SBIR Phase II: Providing Tools for Richer eLearning Assessment

SBIR 第二阶段：提供更丰富的电子学习评估工具

• 批准号: 0620380
• 负责人: Linda Chaput
• 金额: --
• 依托单位: AGILE MIND INC
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-08-01 至 2010-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0620380&HistoricalAwards=false
• 关键词: SBIR; Phase; II; Providing; Tools

This Small Business Innovation Research (SBIR) Phase II project will study effective models for carrying out assessments employing challenging puzzle-like questions that incorporate distractor analyses in which meaning is assigned to complex responses. Such distractor analyses apply where there is the possibility that the test taker can give alternative correct, partially correct, and incorrect answers. Metadata and distractor analyses will be combined to provide in-depth reports on student test performance. This new rule-based solution to distractor analysis meets a significant challenge in being able to include engaging problems in assessments of student progress in quantitative courses, such as Algebra and Geometry. The research will further develop question authoring and test construction tools. As a consequence of this work, educators using these new technologies will be able to move beyond online testing based solely on multiple-choice, single-answer questions that are known to be unmotivating for many students. The goals are twofold: to provide varied, interesting, and even gamelike learning interactions that incorporate motivational and pedagogically valuable feedback; and to do so in a form in which empirical evidence can be used to improve the assessment corpus - both the metadata and the rules used for defining distractor analysis, especially where the items are novel question types.

这个小企业创新研究（SBIR）第二阶段项目将研究有效的模型进行评估，采用具有挑战性的益智类问题，包括干扰分析，其中的意义被分配给复杂的反应。这种干扰分析适用于考生可能给出正确答案、部分正确答案和不正确答案的情况。元数据和干扰因素分析将结合起来，提供深入的报告，对学生的考试成绩。这种新的基于规则的解决方案，分心物分析，满足了一个重大的挑战，能够包括参与问题的学生在定量课程，如代数和几何的进展评估。该研究将进一步开发问题创作和测试构建工具。这项工作的结果是，使用这些新技术的教育工作者将能够超越仅仅基于多项选择、单一答案的问题的在线测试，这些问题对许多学生来说是没有动力的。目标有两个：提供多样的、有趣的、甚至像游戏一样的学习互动，这些互动结合了激励和教学上有价值的反馈;并且以一种可以使用经验证据来改进评估语料库的形式来这样做--元数据和用于定义干扰物分析的规则，特别是在项目是新问题类型的情况下。