that the researcher interrupts that learning experience, and focusing researcher time on the events they most want to focus on DDCIs are facilitated by a research tool called the Quick Red Fox (QRF)--an open-source server-client Android app that optimizes researcher time by directing interviewers to users that have just displayed an interesting behavior (previously defined by the research team). QRF integrates with existing student modeling technologies (e.g., behavior-sensing, affect-sensing, detection of self-regulated learning) to alert researchers to key moments in a learner's experience. This manual documents the tech while providing training on the processes involved in developing triggers and interview techniques; it also suggests methods of analyses.
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