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Journal ArticleDOI

The Power of Feedback

01 Mar 2007-Review of Educational Research (Sage Publications)-Vol. 77, Iss: 1, pp 81-112

AbstractFeedback is one of the most powerful influences on learning and achievement, but this impact can be either positive or negative. Its power is frequently mentioned in articles about learning and teaching, but surprisingly few recent studies have systematically investigated its meaning. This article provides a conceptual analysis of feedback and reviews the evidence related to its impact on learning and achievement. This evidence shows that although feedback is among the major influences, the type of feedback and the way it is given can be differentially effective. A model of feedback is then proposed that identifies the particular properties and circumstances that make it effective, and some typically thorny issues are discussed, including the timing of feedback and the effects of positive and negative feedback. Finally, this analysis is used to suggest ways in which feedback can be used to enhance its effectiveness in classrooms.

Topics: Peer feedback (64%), Dynamic decision-making (61%), Negative feedback (57%), Assessment for learning (51%) more

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Abstract: The topic of how students become self-regulated as learners has attracted researchers for decades. Initial attempts to measure self-regulated learning (SRL) using questionnaires and interviews were successful in demonstrating significant predictions of students’ academic outcomes. The present article describes the second wave of research, which has involved the development of online measures of self-regulatory processes and motivational feelings or beliefs regarding learning in authentic contexts. These innovative methods include computer traces, think-aloud protocols, diaries of studying, direct observation, and microanalyses. Although still in the formative stage of development, these online measures are providing valuable new information regarding the causal impact of SRL processes as well as raising new questions for future study.

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Abstract: Whilst many definitions of formative assessment have been offered, there is no clear rationale to define and delimit it within broader theories of pedagogy. This paper aims to offer such a rationale, within a framework which can also unify the diverse set of practices which have been described as formative. The analysis is used to relate formative assessment both to other pedagogic initiatives, notably cognitive acceleration and dynamic assessment, and to some of the existing literature on models of self-regulated learning and on classroom discourse. This framework should indicate potentially fruitful lines for further enquiry, whilst at the same time opening up new ways of helping teachers to implement formative practices more effectively.

1,489 citations

15 May 2011
Abstract: Contents Historical, Contemporary, and Future Perspectives on Self-Regulated Learning and Performance Dale H. Schunk and Jeffrey A. Greene Section I. Basic Domains of Self-Regulation of Learning and Performance Social Cognitive Theoretical Perspective of Self-Regulation Ellen L. Usher and Dale H. Schunk Cognition and Metacognition Within Self-Regulated Learning Philip H. Winne Developmental Trajectories of Skills and Abilities Relevant for Self-Regulation of Learning and Performance Rick H. Hoyle and Amy L. Dent Motivation and Affect in Self-Regulated Learning: Does Metacognition Play a Role? Anastasia Efklides, Bennett L. Schwartz, and Victoria Brown Self-Regulation, Co-Regulation and Shared Regulation in Collaborative Learning Environments Allyson Hadwin, Sanna Jarvela, and Mariel Miller Section II. Self-Regulation of Learning and Performance in Context Metacognitive Pedagogies in Mathematics Classrooms: From Kindergarten to College and Beyond Zemira R. Mevarech, Lieven Verschaffel, and Erik De Corte Self-Regulated Learning in Reading Keith W. Thiede and Anique B. H. de Bruin Self-Regulation and Writing Steve Graham, Karen R. Harris, Charles MacArthur, and Tanya Santangelo The Self-Regulation of Learning and Conceptual Change in Science: Research, Theory, and Educational Applications Gale M. Sinatra and Gita Taasoobshirazi Using Technology-Rich Environments to Foster Self-Regulated Learning in the Social Studies Eric G. Poitras and Susanne P. Lajoie Self-Regulated Learning in Music Practice and Performance Gary E. McPherson, Peter Miksza, and Paul Evans Self-Regulation in Athletes: A Social Cognitive Perspective Anastasia Kitsantas, Maria Kavussanu, Deborah B. Corbatto, and Pepijn K. C. van de Pol Self-Regulation: An Integral Part of Standards-Based Education Marie C. White and Maria K. DiBenedetto Teachers as Agents in Promoting Students' SRL and Performance: Applications for Teachers' Dual-Role Training Program Bracha Kramarski Section III. Technology and Self-Regulation of Learning and Performance Emerging Classroom Technology: Using Self-Regulation Principles as a Guide for Effective Implementation Daniel C. Moos Understanding and Reasoning About Real-Time Cognitive, Affective, and Metacognitive Processes to Foster Self-Regulation With Advanced Learning Technologies Roger Azevedo, Michelle Taub, and Nicholas V. Mudrick The Role of Self-Regulated Learning in Digital Games John L. Nietfeld Self-Regulation of Learning and Performance in Computer-Supported Collaborative Learning Environments Peter Reimann and Maria Bannert Section IV. Methodology and Assessment of Self-Regulation of Learning and Performance Validity and the Use of Self-Report Questionnaires to Assess Self-Regulated Learning Christopher A. Wolters and Sungjun Won Capturing and Modeling Self-Regulated Learning Using Think-Aloud Protocols Jeffrey A. Greene, Victor M. Deekens, Dana Z. Copeland, and Seung Yu Assessing Self-Regulated Learning Using Microanalytic Methods Timothy J. Cleary and Gregory L. Callan Advancing Research and Practice About Self-Regulated Learning: The Promise of In-Depth Case Study Methodologies Deborah L. Butler and Sylvie C. Cartier Examining the Cyclical, Loosely Sequenced, and Contingent Features of Self-Regulated Learning: Trace Data and Their Analysis Matthew L. Bernacki Data Mining Methods for Assessing Self-Regulated Learning Gautam Biswas, Ryan S. Baker, and Luc Paquette Section V. Individual and Group Differences in Self-Regulation of Learning and Performance 26. Calibration of Performance and Academic Delay of Gratification: Individual and Group Differences in Self-Regulation of Learning Peggy P. Chen and Hefer Bembenutty 27. Academic Help Seeking as a Self-Regulated Learning Strategy: Current Issues, Future Directions Stuart A. Karabenick and Eleftheria N. Gonida 28. The Three Faces of Epistemic Thinking in Self-Regulated Learning Krista R. Muis and Cara Singh 29. Advances in Understanding Young Children's Self-Regulation of Learning Nancy E. Perry, Lynda R. Hutchinson, Nikki Yee, and Elina Maatta 30. Self-Regulation: Implications for Individuals With Special Needs Linda H. Mason and Robert Reid 31. Culture and Self-Regulation in Educational Contexts Dennis M. McInerney and Ronnel B. King

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Journal ArticleDOI
TL;DR: Results suggest games show higher learning gains than simulations and virtual worlds, and for simulation studies, elaborate explanation type feedback is more suitable for declarative tasks whereas knowledge of correct response is more appropriate for procedural tasks.
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Journal ArticleDOI
Abstract: Giving students detailed feedback about the strengths and weaknesses of their work, with suggestions for improvement, is becoming common practice in higher education. However, for many students, feedback seems to have little or no impact, despite the considerable time and effort put into its production. With a view to increasing its effectiveness, extensive theoretical and empirical research has been carried out into its structure, timing and other parameters. For students to be able to apply feedback, they need to understand the meaning of the feedback statements. They also need to identify, with near certainty, the particular aspects of their work that need attention. For these to occur, students must possess critical background knowledge. This article sets out the nature of that knowledge and how students can acquire it. They must appropriate for themselves three fundamental concepts – task compliance, quality and criteria – and also develop a cache of relevant tacit knowledge.

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01 Aug 1975
TL;DR: This chapter discusses the development of Causality Orientations Theory, a theory of personality Influences on Motivation, and its application in information-Processing Theories.
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Abstract: 1. Models of Human Nature and Casualty. 2. Observational Learning. 3. Enactive Learning. 4. Social Diffusion and Innovation. 5. Predictive Knowledge and Forethought. 6. Incentive Motivators. 7. Vicarious Motivators. 8. Self-Regulatory Mechanisms. 9. Self-Efficacy. 10. Cognitive Regulators. References. Index.

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