Steven Dang
Michael Yudelson
Kenneth R. Koedinger
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.
- Vincent Aleven, Ido Roll, Bruce M McLaren, and Kenneth R Koedinger. 2010. Automated, Unobtrusive, Action-by-Action Assessment of SelfRegulation During Learning With an Intelligent Tutoring System. Educational Psychologist 45, 4: 224--233.Google Scholar
Cross Ref
- Carole Ames and Jennifer Archer. 1988. Achievement goals in the classroom: Students' learning strategies and motivation processes. Journal of Educational Psychology 80, 3: 260--267.Google ScholarCross Ref
- Ryan Shaun Baker, Albert T Corbett, and Kenneth R Koedinger. 2004. Detecting Student Misuse of Intelligent Tutoring Systems. In Intelligent Tutoring Systems. Springer Berlin Heidelberg, Berlin, Heidelberg, 531--540.Google Scholar
- Albert Bandura. 1994. Self-efficacy In VS Ramachaudran (Ed.) Encyclopedia of Human Behavior, 4, 71--81.Google Scholar
- Roy F Baumeister, Brandon Schmeichel, and Kathleen Vohs. 2003. Selfregulation and the executive function of the self. In Social Psychology Handbook of basic Principles (2nd ed.). New York, 197--217.Google Scholar
- Matthew L Bernacki and Steven Ritter. 2013. Hopewell 2011-2012. Dataset 613 in DataShop. Retrieved from https://pslcdatashop.web.cmu.edu/DatasetInfo?data setId=613.Google Scholar
- Matthew L Bernacki, Timothy J Nokes-Malach, and Vincent Aleven. 2013. Fine-Grained Assessment of Motivation over Long Periods of Learning with an Intelligent Tutoring System: Methodology, Advantages, and Preliminary Results. In International Handbook of Metacognition and Learning Technologies. Springer New York, New York, NY, 629--644.Google Scholar
- Jeni L Burnette, Ernest H O'Boyle, Eric M VanEpps, Jeffrey M Pollack, and Eli J Finkel. 2013. Mind-sets matter: A meta-analytic review of implicit theories and self-regulation. Psychological Bulletin 139, 3: 655--701.Google ScholarCross Ref
- Angela L Duckworth and Laurence Steinberg. 2015. Unpacking Self-Control. Child Development Perspectives 9, 1: 32--37.Google ScholarCross Ref
- Angela L Duckworth and David Scott Yeager. 2015. Measurement matters assessing personal qualities other than cognitive ability for educational purposes. Educational Researcher 44, 4: 237--251.Google ScholarCross Ref
- Angela L Duckworth, Tamar Szabó Gendler, and James J Gross. 2016. Situational Strategies for SelfControl. Perspectives on Psychological Science 11, 1: 35--55.Google ScholarCross Ref
- Carol Dweck. 2000. Self-theories: Their role in motivation, personality, and development. Psychology Press.Google Scholar
- Andrew J Elliot and Kou Murayama. 2008. On the measurement of achievement goals: Critique, illustration, and application. Journal of Educational Psychology 100, 3: 613--628.Google ScholarCross Ref
- K Anders Ericsson, Ralf T Krampe, and Clemens Tesch-Römer. 1993. The role of deliberate practice in the acquisition of expert performance. Psychological Review 100, 3: 363--406.Google ScholarCross Ref
- Stephen Fancsali, Matthew L Bernacki, Timothy J Nokes-Malach, Michael Yudelson, and Steven Ritter. 2014. Goal Orientation, Self-Efficacy, and "Online Measures" in Intelligent Tutoring Systems. CogSci.Google Scholar
- Brian M Galla, Benjamin D Plummer, Rachel E White, David Meketon, Sidney K D'Mello, and Angela L Duckworth. 2014. The Academic Diligence Task (ADT): assessing individual differences in effort on tedious but important schoolwork. 39, 4: 314--325.Google Scholar
- Veronika Job, Carol S Dweck, and Gregory M Walton. 2010. Ego Depletion? Is It All in Your Head? Psychological Science 21, 11: 1686--1693.Google ScholarCross Ref
- Hanan Khalil and Martin Ebner. 2014. MOOCs completion rates and possible methods to improve retention-a literature review. World Conference on Educational Multimedia.Google Scholar
- John S Kinnebrew, Kirk M Loretz, and Gautam Biswas. 2013. A Contextualized, Differential Sequence Mining Method to Derive Students' Learning Behavior Patterns. JEDM - Journal of Educational Data Mining 5, 1: 190--219.Google Scholar
- Kenneth R Koedinger, Albert T Corbett, and Charles Perfetti. 2012. The Knowledge-LearningInstruction Framework: Bridging the SciencePractice Chasm to Enhance Robust Student Learning. Cognitive Science 36, 5: 757--798.Google ScholarCross Ref
- Kenneth R Koedinger, Jihee Kim, Julianna Zhuxin Jia, Elizabeth A McLaughlin, and Norman L Bier. 2015. Learning is Not a Spectator Sport: Doing is Better than Watching for Learning from a MOOC. ACM, New York, New York, USA. Google ScholarDigital Library
- Carolyn MacCann, Angela Lee Duckworth, and Richard D Roberts. 2009. Empirical identification of the major facets of Conscientiousness. Learning and Individual Differences 19, 4: 451--458.Google ScholarCross Ref
- Gladwell Malcolm. 2008. Outliers: The story of success. New York: Little.Google Scholar
- Walter Mischel, Yuichi Shoda, and Monica L. Rodriguez. 1989. Delay of gratification in children. Science 244, 4907: 933--938.Google Scholar
- National Research Council. 2011. Assessing 21st Century Skills. National Academies Press, Washington, D.C. 26. Paul R Pintrich. 1991. A Manual for the Use of the Motivated Strategies for Learning Questionnaire (MSLQ).Google Scholar
- Paul R Pintrich. 2000. An Achievement Goal Theory Perspective on Issues in Motivation Terminology, Theory, and Research. 25, 1: 92--104.Google Scholar
- Steven Ritter, John R Anderson, Kenneth R Koedinger, and Albert Corbett. 2007. Cognitive Tutor: Applied research in mathematics education. Psychonomic Bulletin & Review 14, 2: 249--255.Google ScholarCross Ref
- Nicole Shechtman, Angela H DeBarger, Carolyn Dornsife, and Soren Rosier. 2013. Promoting grit, tenacity, and perseverance: Critical factors for success in the 21st century. Washington.Google Scholar
- June P Tangney, Roy F Baumeister, and Angie Luzio Boone. 2004. High Self-Control Predicts Good Adjustment, Less Pathology, Better Grades, and Interpersonal Success. Journal of personality 72, 2: 271--324.Google ScholarCross Ref
- Eli Tsukayama, Angela Lee Duckworth, and Betty Kim. 2013. Domain-specific impulsivity in schoolage children. Developmental Science 16, 6: 879--893.Google Scholar
- Phillip H Winne, John C Nesbit, Vive Kumar, et al. 2006. Supporting self-regulated learning with gStudy software: The Learning Kit Project. Technology.Google Scholar
- Barry J Zimmerman. 2008. Investigating SelfRegulation and Motivation: Historical Background, Methodological Developments, and Future Prospects. American Educational Research Journal 45, 1: 166--183.Google ScholarCross Ref
Index Terms
- Detecting Diligence with Online Behaviors on Intelligent Tutoring Systems
Recommendations
Educational Game and Intelligent Tutoring System: A Classroom Study and Comparative Design Analysis
Educational games and intelligent tutoring systems (ITS) both support learning by doing, although often in different ways. The current classroom experiment compared a popular commercial game for equation solving, DragonBox and a research-based ITS, ...
Are There Benefits of Using Multiple Pedagogical Agents to Support and Foster Self-Regulated Learning in an Intelligent Tutoring System?
ITS 2016: Proceedings of the 13th International Conference on Intelligent Tutoring Systems - Volume 9684This study examined the proportional learning gains attained by 165 college students as they learned about the human circulatory system over two sessions with the intelligent tutoring system, MetaTutor. Results indicated that learners in the prompt and ...
Motivation matters
Pedagogical agent scaffolding increased learners' use of self-regulatory strategies.Pedagogical agent scaffolding alone did not increase learners' performance.Achievement goal motivation moderated the effect of agents on performance.Performance was ...
Comments