Workshop on Metacognition and Self- Regulated Learning in Intelligent Tutoring Systems

Prediction of Academic Self-efficacy Based on Self-regulated Learning Strategies, Metacognition Strategies And Goal-Progress Orientation In Students

The purpose of this study was to determine the prediction of academic self-efficacy based on self-regulated learning strategies, metacognition strategies and goal-progress orientation in students of Islamic Azad University branch Ahvaz. This research is correlational. For this purpose, the community of students, 400 people (180 boys and 180 girls) was selected based on stratified random samplin...

Developing Self-Regulated Learners Through an Intelligent Tutoring System

Intelligent tutoring systems have been developed to help students learn independently. However, students who are poor selfregulated learners often struggle to use these systems because they lack the skills necessary to learn independently. The field of psychology has extensively studied self-regulated learning and can provide strategies to improve learning, however few of these include the use ...

In vivo experiments on whether supporting metacognition in intelligent tutoring systems yields robust learning

Designing for Metacognition - Applying Cognitive Tutor Principles to the Tutoring of Help Seeking

Intelligent Tutoring Systems have been shown to be very effective in supporting learning in domains such as mathematics, physics, computer programming, etc. However, they are yet to achieve similar success in tutoring metacognition. While an increasing number of educational technology systems support productive metacognitive behavior within the scope of the system, few attempt to teach skills s...

Metacognition and Learning in Spoken Dialogue Computer Tutoring

We investigate whether four metacognitive metrics derived from student correctness and uncertainty values are predictive of student learning in a fully automated spoken dialogue computer tutoring corpus. We previously showed that these metrics predicted learning in a comparable wizarded corpus, where a human wizard performed the speech recognition and correctness and uncertainty annotation. Our...