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| Main Authors: | , , , , , , , , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2411.14655 |
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| _version_ | 1866915030871572480 |
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| author | Ferland, Matthew Rao, Varun Nagaraj Arora, Arushi van der Poel, Drew Luu, Michael Huynh, Randy Reiber, Freddy Ossman, Sandra Poulsen, Seth Shindler, Michael |
| author_facet | Ferland, Matthew Rao, Varun Nagaraj Arora, Arushi van der Poel, Drew Luu, Michael Huynh, Randy Reiber, Freddy Ossman, Sandra Poulsen, Seth Shindler, Michael |
| contents | Concept inventories are standardized assessments that evaluate student understanding of key concepts within academic disciplines. While prevalent across STEM fields, their development lags for advanced computer science topics like dynamic programming (DP) -- an algorithmic technique that poses significant conceptual challenges for undergraduates. To fill this gap, we developed and validated a Dynamic Programming Concept Inventory (DPCI). We detail the iterative process used to formulate multiple-choice questions targeting known student misconceptions about DP concepts identified through prior research studies. We discuss key decisions, tradeoffs, and challenges faced in crafting probing questions to subtly reveal these conceptual misunderstandings. We conducted a preliminary psychometric validation by administering the DPCI to 172 undergraduate CS students finding our questions to be of appropriate difficulty and effectively discriminating between differing levels of student understanding. Taken together, our validated DPCI will enable instructors to accurately assess student mastery of DP. Moreover, our approach for devising a concept inventory for an advanced theoretical computer science concept can guide future efforts to create assessments for other under-evaluated areas currently lacking coverage. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2411_14655 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Construction and Preliminary Validation of a Dynamic Programming Concept Inventory Ferland, Matthew Rao, Varun Nagaraj Arora, Arushi van der Poel, Drew Luu, Michael Huynh, Randy Reiber, Freddy Ossman, Sandra Poulsen, Seth Shindler, Michael Data Structures and Algorithms Computers and Society Concept inventories are standardized assessments that evaluate student understanding of key concepts within academic disciplines. While prevalent across STEM fields, their development lags for advanced computer science topics like dynamic programming (DP) -- an algorithmic technique that poses significant conceptual challenges for undergraduates. To fill this gap, we developed and validated a Dynamic Programming Concept Inventory (DPCI). We detail the iterative process used to formulate multiple-choice questions targeting known student misconceptions about DP concepts identified through prior research studies. We discuss key decisions, tradeoffs, and challenges faced in crafting probing questions to subtly reveal these conceptual misunderstandings. We conducted a preliminary psychometric validation by administering the DPCI to 172 undergraduate CS students finding our questions to be of appropriate difficulty and effectively discriminating between differing levels of student understanding. Taken together, our validated DPCI will enable instructors to accurately assess student mastery of DP. Moreover, our approach for devising a concept inventory for an advanced theoretical computer science concept can guide future efforts to create assessments for other under-evaluated areas currently lacking coverage. |
| title | Construction and Preliminary Validation of a Dynamic Programming Concept Inventory |
| topic | Data Structures and Algorithms Computers and Society |
| url | https://arxiv.org/abs/2411.14655 |