Education, Science, Technology, Innovation and Life
Open Access
Sign In

Effort Regulation in Meta-reasoning: Monitoring and Control

Download as PDF

DOI: 10.23977/appep.2024.050310 | Downloads: 9 | Views: 198

Author(s)

Zhichao Qian 1

Affiliation(s)

1 School of Education, Anqing Normal University, Anqing, Anhui, China

Corresponding Author

Zhichao Qian

ABSTRACT

Meta-reasoning is an intricate cognitive function that oversees and modulates advanced intellectual activities like reasoning and solving problems, employing continuous self-assessment to navigate complexities. Although this monitoring is somewhat vague, it often harnesses heuristic cues to render judgements and drive decisions. These heuristics, while efficient, vary greatly and can lead to different decision-making paths. The effort regulation in meta-reasoning, as articulated by the Diminishing Criterion Model(DCM), is influenced by a decline in confidence levels, coupled with a decrease in available time which, together, can precipitate a cessation in cognitive engagement. Consequently, compelling avenues for further research include a thorough examination of the dynamics of heuristic cues and an enhancement of reasoning abilities through improved meta-reasoning techniques. Additionally, it is crucial to investigate the specific the neural mechanism of meta-reasoning. Future studies in these areas are expected to refine our comprehension of heuristic reliance and the metacognitive effort.

KEYWORDS

Reasoning, Meta-reasoning, Heuristic Cues, Effort Regulation

CITE THIS PAPER

Zhichao Qian, Effort Regulation in Meta-reasoning: Monitoring and Control. Applied & Educational Psychology (2024) Vol. 5: 78-83. DOI: http://dx.doi.org/10.23977/appep.2024.050310.

REFERENCES

[1] Wansink B, Sobal J. Mindless eating: the 200 daily food decisions we overlook[J]. Environment and Behavior, 2007, 39(1): 106-123.
[2] Flavell J H. Metacognition and cognitive monitoring: a new area of cognitive–developmental inquiry[J]. American Psychologist, 1979, 34(10): 906-911.
[3] Nelson T O. Metamemory: a theoretical framework and new findings[M]//Vol. 26. Elsevier, 1990: 125-173.
[4] Nelson T O. Consciousness and metacognition[J]. American Psychologist, 1996, 51(2): 106-116.
[5] Bjork R A, Dunlosky J, Kornell N. Self-regulated learning: beliefs, techniques, and illusions[J]. Annual Review of Psychology, 2013, 64(1): 417-444.
[6] Ackerman R, Thompson V A. Meta-reasoning: monitoring and control of thinking and reasoning[J]. Trends in Cognitive Sciences, 2017, 21(8): 607-617.
[7] Metcalfe J, Finn B. Evidence that judgments of learning are causally related to study choice[J]. Psychonomic Bulletin & Review, 2008, 15(1): 174-179.
[8] Son L K, Metcalfe J. Metacognitive and control strategies in study-time allocation.[J]. Journal of Experimental Psychology-learning Memory and Cognition, 2000, 26(1): 204-221.
[9] De Neys W, Rossi S, Houdé O. Bats, balls, and substitution sensitivity: cognitive misers are no happy fools[J]. Psychonomic Bulletin & Review, 2013, 20(2): 269-273.
[10] Thompson V A, Prowse Turner J A, Pennycook G. Intuition, reason, and metacognition[J]. Cognitive Psychology, 2011, 63(3): 107-140.
[11] Undorf M, Ackerman R. The puzzle of study time allocation for the most challenging items[J]. Psychonomic Bulletin & Review, 2017, 24(6): 2003-2011.
[12] Scarampi C. Metacognition: Monitoring and Controlling One’s Own Knowledge, Reasoning and Decisions [M]// The Psychology of Human Thought: An Introduction. 2019: 89-111.
[13] Ackerman R, Zalmanov H. The persistence of the fluency–confidence association in problem solving[J]. Psychonomic Bulletin & Review, 2012, 19(6): 1187-1192.
[14] Koriat A. When reality is out of focus: can people tell whether their beliefs and judgments are correct or wrong? [J]. Journal of Experimental Psychology-general, 2018, 147(5): 613-631.
[15] Dunlosky J, Tauber S K. Understanding people’s metacognitive judgments: an isomechanism framework and its implications for applied and theoretical research[M]//Perfect T, Lindsay D S. The SAGE Handbook of Applied Memory. 1 Oliver’s Yard, 55 City Road, London EC1Y 1SP United Kingdom: SAGE Publications Ltd, 2014: 444-464.
[16] Koriat A. Monitoring one’s own knowledge during study: a cue-utilization approach to judgments of learning[J]. Journal of Experimental Psychology: General, 1997, 126(4): 349-370.
[17] Unkelbach C, Greifeneder R. A general model of fluency effects in judgment and decision making[J]. The Experience of Thinking, 2013: 11-32.
[18] Ackerman R. Heuristic cues for meta-reasoning judgments: review and methodology[J]. Psihologijske Teme, 2019, 28(1): 1-20.
[19] Mueller M L, Dunlosky J. How beliefs can impact judgments of learning: evaluating analytic processing theory with beliefs about fluency[J]. Journal of Memory and Language, 2017, 93: 245-258.
[20] Undorf M, Söllner A, Bröder A. Simultaneous utilization of multiple cues in judgments of learning[J]. Memory & Cognition, 2018, 46(4): 507-519.
[21] Morsanyi K, Busdraghi C, Primi C. Mathematical anxiety is linked to reduced cognitive reflection: a potential road from discomfort in the mathematics classroom to susceptibility to biases[J]. Behavioral and Brain Functions, 2014, 10(1): 31.
[22] Ackerman R, Lauterman T. Taking reading comprehension exams on screen or on paper? A metacognitive analysis of learning texts under time pressure[J]. Computers in Human Behavior, 2012, 28(5): 1816-1828.
[23] Touron D R, Hertzog C, Speagle J Z. Subjective learning discounts test type: evidence from an associative learning and transfer task[J]. Experimental Psychology, 2010, 57(5): 327-337.
[24] Wang X, Chen L, Liu X, et al. The screen inferiority depends on test format in reasoning and meta-reasoning tasks[J]. Frontiers in Psychology, 2023, 14: 1067577.
[25] Koriat A, Ma’ayan H, Nussinson R. The intricate relationships between monitoring and control in metacognition: lessons for the cause-and-effect relation between subjective experience and behavior.[J]. Journal of Experimental Psychology-general, 2006, 135(1): 36-69. 
[26] Undorf M, Zimdahl M F. Metamemory and memory for a wide range of font sizes: what is the contribution of perceptual fluency? [J]. Journal of Experimental Psychology-learning Memory and Cognition, 2019, 45(1): 97-109.
[27] Thompson V A, Turner J A P, Pennycook G, et al. The role of answer fluency and perceptual fluency as metacognitive cues for initiating analytic thinking[J]. Cognition, 2013, 128(2): 237-251.
[28] Zacks R T. Invariance of total learning time under different conditions of practice[J]. Journal of Experimental Psychology, 1969, 82(3): 441-447.
[29] Thiede K W, Dunlosky J. Toward a general model of self-regulated study: an analysis of selection of items for study and self-paced study time[J]. Journal of Experimental Psychology-learning Memory and Cognition, 1999, 25(4): 1024-1037.
[30] Glickman M, Moran R, Usher M. Evidence integration and decision-confidence are modulated by stimulus consistency[R]. Neuroscience, 2020.
[31] Yeung N, Summerfield C. Metacognition in human decision-making: confidence and error monitoring[J]. Philosophical Transactions of The Royal Society B-biological Sciences, 2012, 367(1594): 1310-1321.
[32] Ackerman R, Morsanyi K. We know what stops you from thinking forever: a metacognitive perspective[J]. Behavioral and Brain Sciences, 2023, 46: e112.
[33] Koriat A, Ackerman R, Adiv S, et al. The effects of goal-driven and data-driven regulation on metacognitive monitoring during learning: a developmental perspective.[J]. Journal of Experimental Psychology-general, 2014, 143(1): 386-403.
[34] Ackerman R. The diminishing criterion model for metacognitive regulation of time investment.[J]. Journal of Experimental Psychology-general, 2014, 143(3): 1349-1368.
[35] Vernon D, Usher M. Dynamics of metacognitive judgments: pre- and postretrieval mechanisms.[J]. Journal of Experimental Psychology-learning Memory and Cognition, 2003, 29(3): 339-346.
[36] Ackerman R, Binah-Pollak A, Lauterman T. Metacognitive effort regulation across cultures[J]. Journal of Intelligence, 2023, 11(9): 171.
[37] Lauterman T, Ackerman R. Initial judgment of solvability: integrating prior expectations with experience-based heuristic cues[J]. Thinking & Reasoning, 2023: 1-34.
[38] De Bruin A B H, Kok E M, Lobbestael J, et al. The impact of an online tool for monitoring and regulating learning at university: overconfidence, learning strategy, and personality[J]. Metacognition and Learning, 2017, 12(1): 21-43.
[39] Prowse Turner J A, Thompson V A. The role of training, alternative models, and logical necessity in determining confidence in syllogistic reasoning[J]. Thinking & Reasoning, 2009, 15(1): 69-100.

All published work is licensed under a Creative Commons Attribution 4.0 International License.

Copyright © 2016 - 2031 Clausius Scientific Press Inc. All Rights Reserved.