The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
Improving Measurements of Self-Regulated Learning
Abstract
Articles in this special issue present recent advances in using state-of-the-art software systems that gather data with which to examine and measure features of learning and particularly self-regulated learning (SRL). Despite important advances, there remain challenges. I examine key features of SRL and how they are measured using common tools. I advance the case that traces of cognition and metacognition offer critical information about SRL that other state-of-the-art measurements cannot.
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Citations
Cites
Studying as Self-Regulated Learning
(1998) · Metacognition in Educational Theory and Practice · doi:10.4324/9781410602350-19 · Cited by 1,589
Self-citationThe theoretical status of latent variables.
Borsboom, D., Mellenbergh, G. J., & van Heerden, J. (2003) · Psychological Review · doi:10.1037/0033-295x.110.2.203 · Cited by 1,566
Handbook of Metacognition in Education
Hacker, D. J., Dunlosky, J., & Graesser, A. C. (2009) · doi:10.4324/9780203876428 · Cited by 1,509
Measuring Self-Regulated Learning
Winne, P. H., & Perry, N. E. (2000) · Handbook of Self-Regulation · doi:10.1016/b978-012109890-2/50045-7 · Cited by 1,383 · cited 16×
“CBLEs are splendid tools for gathering extensive data about many factors in the learner’s environment that may shape SRL.”
BackgroundInfluentialSelf-citationThe promise and perils of self-regulated study
Kornell, N., & Bjork, R. A. (2007) · Psychonomic Bulletin & Review · doi:10.3758/bf03194055 · Cited by 527
The dynamics of learning and allocation of study time to a region of proximal learning
Metcalfe, J., & Kornell, N. (2003) · Journal of Experimental Psychology: General · doi:10.1037/0096-3445.132.4.530 · Cited by 186
Minimizing the black box problem to enhance the validity of theories about instructional effects.
Winne, P. H. (1982) · Instructional Science · doi:10.1007/bf00120978 · Cited by 123
Self-citation
Cited by
Mega, C., Ronconi, L., & De Beni, R. (2014) · Journal of Educational Psychology · doi:10.1037/a0033546 · Cited by 1,007
Comparing online and blended learner's self-regulated learning strategies and academic performance
Broadbent, J. (2017) · The Internet and Higher Education · doi:10.1016/j.iheduc.2017.01.004 · Cited by 679
ChatGPT improves creative problem-solving performance in university students: An experimental study
Urban, M., Děchtěrenko, F., Lukavský, J., Hrabalová, V., Svacha, F., Brom, C., & Urban, K. (2024) · Computers & Education · doi:10.1016/j.compedu.2024.105031 · Cited by 396
Jansen, R. S., van Leeuwen, A., Janssen, J., Jak, S., & Kester, L. (2019) · Educational Research Review · doi:10.1016/j.edurev.2019.100292 · Cited by 310
GREENE, J. A., & AZEVEDO, R. (2010) · Educational Psychologist · doi:10.1080/00461520.2010.515935 · Cited by 267
Metadata
- Authors
- WINNE, P. H.
- Venue
- Educational Psychologist
- Publisher
- Informa UK Limited
- Published
- 2010-10-25
- Volume
- 45
- Issue
- 4
- Pages
- 267-276
- ISSN
- 0046-1520 (ISSN-L)
- 1532-6985
- OpenAlex
- W2129062063
- Cited by
- 405
- References
- 7
- FWCI
- 37.85
- Type
- journal article
- Language
- en
- Open access
- closed
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