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Supporting Durable and Efficient Student Learning. Katherine Rawson Kent State University. Research supported by the Institute of Education Sciences, U.S. Department of Education, through Grants #R305H050038 and #R305A080316 to Kent State University.
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Supporting Durable and Efficient Student Learning Katherine Rawson Kent State University Research supported by the Institute of Education Sciences, U.S. Department of Education, through Grants#R305H050038 and #R305A080316 toKent State University. The opinions expressed are those of the author and do not represent views of the Institute or the U.S. Department of Education.
Retrieval-Monitoring-Feedback (RMF) Method Why key term definitions? Why is durability important? Why is efficiency important? Why retrieval practice?
What We Know… Retrieval practice + restudy is good More is better Spaced practice is best What We Don’t Know… Optimal schedule for durability and efficiency ?
Experiment 1 130 students in Introductory Psychology Short text with 8 key term definitions What is the availability heuristic? Judging the likelihood of an event based on how easy it is to think of real or imagined examples. Day 1: Initial study Retrieval practice (with restudy) until 1,2,3,or 4correct recalls Day 3: Final recall test
Experiment 2 335 students, 16 key term definitions Initial learning: 1 or 3 correct recalls Relearning sessions: 1, 2, 3, 4,or5 Criterion Test #1: one monthafter practice Criterion Test #2: four monthsafter practice
2.6 > 2.1 1.9 ~ 1.7 1.5 ~ 1.5 2.3 > 2.0 1.7 ~ 1.6
Experiment 3 180 students, 8 key term definitions Day 1: Retrieval practice until ~2 correct recalls LAG:zero, one, three, or seven other items between trials Day 3: relearning session Day 8: relearning session Day 10: final cued recall test
Conclusions: Optimizing Durability and Efficiency What We Knew… More is better Spaced practice is best What We Now Know… More is increasingly less better Spaced practice not always best?
Thanks to our tireless team of research assistants who collected data from 645 participants and who hand-scored more than 80,000 recall responses for just these three experiments alone! Mike Appleman John Kozlik Melissa Bishop Korin Lee Tina Burke Caitlin Metelko Sean Burton Rochelle O’Neil Dan Molnar Jill Peterson Nicole Gonzalez Danielle Roberto Phil Grimaldi Melissa Roderick Tonya Hardway Sara Smith Alison Kane Katie Wissman
Percent of commission errors judged to be worth no credit, partial credit, or full credit None Part Full no definition 17 58 25 definition 48 38 14 idea units 78 20 2