Internal mapping and its impact on measures of absolute and relative metacognitive accuracy
Internal mapping and its impact on measures of absolute and relative metacognitive accuracy
Research in decision making and metacognition has long investigated the calibration of subjective probabilities. To assess calibration, mean ratings on a percentage scale (e.g., subjective likelihood of recalling an item) are typically compared directly to performance percentages (e.g., actual likelihood of recall). Means that are similar versus discrepant are believed to indicate good versus poor calibration, respectively. This chapter argues that this process is incomplete: it examines only the mapping between the overt scale values and objective performance (mapping 2), while ignoring the process by which the overt scale values are first assigned to different levels of subjective evidence (mapping 1). The chapter demonstrates how ignoring mapping 1 can lead to conclusions about calibration that are misleading. It proposes a signal detection framework that not only provides a powerful method for analyzing calibration data, but also offers a variety of measures of relative metacognitive accuracy (resolution)
Higham, P. A.
4093b28f-7d58-4d18-89d4-021792e418e7
Zawadzka, K.
b30f4b52-cfbc-4596-9069-0aa193bf7d77
Hanczakowski, M.
6214c11e-0fd6-4c3d-a7f8-20b72e4b281d
February 2015
Higham, P. A.
4093b28f-7d58-4d18-89d4-021792e418e7
Zawadzka, K.
b30f4b52-cfbc-4596-9069-0aa193bf7d77
Hanczakowski, M.
6214c11e-0fd6-4c3d-a7f8-20b72e4b281d
Higham, P. A., Zawadzka, K. and Hanczakowski, M.
(2015)
Internal mapping and its impact on measures of absolute and relative metacognitive accuracy.
In,
Dunlosky, J. and Tauber, S.
(eds.)
Oxford Handbook of Metamemory.
Oxford, GB.
Oxford University Press.
(doi:10.1093/oxfordhb/9780199336746.013.15).
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Abstract
Research in decision making and metacognition has long investigated the calibration of subjective probabilities. To assess calibration, mean ratings on a percentage scale (e.g., subjective likelihood of recalling an item) are typically compared directly to performance percentages (e.g., actual likelihood of recall). Means that are similar versus discrepant are believed to indicate good versus poor calibration, respectively. This chapter argues that this process is incomplete: it examines only the mapping between the overt scale values and objective performance (mapping 2), while ignoring the process by which the overt scale values are first assigned to different levels of subjective evidence (mapping 1). The chapter demonstrates how ignoring mapping 1 can lead to conclusions about calibration that are misleading. It proposes a signal detection framework that not only provides a powerful method for analyzing calibration data, but also offers a variety of measures of relative metacognitive accuracy (resolution)
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Published date: February 2015
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Local EPrints ID: 396608
URI: http://eprints.soton.ac.uk/id/eprint/396608
PURE UUID: e5dc2a67-0828-42c8-8648-a7234a15ff33
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Date deposited: 10 Jun 2016 13:12
Last modified: 13 Sep 2024 01:37
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Contributors
Author:
K. Zawadzka
Author:
M. Hanczakowski
Editor:
J. Dunlosky
Editor:
S. Tauber
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