Philip H. Winne

Feedback and Self-Regulated Learning: A Theoretical Synthesis

Self-regulated learning (SRL) is a pivot upon which students’ achievement turns. We explain how feedback is inherent in and a prime determiner of processes that constitute SRL, and review areas of research that elaborate contemporary models of how feedback functions in learning. Specifically, we begin by synthesizing a model of self-regulation based on contemporary educational and psychological literatures. Then we use that model as a structure for analyzing the cognitive processes involved in self-regulation, and for interpreting and integrating findings from disparate research traditions. We propose an elaborated model of SRL that can embrace these research findings and that spotlights the cognitive operation of monitoring as the hub of self-regulated cognitive engagement. The model is then used to reexamine (a) recent research on how feedback affects cognitive engagement with tasks and (b) the relation among forms of engagement and achievement. We conclude with a proposal that research on feedback and research on self-regulated learning should be tightly coupled, and that the facets of our model should be explicitly addressed in future research in both areas.

Chapter 16 – Measuring Self-Regulated Learning

Publisher Summary Research on self-regulated learning (SRL) and measurement protocols used in this chapter are relatively new and inherently intertwined enterprises. Each helps to bootstrap the other. One adopts the view that a measurement protocol is an intervention in an environment, disturbing it in a fashion that causes data to be generated. Using that data and logic of causal inference, he/she infers properties and qualities of a target of measurement. Thus, measurement involves understandings about a target, its environment, and causal relationships that connect the two. Under this view, measurement is akin to model building and model testing, and thus, all measures of SRL are reflections of a model of SRL. SRL has dual qualities as an aptitude and an event. It is situated within a broad range of environmental plus mental factors and potentials, and manifests itself in recursively applied forms of metacognitive monitoring and metacognitive control that change information over time as learners engage with a task.

Exploring students’ calibration of self reports about study tactics and achievement

When students self-regulate studying, they monitor achievement and study tactics. Proximal input to monitoring is perceptions that the student constructs based on experience. Productive self-regulation theoretically requires strong correspondence between (a) perceptions of achievement and actual achievement and (b) perceived use of study tactics and actual use of study tactics. That is, calibration should be high. Students studied using a software tool that traced study tactics they used. Subsequently their self-reports about study tactics and estimates of achievement were gathered, and a test was administered. Students were slightly positively biased (overconfident) about their achievement and moderately positively biased about (overestimated) their use of study tactics. An individual difference measure of calibration was very high for achievement but modest for study tactics. It is explained why calibration of self-reports about study tactics did not predict achievement, examine theoretical links between calibration and other prominent constructs, and discuss issues of self-regulated learning.

Improving Measurements of Self-Regulated Learning

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.

Self-regulating studying by objectives for learning: Students' reports compared to a model

Abstract Research often tests whether students achieve more or less by varying cues to guide studying. Usually, these hypotheses are tested in between-groups experiments that contrast the achievement of students presented cues, such as bold terms and figures elaborating text, to other students not experiencing the cue(s). We took a different tack. We presented students with four objectives that set four different tasks for studying a chapter. In the chapter, we embedded other cues that theoretically trigger seven specific study tactics. After studying, students self-reported their use of those seven study tactics. Within each task (objective), we compared students’ self-reported use of study tactics—their perceptions about how they studied—to a research-based model specifying optimal use of those seven study tactics. Compared to our theoretical model, students self-reported using tactics at considerably lower intensities and in approximately opposite patterns. Our study raises questions about how students study versus how they report they study. We suggest more experiments are needed that test models of how students perceive cues for studying and relation between such perceptions and actual self-regulated learning.

How Software Technologies Can Improve Research on Learning and Bolster School Reform

Realizing the promise of software technologies in education requires thinking differently about how software simultaneously can serve research and contribute to learning. This article examines 3 axioms underlying contemporary educational psychology: Learners construct knowledge, learners are agents, and data include lots of randomness. By drawing out corollaries of these axioms, this research uncovers significant challenges researchers face in using classical forms of experimental research to build a basis for school reform and for testing school reforms using randomized field trials. This article describes a software system, gStudy, that is designed to address these challenges by gathering finer grained data that better support theorizing about the processes of learning and self-regulated learning. This research illustrates how this can be realized and suggests 10 ways that using software like gStudy can help pull up research by its bootstraps and bolster searches for what works.

Minimizing the Black Box Problem to Enhance the Validity of Theories about Instructional Effects.

Prior research on learning from instruction has used a three-stage model of effects. The model posits that (1) an instructional stimulus cues the learner to use particular cognitive processes to operate on content, (2) these operations are executed, and (3) the result facilitates learning. While theories focus on all three stages, experiments have provided only indirect evidence about how well each is accomplished and rarely have controlled directly all three key sources of variance. An illustrative analysis of learning from instruction is presented, and a procedure is proposed that probabilistically increases control over the theoretically significant cognitive causes of instructional effects.

CoNoteS2: A Software Tool for Promoting Self-Regulation

Integrating state-of-the-art computer technologies with pedagogically sound practice provides interesting challenges and potentially significant opportunities to simultaneously promote and examine learning in context. This paper unfolds in 3 parts. We begin by introducing the reader to contemporary theories of self-regulation. We present a 4-phase model of self-regulating and a sparse literature on instructional design for SRL. Second, we build on this theory to describe features of CoNoteS2 (a prototype electronic notebook) that support self-regulation through tacit and explicit scaffolding. And finally, we describe the role of CoNoteS2 in researching about how students self-regulate their own learning. Our intent is to illustrate how contemporary learning theory can be used to drive instructional innovation and technological enhancement for the classroom.

Innovative ways for using gStudy to orchestrate and research social aspects of self-regulated learning

This paper explores the ways three different theoretical perspectives of the social aspects of self-regulated learning [Hadwin, A. F. (2000). Building a case for self-regulating as a socially constructed phenomenon. Unpublished doctoral dissertation, Simon Fraser University, Burnaby, BC, Canada; Hadwin, A. F., & Oshige, M. (2006). Self-regulation, co-regulation, and socially-shared regulation: Examining many faces of social in models of SRL. In A. F. Hadwin, & S. Jarvela (Chairs), Socially constructed self-regulated learning: Where social and self meet in strategic regulation of learning. Symposium conducted at the Annual Meeting of the American Educational Research Association, San Francisco, CA] have been operationalized in a computer supported learning environment called gStudy. In addition to contrasting social aspects of SRL and drawing connections with specific collaborative tools and structures, this paper explores the potential of gStudy to advance theory, research, and practice. Specifically it discusses how the utilization of differing collaborative models provides new avenues for systematically researching social aspects of SRL and their roles in collaboration.

Construct Interpretations of Three Self-Concept Inventories:

Three self-report measures of self-concept were administered in counterbalanced order to 488 sixth grade children as the basis for a multitrait-multimethod study of self-concept measurement. The subscales on these instruments were clustered into facets representing physical, social, and academic self-concept. The analyses indicate that all three facets demonstrate some degree of convergent validity, particularly physical self-concept, but discriminant validity is not established. Results also indicate that the response requirements of the instruments affect construct interpretations. Although developers of self-concept inventories strongly imply the existence of significantly different facets of self-concept by the separation and naming of subscales, there is little evidence for this implication.