{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,6]],"date-time":"2026-03-06T12:56:39Z","timestamp":1772801799921,"version":"3.50.1"},"reference-count":37,"publisher":"Association for Computing Machinery (ACM)","issue":"3","license":[{"start":{"date-parts":[[2013,8,1]],"date-time":"2013-08-01T00:00:00Z","timestamp":1375315200000},"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":["ACM Trans. Comput. Educ."],"published-print":{"date-parts":[[2013,8]]},"abstract":"<jats:p>POGIL has been successfully implemented in a scientific computing course to teach science students how to program in Python. Following POGIL guidelines, the authors have developed guided inquiry activities that lead student teams to discover and understand programming concepts. With each iteration of the scientific computing course, the authors have refined the activities and learned how to better adapt POGIL for the computer science classroom. This article details how POGIL activities differ from both traditional computer science labs and other active-learning pedagogies. Background is provided on POGIL's effectiveness. The article then includes a full description of how POGIL activities were used in the scientific computing course, as well as an example POGIL activity on recursion. Discussion is provided on how to facilitate and develop POGIL activities. Quotes from student evaluations and an assessment on how well students learned to program are provided.<\/jats:p>","DOI":"10.1145\/2499947.2499950","type":"journal-article","created":{"date-parts":[[2013,8,20]],"date-time":"2013-08-20T14:07:13Z","timestamp":1377007633000},"page":"1-23","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":56,"title":["Using POGIL to help students learn to program"],"prefix":"10.1145","volume":"13","author":[{"given":"Helen H.","family":"Hu","sequence":"first","affiliation":[{"name":"Westminster College, Salt Lake City, UT"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tricia D.","family":"Shepherd","sequence":"additional","affiliation":[{"name":"Westminster College, Salt Lake City, UT"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2013,8,16]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/290320.283000"},{"key":"e_1_2_1_2_1","volume-title":"Chemists' Guide to Effective Teaching.","author":"Abraham M.","unstructured":"Abraham , M. 2005. Inquiry and the learning cycle approach . In Chemists' Guide to Effective Teaching. Vol. 1 . Prentice Hall , Upper Saddle River, NJ, 41--52. Abraham, M. 2005. Inquiry and the learning cycle approach. In Chemists' Guide to Effective Teaching. Vol. 1. Prentice Hall, Upper Saddle River, NJ, 41--52."},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/1734263.1734319"},{"key":"e_1_2_1_4_1"},{"key":"e_1_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/1734263.1734417"},{"key":"e_1_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/1536513.1536557"},{"key":"e_1_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/1953163.1953312"},{"key":"e_1_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/2157136.2157244"},{"key":"e_1_2_1_9_1","doi-asserted-by":"crossref","unstructured":"Chiel H. Gill J. Mcmanus J. and Shaw K. 2012. Learning biology by recreating and extending mathematical models. Science. 336 6084 993--994.  Chiel H. Gill J. Mcmanus J. and Shaw K. 2012. 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