Studied Questions in Data Structures and Algorithms Assessments

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Abstract

Designing a proper exam that accurately evaluates students' knowledge and skills is one of the important tasks of every teacher. The format of the exams affects the way students learn throughout the course, and a well-designed exam can enhance meaningful learning. In this paper, we address this topic in the context of Data Structures and Algorithms courses, and argue that a good exam should contain questions that students have seen during the semester, and that the grading of those questions should be strict. We describe a case study which, over three semesters, supports the claim that answering these questions require the "Understand"level of Bloom's taxonomy, and that this strategy fosters more meaningful learning and better assesses students' knowledge.

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Gaber, I., Kirsh, A., & Statter, D. (2023). Studied Questions in Data Structures and Algorithms Assessments. In Annual Conference on Innovation and Technology in Computer Science Education, ITiCSE (Vol. 1, pp. 250–256). Association for Computing Machinery. https://doi.org/10.1145/3587102.3588843

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