%0 Conference Paper %1 citeulike:14340919 %A Dang, Steven %A Yudelson, Michael %A Koedinger, Kenneth R. %B Proceedings of the Fourth (2017) ACM Conference on Learning @ Scale %C New York, NY, USA %D 2017 %I ACM %K intelligent-tutoring las2017 %P 51--59 %R 10.1145/3051457.3051470 %T Detecting Diligence with Online Behaviors on Intelligent Tutoring Systems %U http://dx.doi.org/10.1145/3051457.3051470 %X The current study introduces a model for measuring student diligence using online behaviors during intelligent tutoring system use. This model is validated using a full academic year dataset to test its predictive validity against long-term academic outcomes including end-of-year grades and total work completed by the end of the year. The model is additionally validated for robustness to time-sample length as well as data sampling frequency. While the model is shown to be predictive and robust to time-sample length, the results are inconclusive for robustness in data sampling frequency. Implications for research on interventions, and understanding the influence of self-control, motivation, metacognition, and cognition are discussed. %@ 978-1-4503-4450-0

@inproceedings{citeulike:14340919, abstract = {{The current study introduces a model for measuring student diligence using online behaviors during intelligent tutoring system use. This model is validated using a full academic year dataset to test its predictive validity against long-term academic outcomes including end-of-year grades and total work completed by the end of the year. The model is additionally validated for robustness to time-sample length as well as data sampling frequency. While the model is shown to be predictive and robust to time-sample length, the results are inconclusive for robustness in data sampling frequency. Implications for research on interventions, and understanding the influence of self-control, motivation, metacognition, and cognition are discussed.}}, added-at = {2017-11-15T17:02:25.000+0100}, address = {New York, NY, USA}, author = {Dang, Steven and Yudelson, Michael and Koedinger, Kenneth R.}, biburl = {https://www.bibsonomy.org/bibtex/2e4222aae416f77940d98c8a29bd74f77/brusilovsky}, booktitle = {Proceedings of the Fourth (2017) ACM Conference on Learning @ Scale}, citeulike-article-id = {14340919}, citeulike-linkout-0 = {http://portal.acm.org/citation.cfm?id=3051470}, citeulike-linkout-1 = {http://dx.doi.org/10.1145/3051457.3051470}, doi = {10.1145/3051457.3051470}, interhash = {3da307a4aaaa53df029f398d5db9e2fe}, intrahash = {e4222aae416f77940d98c8a29bd74f77}, isbn = {978-1-4503-4450-0}, keywords = {intelligent-tutoring las2017}, location = {Cambridge, Massachusetts, USA}, pages = {51--59}, posted-at = {2017-04-21 14:44:11}, priority = {2}, publisher = {ACM}, series = {L@S '17}, timestamp = {2023-06-05T04:48:31.000+0200}, title = {{Detecting Diligence with Online Behaviors on Intelligent Tutoring Systems}}, url = {http://dx.doi.org/10.1145/3051457.3051470}, year = 2017 }