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Why is externally-facilitated regulated learning more effective than self-regulated learning with hypermedia?
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“Evidence from this study aligns with the existing literature on self-regulated learning and instructional scaffolding and underscores the potential of self-monitoring tools as effective aids for students in learning environments (Azevedo et al., 2008; Ga ˇ sevi ´ c et al., 2015, 2017).”
From Impact of AI assistance on student agency (2024) · cites this paper as Azevedo et al., 2008
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“Prior knowledge is a major predictor of learning performance (Azevedo et al. 2008; Greene and Azevedo 2007).”
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“In addition, studies have confirmed that metacognitive scaffolding strategies help learners gain better collaborative task outcomes (Pifarre & Cobos, 2010), and complete social metacognitive activities (Azevedo et al., 2008).”
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“There are various models for self-regulated learning (SRL), each placing emphasis in different aspects (e.g., [3, 8, 12, 37, 48, 53]).”
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“The higher levels of metacognitive monitoring are important, as according to Azevedo et al. (2008) they associated with an increase of feeling of knowing, judgment of learning, and monitoring of progress toward goals.”
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“Given the evidence that SRL can be taught to students, the teacher’s role in developing students’ SRL ability cannot be overemphasised (Azevedo et al. 2008; Cazan 2013).”
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“Teachers can play a key role in helping students become self-regulated learners (Azevedo et al., 2008; Hattie, 2011; Paris & Paris, 2001; Perry, 1998), both directly as mentioned earlier, or through the design of appropriate learning environments (Perry & Rahim, 2011; Veenman, 2017).”
A comprehensive reanalysis of the metacognitive self-regulation scale from the MSLQ
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“This requires co-regulation or, at least in the beginning, externally-facilitated regulation (Azevedo et al., 2008).”
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“Azevedo et al. (2008) investigated the role of self-regulation in learning with hypermedia, and how it might be facilitated.”
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“…of metacognitive strategies, it is still daunting and hard for them to develop and deploy the appropriate strategies in the online mode of language education (Azevedo et al., 2008), thus influencing their motivation and self-efficacy for online English learning achievement (Teng et al., 2021).”
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“In addition to log data, think-aloud as another approach to measure SRL in situ has been used in seminal work in SRL [7].”
MethodThe landscape of educational technology viewed from the ETR & D journal
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“Azevedo et al. (2008) compared self-regulated learners to self-regulated learners that were supported by a human regulating agent.”
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“Various techniques e.g., prompts (Bannert et al., 2009), scaffolding (Azevedo et al., 2008), and intelligent tutor systems (Azevedo et al., 2016) have been used previously to assist learners’ regulation in ALTs.”
Empirical assessment of e-learning on performance in principles of economics
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Utilizing Dynamic Bayes Nets to Improve Early Prediction Models of Self-regulated Learning
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“Unfortunately there is evidence that not all students are capable of guiding their own learning in this way [11] and may consequently experience limited success with systems that require these skills [5, 6, 12].”
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Supporting College Students' Ill-Structured Problem Solving in a Web-Based Learning Environment
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“In a comparable study of DT use (Azevedo et al., 2008), adolescent students learned science more effectively when supported by a human tutor.”
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“Moreover, they need an adaptive scaffolding as an external regulating agent that supports the students to deploy certain key processes and strategies and can be beneficial during web-based learning (Azevedo et al., 2008).”
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“All the theoretical models share the autonomous and self-directed nature of the self-regulated learning process, but they differ on the importance they attach to various elements (Azevedo et al., 2008).”
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Chen, P. P., Cleary, T. J., & Lui, A. M. (2014) · School Psychology Quarterly · doi:10.1037/spq0000098 · Cited by 13
Search+Chat: Integrating Search and GenAI to Support Users with Learning-oriented Search Tasks
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“Such reflections are critical metacognitive monitoring processes [2, 3, 14].”
InfluentialScaffolding self-regulated learning in student-generated questioning using mobile phones
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“From another standpoint, SGQ could be related to a learner’s monitoring activity by supporting learners’ control over the progress toward their learning goals and content evaluation (Azevedo & Cromley, 2004; Azevedo et al., 2008).”
Background
Metadata
- Authors
- Azevedo, R., Moos, D. C., Greene, J. A., Winters, F. I., & Cromley, J. G.
- Affiliations
- University of Memphis (US)
- Gustavus Adolphus College (US)
- University of North Carolina at Chapel Hill (US)
- University of Maryland, College Park (US)
- Temple University (US)
- Corresponding author
- Azevedo, Roger
- Venue
- Educational Technology Research and Development
- Published
- 2007-09-29
- Volume
- 56
- Issue
- 1
- Pages
- 45-72
- ISSN
- 1042-1629 (ISSN-L)
- 1556-6501
- OpenAlex
- W2093529413
- Semantic Scholar
- c30f1553e28353e3e04210696da6d59b16a685e9
- Cited by
- 380
- References
- 65
- Citations by year
- 2026: 7 · 2025: 22 · 2024: 19 · 2023: 19 · 2022: 20 · 2021: 22 · 2020: 20 · 2019: 15 · 2018: 22 · 2017: 27 · 2016: 20 · 2015: 15 · 2014: 27 · 2013: 24 · 2012: 21
- FWCI
- 27.45
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Educational Technology Research and Development (publishedVersion)
- Funders
- National Science Foundation
- Topics
- Social Sciences › Psychology › Developmental and Educational Psychology › Innovative Teaching and Learning Methods
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Visual and Cognitive Learning Processes
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Keywords
- student self-regulation, hypermedia learning, cardiovascular system, adolescents, declarative knowledge, mental models, learning strategies, adaptive help-seeking, prior knowledge activation, science learning
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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.
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