Nina Slamnik-Kriještorac
Thomas Huybrechts
ABSTRACT
Due to the dynamic nature of changes in various ICT technologies nowadays, the gaps between industry, research, and academia need to be bridged in order to adequately support STEM students towards their future career paths. With the COVID-19 pandemic, and restrictions on access to university premises, an agile transition of both teaching and experimentation was essential, and adjustments in the curriculum were needed more than ever. Therefore, in this paper we present an adaptive and on-demand education framework for engineering students, thereby enabling remote experimentation and adjustments of exercise content to enhance students' learning experience. We present the two types of practical experimentation environments, i.e., cloud and real-life net-working testbed, for performing remote laboratory exercises, as well as the assessment of students' experience that is used as an input for the dynamic adjustments of the exercise content. Our results show that students consider they significantly improved the baseline skills our courses tend to build and strengthen towards preparing students for their future jobs.
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Digital Library
- Henrique Carvalho de Resende, Nina Slamnik-Krijestorac, Cristiano Bonato Both, and Johann Marquez-Barja. 2020. Introducing Engineering Undergraduate Students to Network Management Techniques: a Hands-on approach using the City-lab Smart City. In 2020 IEEE Global Engineering Education Conference (EDUCON). 1316--1324. doi: http://dx.doi.org/10.1109/EDUCON45650.2020.9125159.Google ScholarCross Ref
- Guillaume Jourjon, Johann Marquez-Barja, Thierry Rakotoarivelo, Alexander Mikroyannidis, Kostas Lampropoulos, Spyros Denazis, Christos Tranoris, Daan Pareit, John Domingue, Luiz Dasilva, and Max Ott. 2015. FORGE Toolkit: Leveraging Distributed Systems in eLearning Platforms. IEEE Transactions on Emerging Topics in Computing 5 (12 2015), 1--1. doi: http://dx.doi.org/10.1109/TETC.2015.2511454.Google Scholar
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- Daniel A. Parker and Elizabeth A. Roumell. 2020. A Functional Contextualist Approach to Mastery Learning in Vocational Education and Training. Frontiers in Psychology 11 (2020), 1479. https://www.frontiersin.org/article/10.3389/fpsyg.2020.01479 doi: http://dx.doi.org/10.3389/fpsyg.2020.01479.Google ScholarCross Ref
- A. R. Rao and R. Dave. 2019. Developing hands-on laboratory exercises for teaching STEM students the internet-of-things, cloud computing and blockchain applications. In 2019 IEEE Integrated STEM Education Conference (ISEC). 191--198. http://dx.doi.org/10.1109/ISECon.2019.8882068.Google ScholarCross Ref
- N. Slamnik-Krijestorac, S. Bosmans, P. Hellinckx, and J. M. Marquez-Barja. 2019. Enhancing Students' Learning Experience via Low-Cost Network Laboratories. IEEE Communications Magazine 57, 11 (2019), 34--40. doi: http://dx.doi.org/10.1109/MCOM.001.1900233.Google ScholarDigital Library
- N. Slamnik-Krijestorac, H. C. Carvalho de Resende, and J. M. Marquez-Barja. 2020. Practical teaching of distributed systems: A scalable environment for on-demand remote experimentation. In EAI GOODTECHS 2020 - 6th EAI International Conference on Smart Objects and Technologies for Social Good. http://dx.doi.org/10.1145/3411170.3411230.Google Scholar
- Ying Tang, Joleen Liang, Ryan Hare, and Fei-Yue Wang. 2020. A Personalized Learning System for Parallel Intelligent Education. IEEE Transactions on Computational Social Systems 7, 2 (2020), 352--361. doi: http://dx.doi.org/10.1109/TCSS.2020.2965198.Google ScholarCross Ref
- Hongxin Yan. 2020. Using Learning Analytics and Adaptive Formative Assessment to Support At-risk Students in Self-paced Online Learning. In 2020 IEEE 20th International Conference on Advanced Learning Technologies (ICALT). 396--398. doi: http://dx.doi.org/10.1109/ICALT49669.2020.00125.Google ScholarCross Ref
Index Terms
- Adaptive remote experimentation for engineering students
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