EduBot Unleashed - Elevating Digital Competence in Online Collaborative Learning

Publikation: Beitrag in Buch/Konferenzbericht/Sammelband/GutachtenBeitrag in KonferenzbandBeigetragenBegutachtung

Abstract

This study introduces a data-driven approach to measure and enhance digital competencies in Online Collaborative Learning (OCL) environments. Recognizing the critical role of digital competence for student engagement and collaborative success, this research leverages Learning Analytics (LA) and Large Language Models (LLMs) within a Conversational Agent (CA), “EduBot.” EduBot analyzes user activity data and provides tailored feedback to triger self-reflection for competence development. Experts identified 57 behavioral patterns of digital competence, of which five were operationalized based on alignment with available data types and measurability. Integrated into an OCL framework, EduBot collected and analyzed activity data from student interactions, providing feedback on communication, ethical practices, and collaborative tool use. The evaluation involved 20 students, revealing mixed responses: some participants found EduBot beneficial for self-reflection, while others raised concerns about feedback accuracy. Key findings highlight EduBot's potential in fostering digital competencies, though challenges in data precision and CA personalization remain. This research contributes a foundational model for competence-based feedback in digital learning and emphasizes the need for refined data collection to fully capture complex digital behaviors.

Details

OriginalspracheEnglisch
Titel2024 21st International Conference on Information Technology Based Higher Education and Training, ITHET 2024
ErscheinungsortParis
Herausgeber (Verlag)IEEE
Seitenumfang9
ISBN (elektronisch)979-8-3315-1663-5
ISBN (Print)979-8-3315-1664-2
PublikationsstatusVeröffentlicht - 16 Jan. 2025
Peer-Review-StatusJa

Externe IDs

unpaywall 10.1109/ithet61869.2024.10837628
Mendeley f60cde3c-49b9-3a86-9ae8-fccd8a4ebbc0
Scopus 85218139674

Schlagworte

Schlagwörter

  • Conversational Agent, Digital Competence, Large Language Models, Learning Analytics, Online Collaborative Learning