Creating the digital logic concept inventory

Herman, Geoffrey L.; Loui, Michael C.; Zilles, Craig

doi:10.1145/1734263.1734298

Cited by 64 publications

(31 citation statements)

References 8 publications

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“…This is one example of what has necessitated the general classification for these instruments as CLAIs and not simply concept inventories. BEDCI [10] BCI [11] BRI [12] CCMI [13] CINS [14] CUE [15] DLCI [16] ECCI [17] ESICI [18] FTCI [19] GeDI [20] HPI-CI [21] LPCI [22] MCI [23] Meiosis [24] MWCS [25] NGCI [26] QMCA [28] QMCI [29] QMCS [30] R-FCI [31] RCI [32] ROXCI [33] SSCI [34] TUV [35] VKT [36]…”

Section: Differences In Instrument Designmentioning

confidence: 99%

Preliminary results for the development and deployment of Conceptual Learning Assessment Instruments Methodology Survey (CLAIMS)

Henning¹,

Douglas²,

Lindell³

2015

2015 Physics Education Research Conference Proceedings

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Abstract. Following the creation of the Force Concept Inventory (FCI), many STEM discipline-based education researchers developed their own version of concept inventories. To incorporate all types of concept inventories created, we introduce the terminology of Conceptual Learning Assessment Instruments (CLAIs). Previous research shows much variation between what is considered a CLAI and the type of evidence used to support the inferences made from the results of CLAIs. As part of our study, we began by creating the Conceptual Learning Assessment Inventory Methodology Survey (CLAIMS). The CLAIMS was sent to developers of over 100 CLAIs identified via a systematic/ structured literature review. This paper discusses the research behind the CLAIMS as well as the preliminary results for the different CLAIs specifically differences in the field-testing of the CLAIs.

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Section: Differences In Instrument Designmentioning

confidence: 99%

Preliminary results for the development and deployment of Conceptual Learning Assessment Instruments Methodology Survey (CLAIMS)

Henning¹,

Douglas²,

Lindell³

2015

2015 Physics Education Research Conference Proceedings

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show abstract

“…In the field of computer science, concept inventories have been created for digital logic [16,17] using the Delphi process, algorithms and data structures [11], and introductory courses [13,14,19]. Although these CIs are a good start, the majority of computer science topics remain without concept inventories.…”

Section: Related Workmentioning

confidence: 99%

“…In both formal CIs and other assessment mechanisms, findings often demonstrate that students understand far less than instruc- [31] 42% Digital Logic CI [17] 55% CS1 Language Independent CI [30] 34%…”

Section: Related Workmentioning

confidence: 99%

Leveraging open source principles for flexible concept inventory development

Porter

Taylor

Webb

2014

Proceedings of the 2014 Conference on Innovation &Amp; Technology in Computer Science Education - ITiCSE '14

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Concept Inventory (CI) assessments, which target high-level learning goals, have proven highly valuable for higher education research. These assessments have helped to evaluate pedagogical practices among individual instructors, both within and across institutions, and have hence elevated the level of discourse on education within the community. The success of CIs in physics has inspired similar developments in computer science, with a few CIs now developed for computer science courses. However, the development of a CI typically follows a burdensome process, requiring a significant investment to produce a single CI that may be difficult to deploy due to institutional curricular differences. Furthermore, as our field continues to be shaped by technological advances, a path to faster, more modular CI development is critical. This paper proposes an alternative CI development model and continues the discussion within the community about the need for, and path to, concept inventories throughout the computer science curriculum. Specifically, we explore the implications of an open collaboration system for CI development that would mimic the principles common to open source software communities, which have regularly demonstrated their ability to produce high-quality results.

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“…In the field of computer science, concept inventories have been created for digital logic [12,13], algorithms and data structures [8], introductory courses [10,17], and discrete math [2]. However, most pedagogical literature on the subject of operating systems has focused on designing student projects [3,6,14].…”

Section: Introductionmentioning

confidence: 99%

Developing a pre- and post-course concept inventory to gauge operating systems learning

Webb

Taylor

2014

Proceedings of the 45th ACM Technical Symposium on Computer Science Education

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Operating systems courses often present students with multiple approaches to solve a problem, often with differing trade-offs. While students are more than capable of memorizing the details of these competing approaches, they often struggle to recommend a specific approach and analyze its implications. In particular, we find that students exhibit difficultly in interpreting text-based scenario descriptions in a way that allows them to correctly choose between potential solutions when presented with a high-level, conceptual scenario.In this paper, we describe the development of a pre-and postcourse concept inventory, which we utilize to explore students' misconceptions of operating systems and their associated trade-offs. We compare the results of our assessment with in-class peer instruction questions and exam questions to characterize the areas in which students most commonly struggle with operating systems material.

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Creating the digital logic concept inventory

Cited by 64 publications

References 8 publications

Preliminary results for the development and deployment of Conceptual Learning Assessment Instruments Methodology Survey (CLAIMS)

Preliminary results for the development and deployment of Conceptual Learning Assessment Instruments Methodology Survey (CLAIMS)

Leveraging open source principles for flexible concept inventory development

Developing a pre- and post-course concept inventory to gauge operating systems learning

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