The DOI matches its Crossref record.
Cognition, Metacognition, and Epistemic Cognition
Abstract
A three-level model of cognitive processing to account for complex monitoring when individuals are faced with ill-structured problems, i.e., problems on which opposing or contradictory evidence and opinion exists, is proposed. At the first level, cognition, individuals compute, memorize, read, perceive, solve problems, etc. At the second, metacognitive level, individuals monitor their own progress when they are engaged in these first-order tasks. At the third level, epistemic cognition, individuals reflect on the limits of knowing, the certainty of knowing, and criteria of knowing. Epistemic assumptions influence how individuals understand the nature of problems and decide what kinds of strategies are appropriate for solving them. While cognitive and metacognitive processes appear to develop in childhood and are used throughout the life span, current research on adult reasoning suggests that epistemic cognitive monitoring develops in the late adolescent and adult years.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Hofer, B. K., & Pintrich, P. R. (1997) · Review of Educational Research · doi:10.3102/00346543067001088 · Cited by 3,181
The ICAP framework: Linking cognitive engagement to active learning outcomes
Chi, M. T. H., & Wylie, R. (2014) · Educational Psychologist · doi:10.1080/00461520.2014.965823 · Cited by 2,911
Toward a design theory of problem solving
Jonassen, D. H. (2000) · Educational Technology Research and Development · doi:10.1007/bf02300500 · Cited by 2,114
Instructional design models for well-structured and III-structured problem-solving learning outcomes
Jonassen, D. H. (1997) · Educational Technology Research and Development · doi:10.1007/bf02299613 · Cited by 1,608
Schraw, G., & Moshman, D. (1995) · Educational Psychology Review · doi:10.1007/bf02212307 · Cited by 1,443
Metacognition and affect: What can metacognitive experiences tell us about the learning process?
Efklides, A. (2006) · Educational Research Review · doi:10.1016/j.edurev.2005.11.001 · Cited by 724
Epistemological Understanding as a Metacognitive Process: Thinking Aloud During Online Searching
Hofer, B. K. (2004) · Educational Psychologist · doi:10.1207/s15326985ep3901_5 · Cited by 573
The Science of Wisdom in a Polarized World: Knowns and Unknowns
Grossmann, I., Weststrate, N. M., Ardelt, M., Brienza, J. P., Dong, M., Ferrari, M., Fournier, M. A., Hu, C. S., Nusbaum, H. C., & Vervaeke, J. (2020) · Psychological Inquiry · doi:10.1080/1047840x.2020.1750917 · Cited by 330
“Here, we will describe them as perspectival aspects of metacognition or PMC (Figure 3; also see Kitchner, 1983; Vervaeke & Ferraro, 2013, for a similar distinction between meta-cognition and epistemic cognition).”
MethodStephen, J., Fraser, E., & Marcia, J. E. (1992) · Journal of Adolescence · doi:10.1016/0140-1971(92)90031-y · Cited by 258
Wisdom, bias, and balance: Toward a process-sensitive measurement of wisdom-related cognition.
Brienza, J. P., Kung, F. Y. H., Santos, H. C., Bobocel, D. R., & Grossmann, I. (2018) · Journal of Personality and Social Psychology · doi:10.1037/pspp0000171 · Cited by 235
Järvelä, S., Järvenoja, H., Malmberg, J., Isohätälä, J., & Sobocinski, M. (2016) · Learning and Instruction · doi:10.1016/j.learninstruc.2016.01.005 · Cited by 220
Kirschner, F., Paas, F., & Kirschner, P. A. (2011) · Applied Cognitive Psychology · doi:10.1002/acp.1730 · Cited by 219
The Activity of Meaning Making: A Holistic Perspective on College Student Development
Baxter Magolda, M. B. (2009) · Journal of College Student Development · doi:10.1353/csd.0.0106 · Cited by 203
Barzilai, S., & Zohar, A. (2014) · Educational Psychologist · doi:10.1080/00461520.2013.863265 · Cited by 169
Sandoval, W. A., Greene, J. A., & Bråten, I. (2016) · Review of Research in Education · doi:10.3102/0091732x16669319 · Cited by 143
Epistemic metacognition in context: evaluating and learning online information
Mason, L., Boldrin, A., & Ariasi, N. (2010) · Metacognition and Learning · doi:10.1007/s11409-009-9048-2 · Cited by 139
Epistemological beliefs and epistemic strategies in self-regulated learning
Richter, T., & Schmid, S. (2010) · Metacognition and Learning · doi:10.1007/s11409-009-9038-4 · Cited by 120
King, P. M. (2009) · Journal of College Student Development · doi:10.1353/csd.0.0104 · Cited by 77
Eye tracking technology for examining cognitive processes in education: a systematic review
Liu, X., & Cui, Y. (2025) · Computers & Education · doi:10.1016/j.compedu.2025.105263 · Cited by 59
A Schema-Based Instructional Design Model for Self-Paced Learning Environments
Jung, E., Lim, R., & Kim, D. (2022) · Education Sciences · doi:10.3390/educsci12040271 · Cited by 46
Maclellan, E., & Soden, R. (2012) · Instructional Science · doi:10.1007/s11251-011-9183-4 · Cited by 19
Knight, J. K., Weaver, D. C., Peffer, M. E., & Hazlett, Z. S. (2022) · CBE—Life Sciences Education · doi:10.1187/cbe.21-12-0341 · Cited by 18
Metadata
- Authors
- Kitchner, K. S.
- Venue
- Human Development
- Publisher
- S. Karger AG
- Published
- 1983
- Volume
- 26
- Issue
- 4
- Pages
- 222-232
- ISSN
- 0018-716X (ISSN-L)
- 1423-0054
- OpenAlex
- W2034092570
- Cited by
- 831
- References
- 0
- FWCI
- 81.89
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
