SmaEPho–Smart Photometry in Education 4.0

Bibliographic Data

ID22042567
AuthorsLena Geuer (0000-0002-8396-5881, University of Kaiserslautern), Frederik Lauer (0000-0001-5935-4872, University of Kaiserslautern), Jochen Kühn (0000-0002-6985-3218, Ludwig-Maximilians-Universität München), Norbert Wehn (0000-0002-9010-086X, University of Kaiserslautern), Roland Ulber (0000-0002-7674-0967, University of Kaiserslautern, corresponding author)
Year2023
Volume13
Issue2
Pages136
Publication date2023-01-28
Open AccessYes
TypeARTICLE
VenueEducation Sciences (JOURNAL)
Journal identifiersISSN: 2227-7102 • E-ISSN: 2227-7102
PublisherMDPI AG (PUBLISHER • IT)
DOI10.3390/educsci13020136
OpenAlexW4318473277
LanguageEN
References cited36

Digitization offers new perspectives for educational research to identify the effects of visualizations regarding cognitive processing. In addition, new types of data can be generated, expanding the possibilities for visualizing cognitive processes and understanding human learning. Digital twins are already used in Industry 4.0, as an additional visualization to a real object, for data mining and data analysis for process optimization. The increasing integration of digital twins in the industrial sector requires the formulation of corresponding educational goals to ensure high-quality and future-oriented education. Therefore, future generations must be introduced to technologies from industry during their education. In this paper, an intelligent photometric measurement system called SmaEPho with a digital twin for science, technology, engineering, and mathematics (STEM) learning is presented. In addition to its function as a photometric measurement device, an intelligent sensor technology allows for data generation on the user’s usage behavior. The digital twin reflects and visualizes these data in real-time. This enables a variety of new didactic and methodological approaches in teaching. A first study evaluating the hardware and tracking components of SmaEPho shows that the deviation accuracy of the measurement system is sufficient for experimental applications in schools. Another study with n=52 students confirmed the excellent usability of the SmaEPho hardware platform. These research results lay the foundation for a variety of future research questions on data analysis and machine learning algorithms with the aim of increasing the quality of education. The use of intelligent digital twins as an element of digitization in educational contexts offers the extended possibility of identifying cognitive processing steps using this technology

Big data · Data mining · Data science · Digitization · Human–computer interaction · Multimedia · Usability · Visualization · Computer Science · Digital Transformation in Industry · Engineering Education and Technology · Technology Assessment and Management · Artificial Intelligence

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