The DOI matches its Crossref record; 44 of the 44 references it cites were found in a registry or an index.
Self-assessment in the process of self-regulated learning and its relationship with academic achievement
Abstract
Despite the theoretical argument and empirical evidence regarding the impact of self- assessment on academic achievement and self-regulated learning (SRL), the mechanism for this impact is understudied. The present study aimed to investigate the characteristics of self-assessment practices at different SRL phases and its relationship with academic achievement. Using a course assignment as the learning task, sixty-three students enrolled in a one-year master programme in a teacher education institute responded to an instrument assessing their self-assessment practices (including four self-assessment actions) at the SRL Preparatory, Performance and Appraisal phases of the task. Their final scores of the assignment were also collected. The results showed that self-assessment is a fundamental skill for SRL and occurs at each SRL phase with different patterns. Autoregressive relationships were found for all self-assessment actions between different SRL phases. Self-reflection at Performance phase was found to influence feedback seeking at Appraisal phase. Self-directed feedback seeking through monitoring at Performance phase was the strongest and positive predictor of academic achievement; and achievement had negative impact on all self-assessment actions at Appraisal phase. This study may assist educators and researchers to better understand the complexity of self-assessment in relation to learning process.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“It is widely reported in many reviews and empirical studies that self-assessment can benefit academic achievement.”
From Artificial Intelligence for Assessment and Feedback to Enhance Student Success in Higher Education (2022) · cites this paper as [46]
In the citing paper
“It can be achieved through the activities such as selfgrading and self-regulated learning [45,46].”
From Artificial Intelligence for Assessment and Feedback to Enhance Student Success in Higher Education (2022) · cites this paper as [46]
Citations
Cites
Hu, L., & Bentler, P. M. (1999) · Structural Equation Modeling A Multidisciplinary Journal · doi:10.1080/10705519909540118 · Cited by 108,788
Zimmerman, B. J. (2000) · Handbook of Self-Regulation · doi:10.1016/b978-012109890-2/50031-7 · Cited by 6,069
Principles and practice in reporting structural equation analyses.
McDonald, R. P., & Ho, M.-H. R. (2002) · Psychological Methods · doi:10.1037/1082-989x.7.1.64 · Cited by 4,734 · cited 7×
“Puustinen and Pulkkinen (2001) compared five major SRL models in a theoretical review. They concluded that, even if the terminology used varied, these models shared three common phases: (a) Preparatory, which consists of activities relevant to task analysis, goal setting and planning; (b) Performance, in which the act…”
BackgroundMethodInfluentialA Rating Formulation for Ordered Response Categories
Andrich, D. (1978) · Psychometrika · doi:10.1007/bf02293814 · Cited by 2,984
A Review of Self-regulated Learning: Six Models and Four Directions for Research
Panadero, E. (2017) · Frontiers in Psychology · doi:10.3389/fpsyg.2017.00422 · Cited by 2,915 · cited 2×
“In a more recent review of SRL models, Panadero (2017) echoed this classification.”
BackgroundMissing Data Techniques for Structural Equation Modeling.
Allison, P. D. (2003) · Journal of Abnormal Psychology · doi:10.1037/0021-843x.112.4.545 · Cited by 1,335
Bond, T. G. (2015) · Routledge eBooks · doi:10.4324/9781315814698 · Cited by 1,062
Electronic Journal of Research in Educational Psychology
(2018) · Electronic Journal of Research in Educational Psychology · doi:10.14204/ejrep · Cited by 944
Smith, J. M., & Alloy, L. B. (2008) · Clinical Psychology Review · doi:10.1016/j.cpr.2008.10.003 · Cited by 908
Effects of self-assessment on self-regulated learning and self-efficacy: Four meta-analyses
Panadero, E., Jonsson, A., & Botella, J. (2017) · Educational Research Review · doi:10.1016/j.edurev.2017.08.004 · Cited by 712
Research works printed but not linked: 8
- 10.2307/259209 · DOI
- Linacre J. M, 2006, A User’s Guide to WINSTEPS/MINISTEP: Rasch-Model Computer Programs
- 10.1037//1082-989X.7.1.64 · DOI · Paper page
- McMillan J. H., 2008, Educational Horizons, 87, 40
- Rasch G, 1960, Probabilistic Models for Some Intelligence and Achievement Test.
- Ross J. A, 2006, Practical Assessment, 11, 1
- Wu M. L., 2007, ACER ConQuest [Computer Program and Manual].
- Yan Z, 2016, Journal of Applied Measurement, 17, 1
Cited by
Sorted by citations
Artificial Intelligence for Assessment and Feedback to Enhance Student Success in Higher Education
Hooda, M., Rana, C., Dahiya, O., Rizwan, A., & Hossain, M. S. (2022) · Mathematical Problems in Engineering · doi:10.1155/2022/5215722 · Cited by 444
“It can be achieved through the activities such as selfgrading and self-regulated learning [45, 46].”
BackgroundThe power of internal feedback: Exploiting natural comparison processes
Nicol, D. (2021) · Assessment & Evaluation in Higher Education · doi:10.1080/02602938.2020.1823314 · Cited by 402
“More recently, researchers who posit internal feedback as inherent in self-regulation have taken the position that the main mechanism by which it is generated is ‘self-assessment’, although other terms are also used, for example, ‘evaluation’, ‘evaluative judgement’ and even ‘reflection’, sometimes interchangeably and…”
BackgroundSelf-assessment is about more than self: the enabling role of feedback literacy
Yan, Z., & Carless, D. R. (2021) · Assessment & Evaluation in Higher Education · doi:10.1080/02602938.2021.2001431 · Cited by 295
Self-citationYan, Z., Lao, H., Panadero, E., Fernández‐Castilla, B., Yang, L., & Yang, M. (2022) · Educational Research Review · doi:10.1016/j.edurev.2022.100484 · Cited by 182
Self-citationSharma, K., Nguyen, A., & Hong, Y. (2024) · British Journal of Educational Technology · doi:10.1111/bjet.13459 · Cited by 149
Metadata
- Authors
- Yan, Z.
- Affiliations
- Education University of Hong Kong (HK)
- Corresponding author
- Yan, Zi
- ORCID
- Yan, Zi
- Venue
- Assessment & Evaluation in Higher Education
- Publisher
- Informa UK Limited
- Published
- 2019-06-26
- Volume
- 45
- Issue
- 2
- Pages
- 224-238
- ISSN
- 0260-2938 (ISSN-L)
- 1469-297X
- OpenAlex
- W2955338425
- Cited by
- 217
- References
- 44
- Citations by year
- 2026: 22 · 2025: 38 · 2024: 39 · 2023: 49 · 2022: 39 · 2021: 23 · 2020: 6 · 2019: 1
- FWCI
- 46.54
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Assessment & Evaluation in Higher Education (publishedVersion)
- Topics
- Social Sciences › Education › Student Assessment and Feedback
- Social Sciences › Psychology › Developmental and Educational Psychology › Innovative Teaching and Learning Methods
- Social Sciences › Education › Evaluation of Teaching Practices
- Keywords
- self-assessment, student self-regulation, academic performance, self-reflection, feedback seeking, self-monitoring, pre-service teachers, course assignments
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