Contextual Research-Empirical Research--Detecting, Tracking, and Modeling Cognitive, Affective, and Metacognitive Regulatory Processes to Optimize Learning with MetaTutor

这个为期3年的项目以实验室为基础进行实验研究，以扩展和应用基于多智能体的智能超媒体学习环境来检测、跟踪和模拟大学生在学习生物时的多重自我调节过程。研究人员检验的假设是，许多大学生在学习生物时可能会因为无法自我调节而受到阻碍。研究人员开发了一种家教，预计将提供认知、情感和元认知(CAM)支持。这项拟议的研究将对不同版本的导师计划进行实验测试，以检验自我调节过程是如何出现的，以及程序变化对自我调节行为的影响。研究人员将在田纳西州孟菲斯和加拿大蒙特利尔的一个实验室里对大学生进行实验。本实验将检测、跟踪和模拟大学生学习复杂生物主题的计算机辅助教学过程。在实验期间，他们将使用远程眼睛跟踪器收集数据，以记录参与者的眼睛凝视、凝视、眼跳和倒退。参与者的言辞将用耳机麦克风记录下来。他们将使用压力鼠标来捕捉整个活动过程中对鼠标施加的压力，并使用身体压力测量系统(BPMS)来评估身体的总体运动。他们将修订和开发循环系统的新的前测和后测学习方法，其中将包括大约15个多项选择题、10个推理问题、标记任务和心理模型论文。这些措施将评估循环系统的陈述性、程序性、推断性和心智模型。研究人员将审查几个关于自我调节的理论、实证和教育问题，旨在打造科学学习的新方向。该团队包括心理学家、计算机科学家、心理测量学家和电气工程师。课程将结合心理学、教育学、计算机科学和电子工程学的方法论，以检测、追踪、模拟和评估学生在学习复杂和具有挑战性的科学主题过程中的CAM自我调节过程。拟议的研究活动旨在促进复杂传感数据的学习、方法论和定量分析的科学，以及教育、研究和评估，并展示能够分析和预测学生关于复杂科学主题的自我调节学习的多种方法研究工具、软件和传感设备的力量。

This 3-year project conducts laboratory based experimental research to extend and apply a multiagent intelligent hypermedia-based learning environment to detect, track, and model college students' multiple self-regulatory processes while learning biology. The hypothesis examined by the researchers is that many college students may be hampered in learning biology by their inability to self-regulate themselves. The researchers have developed a Tutor that is expected to provide cognitive, affective, and metacognitive (CAM) support. The proposed research will test experimentally different versions of the Tutor program to examine how self-regulatory processes emerge and the effects of program variations on self-regulatory behaviors.The investigators will conduct experiments in a laboratory with college students in Memphis Tennessee and Montreal, Canada. The experiment will detect, track, and model the CAM processes in college students' learning about a complex biology topic. During the experimental session they will collect data using a remote eye-tracker to record participants' eye gaze, fixations, saccades, and regressions. The participants' verbalizations will be recorded with a headset microphone. They will use a Pressure Mouse to capture the amount of pressure placed on the mouse throughout the activity, and the Body Pressure Measurement System (BPMS) to assess gross body movements. They will revise and develop new pretest and posttest learning measures for the circulatory system which will include approximately 15 multiple-choice questions, 10 inference questions, labeling tasks, and mental model essays. The measures will assess declarative, procedural, inferential, and mental models of the circulatory system. The research investigators will examine several theoretical, empirical, and educational questions about self regulation intended to forge new directions of science learning. The team includes psychologists, computer scientists, psychometricians, and electrical engineers. Methodologies will be incorporated from psychology, education, computer science, and electrical engineering to detect, trace, model, and assess students' CAM self-regulatory processes during learning about a complex and challenging science topic. The proposed research activities are intended to advance the science of learning, methodologies, and quantitative analysis of complex sensing data, and education, research, and evaluation, and demonstrate the power of multi-method research tools, software, and sensing devices capable of analyzing and predicting students' self-regulated learning about complex science topics.