A Mastery Approach to Flashcard-Based Adaptive Training

Students often use flashcards to study but they do not always use them effectively. In this experiment, we explored different methods of dropping flashcards to inform the development of an adaptive flashcard-based trainer. Forty-seven U.S. Marine Corps students were randomly assigned to one of three groups in an armored vehicle training task. In the Mastery Drop condition, cards were dropped from training based on objective criteria (i.e., accuracy and reaction time). In the Learner Drop condition, cards were dropped based on the learner’s choice. In the No Drop condition, cards were not dropped during training, which served as a control group. Using a pre-test post-test design, results showed that the Learner Drop condition had the lowest learning gains on the immediate post-test and the delayed post-test (two days after training), perhaps because participants were unsuccessful at self-regulating their learning and completed training too quickly. Although the No Drop condition had the highest learning gains on the immediate post-test, the gains significantly decreased on the delayed post-test. In contrast, the Mastery Drop condition maintained consistent learning gains from immediate to delayed post-test. Although the No Drop condition completed more training trials than the Mastery Drop condition, this additional practice did not significantly aid long-term retention. Finally, the No Drop condition had the highest immediate transfer test scores, which involved identifying images of real-world vehicles, but there were no group differences on the delayed transfer test. These results suggest that adaptive flashcard training should incorporate mastery criteria, rather than learner-driven decisions about when to drop flashcards from the deck.

[1]  Jeffrey D. Karpicke,et al.  The Critical Importance of Retrieval for Learning , 2008, Science.

[2]  J. Sweller Implications of Cognitive Load Theory for Multimedia Learning , 2005, The Cambridge Handbook of Multimedia Learning.

[3]  R. Bjork,et al.  Self-regulated learning: beliefs, techniques, and illusions. , 2013, Annual review of psychology.

[4]  R. Oxford,et al.  Vocabulary Learning: A Critical Analysis of Techniques , 1990 .

[5]  Rebecca L. Oxford,et al.  Second language vocabulary learning among adults: State of the art in vocabulary instruction , 1994 .

[6]  M. Guadagnoli,et al.  Challenge Point: A Framework for Conceptualizing the Effects of Various Practice Conditions in Motor Learning , 2004, Journal of motor behavior.

[7]  Nate Kornell,et al.  Optimising self-regulated study: The benefits—and costs—of dropping flashcards , 2008, Memory.

[8]  Paula J. Durlach,et al.  Fundamentals, Flavors, and Foibles of Adaptive Instructional Systems , 2019, HCI.

[9]  Richard Mayer,et al.  Multimedia Learning , 2001, Visible Learning Guide to Student Achievement.

[10]  Katherine A. Rawson,et al.  Metacognitive monitoring during criterion learning: When and why are judgments accurate? , 2014, Memory & cognition.

[11]  P. Kellman,et al.  A comparison of adaptive and fixed schedules of practice. , 2016, Journal of experimental psychology. General.

[12]  Paula J Durlach,et al.  Designing Adaptive Instructional Environments: Insights from Empirical Evidence , 2011 .

[13]  Jeffrey D. Karpicke,et al.  Test-Enhanced Learning , 2006, Psychological science.

[14]  Katherine A Rawson,et al.  How and when do students use flashcards? , 2012, Memory.

[15]  B. Thon,et al.  Self-Control of Task Difficulty During Training Enhances Motor Learning of a Complex Coincidence-Anticipation Task , 2012, Research quarterly for exercise and sport.

[16]  T. O. Nelson Metamemory: A Theoretical Framework and New Findings , 1990 .

[17]  Jeffrey D. Karpicke,et al.  Metacognitive control and strategy selection: deciding to practice retrieval during learning. , 2009, Journal of experimental psychology. General.

[18]  R. Atkinson Optimizing the Learning of a Second-Language Vocabulary. , 1972 .

[19]  Philip J. Kellman,et al.  Improving Adaptive Learning Technology through the Use of Response Times , 2011, CogSci.

[20]  Jeffrey D. Karpicke,et al.  Metacognitive strategies in student learning: Do students practise retrieval when they study on their own? , 2009, Memory.

[21]  J. Sweller,et al.  Cognitive Load Theory and Complex Learning: Recent Developments and Future Directions , 2005 .

[22]  Natalie B. Steinhauser,et al.  Evaluation of an Adaptive Training System for Submarine Periscope Operations , 2012 .

[23]  Daniel Gopher,et al.  Adaptive training of perceptual-motor skills: issues, results, and future directions , 1978 .

[24]  Vincent Wade,et al.  Personalised Learning for Casual Games: The 'Language Trap' Online Language Learning Game , 2010 .

[25]  Burr Settles,et al.  A Trainable Spaced Repetition Model for Language Learning , 2016, ACL.

[26]  K. Scheiter,et al.  Learner Control in Hypermedia Environments , 2007 .

[27]  Kurt VanLehn,et al.  The Andes Physics Tutoring System: Lessons Learned , 2005, Int. J. Artif. Intell. Educ..