Math Education: An Eye-Tracking and Emotion Analysis Experiment for Creating Automated Competency Assessments
In an intriguing development, a new study is underway to determine if close visual observation of learners can be used as a means to automatically elicit competency data, a task that is typically performed by human educators.
The study, presented in a recent paper, is spearheaded by a team of experts in educational technology, computer vision, and learning analytics. The objective is to explore whether visual observation can be a reliable method for automatically gathering competency data, without the need for manual input or maintenance.
The focus of the study is on adaptive learning systems like ALeA, which contain competency estimations for thousands of concepts across multiple dimensions, such as Bloom's learning levels. The researchers aim to help these systems adapt their behaviour based on learners' competencies, preferences, and skills, similar to human educators.
The anticipated gain in productivity from personalization is often offset by the effort involved in collecting and maintaining user models. If successful, the study's findings could potentially reduce this effort, contributing to increased productivity gains in adaptive learning systems.
The study's methodology involves observing learners closely to gather competency data automatically. This approach could potentially increase the productivity gains from personalization in adaptive learning systems, while bridging the gap between human educators' abilities to assess learners' competencies and the capabilities of adaptive learning systems.
It is important to note that the study does not involve the use of advertisements in the process of eliciting competency data. The ultimate goal is to enable adaptive learning systems to perform tasks similar to those performed by human educators, such as eliciting competency data.
The study's results could contribute to the development of adaptive learning systems that can adapt their behaviour based on learners' competencies, preferences, and skills, ultimately enhancing the learning experience for all.
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