{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,30]],"date-time":"2025-07-30T14:21:41Z","timestamp":1753885301830,"version":"3.41.2"},"reference-count":0,"publisher":"Association for Computing Machinery (ACM)","issue":"1","license":[{"start":{"date-parts":[[2015,1,13]],"date-time":"2015-01-13T00:00:00Z","timestamp":1421107200000},"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":["eLearn"],"published-print":{"date-parts":[[2015,1,13]]},"abstract":"<jats:p>The growth of online learning mandates that institutions evaluate instructional effectiveness to ensure students receive a high-quality educational experience. While a number of rubrics exist to benchmark best practices in online teaching, advances in learning management technology are expanding opportunities for utilizing data analytics to effectively and efficiently monitor instructional quality. At present, learning management systems can track logins, activity patterns and time-on-task, but this represents only a fraction the possibilities. Predictive modeling may soon allow for more integrated analytics that can quickly and easily inform evaluations of online teaching.<\/jats:p>","DOI":"10.1145\/2721891.2696534","type":"journal-article","created":{"date-parts":[[2015,1,16]],"date-time":"2015-01-16T14:29:58Z","timestamp":1421418598000},"update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["Data Analytics and Predictive Modeling"],"prefix":"10.1145","volume":"2015","author":[{"given":"B. Jean","family":"Mandernach","sequence":"first","affiliation":[{"name":"Grand Canyon University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kelly","family":"Palese-Sanderson","sequence":"additional","affiliation":[{"name":"Grand Canyon University"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2015,1,14]]},"container-title":["eLearn"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/2721891.2696534","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/ft_gateway.cfm?id=2696534&ftid=1529588&dwn=1","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T06:13:27Z","timestamp":1750227207000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/2721891.2696534"}},"subtitle":["The future of evaluating online teaching"],"short-title":[],"issued":{"date-parts":[[2015,1,13]]},"references-count":0,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2015,1,13]]}},"alternative-id":["10.1145\/2721891.2696534"],"URL":"https:\/\/doi.org\/10.1145\/2721891.2696534","relation":{},"ISSN":["1535-394X"],"issn-type":[{"type":"electronic","value":"1535-394X"}],"subject":[],"published":{"date-parts":[[2015,1,13]]},"assertion":[{"value":"2015-01-14","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"2721891.2696534"}}