Topic: Preliminary Work for a Dynamic Programming Concept Inventory
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, 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 dynamic programming 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 and found 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.
Speaker Bio:
Michael Shindler is an Associate Professor of Teaching at UC Irvine, where he has been since 2019. Michael is interested in educational issues in computer science, particularly issues related to teaching Computer Science Theory courses, such as identifying and correcting student misconceptions in these courses and also discovering concept inventories. He is also interested in more general issues involving the scaling of class sizes and making efficient use of resources for student learning.
Topic: Preliminary Work for a Dynamic Programming Concept Inventory
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, 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 dynamic programming 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 and found 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.
Speaker Bio:
Michael Shindler is an Associate Professor of Teaching at UC Irvine, where he has been since 2019. Michael is interested in educational issues in computer science, particularly issues related to teaching Computer Science Theory courses, such as identifying and correcting student misconceptions in these courses and also discovering concept inventories. He is also interested in more general issues involving the scaling of class sizes and making efficient use of resources for student learning.