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Automated Monitoring of Human-Computer Interaction for Assessing Teachers' Digital Competence Based on LMS Data

Eduard de-Torres¹, Xavi Canaleta¹, David Fonseca¹

¹Human-Environment Research Group, Universitat Ramon Llull (URL), La Salle, 08022 Barcelona, Spain.

Sensors (Basel, Switzerland)

|June 19, 2024

Summary

This summary is machine-generated.

This study automates teacher digital competence evaluation using Learning Management System (LMS) interaction data. This approach offers a resource-efficient method for assessing educators' digital skills, crucial for modern education.

Keywords:

21st century skills automation digital competence digital literacy human–computer interaction teacher evaluation

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Area of Science:

Educational Technology
Computer Science

Background:

Digitalization necessitates educators developing digital competencies for effective teaching.
Existing digital competence assessment methods, like video analysis, are resource-intensive.
There's a need for scalable and efficient digital skill evaluation in education.

Purpose of the Study:

To propose an automated system for evaluating teachers' digital competence.
To leverage Learning Management System (LMS) interaction metrics for assessment.
To align evaluation with the Digital Competence Framework for Educators (DigCompEdu).

Main Methods:

Defined and extracted indicators from teacher-LMS interactions.
Developed a tool for automated digital competence evaluation.
Implemented a proof of concept for university faculty assessment.

Main Results:

Successfully automated the digital competence evaluation process.
Collected data from 987 university lecturers across diverse fields.
Enabled analysis of technological adoption based on teacher profiles.

Conclusions:

Automated LMS-based evaluation is feasible and efficient.
Results inform targeted educational interventions to enhance digital skills.
The approach supports data-driven strategies for improving digital competencies in higher education.