{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,21]],"date-time":"2026-02-21T12:33:32Z","timestamp":1771677212976,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":18,"publisher":"ACM","license":[{"start":{"date-parts":[[2018,3,8]],"date-time":"2018-03-08T00:00:00Z","timestamp":1520467200000},"content-version":"vor","delay-in-days":365,"URL":"http:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["DUE-1139861 and IIS-1258471"],"award-info":[{"award-number":["DUE-1139861 and IIS-1258471"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2017,3,8]]},"DOI":"10.1145\/3017680.3017698","type":"proceedings-article","created":{"date-parts":[[2017,3,7]],"date-time":"2017-03-07T13:35:25Z","timestamp":1488893725000},"page":"201-206","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":19,"title":["Evaluating the Effectiveness of Algorithm Analysis Visualizations"],"prefix":"10.1145","author":[{"given":"Mohammed F.","family":"Farghally","sequence":"first","affiliation":[{"name":"Virginia Tech, Blacksburg, VA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kyu Han","family":"Koh","sequence":"additional","affiliation":[{"name":"California State University Stanislaus, Turlock, CA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hossameldin","family":"Shahin","sequence":"additional","affiliation":[{"name":"Virginia Tech, Blacksburg, VA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Clifford A.","family":"Shaffer","sequence":"additional","affiliation":[{"name":"Virginia Tech, Blacksburg, VA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2017,3,8]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/1595496.1562979"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0360-1315(99)00023-8"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1177\/016146816306400801"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.chb.2014.09.061"},{"key":"e_1_3_2_1_5_1","first-page":"370","volume-title":"Proceedings of the 9th international conference on educational data mining","author":"Fouh E.","year":"2016","unstructured":"E. Fouh, M. F. Farghally, S. Hamouda, K. H. Koh, and C. A. Shaffer. Investigating difficult topics in a data structures course using item response theory and logged data analysis. In Proceedings of the 9th international conference on educational data mining, pages 370--375, July 2016."},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.scico.2013.11.040"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/274790.274298"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/2556325.2566239"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1093\/teamat\/hri005"},{"key":"e_1_3_2_1_10_1","volume-title":"Statistical methods for meta-analysis: Academic press","author":"Hedges L.","year":"1985","unstructured":"L. Hedges and I. Olkin. Statistical methods for meta-analysis: Academic press. Orlando, FL, 1985."},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1006\/jvlc.2002.0237"},{"key":"e_1_3_2_1_12_1","volume-title":"April-June","author":"Karavirta V.","year":"2016","unstructured":"V. Karavirta and C. Shaffer. Creating engaging online learning material with the JSAV Javascript Algorithm Visualization Library. 9:171--183, April-June 2016."},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1214\/aoms\/1177730491"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1037\/0003-066X.63.8.760"},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.5555\/2591468.2591495"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1145\/1821996.1821997"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1145\/1383602.1383639"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1145\/2003616.2003630"}],"event":{"name":"SIGCSE '17: The 48th ACM Technical Symposium on Computer Science Education","location":"Seattle Washington USA","acronym":"SIGCSE '17","sponsor":["SIGCSE ACM Special Interest Group on Computer Science Education"]},"container-title":["Proceedings of the 2017 ACM SIGCSE Technical Symposium on Computer Science Education"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3017680.3017698","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3017680.3017698","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3017680.3017698","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,18]],"date-time":"2025-11-18T09:48:47Z","timestamp":1763459327000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3017680.3017698"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,3,8]]},"references-count":18,"alternative-id":["10.1145\/3017680.3017698","10.1145\/3017680"],"URL":"https:\/\/doi.org\/10.1145\/3017680.3017698","relation":{},"subject":[],"published":{"date-parts":[[2017,3,8]]},"assertion":[{"value":"2017-03-08","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}