Developing Concept Inventory Tests for Electrical Engineering: Extractable Information, Early Results, and Learned Lessons

Fjällström, Eva; Knorn, Steffi; Staffas, Kjell; Varagnolo, Damiano

doi:10.1109/control.2018.8516766

Cited by 3 publications

(2 citation statements)

References 9 publications

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“…A CCM thus allocates one column per course j and one row per concept k, so that the value of each (k, j)th element may be used to quantify how relevant the concept k is for course j on a predefined scale. As for which scale to use, as indicated in Fjällström et al (2018), a simple option consists in '0' = not relevant, '1' = somewhat relevant but not central and '2' = very relevant/central for the course. A more refined option may instead consist in associating a number to each level of an opportune taxonomy (e.g.…”

Section: Data Acquisition Through the Concepts-courses Matrix Toolmentioning

confidence: 99%

Graph-theoretic approaches and tools for quantitatively assessing curricula coherence

Varagnolo

Knorn

Staffas

et al. 2020

European Journal of Engineering Education

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In this paper, we propose a method to analyse the coherence of existing curricula at higher education institution. We focus our attention to engineering programmes at universities but the proposed method is by no means restricted to those cases. In contrast to other known methods, our approach is quantitative, decentralised, and asynchronous and allows to analyse entire programmes (in contrast to single courses) and does not depend on using specific teaching methods or tools. We propose to perform this quantitative assessment in two steps: first, representing the university programme as an opportune graph with courses and concepts as nodes and connections between courses and concepts as edges; second, analysing the structure of the programme using methods from graph theory. We thus perform two investigations, both leveraging a practical casedata collected from three engineering programmes at two Swedish universities: (a) how to represent university programmes in terms of graphs (here called concepts-courses graph (CCG)) and (b) how to reinterpret the most classical graph-theoretical node centrality indexes and connectivity and network flow results in order to analyse the programme structure, including to discover flows and mismatches.

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Section: Data Acquisition Through the Concepts-courses Matrix Toolmentioning

confidence: 99%

Graph-theoretic approaches and tools for quantitatively assessing curricula coherence

Varagnolo

Knorn

Staffas

et al. 2020

European Journal of Engineering Education

Self Cite

View full text Add to dashboard Cite

show abstract

“…These theoretical frameworks are research-based in engineering conceptual learning, socioemotional learning, and EHoM. To assess the engineering knowledge gained in challenges, we will create assessments that are inspired by and adapted from concept inventories in mechanical engineering [2,3], structural and civil engineering [4][5][6], chemical engineering [2,3,7,8], electrical engineering [9,10], structural and civil engineering [4][5][6], materials engineering [11,12], and physics [13] and chemistry [14,15]. To assess perceptions, we will take current findings from recent literature on engineering perceptions in first year students, marginalized students, and girls [16][17][18][19].…”

Section: Theoretical Framework For Toolsmentioning

confidence: 99%