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Cognition, Metacognition, and Culture in STEM Education pp 191–216Cite as

Metacognition and Meta-assessment in Engineering Education

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Part of the Innovations in Science Education and Technology book series (ISET,volume 24)

Abstract

In this chapter, we first discuss metacognition in engineering education. We then focus on meta-assessment in general and on student-oriented meta-assessment in engineering education in particular. We describe studies focusing on metacognition and the three meta-assessment types in engineering education. We describe in detail two studies, in which we have investigated the meta-assessment of engineering students at higher education institutes in two project-based courses with different characteristics. The first study involved a large undergraduate information systems engineering course at the Technion, Israel Institute of Technology, while the second study involved a small graduate model-based systems engineering course at Massachusetts Institute of Technology. We discuss the advantages of incorporating metacognition in general and meta-assessment in particular into engineering education and using it for enhancing students’ metacognitive skills. In this study, formative assessment was made paossible by providing feedback to the teams as they were engaged in the project-based learning. Our meta-assessment approach enables individual summative assessment of each student’s learning outcomes, whereas each team project served as a basis for the collective team's summative assessment.

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Fig. 9.1
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Fig. 9.3
Fig. 9.4

Notes

  1. 1.

    The terms personal, task, and strategy knowledge of cognition were coined by Flavell and Wellman (1977). Cross and Paris (1988) changed those terms to declarative, procedural, and conditional.

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Affiliations

  1. Faculty of Industrial Engineering and Management, Technion, Haifa, Israel

    Niva Wengrowicz & Dov Dori

  2. Faculty of Education in Science and Engineering, Technion, Haifa, Israel

    Niva Wengrowicz

  3. Faculty of Education in Science and Technology, Technion, Haifa, Israel

    Yehudit Judy Dori

  4. The Samuel Neaman Institute for National Policy Research, Haifa, Israel

    Yehudit Judy Dori & Dov Dori

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  1. Niva Wengrowicz
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Correspondence to Niva Wengrowicz .

Appendix: Students’ Reflections on the Course as a Whole

Appendix: Students’ Reflections on the Course as a Whole

Students’ reflections on the course as a whole in the large-scale undergraduate course revolved around the high demands of the course and the effort they had to spend on the one hand and the lack of familiarity with this kind of tasks on the other hand:

  • “The course requires a lot of work.”

  • “Where is the peace of mind? I invested in this course more than any other course of the semester.”

  • “Takes up a lot of time.”

  • “The course is a time and effort consumer.”

  • “The course is not an easy course; it required a very large investment relative to other courses I’ve taken to date.”

  • “Busy course relative to other courses.”

  • “High level of time and effort investment than any other course.”

  • “This is the first time I had to perform such a task.”

  • “We do not have adequate tools to analyze our peer projects.”

  • “I’m not sure that I have classified my findings to the appropriate categories since I have never done it before.”

Reflection on the course as a whole in the small-scale graduate course revolved around the learning of the two modeling languages in parallel. Students emphasized that this method helped them to better understand the uniqueness of each language:

  • “I thoroughly enjoyed this class. … not only the syntax of both modeling languages, but also how they compare to each other.”

  • “I like presenting both OPM and SysML in the class, not necessarily so I can efficiently use both, but so I could understand their differences, strengths and weaknesses.”

  • “I was able to develop a good understanding of the various types of modeling language over the course.”

  • “Very useful, and helped solidify understanding … when translating between the two modeling languages.”

  • “The hands-on session and converting other standard diagrams with class discussion are awesome experiences.”

  • “The exercises of converting other diagrams are really good ways to understand other diagrams and at the same time improve students’ understanding and skill.”

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Wengrowicz, N., Dori, Y.J., Dori, D. (2018). Metacognition and Meta-assessment in Engineering Education. In: Dori, Y.J., Mevarech, Z.R., Baker, D.R. (eds) Cognition, Metacognition, and Culture in STEM Education. Innovations in Science Education and Technology, vol 24. Springer, Cham. https://doi.org/10.1007/978-3-319-66659-4_9

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