Speech Technology Enhanced Assessment of Modeling (STEAM)

该项目旨在通过开发改进的语音识别技术，校准以识别儿童的语音，并将其与涉及交互式表示和模拟的计算机化数学教育环境（SimCalc）相结合，实现对学生数学推理的更有效和更准确的评估。 具体问题包括：Q1。约束学生的最有前途的任务相关机制是什么？以这样一种方式，使有效和可靠的语音为基础的评估，尽管自动口语系统的准确性不完美的口语反应？Q2.对现有的口语技术进行什么样的最有效的修改，才能让中学生在进行关于数学模型、表征和模拟的自发言语行为时达到可接受的表现？Q3.基于计算机的动态表示系统的哪些方面必须与学生的语音相结合，以提供更完整的表示学生的数学知识的基础模型？Q4.基于计算机的环境和学生语音的组合输出的哪些特征允许口语理解引擎可靠地为学生作业分配基于规则的分数？评估将解决数学模型流畅性的五个关键方面：理解，预测，解释，改进和反思。 这项工作的一个特别独特的重点将是结合从语音识别引擎的输入与时间戳的信息，从数学教育环境中可靠地得分学生的反应，根据一个标题。除了在教育方面的应用外，这项关于青少年自发数学语言的研究将推动口语技术的进步。

This project seeks to achieve more efficient and accurate assessment of students' mathematical reasoning by developing improved speech recognition technology, calibrated to recognize children's speech, and integrating it with a computerized mathematics education environment (SimCalc) involving interactive representations and simulations. Specific questions of interest include:Q1. What are the most promising task-relevant mechanisms for constraining students? spoken responses in such a way that enables valid and reliable speech-based assessments despite the imperfect accuracy of automatic spoken language systems?Q2. What are the most efficient modifications to existing spoken language technologies that achieve acceptable performance with middle-school students engaged in spontaneous speech acts about mathematical models, representations, and simulations?Q3. Which aspects of the computer-based dynamic representation system must be integrated with student speech to provide a more complete representation of student knowledge of the mathematics underlying the model?Q4. Which features of the combined output of the computer-based environment and student speech allow the spoken language understanding engine to reliably assign rubric-based scores to student work?Assessments will address five key aspects of fluency with mathematical models: comprehending, predicting, explaining, improving, and reflecting. A particularly unique focus of this work will be on combining inputs from the speech recognition engine with time-stamped information from a mathematics education environment to reliably score student responses according to a rubric. In addition to its application to education, this research on adolescents' spontaneous mathematical speech will drive advances in spoken language technology.