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Related Experiment Video

Updated: Apr 29, 2026

Creating Objects and Object Categories for Studying Perception and Perceptual Learning

Creating Objects and Object Categories for Studying Perception and Perceptual Learning

Published on: November 2, 2012

Self-insight in probabilistic category learning.

Ferenc Kemény¹, Ágnes Lukács

¹a Budapest University of Technology and Economics.

The Journal of General Psychology

|May 20, 2014

Summary

This study investigates explicit knowledge acquisition in the Weather Prediction (WP) task. Findings suggest participants gain explicit understanding, challenging its implicit learning classification.

Keywords:

Weather Prediction Task consciousness explicit learning implicit learning multiple-cue learning probabilistic category learning self-insight

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Area of Science:

Cognitive Psychology
Learning Sciences

Background:

The Weather Prediction (WP) task is a common Probabilistic Category Learning paradigm.
Its classification as an implicit task has been debated, with questions arising about acquired structural knowledge.

Purpose of the Study:

To determine if participants acquire explicit knowledge during the WP task.
To challenge the prevailing view of the WP task as solely implicit.

Main Methods:

Experiment 1 used a subjective self-insight measure comparing an experimental group (WP task) with a control group (no predictive structure).
Experiment 2 manipulated stimulus presentation times to assess learning implicitness.

Main Results:

Participants in the WP task group reported more explicit knowledge than the control group.
Performance improvements were linked to trials where explicit knowledge was reported.
Reduced stimulus presentation times prolonged learning but did not increase implicit processes.

Conclusions:

The findings provide evidence that explicit knowledge is acquired in the Weather Prediction task.
This challenges the traditional categorization of the WP task as purely implicit learning.