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Development of Research-Based RRSDI Learning Model for Telecommunication Engineering Education

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The Impact of the 4th Industrial Revolution on Engineering Education (ICL 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1134))

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Abstract

The paper presents the development of an instructional package using a research-based model for learning in telecommunication engineering. The model includes 5 steps (requirement, reviewing, solution, discussion and improvement) has been tested on a student group and has been assessed by several course instructors. The developed RRSDI learning model can encourage learners to have more participation in learning activities and highly learning achievement. The active RRSDI learning model can promote students to research and develop novel knowledge and to solve the problems by themselves using research results and methodology. The research results of the developed RRSDI learning model was assessed by five experts and then was implemented on 15 undergraduate students of microwave engineering course. The quality of the developed RRSDI learning model was appropriate (mean = 4.10, S.D. = 0.22) and was efficient with regards to Meguigans’ theory. The student’s satisfaction for the developed RRSDI learning model was at a high level. Moreover, the research results can be applied in order to create an effective innovation for learning and teaching of higher education.

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Acknowledgment

This research has been granted financial support by Graduate College and King Mongkut’s University of Technology North Bangkok. Also, we would like to acknowledge Dr. Thanawit Bunsit for proofreading and for some comments on this paper.

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Correspondence to Nattapong Intarawiset .

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Intarawiset, N., Noulnoppadol, S., Jeenawong, R., Akatimagool, S. (2020). Development of Research-Based RRSDI Learning Model for Telecommunication Engineering Education. In: Auer, M., Hortsch, H., Sethakul, P. (eds) The Impact of the 4th Industrial Revolution on Engineering Education. ICL 2019. Advances in Intelligent Systems and Computing, vol 1134. Springer, Cham. https://doi.org/10.1007/978-3-030-40274-7_64

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