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Information on IES-Funded Research
Grant Closed

Perceptual Learning Technology in Mathematics Education: Efficacy and Replication

NCER
Program: Education Research Grants
Program topic(s): Cognition and Student Learning
Award amount: $1,991,881
Principal investigator: Philip Kellman
Awardee:
University of California, Los Angeles
Year: 2012
Award period: 5 years (07/01/2012 - 06/30/2017)
Project type:
Efficacy
Award number: R305A120288

Purpose

An important expertise in mathematics is the rapid pick-up of task-relevant patterns and structures. Yet such skills are seldom taught explicitly. Instruction usually emphasizes declarative knowledge and procedures that can be enacted. Indeed, instruction is commonly understood to require verbal explanation and discussion-whether it takes the form of teacher led lectures, reading assignments, small group discussion, or self-explanation. Similarly, procedural learning in mathematics generally involves steps or strategies that can be articulated and then practiced. While these pedagogical processes are clearly important, studies of mathematics learning point to persistent problems in student learning, including difficulties in retention, failure to transfer, lack of fluency, and poor understanding of the conditions of application of knowledge. The perceptual learning modules (PLMs), which were developed under a prior IES Development grant, incorporate principles of perceptual and adaptive learning to target conceptually difficult areas of the middle school mathematics curriculum related to fractions and measurement. In smaller-scale classroom based efficacy studies, the PLM modules have shown robust and durable gains in student learning. The goal of this study is to test the efficacy of the PLMs to improve student learning compared to students who do not have access to the intervention.

Project Activities

This project will conduct a randomized controlled trial of a web-based intervention that consists of four perceptual learning modules that integrate (1) principles of perceptual learning that accelerate learners' abilities to recognize and discriminate key structures and relations in complex domains, and (2) adaptive learning algorithms that use a constant stream of performance data, combined with principles of learning and memory, to improve the effectiveness and efficiency of learning by adapting the learning process to each individual. These learning techniques have been combined with an approach to the mathematical content that connects and integrates domains of measurement and fractions to each other and to other core concepts with which they share deep underlying structures. The study will include approximately 3,000 6th grade students in 60 classrooms and will take place over the course the school year.

Structured Abstract

Setting

The study will be conducted in urban and suburban school districts in the Los Angeles and Philadelphia areas.

Sample

Classrooms of teachers who teach two comparable sections of 6th grade mathematics classes that can be randomly assigned to study conditions will be eligible for the study. The participating school districts have varied demographic and achievement profiles.

Intervention

The intervention consists of four perceptual learning modules that integrate (1) principles of perceptual learning that accelerate learners' abilities recognize and discriminate key structures and relations in complex domains, and (2) adaptive learning algorithms that use a constant stream of performance data, combined with principles of learning and memory, to improve the effectiveness and efficiency of learning by adapting the learning process to each individual. These learning techniques have been combined with an approach to the mathematical content that connects and integrates domains of measurement and fractions to each other and to other core concepts with which they share deep underlying structures. Students in intervention classrooms will complete the four PLMs over the course of their 6th grade year.

Research design and methods

Comparable sections of 6th grade mathematics taught by the same teachers will be randomly assigned to intervention and control conditions. The researchers will recruit 30 teachers in total across the two sites, representing 60 classes per year, and run two cohorts in successive years. This will result in approximately 1,500 students in each condition of the study. A team of mathematics curriculum and learning specialists will analyze district curricula and substitute PLMs for related activities in the normal curriculum, so that total math instruction time will be equal across conditions.

Control condition

The research design employs a business-as-usual control condition in classrooms taught by the same teachers.

Key measures

Assessments will consist of state math tests administered at the end of 6th grade plus constructed assessments for each module drawn from publicly available items that are analyzed for alignment with the content addressed by the intervention. A delayed posttest will be administered to participants one year later to examine durability of learning. Fidelity of implementation will be assessed using time-stamped data automatically collected by the software, by a teacher implementation survey, and a small observational sub-study. Student scores on 5th grade state tests will be used as covariates.

Data analytic strategy

To analyze data collected from both study locations, one three-level, place-based randomized trial will be employed to determine whether the intervention has discernible effects relative to the control group, and if so, what their magnitude is.

People and institutions involved

IES program contact(s)

Edward Metz

Education Research Analyst
NCER

Project contributors

Christine Massey

Co-principal investigator
University of Pennsylvania

Andrew Porter

Co-principal investigator
University of Pennsylvania

Laura Desimone

Co-principal investigator
University of Pennsylvania

Products and publications

The products for this publication will be evidence of the efficacy of the PLM. Peer reviewed publications will also be produced.

Publications:

Book

Kellman, P.J., and Massey, C.M. (2013). Perceptual Learning, Cognition, and Expertise. (1st ed.). San Diego: Elsevier Academic Press.

Journal article, monograph

Desimone, L. M., & Hill, K. L. (2017). Inside the black box: Examining mediators and moderators of a middle school science intervention. Educational Evaluation and Policy Analysis, 39(3), 511-536.

Kellman, P. J. (2013). Adaptive and perceptual learning technologies in medical education and training. Military Medicine, 178(suppl_10), 98-106.

Kellman, P. J., & Krasne, S. (2018). Accelerating expertise: Perceptual and adaptive learning technology in medical learning. Medical Teacher, 40(8), 797-802.

Mettler, E., & Kellman, P. J. (2014). Adaptive response-time-based category sequencing in perceptual learning. Vision Research, 99, 111-123.

Mettler, E., Massey, C. M., & Kellman, P. J. (2016). A comparison of adaptive and fixed schedules of practice. Journal of Experimental Psychology: General, 145(7), 897.

Proceeding

Bufford, C. A., Mettler, E., Geller, E. H., & Kellman, P. J. (2014, July). The psychophysics of algebra expertise: Mathematics perceptual learning interventions produce durable encoding changes. In CogSci... Annual Conference of the Cognitive Science Society. Cognitive Science Society (US). Conference (Vol. 36, p. 272).

Massey, C. M., Kregor, J. D., Cosgrove, L. E., & Lee, H. (2016). What Were They Thinking? Diagnostic Coding of Conceptual Errors ina Mathematics Learning Software Data Archive. In Proceedings of the Annual Meeting of the Cognitive Science Society (Vol. 38).

 

Related projects

Integrating Conceptual Foundations in Mathematics through the Application of Principles of Perceptual Learning

R305H060070

Questions about this project?

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

 

Tags

CognitionK-12 EducationMathematicsStudents

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Questions about this project?

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

 

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