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Using Commutative Assessments to Compare Conceptual Understanding in Blocks-based and Text-based Programs
Abstract
Blocks-based programming environments are becoming increasingly common in introductory programming courses, but to date, little comparative work has been done to understand if and how this approach affects students' emerging understanding of fundamental programming concepts. In an effort to understand how tools like Scratch and Blockly differ from more conventional text-based introductory programming languages with respect to conceptual understanding, we developed a set of "commutative" assessments. Each multiple-choice question on the assessment includes a short program that can be displayed in either a blocks- based or text-based form. The set of potential answers for each question includes the correct answer along with choices informed by prior research on novice programming misconceptions. In this paper we introduce the Commutative Assessment, discuss the theoretical and practical motivations for the assessment, and present findings from a study that used the assessment. The study had 90 high school students take the assessment at three points over the course of the first ten weeks of an introduction to programming course, alternating the modality (blocks vs. text) for each question over the course of the three administrations of the assessment. Our analysis reveals differences on performance between blocks-based and text-based questions as well as differences in the frequency of misconceptions based on the modality. Future work, potential implications, and limitations of…
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“The pre-test, and isomorphic post-test1 and post-test2, were adapted from the block-based version of the Commutative Assessments [25], with 16 multiple-choice questions on variables, loops, procedures, and conditionals.”
From Exploring the Impact of Worked Examples in a Novice Programming Environment (2019) · cites this paper as [25]
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Metadata
- Authors
- Weintrop, D., & Wilensky, U.
- Affiliations
- Northwestern University (US)
- Venue
- Proceedings of the eleventh annual International Conference on International Computing Education Research
- Publisher
- ACM
- Published
- 2015-08-09
- Pages
- 101-110
- OpenAlex
- W2016385238
- Cited by
- 198
- References
- 73
- Citations by year
- 2026: 6 · 2025: 4 · 2024: 6 · 2023: 13 · 2022: 19 · 2021: 20 · 2020: 24 · 2019: 59 · 2018: 12 · 2017: 20 · 2016: 10 · 2015: 5
- FWCI
- 11.21
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- ACM Conference on International Computing Education Research (ICER) (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Science Applications › Teaching and Learning Programming
- Social Sciences › Education › Science Education and Pedagogy
- Social Sciences › Education › Educational Robotics and Engineering
- Keywords
- text-based programming, introductory programming, conceptual understanding, Scratch, Blockly, high school students
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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