Papers

The list below includes a selection of papers which deal with Meta-Reasoning issues. It is clearly not an exhaustive list. Suggestions for additional papers to include in this list are welcome

YearReferenceOfficial publicationPre-printMisc.
2017Ackerman, R., & Thompson, V. (2017). Meta-Reasoning: Monitoring and control of thinking and reasoning. Trends in Cognitive Sciences, 21(8), 607-617.Sciencedirect
2017Ackerman, R., & Beller, Y. (2017). Shared and distinct cue utilization for metacognitive judgments during reasoning and memorisation. Thinking & Reasoning, 23:4, 376-408.Tandfonline
2013De Neys, W., Rossi, S., & Houdé, O. (2013). Bats, balls, and substitution sensitivity: Cognitive misers are no happy fools. Psychonomic Bulletin & Review, 20, 269-273.Springer
2015Lubin, A., Houdé, O., & De Neys, W. (2015). Evidence for children's error sensitivity during arithmetic word problem solving. Learning and Instruction, 40, 1-8.Sciencedirect
2017Bago, B., & De Neys, W. (2017). Fast logic?: Examining the time course assumption of dual process theory. Cognition, 158, 90-109.Sciencedirect
2012Ackerman, R., & Zalmanov, H. (2012). The persistence of the fluency-confidence association in problem solving. Psychonomic Bulleting & Review, 19(6), 1189-1192.Springer
2012Thompson, V.A. & Morsanyi, K. (2012). Analytic thinking: Do you feel like it? Mind & Society, 11, 93-105.Springer
2013Thompson, V., Prowse Turner, J., Pennycook, G., Ball, L., Brack, H., Ophir, Y., & Ackerman, R. (2013). The role of answer fluency and perceptual fluency as metacognitive cues for initiating analytic thinking. Cognition, 128, 237-251.Sciencedirect
2014Ackerman, R. (2014). The Diminishing Criterion Model for metacognitive regulation of time investment. Journal of Experimental Psychology: General, 143(3), 1349-1368. APA PsycNET

Supplementary Materials
2016Trippas, D., Handley, S.J., Verde, M. & Morsanyi, K. (2016). Logic brightens my day: Evidence for implicit sensitivity to logical validity. Journal of Experimental Psychology: Learning Memory and Cognition, 42, 1448-1457.
APA PsycNET
2012Morsanyi, K., & Handley, S.J. (2012). Logic feels so good -I like it! Evidence for intuitive detection of logicality in syllogistic reasoning. Journal of Experimental Psychology: Learning, Memory and Cognition, 38, 596-616.

APA PsycNET
2015Ackerman, R. & Thompson, V. (2015). Meta-Reasoning: What can we learn from meta-memory. In A. Feeney & V. Thompson (Eds.), Reasoning as Memory (pp. 164-182). Hove, UK: Psychology Press.
2016Žauhar, V., Bajšanski, I., & Domijan, D. (2016). Concurrent Dynamics of Category Learning and Metacognitive
Judgments. Frontiers in Psychology, 7(1473), 1–11.		Frontiers
2017Christensen, B. T., & Ball, L. J. (2017). Fluctuating epistemic uncertainty in a design team as a metacognitive driver for creative cognitive processes. In B. T. Christensen, L. J. Ball, & K. Halskov, K. (Eds.), Analysing design thinking: Studies of cross-cultural co-creation (pp. 249-269). London: CRC Press/Taylor & Francis.  pdf
2009Thompson, V. A. (2009). Dual-process theories: A metacognitive perspective. In J. Evans and K. Frankish (Eds.) In Two Minds: Dual Processes and Beyond (pp. 171-195). Oxford: Oxford University Press.pdf
2011Thompson, V.A., ProwseTurner, J., & Pennycook, G. (2011). Intuition, Metacognition, and
Reason. Cognitive Psychology, 63, 107-140.		Sciencedirect
2016Sidi, Y., Ophir, Y., Ackerman, R. (2016). Generalizing Screen Inferiority - Does the Medium, Screen versus Paper, Affect Performance Even with Brief Tasks? Metacognition & Learning, 11(1), 15-33. Springer
2017Ackerman, R. & Thompson, V. (2017). Meta-Reasoning: Shedding meta-cognitive light on reasoning research. L. Ball & V. Thompson (Eds.), International Handbook of Thinking & Reasoning. Psychology Press.pdf
2017Sidi, Y., Shpigelman, M., Zalmanov, H., & Ackerman, R. (2017). Understanding metacognitive inferiority on screen by exposing cues for depth of processing. Learning and Instruction, 51, 61-73.Sciencedirect
2016Johnson, E. D., Tubau, E., & De Neys, W. (2016). The doubting System 1: Evidence for automatic substitution sensitivity. Acta Psychologica, 164, 56-64.
Sciencedirect
2006Shynkaruk, J. M., & Thompson, V. A. (2006). Confidence and accuracy in deductive reasoning. Memory & cognition, 34(3), 619-632.Springer
2015Markovits, H., Thompson, V. A., & Brisson, J. (2015). Metacognition and abstract reasoning. Memory & cognition, 43(4), 681-693.Springer
2018Frey, D., Johnson, E. D., & De Neys, W. (2018). Individual differences in conflict detection during reasoning. Quarterly Journal of Experimental Psychology, 71(5), 1188-1208.pdf
2016Ball, L. J., & Stupple, E. J. N. (2016). Dual reasoning processes and the resolution of uncertainty: The case of belief bias. In L. Macchi, M. Bagassi, & R. Viale (Eds.), Cognitive unconscious and human rationality (pp. 143-165). Cambridge, MA: MIT Press. 
2000Quayle, J. D., & Ball, L. J. (2000). Working memory, metacognitive uncertainty, and belief bias in syllogistic reasoning. Quarterly Journal of Experimental Psychology, 53A, 1202-1223.Tandfonline
2013Wiltschnig, S., Christensen, B. T., & Ball, L. J. (2013). Collaborative problem–solution co-evolution in creative design. Design Studies, 34, 515-542.Sciencedirect
2009Ball, L. J., & Christensen, B. T. (2009). Analogical reasoning and mental simulation in design: Two strategies linked to uncertainty resolution. Design Studies, 30, 169-186.Sciencedirect
2010Ball, L. J., Onarheim, B., & Christensen, B. T. (2010). Design requirements, epistemic uncertainty and solution development strategies in software design. Design Studies, 31, 567-589.Sciencedirect
2013Stupple, E. J. N., Ball, L. J., & Ellis, D. (2013). Matching bias in syllogistic reasoning: Evidence for a dual-process account from response times and confidence ratings. Thinking & Reasoning, 19, 54-77.Tandfonline
1986Metcalfe, J. (1986). Feeling of knowing in memory and problem solving. Journal of Experimental Psychology: Learning, Memory, and Cognition, 12(2), 288-294.semanticscholar
1987Metcalfe, J., & Wiebe, D. (1987). Intuition in insight and noninsight problem solving. Memory & cognition, 15(3), 238-246.Springer
2003Vernon, D., & Usher, M. (2003). Dynamics of metacognitive judgments: Pre-and postretrieval mechanisms. Journal of Experimental Psychology: Learning, Memory, and Cognition, 29(3), 339-346.APA PsycNET
2010Mitchum, A. L., & Kelley, C. M. (2010). Solve the problem first: constructive solution strategies can influence the accuracy of retrospective confidence judgments. Journal of Experimental Psychology: Learning, Memory, and Cognition, 36(3), 699-710.APA PsycNET
2010Topolinski, S., & Reber, R. (2010). Gaining insight into the “Aha” experience. Current Directions in Psychological Science, 19(6), 402-405.Sage
2014Stankov, L., Kleitman, S., and Jackson, S. A. (2014). Measures of the Trait of Confidence. In G. J. Boyle, D. H. Saklofske and G. Matthews (Eds.), Measures of Personality and Social Psychological Constructs, 158-189. Academic Press.ResearchGate
2016Jackson, S. A., Kleitman, S., Howie, P., & Stankov, L. (2016). Cognitive abilities, monitoring confidence, and control thresholds explain individual differences in heuristics and biases. Frontiers in psychology, 7(1559).Frontiers
2016Jackson, S. A. (2016). Greater response cardinality indirectly reduces confidence. Journal of Cognitive Psychology, 28(4), 496-504.Tandfonline
2014Bajšanski, I., Močibob, M., & Valerjev, P. (2014). Metacognitive judgments and syllogistic reasoning. Psychological Topics, 23(1), 143-165.Hrcak
2016Hedne, M. R., Norman, E., & Metcalfe, J. (2016). Intuitive feelings of warmth and confidence in insight and noninsight problem solving of magic tricks. Frontiers in psychology, 7:1314.semanticscholar
2017Valerjev, P., & Dujmović, M. (2017). Instruction type and believability influence on metareasoning in a base rate task. In: G. Gunzelmann, A. Howes, T. Tenbrink, E. Davelaar (Eds.), Proceedings of the 39th Annual Meeting of the Cognitive Science Society (pp. 3429-3434.).  Austin, TX: Cognitive Science Society.CogScipdf
2016Dujmović, M., & Valerjev, P. (2016). Metacognitive assessment of visual search tasks by 5th and 8th grade children. In: Lj. Lazarević, S. Marković, D. Pavlović Babić, O. Tošković, O. Marković Rosić (Eds.), Proceedings of the XXII Empirical Studies in Psychology conference (pp. 123-128). Belgrade: Institute for psychology, Faculty of phylosophy, University of Belgrade.Empirical Studies in Psychologypdf
2013Mata, A., Ferreira, M. B., & Sherman, S. J. (2013). The metacognitive advantage of deliberative thinkers: A dual-process perspective on overconfidence. Journal of Personality and Social Psychology, 105, 353–373.APA PsycNET
2014Mata, A., & Almeida, T. (2014). Using metacognitive cues to infer others’ thinking. Judgment and Decision Making, 9, 349–359.APA PsycNET
2017Pennycook, G., Ross, R. M., Koehler, D. J., & Fugelsang, J. A. (2017). Dunning–Kruger effects in reasoning: Theoretical implications of the failure to recognize incompetence. Psychonomic Bulletin & Review, 24 (6), 1174-1784.Springer
2017Dujmović, M., & Valerjev, P. (2017). An image is worth a thousand words, but what of numbers? The impact of multi-modal processing on response times and judgments of confidence in base-rate tasks. In: O. Tošković, K. Damnjanović, Lj. Lazarević (Eds.), Proceedings of the XXIII Science Conference Empirical Studies in Psychology (pp. 30-36). pdf
2015Mercier, H., Trouche, E., Yama, H., Heintz, C., & Girotto, V. (2015). Experts and laymen grossly underestimate the benefits of argumentation for reasoning. Thinking & Reasoning, 21(3), 341-355.Tandfonline
2018Žauhar, V., Bajšanski, I., & Domijan, D. (2018). The influence of rule availability and item similarity on metacognitive monitoring during categorisation. Journal of Cognitive Psychology, 30(2), 138-162.Tandfonline
2018Baars, M., Leopold, C., & Paas, F. (2018). Self-explaining steps in problem-solving tasks to improve self-regulation in secondary education. Journal of Educational Psychology, 110(4), 578–595.APA PsycNET
2017Baars, M., Wijnia, L., & Paas, F. (2017). The association between motivation, affect, and self-regulated learning when solving problems. Frontiers in Psychology, 8, 1346.Frontiers
2017Baars, M., Van Gog, T., de Bruin, A., & Paas, F. (2017). Effects of problem solving after worked example study on secondary school children’s monitoring accuracy. Educational Psychology, 37, 810-834. Tandfonline
2014Baars, M., Van Gog, T., de Bruin, A., & Paas, F. (2014). Effects of problem solving after worked example study on primary school children's monitoring accuracy. Applied Cognitive Psychology, 28, 382-391.Wiley
2014Baars, M., Vink, S., Van Gog, T., de Bruin, A., & Paas, F. (2014). Effects of training self-assessment and using assessment standards on retrospective and prospective monitoring of problem solving. Learning and Instruction, 33, 92-107.
Sciencedirect
2013Baars, M., Visser, S., Van Gog, T., de Bruin, A., & Paas, F. (2013). Completion of partially worked examples as a generation strategy for improving monitoring accuracy. Contemporary Educational Psychology, 38, 395-406.
Sciencedirect
2017Lieder, F., & Griffiths, T. L. (2017). Strategy selection as rational metareasoning. Psychological Review, 124(6), 762-794.APA PsycNET
2017Shenhav, A., Musslick, S., Lieder, F., Kool, W., Griffiths, T. L., Cohen, J. D., & Botvinick, M. M. (2017). Toward a rational and mechanistic account of mental effort. Annual review of neuroscience, 40, 99-124.Annual Review
2017Milli, S., Lieder, F., & Griffiths, T. (2017, February). When does bounded-optimal metareasoning favor few cognitive systems?. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 31, No. 1).AAAI
2014Lieder, F., Plunkett, D., Hamrick, J.B., Russell, S.J, Hay, N.J., & Griffiths, T.L. (2014). Algorithm Selection by Rational Metareasoning as a Model of Human Strategy Selection. In Z. Ghahramani, M. Welling, C. Cortes, N.D. Lawrence, and K.Q. Weinberger (Eds.). Advances in Neural Information Processing Systems 27, pp. 2870-2878. NIPS
2018Dujmović, M., & Valerjev, P. (2018). The influence of conflict monitoring on meta-reasoning and response times in a base rate task. Quarterly Journal of Experimental Psychology, 71(12), 2548-2561.Sagepdf
2018Lieder, F., Shenhav, A., Musslick, S., & Griffiths, T. L. (2018). Rational metareasoning and the plasticity of cognitive control. PLoS computational biology, 14(4), e1006043.SageResearchGate
2018 Ball, L. J., Threadgold, E., Solowiej, A., & Marsh, J. E. (2018). Can Intrinsic and Extrinsic Metacognitive Cues Shield Against Distraction in Problem Solving?. Journal of Cognition, 1(1), 15. DOI: http://doi.org/10.5334/joc.9 J. of Cognition
2014Thompson, V. A., & Johnson, S. C. (2014). Conflict, metacognition, and analytic thinking. Thinking & Reasoning, 20(2), 215-244.Tandfonline
2019Bajšanski, I., Žauhar, V., & Valerjev, P. (2019). Confidence judgments in syllogistic reasoning: the role of consistency and response cardinality. Thinking & Reasoning, 25(1), 14-47.Tandfonline
2020Danek, A.H., Williams, J. & Wiley, J. (2020). Closing the gap: connecting sudden representational change to the subjective Aha! experience in insightful problem solving. Psychological Research, 84, 111–119.Springer
2017 Danek, A. H., & Wiley, J. (2017). What about false insights? Deconstructing the Aha! Experience along its multiple dimensions for correct and incorrect solutions separately. Frontiers in psychology, 7:2077.Frontiers
2011Payne, S. J., & Duggan, G. B. (2011). Giving up problem solving. Memory & cognition, 39(5), 902-913.Springer
2016Siedlecka, M., Paulewicz, B., & Wierzchoń, M. (2016). But I was so sure! Metacognitive judgments are less accurate given prospectively than retrospectively. Frontiers in psychology, 7:218.Frontiers
2014Pennycook, G., Trippas, D., Handley, S. J., & Thompson, V. A. (2014). Base rates: Both neglected and intuitive. Journal of Experimental Psychology: Learning, Memory, and Cognition, 40(2), 544-554.APA
2014Pennycook, G., Cheyne, J. A., Barr, N., Koehler, D. J., & Fugelsang, J. A. (2014). Cognitive style and religiosity: The role of conflict detection. Memory & Cognition, 42(1), 1-10.Springer
2015Pennycook, G., Fugelsang, J. A., & Koehler, D. J. (2015). What makes us think? A three-stage dual-process model of analytic engagement. Cognitive Psychology, 80, 34-72.Sciencedirect
2018Ball, L. J., Threadgold, E., Marsh, J. E., & Christensen, B. T. (2018). The effects of stimulus complexity and conceptual fluency on aesthetic judgments of abstract art: Evidence for a default–interventionist account. Metaphor & Symbol, 33, 235-252.Tandfonline
2018Noah, T., Schul, Y., & Mayo, R. (2018). Thinking of oneself as an object of observation reduces reliance on metacognitive information. Journal of Experimental Psychology: General, 147(7), 1023-1042.APA
2014Mata, A., Schubert, A. L., & Ferreira, M. B. (2014). The role of language comprehension in reasoning: How “good-enough” representations induce biases. Cognition, 133(2), 457-463.Sciencedirect
2017Mata, A., Ferreira, M. B., Voss, A., & Kollei, T. (2017). Seeing the conflict: an attentional account of reasoning errors. Psychonomic Bulletin & Review, 24(6), 1980-1986.Springer
2018Mata, A., & Ferreira, M. B. (2018). Response: Commentary: Seeing the conflict: an attentional account of reasoning errors. Frontiers in psychology, 9, 24.Frontiers
2018Grossner, E. C., Bernier, R. A., Brenner, E. K., Chiou, K. S., & Hillary, F. G. (2018). Prefrontal gray matter volume predicts metacognitive accuracy following traumatic brain injury. Neuropsychology, 32(4), 484-494.
APA PsycNET
2018Laukkonen, R. E., & Tangen, J. M. (2018). How to detect insight moments in problem solving experiments. Frontiers in psychology, 9, 282.
Frontiers
2008Reber, R., Brun, M., & Mitterndorfer, K. (2008). The use of heuristics in intuitive mathematical judgment. Psychonomic Bulletin & Review, 15, 1174–1178.Springer
2016Ais, J., Zylberberg, A., Barttfeld, P., & Sigman, M. (2016). Individual consistency in the accuracy and distribution of confidence judgments. Cognition, 146, 377-386.Sciencedirect
2018Valerjev, P. & Dujmović, M. (2018). The effect of stimulus onset asynchrony between different response cues on reasoning in a base rate task. In K. Damnjanović, I. Stepanović Ilić, & S. Marković (Eds.), Proceedings of the 24th Scientific Conference Empirical Studies In Psychology (pp. 12-14). Belgrade: Institute of Psychology, Laboratory for Experimental Psychology, Faculty of Philosophy, University of Belgrade.ResearchGate
2014Caro, M. F., Josyula, D. P., Cox, M. T., & Jiménez, J. A. (2014). Design and validation of a metamodel for metacognition support in artificial intelligent systems. Biologically Inspired Cognitive Architectures, 9, 82-104.Sciencedirect
2015Caro, M. F., Josyula, D. P., Jiménez, J. A., Kennedy, C. M., & Cox, M. T. (2015). A domain-specific visual language for modeling metacognition in intelligent systems. Biologically Inspired Cognitive Architectures, 13, 75-90.Sciencedirect
1996Kelley, C. M., & Jacoby, L. L. (1996). Adult egocentrism: Subjective experience versus analytic bases for judgment. Journal of Memory and Language, 35(2), 157-175.Sciencedirect
2016Siedlecka, M., Paulewicz, B., & Wierzchoń, M. (2016). But I was so sure! Metacognitive judgments are less accurate given prospectively than retrospectively. Frontiers in Psychology, 7, 218.Frontiers
2009Prowse Turner, J. A., & Thompson, V. A. (2009). The role of training, alternative models, and logical necessity in determining confidence in syllogistic reasoning. Thinking & Reasoning, 15(1), 69-100.Tandfonline
2019Griffiths, T.L., Callaway, F., Chang. M., Grant, E., Krueger, P. M., & Lieder, F. (2019). Doing more with less: Meta-reasoning and meta-learning in humans and machines. Current Opinion in Behavioral Sciences, 29, 24-30. doi:10.1016/j.cobeha.2019.01.005 Sciencedirect
2020Lieder, F., & Griffiths, T. L. (2020). Resource-rational analysis: understanding human cognition as the optimal use of limited computational resources. Behavioral and Brain Sciences, 43. BBS
2018Loesche, F., Goslin, J., & Bugmann, G. (2018). Paving the way to eureka—introducing “Dira” as an experimental paradigm to observe the process of creative problem solving. Frontiers in psychology, 9.Frontiers
2016Fernandez Cruz, A. L., Arango-Muñoz, S., & Volz, K. G. (2016). Oops, scratch that! Monitoring one’s own errors during mental calculation. Cognition, 146, 110-120.Sciencedirect
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2018Logg, J. M., Haran, U., & Moore, D. A. (2018). Is overconfidence a motivated bias? Experimental evidence. Journal of Experimental Psychology: General, 147(10), 1445-1465. doi: 2018-48183-001APA PsycNET
2019Aidman, E., Jackson, S. A., & Kleitman, S. (2019). Effects of sleep deprivation on executive functioning, cognitive abilities, metacognitive confidence, and decision making. Applied Cognitive Psychology, 33(2), 188-200.Wiley
2012Fiedler, K. (2012). Meta-cognitive myopia and the dilemmas of inductive-statistical inference. In Psychology of learning and motivation (Vol. 57, pp. 1-55). Academic Press.APA PsycNET
2019Fiedler, K., Hütter, M., Schott, M., & Kutzner, F. (2019). Metacognitive myopia and the overutilization of misleading advice. Journal of Behavioral Decision Making, 32(3), 317-333.Wiley
2019Lauterman, T., & Ackerman, R. (2019). Initial judgment of solvability in non-verbal problems–A predictor of solving processes. Metacognition and Learning, 14(3), 365-383.Springer
2015Mevel, K., Poirel, N., Rossi, S., Cassotti, M., Simon, G., Houdé, O., & De Neys, W. (2015). Bias detection: Response confidence evidence for conflict sensitivity in the ratio bias task. Journal of Cognitive Psychology, 27(2), 227-237.Tandfonline
2011De Neys, W., Cromheeke, S., & Osman, M. (2011). Biased but in doubt: Conflict and decision confidence. PloS one, 6(1), e15954.PlosOne
2008De Neys, W., & Glumicic, T. (2008). Conflict monitoring in dual process theories of thinking. Cognition, 106(3), 1248-1299.Sciencedirect
2016Aczel, B., Szollosi, A., & Bago, B. (2016). Lax monitoring versus logical intuition: The determinants of confidence in conjunction fallacy. Thinking & Reasoning, 22(1), 99-117.Tandfonline
2017Scherer, L. D., Yates, J. F., Baker, S. G., & Valentine, K. D. (2017). The influence of effortful thought and cognitive proficiencies on the conjunction fallacy: implications for dual-process theories of reasoning and judgment. Personality and Social Psychology Bulletin, 43(6), 874-887.Sage
2019Ackerman, R. (2019). Heuristic cues for meta-reasoning judgments: Review and methodology. Psychological Topics, 28(1), 1-20.HRCAKOpen access
2019Morsanyi, K., Cheallaigh, N. N. & Ackerman, R. (2019). Mathematics anxiety and metacognitive Processes: Proposal for a new line of inquiry. Psychological Topics, 28 (1), 147-169. HRCAKOpen access
2019Meta-Reasoning SPECIAL ISSUE in Psychological topics. Guest Editor: Igor Bajšanski HRCAKOpen access
2019Dentakos, S., Saoud, W., Ackerman, R., & Toplak, M. E. (2019). Does domain matter? Monitoring accuracy across domains. Metacognition and Learning, 14(3), 413-436.Springer
2019Beeson, N., Stupple, E. J. N., Schofield, M. B. & Staples, P. (2019). Mental Models or Probabilistic Reasoning or Both: Reviewing the Evidence for and Implications of Dual-Strategy Models of Deductive Reasoning. Psychological Topics, 28 (1), 21-35. HRCAK
2019Wang, S. & Thompson, V. (2019). Fluency and Feeling of Rightness: The Effect of Anchoring and Models. Psychological Topics, 28 (1), 37-72.HRCAK
2019Bajšanski, I. & Žauhar, V. (2019). The Relationship between Consistency and Consensuality in Syllogistic Reasoning. Psychological Topics, 28 (1), 73-91. HRCAK
2019Valerjev, P. & Dujmović, M. (2019). Performance and Metacognition in Scientific Reasoning: The Covariation Detection Task. Psychological Topics, 28 (1), 93-113. HRCAK
2019Mata, A. (2019). Further Tests of the Metacognitive Advantage Model: Counterfactuals, Confidence and Affect. Psychological Topics, 28 (1), 115-124. HRCAK
2019Putarek, V. & Vlahović-Štetić, V. (2019). Metacognitive Feelings, Conflict Detection and Illusion of Linearity. Psychological Topics, 28 (1), 171-192. HRCAK
2019Wanstall, E. A., Doidge, J., Weiss, J. & Toplak, M. E. (2019). Estimations of Competence in Neurodevelopmental Conditions: A Review. Psychological Topics, 28 (1), 193-232. HRCAK
2020Fiedler, K., Schott, M., Kareev, Y., Avrahami, J., Ackerman, R., Goldsmith, M., Mata, A., Ferreira, M. B., Newell, B. R., & Pantazi, M. (2020). Metacognitive myopia in change detection: A collective approach to overcome a persistent anomaly. Journal of Experimental Psychology: Learning, Memory, and Cognition, 46(4), 649–668. APA PsycNET
2017Koriat, A. (2017). Can people identify “deceptive” or “misleading” items that tend to produce mostly wrong answers?. Journal of Behavioral Decision Making, 30(5), 1066-1077.Wiley
2019Amidu, A. R., Boyd, D., & Agboola, A. O. (2019). The role of knowledge in valuation practice: expert valuers’ perceptions. Journal of Property Investment & Finance.Emerald
2020Mata, A. (2020). Conflict detection and social perception: Bringing meta-reasoning and social cognition together. Thinking & Reasoning, 26(1), 140-149.Tandfonline
2019Mata, A. (2019). Social metacognition in moral judgment: Decisional conflict promotes perspective taking. Journal of personality and social psychology, 117(6), 1061–1082. APA PsycNET
2019 Fiedler, K., Ackerman, R., & Scarampi, C. (2019). Metacognition: Monitoring and controlling one’s own knowledge, reasoning and decisions. In R. J. Sternberg & J. Funke (Eds.). Introduction to the Psychology of Human Thought (pp. 89-111). Heidelberg: Heidelberg University Publishing.Heidelberg Univ. PublishingOpen access
2019Caro, M. F., Josyula, D. P., Madera, D. P., Kennedy, C. M., & Gómez, A. A. (2019). The CARINA Metacognitive Architecture. International Journal of Cognitive Informatics and Natural Intelligence (IJCINI), 13(4), 71-90.IGI Global
2019Walker, A., Turpin, M. H., Fugelsang, J., & Koehler, D. (2019). Intuition speed as a predictor of choice and confidence in point spread predictions. Judgment and Decision Making, 14(2), 148-155.SSRN
2017Szollosi, A., Bago, B., Szaszi, B., & Aczel, B. (2017). Exploring the determinants of confidence in the bat-and-ball problem. Acta psychologica, 180, 1-7.Sciencedirect
2020Littrell, S., Fugelsang, J., & Risko, E. F. (2020). Overconfidently underthinking: Narcissism negatively predicts cognitive reflection. Thinking & Reasoning, 26(3), 352-380.Tandfonline
2019Hoover, J. D., & Healy, A. F. (2019). The bat-and-ball problem: Stronger evidence in support of a conscious error process. Decision, 6 (4), 369-380.APA PsycNET
2019Bago, B., & De Neys, W. (2019). The smart System 1: Evidence for the intuitive nature of correct responding on the bat-and-ball problem. Thinking & Reasoning, 25(3), 257-299.Tandfonline
2019Webb, M. E., Cropper, S. J., & Little, D. R. (2019). “Aha!” is stronger when preceded by a “huh?”: presentation of a solution affects ratings of aha experience conditional on accuracy. Thinking & Reasoning, 25(3), 324-364.Tandfonline
2019Ball, L. J., & Christensen, B. T. (2019). Advancing an understanding of design cognition and design metacognition: Progress and prospects. Design Studies, 65, 35-59.Sciencedirect
2020Laukkonen, R. E., Kaveladze, B. T., Tangen, J. M., & Schooler, J. W. (2020). The dark side of Eureka: Artificially induced Aha moments make facts feel true. Cognition, 196, 104122.Sciencedirect
2017Jackson, S. A., Kleitman, S., Stankov, L. & Howie, P. (2017). Individual differences in decision making depend on cognitive abilities, monitoring and control. Journal of Behavioral Decision Making, 30(2), 209-223.Wiley
2016Jackson, S. A., Kleitman, S., Howie, P. and Stankov, L. (2016). Cognitive abilities, monitoring, and control explain individual differences in heuristics and biases. Frontiers-Psychology, 7. DOI=10.3389/fpsyg.2016.01559.Frontiers
2016Jackson, S. A., Kleitman, S., Stankov, L. & Howie, P. (2016). Decision pattern analysis as a general framework for studying individual differences in decision making. Journal of Behavioral Decision Making, 29(4), 392-408. Wiley
2018Jackson, S.A., Martin, G. D., Aidman, E., & Kleitman, S. (2018). Acute short-term sleep deprivation does not affect metacognitive monitoring captured by confidence ratings: A systematic literature review. Metacognition & Learning, 13(1), 39–56.Springer
2020Blanchard, M. D., Jackson, S. A., & Kleitman, S. (2020). Collective decision making reduces metacognitive control and increases error rates, particularly for overconfident individuals. Journal of Behavioral Decision Making, 33(3), 348-375.Wiley
2019Kleitman, S., Hui, J. S. W., & Jiang, Y. (2019). Confidence to spare: individual differences in cognitive and metacognitive arrogance and competence. Metacognition and Learning, 14(3), 479-508.Springer
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