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Teaching & Learning Analytics for Data-Based Optimization of Teaching and Learning Processes in Courses with Blended Learning

  • Learning Management Systems (LMS), such as Moodle, enable the rapid progress of digitisation in teaching, which is no longer only taking place in the lecture hall, but increasingly “online” and asynchronously. New didactic concepts (blended learning, “flipped classroom”) consist of alternating self-learning and face-to-face phases, with the former taking place in the LMS, i.e. online. However, no analysis has yet been carried out as to how students act with the material in the self-learning phase, or the teachers are not provided with any information about the learning progress of the students during the self-learning phase. In this paper, concepts of learning and teaching analytics are presented to answer these questions and to integrate the measures derived from them into the teaching processes in a sustainable manner.

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Metadaten
Author:Lars MehnenORCiD, Birgit Pohn, Matthias Blaickner, Thomas Mandl, Isabel Dregely
ISBN:978-953-290-117-7
Parent Title (English):2022 International Conference on Software, Telecommunications and Computer Networks (SoftCOM), 2022
Publisher:IEEE
Document Type:Conference Proceeding
Language:English
Completed Date:2022/10/18
Date of first Publication:2022/10/18
Responsibility for metadata:Fachhochschule Technikum Wien
Release Date:2023/01/22
GND Keyword:Learning management systems; artificial intelligence; learning analytics; learning management systems; teaching analytics
Pagenumber:5
Publish on Website:1
Open Access:0
Reviewed:0
Link to Publication:https://doi.org/10.23919/SoftCOM55329.2022.9911349
Invited:0
Keynote:0
Department:Department Computer Science
Dewey Decimal Classification:0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik
Research Focus:Sonstiges
Projects:Import
Studienjahr:2022/2023