SGER: Detecting, Identifying, and Analyzing Cognitive, Affective, Metacognitive, and Motivational (CAMM) States During Self-Regulated Learning with Hypermedia

了解超媒体学习背景下认知、情感、元认知和动机 (CAMM) 过程的部署是理解成功和不成功的学习者在自我调节学习 (SRL) 过程中这些过程的线性、迭代和动态展开的关键。然而，这是一个非常困难的问题。该探索性项目的目标是使用尖端传感器（即生理设备（例如肌电图传感器）、视频捕获和记录设备、眼球追踪设备和录音）来尝试系统地捕获、识别和分析复杂学习过程中这些过程的部署。该项目将通过以下方式扩展当前的理论、方法和分析方法和工具：（1）通过精心设计实验性地诱导特定的SRL过程，研究学生如何使用超媒体在SRL期间实现学习目标超媒体环境的影响；（2）检查 CAMM 过程的波动及其与学习结果的关系；以及（3）建立研究协议，通过使用多个生理传感器，最大限度地提高研究人员在 SRL 期间收集 CAMM 状态的能力。学习问题，例如适应性、元认知监控和控制的作用以及超媒体学习期间动机和情感的调节。

Understanding the deployment of cognitive, affective, metacognitive, and motivation (CAMM) processes in the context of hypermedia learning is key to understanding the linear, iterative, and dynamic unfolding of these processes during self-regulated learning (SRL) among successful and unsuccessful learners. However, this is a very difficult problem. The goal of this exploratory project is to use cutting-edge sensors (i.e., physiological devices (e.g., EMG sensors), video capturing and recording devices, eye-tracking equipment, and voice recording to attempt to systematically capture, identify, and analyze the deployment of these processes during complex learning. This project will extend current theoretical,methodological, and analytical methods and tools by: (1) studying how students accomplish learning goals during SRL with hypermedia by experimentally inducing specific SRL processes through the deliberate design of a hypermedia environment; (2) examining the fluctuations in the CAMM processes and how they are related to learning outcomes; and (3) establishing research protocols that maximize researchers? ability to converge and concurrently collect the temporal deployment of CAMM states during SRL with hypermedia via the use of several physiological sensors. The broader impact of this research includes the design and development of learning interventions for adaptive computer-based learning environments designed to detect, model, trace, and foster students? self-regulated learning. More specifically, instructional prescriptions will be derived focusing on key learning issues such as adaptivity, the role of metacognitive monitoring and control, and the regulation of motivation and affect during hypermedia learning.