Exploring the Relationship between Calibration and Self-Regulated Learning
By Nancy J. Stone. 2000
206 citations recorded by the source corpus.
Subfields: Developmental and Educational Psychology, Education, Social Psychology
View Paper: https://www.semanticscholar.org/paper/38dd319014598fc7df51133cba64e8776b8f3ba6
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Developmental and Educational Psychology
- Roger Azevedo
- Jeffrey Alan Greene
- Ernesto Panadero
- B. Zimmerman
- John L. Nietfeld
- Anthony R. Artino Jr.
- Gregory Schraw
- Sanna Järvelä
In Education
- Roger Azevedo
- Jeffrey Alan Greene
- B. Zimmerman
- Ernesto Panadero
- John L. Nietfeld
- A. S. Labuhn
- Marcus Hasselhorn
- Li Cao
In Social Psychology
- Roger Azevedo
- Anthony R. Artino Jr.
- Jeffrey Alan Greene
- P. Pintrich
- B. Zimmerman
- Gregory Schraw
- A. S. Labuhn
- John L. Nietfeld
Citations in the corpus
- Academic self-efficacy: from educational theory to instructional practice (2012, background): “immediate feedback that encourages students to shift their focus from actual performance to performance monitoring and evaluation is thought to be particularly effective in improving self-efficacy calibration [17, 19].”
- Miscalibration of self-efficacy and academic performance: Self-efficacy ≠ self-fulfilling prophecy (2019, background): “Calibration indicates that accurate self-monitoring is occurring, which enables students to take the necessary actions to perform well (Bol & Hacker, 2012; Stone, 2000).”
- Enhancing students’ self-regulation and mathematics performance: the influence of feedback and self-evaluative standards (2010, background): “This metacognitive skill is closely related to a concept known as calibration or calibration accuracy (e.g., Nietfeld et al. 2006; Pieschl 2009 ;S chraw2009; Schraw et al. 1993; Stone 2000; for an in-depth analysis of the related concept of accuracy in metamemory research, see Hager and Hasselhorn”
- A Theoretical Review of Winne and Hadwin’s Model of Self-Regulated Learning: New Perspectives and Directions (2007, background): “These judgments can have an influence on both performance and metacognitive monitoring in general (for a thorough review of calibrations and SRL, see Stone, 2000).”
- Conceptions of Efficiency: Applications in Learning and Problem Solving (2010, background): “The difference between performance and self-reports of performance or effort have been studied in detail within the calibration of performance literature (Allwood, Jonsson, & Granhag, 2005; Burson, Larrick, & Klayman, 2006; Schraw, Potenza, & Nebelsick-Gullet, 1993; Stone, 2000).”
- The effects of feedback on achievement, interest and self-evaluation: the role of feedback’s perceived usefulness (2014, background): “Calibration expresses the degree to which a student’s judgement about his or her own capability or performance actually represents the student’s competence (Pieschl, 2009) and, thus, is related closely to the metacognitive concept of self-evaluation (Stone, 2000).”
- Metacognitive Monitoring Accuracy and Student Performance in the Postsecondary Classroom. (2005, background): “METACOGNITIVE MONITORING plays a central role in the development of self-regulated learning (Butler & Winne, 1995; Stone, 2000).”
- Investigating Self-Regulation and Motivation: Historical Background, Methodological Developments, and Future Prospects (2008, methodology): “Research in noncomputer contexts (Stone, 2000) has similarly revealed a positive relation between students’ use of SRL processes and their calibration of knowledge (i.”
- Successful Lecturing: Presenting Information in Ways That Engage Effective Processing (2002, background): “An additional benefit of retrieval practice is that students become explicitly aware of when they do not know the answers to questions and thereby may spend more time studying the information outside a lecture (see Stone, 2000, for a review of calibration and self-regulated learning).”