Memory Retrieval Strategies to Help Retain STEM Content Knowledge
Osman Yasar, Peter Veronesi, Jose Maliekal, Leigh Little, John Tillotson
2019 ASEE Annual Conference & Exposition Proceedings
is an endowed professor and director of the CMST Institute at The College at Brockport, SUNY. He established the first undergraduate degree program in computational science in the United States, and his research interests include engineering and science education, computational pedagogy, fluid and particle dynamics, engine ignition modeling, and parallel computing. Yasar has a PhD in engineering physics and an MS in computer science from the University of Wisconsin-Madison. Abstract We report
... out memory retrieval experiences to help students retrieve content they learned in class, retain it, and apply it in different contexts to solve novel problems. Supported by multiyear fall/spring professional development opportunities for teachers, these technological and pedagogical experiences range in complexity from simple electronic flashcards for basic retrieval strategies to low-stakes quizzes for spaced-out (initial exposure and retrieval effort are spaced out) and interleaved (two or more spaced-out topics are interleaved) practices. A sequential mixed-methods approach was used to collect quantitative data from a large number of participating teachers (N=180), followed by an enriched case study with a qualitative component to explore the meaning of the quantitative trends/findings in the first part of the study. Participants reported that they gained a greater understanding of the science behind the concept of interleaving, a greater understanding of how it can be implemented and tested in the classroom, and a higher level of confidence in the effectiveness of interleaving on knowledge retention than they had prior to training. While deployment of retrieval strategies in the classroom has been required of all participants, those who attended additional training in the summers (N=68) have also conducted Action Research to measure the effect of new strategies on learning. These teachers randomly selected control and target student groups within the same school, grade and course environment. They also self-selected an area of content within their respective science disciplines or mathematics curriculum and created two different retrieval practices -a blocked practice that examines student knowledge and skills for applying a certain method to the solution of various questions on only one topic or type, and the interleaved practice that involves questions on two or more topics that need different methods to solve. Results from the first summer cohort (N=16) show that students who learned math and science topics through interleaved practices consistently scored 5-30% better than those who learned it in the more traditional blocked practice. In many cases, the differences were statistically significant (p <0.05). While the second summer cohort (N=42) continues its action research, our future work will attempt to reduce confounding variables in research experiments and repeat them with more robust techniques and another level of memory retrieval strategy to help students not only recall what they learned in a classroom but also apply their content knowledge and computational skills to problem solving in a generative fashion beyond just answering multiple-choice questions.