{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,27]],"date-time":"2026-03-27T02:10:23Z","timestamp":1774577423001,"version":"3.50.1"},"reference-count":28,"publisher":"Association for Computing Machinery (ACM)","issue":"1","license":[{"start":{"date-parts":[[2019,12,20]],"date-time":"2019-12-20T00:00:00Z","timestamp":1576800000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["Commun. ACM"],"published-print":{"date-parts":[[2019,12,20]]},"abstract":"<jats:p>Although it has never been rigorously demonstrated, there is a common belief that grades in computer science courses are bimodal. We statistically analyzed 778 distributions of final course grades from a large research university and found that only 5.8% of the distributions passed tests of multimodality. We then devised a psychology experiment to understand why CS educators believe their grades to be bimodal. We showed 53 CS professors a series of histograms displaying ambiguous distributions that we asked them to categorize. A random half of participants were primed to think about the fact that CS grades are commonly thought to be bimodal; these participants were more likely to label ambiguous distributions as \"bimodal.\" Participants were also more likely to label distributions as bimodal if they believed that some students are innately predisposed to do better at CS. These results suggest that bimodal grades are instructional folklore in CS, caused by confirmation bias and instructor beliefs about their students.<\/jats:p>","DOI":"10.1145\/3372161","type":"journal-article","created":{"date-parts":[[2019,12,20]],"date-time":"2019-12-20T19:45:25Z","timestamp":1576871125000},"page":"91-98","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":11,"title":["Evidence that computer science grades are not bimodal"],"prefix":"10.1145","volume":"63","author":[{"given":"Elizabeth","family":"Patitsas","sequence":"first","affiliation":[{"name":"McGill University Montreal, Qu\u00e9bec, Canada"}]},{"given":"Jesse","family":"Berlin","sequence":"additional","affiliation":[{"name":"Toronto, Ontario, Canada"}]},{"given":"Michelle","family":"Craig","sequence":"additional","affiliation":[{"name":"University of Toronto Toronto, Ontario, Canada"}]},{"given":"Steve","family":"Easterbrook","sequence":"additional","affiliation":[{"name":"University of Toronto Toronto, Ontario, Canada"}]}],"member":"320","published-online":{"date-parts":[[2019,12,20]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/2493394.2493416"},{"key":"e_1_2_1_2_1","first-page":"10","article-title":"Exploring bimodality in introductory computer science performance distributions","volume":"14","author":"Basnet R.B.","year":"2018","journal-title":"EURASIA J. 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