SBIR Phase II: Providing Tools for Richer eLearning Assessment

这项小企业创新研究（SBIR）第二阶段项目将研究有效的评估模型，该模型采用具有挑战性的谜题式问题进行评估，这些问题包括干扰因素分析，在这些分析中，复杂的回答被赋予了意义。这种干扰因素分析适用于考生可能给出正确答案、部分正确答案和错误答案的情况。元数据和干扰因素分析将结合起来，提供有关学生考试成绩的深入报告。这种新的基于规则的干扰分析解决方案面临着一个重大挑战，即能够在量化课程（如代数和几何）的学生进度评估中包含引人入胜的问题。本研究将进一步开发问题编写和测试构建工具。作为这项工作的结果，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、单答案的在线测试，这些问题对许多学生来说是没有动力的。其目标有两个：提供多样化、有趣甚至是游戏式的学习互动，其中包含有激励和教学价值的反馈；而且要以一种经验证据可以用来改进评估语料库的形式来做到这一点——包括元数据和用于定义干扰分析的规则，特别是在项目是新问题类型的情况下。

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.