Grant Closed

Supporting Efficient and Durable Student Learning

NCER

Program: Education Research Grants

Program topic(s): Cognition and Student Learning

Award amount: $879,668

Principal investigator: John Dunlosky

Awardee:

Kent State University

Year: 2005

Project type:

Development and Innovation

Award number: R305H050038

Purpose

The research team developed and evaluated the promise of a new method of learning and study, called retrieval-feedback-monitoring. The goal of this new method was to support students' learning for long-term retention of key concepts in academic content areas. Researchers based this method on two cognitive theories. First, research demonstrates that the durability of learning can be improved by requiring learners to study concepts systematically spaced over time instead of trying to master many concepts in a single study session (i.e., "cramming"). Second, study time can be used most efficiently when there is accurate monitoring of what has been learned and what still needs to be learned. The researchers hypothesized that computer-assisted studying based on these principles would improve learning. In this project, the researchers completed laboratory research in order to optimize this process and implemented it with undergraduate psychology students and middle school science students. At the conclusion of this project, this research team had a new, validated method to support long-term learning of academic content that could be used in many content areas and for many grade levels.

Structured Abstract

Setting

Students participating in this research project reside in northeastern Ohio.

Sample

Approximately 300 undergraduate students at Kent State University, and approximately 8 classes of middle school students are participating in this project.

Intervention

The retrieval-feedback-monitoring (RFM) procedure is a computer-assisted study process based on two important principles from cognitive psychology. First, spacing out recall or retrieval of information yields superior learning as compared to other study schedules. Second, improving student ability to accurately monitor how well new information has been learned will increase learning. In the RFM process, students will participate in one study session each week on the computer. During the study session, the key concepts from one chapter of the textbook students are using will be introduced. After studying the concepts, the computer will generate questions for the students to answer about these concepts. Students will see their answers along with the correct answer. Then students will be asked to judge their learning of the concept. Finally, the computer program will schedule subsequent practice tailored for each student and each concept. This process will continue over the weeks that students participate, and students will receive practice of concepts spaced over time. The RFM method includes initial study of concepts, practice retrieving the concepts, feedback about what is remembered, and student monitoring of the quality of what they retrieved.

Research design and methods

In phase 1, the research team is conducting laboratory research with university undergraduates in order to establish optimal schedules of item presentation and optimal intervals for spacing study sessions. In phase 2, the researchers are implementing the RFM method in an Introductory Psychology classroom to support students' learning of key concepts from the course materials. During the classroom trials, the researchers are measuring the effect of the new study method against standard controls and are using outcomes from initial experiments to improve the computer-assisted learning method. In phase 3, the researchers are modifying the RFM technology for fifth- to seventh-grade students in science classes from the local community.

Control condition

The control conditions vary across each of the six experiments and are appropriate to the questions addressed in each experiment.

Key measures

Measures are being developed to test student mastery of the key concepts tested within the content area covered during instruction.

Data analytic strategy

Repeated measures analysis of variance is being carried out to examine student performance in conditions explored in each experiment.

People and institutions involved

IES program contact(s)

Elizabeth Albro

Commissioner of Education Research

NCER

Products and publications

ERIC Citations: Find available citations in ERIC for this award here.

Select Publications:

Book chapters

Dunlosky, J., Bottiroli, S., and Hartwig, M. (2009). Sins Committed in the Name of Ecological Validity: A Call for Representative Design in Education Research. In D. Hacker, J. Dunlosky, and A. Graesser (Eds.), Handbook of Metacognition in Education (pp. 430-440). New York: Taylor and Francis.

Journal articles Dunlosky, J., and Lipko, A.R. (2007). Metacomprehension: A Brief History and how to Improve its Accuracy. Current Directions in Psychological Science, 16(4): 228-232.

Dunlosky, J., and Rawson, K.A. (2012). Overconfidence Produces Underachievement: Inaccurate Self Evaluations Undermine Students' Learning and Retention. Learning and Instruction, 22(4): 271-280.

Grimaldi, P.J., Pyc, M.A., and Rawson, K.A. (2010). Normative Multitrial Recall Performance, Metacognitive Judgments, and Retrieval Latencies for Lithuanian-English Paired Associates. Behavior Research Methods, 42(3): 634-642.

Hartwig, M.K., Rawson, K.A., and Lipko, A.R. (2011). Improving College Students' Evaluation of Text Learning Using Idea-Unit Standards. The Quarterly Journal of Experimental Psychology, 64(3): 467-484.

Lipko, A.R., Dunlosky, J., Hartwig, M., Rawson, K.A., Swan, K., and Cook, D. (2009). Using Standards to Improve Middle School Students' Accuracy at Evaluating the Quality of Their Recall. Journal of Experimental Psychology: Applied, 15(4): 307-318.

Pyc, M.A., and Rawson, K.A. (2007). Examining the Efficiency of Schedules of Distributed Retrieval Practice. Memory and Cognition, 35(8): 1917-1927.

Pyc, M.A., and Rawson, K.A. (2009). Testing the Retrieval Effort Hypothesis: Does Greater Difficulty Correctly Recalling Information Lead to Higher Levels of Memory?. Journal of Memory and Language, 60(4): 437-447.

Pyc, M.A., and Rawson, K.A. (2011). Costs and Benefits of Dropout Schedules of Test-Restudy Practice: Implications for Student Learning. Applied Cognitive Psychology, 25(1): 87-95.

Pyc, M.A., and Rawson, K.A. (2012). Are Judgments of Learning Made After Correct Responses During Retrieval Practice Sensitive to Lag and Criterion Level Effects?. Memory and Cognition, 40(6): 976-988.

Rawson, K.A. (2012). Why do Rereading Lag Effects Depend on Test Delay?. Journal of Memory and Language, 66(4): 870-884.

Rawson, K.A., and Dunlosky, J. (2007). Improving Students' Self-Evaluation of Learning for Key Concepts in Textbook Materials. European Journal of Cognitive Psychology, 19(4): 559-579.

Rawson, K.A., and Dunlosky, J. (2011). Optimizing Schedules of Retrieval Practice for Durable and Efficient Learning: How Much Is Enough?. Journal of Experimental Psychology: General, 140(3): 283-302.

Wissman, K.T., Rawson, K.A., and Pyc, M.A. (2011). The Interim Test Effect: Testing Prior Material can Facilitate the Learning of New Material. Psychonomic Bulletin and Review, 18(6): 1140-1147.

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Questions about this project?

To answer additional questions about this project or provide feedback, please contact the program officer.

Supporting Efficient and Durable Student Learning

Purpose

Structured Abstract

Setting

Sample

Research design and methods

Control condition

Key measures

Data analytic strategy

People and institutions involved

IES program contact(s)

Elizabeth Albro

Products and publications

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Purpose

Structured Abstract

Setting

Sample

Research design and methods

Control condition

Key measures

Data analytic strategy

People and institutions involved

IES program contact(s)

Elizabeth Albro

Products and publications

Related projects

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