CU Thinking: Problem-Solving Strategies Revealed
CU Thinking: Problem-Solving Strategies Revealed
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CU 思维：揭示解决问题的策略
DOI：
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发表时间：
2011
期刊：
影响因子：
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通讯作者：
R. Pargas
中科院分区：
文献类型：
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作者：
L. Benson;Sarah J. Grigg;David R. Bowman;Michelle Cook;R. Pargas
为了分析工科学生的问题解决策略，我们正在收集在平板电脑上完成的作业，并使用“标签”分析数字 Ink，以使用名为 MuseInk 的定制设计软件识别感兴趣的事件。收集的工作包括在克莱姆森大学 (CU) 第一年工程课程中完成的问题，这些问题是根据其复杂程度、多种方法或表示的潜力以及所提供的结构和/或定义的水平而专门选择的。 “标签宇宙”是一个包含程序事件、错误和其他感兴趣项目的数据库，用于标记学生作业中的相关事件。标签宇宙根据问题解决过程中使用的过程活动的理论框架进行分类：知识获取、知识生成和自我管理。标签包括诸如勾画问题、识别已知和未知值、操纵方程来求解所需变量以及检查解的合理性等项目。此外，对学生的错误进行分类（概念性、程序性和机械性），并根据信号检测理论分析学生对错误的认识。这可以识别“命中”（学生犯了错误并自我纠正）、“未命中”（学生犯了错误但没有意识到）和“误报”（学生事后猜测正确的方法）。 MuseInk 还允许插入音频标签来记录学生对特定事件发生时的想法的口头评论。我们进行了一项用户调查，以确定如何增加使用 MuseInk 的学生的收益。使用 MuseInk 的教程和其他课堂活动是根据 2010 年秋季/2011 年春季使用的调查数据开发的。迄今为止，已从总共 26 名学生（19 名男性，7 名女性）收集了三个问题集的工作解决方案和音频评论。我们的研究团队已对三个问题集之一进行了标记，并进行了评分者间的可靠性分析以确保标记的一致性。标签数据（书面和口头）正在根据标签类别与学生的学术背景和工程先验知识之间的关系进行分析。我们开始定义构建问题的标准，让具有广泛教育经验和学术准备的学生培养有效且可转移的解决问题的技能。虽然我们使用 MuseInk 作为研究工具的方法正在不断发展，但我们也在考虑如何将该软件用作教学工具。我们进行了一项用户调查，以确定如何增加使用 MuseInk 的学生的收益。课堂内外使用 MuseInk 的活动正在根据调查数据（例如教程和同伴反馈）进行开发。
In order to analyze engineering students’ problem-solving strategies, we are collecting work completed on Tablet PCs and analyzing the digital Ink using “tags” to identify events of interest using custom-designed software called MuseInk. The work collected includes problems completed in a first year engineering course at Clemson University (CU) specifically selected for their level of complexity, potential for multiple approaches or representations, and the level of structure and/or definition provided. A “Tag Universe,” a database of procedural events, errors, and other items of interest, has been developed to tag relevant events within student work. The Tag Universe is organized into categories based on a theoretical framework of process activities used during problem solving: knowledge access, knowledge generation and self-management. Tags include items such as sketching the problem, identifying known and unknown values, manipulating an equation to solve for a desired variable, and checking the reasonableness of a solution. In addition, student errors are categorized (conceptual, procedural, and mechanical), and students’ recognition of their errors are being analyzed based on signal detection theory. This identifies “hits” (student makes an error and self-corrects), “misses” (student makes an error and does not recognize it) and “false alarms” (student second-guesses a correct approach). MuseInk also allows the insertion of audio tags to document students’ verbal commentaries about what they were thinking when specific events occurred. A user survey was implemented to identify ways to increase benefits to students using MuseInk. Tutorials and additional classroom activities using MuseInk were developed based on survey data for use in Fall 2010/Spring 2011. To date, worked solutions and audio commentary for three problem sets were collected from total of 26 students (19 males, 7 females). One of the three problem sets has been tagged by our research team, and inter-rater reliability analysis was conducted to ensure consistent tagging. Tag data (written and verbal) is in the process of being analyzed in terms of relationships between tag categories and students’ academic backgrounds and prior knowledge about engineering. We are beginning to define criteria for structuring problems to allow students from a broad array of prior educational experiences and academic preparation to develop effective and transferrable problem-solving skills. While our methods, which use MuseInk as a research tool, are evolving, we are also considering how the software is being used as an instructional tool. A user survey was implemented to identify ways to increase benefits to students using MuseInk. Activities using MuseInk both inside and outside the classroom are being developed based on survey data, such as tutorials and peer feedback.