Abstract
Teachers often have their own professional requirements for e-learning systems. However, these are often only subliminal known. In times of Industry 4.0 and AI, teachers e.g. in engineering are also confronted with the need to teach increasingly complex concepts. Those are only two of the reasons why an e-learning recommendation system has been developed to support teachers in choosing an e-learning format. To better understand the perspective of the teachers, the central question is: What are the teachers’ requirements for the e-learning formats examined here? After a introduction to the recommendation system, the analysis of the collected data is explained. Based on recommendations given in the past, we examine which requirements have led to a clear recommendation or to the advice against individual formats. Among the formats considered here, virtual reality and simulations are the most recommended on average, as they are best suited to the teacher’s requirements. Subsequently, the profound results in the areas of virtual laboratories, virtual reality, simulations and gaming-based solutions will be presented and discussed. However, the results also show how diverse the requirements are. The recommendation for e-learning developers and companies is therefore: e-learning solutions should be adaptive for teachers and students. Finally, it can be concluded that in the future teachers will have to use a mix of different e-learning solutions in order to be able to teach the increasingly complex world of tomorrow.
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Acknowledgment
This work is part of the project ELLI, “Excellent Teaching and Learning in Engineering Sciences,” and was funded by the federal ministry of education and research (“BMBF”), Germany.
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Sommer, T., Stehling, V., Haberstroh, M., Hees, F. (2019). What Are Teachers’ Requirements for Remote Learning Formats? Data Analysis of an E-Learning Recommendation System. In: Auer, M., Langmann, R. (eds) Smart Industry & Smart Education. REV 2018. Lecture Notes in Networks and Systems, vol 47. Springer, Cham. https://doi.org/10.1007/978-3-319-95678-7_23
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