Perceptual learning and the technology of expertise Studies in fraction learning and algebra
Bibliographic Data
| ID | 20484363 |
|---|---|
| Authors | PHILIP J KELLMAN (0000-0002-9173-2607, University of California, Los Angeles), Christine Massey (0000-0001-8779-9676, California University of Pennsylvania), Zipora Roth, Tim Burke (0009-0003-9593-303X), Timothy Burke, Joel Zucker, Amanda Sawa, Amanda Saw, Katherine E Aguero, Joseph A Wise |
| Year | 2008 |
| Volume | 16 |
| Issue | 2 |
| Pages | 356-405 |
| Publication date | 2008-08-01 |
| Open Access | No |
| Type | ARTICLE |
| Venue | Pragmatics & Cognition (JOURNAL) |
| Journal identifiers | ISSN: 0929-0907 • E-ISSN: 1569-9943 |
| Publisher | John Benjamins Publishing Company (PUBLISHER • NL) |
| DOI | 10.1075/p&c.16.2.07kel |
| OpenAlex | W1998753409 |
| Language | EN |
| Citations received | 5 |
Learning in educational settings most often emphasizes declarative and procedural knowledge. Studies of expertise, however, point to other, equally important components of learning, especially improvements produced by experience in the extraction of information: Perceptual learning . Here we describe research that combines principles of perceptual learning with computer technology to address persistent difficulties in mathematics learning. We report three experiments in which we developed and tested perceptual learning modules (PLMs) to address issues of structure extraction and fluency in relation to algebra and fractions. PLMs focus students’ learning on recognizing and discriminating, or mapping key structures across different representations or transformations. Results showed significant and persisting learning gains for students using PLMs. PLM technology offers promise for addressing neglected components of learning: Pattern recognition, structural intuition, and fluency. Using PLMs as a complement to other modes of instruction may allow students to overcome chronic problems in learning
Cognitive psychology · Cognitive science · Fluency · Intuition · Mathematics education · Perception · Perceptual Learning · Sequence learning · Computer Science · Evaluation of Teaching Practices · Mathematics Education and Teaching Techniques · Psychology · Statistics Education and Methodologies · Artificial Intelligence
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| Citations per year | 0.36 |
|---|---|
| Citation span | 2012 - 2023 (12) |
| Highly cited | No |