The Trajectory of Scholarship About Self-Regulated Learning

by Philip H. Winne - 2017

The trajectory of scholarship about self-regulated learning (SRL) originates in mid-19th-century writings about learners’ sense of responsibility in self education. Although Descartes’s 17th-century writings implied mental activities consistent with metacognition, a central feature of SRL, these were inarticulate until Flavell and colleagues’ studies circa 1970. Since then, research on metacognition and its role in SRL has approximately doubled every decade. Foundations for modeling SRL include Skinner’s behaviorism, which acknowledged learners’ choices about reinforcers for behavior, and Bandura’s social learning theory, with its construct of agency. Research in the 1980s gathered data about SRL mainly using interviews, self-report questionnaires, and think-aloud protocols. These methods were quickly supplemented by observations of behavior and traces of learning activities tightly coupled to features of SRL. Today, SRL research is prominent across a broad spectrum of educational topics. Its importance will grow with trends toward lifelong learning and self-directed inquiries that survey vast information on the Internet, where students control what and how they will learn. Implications for future research include reconceptualizing “error variance” as arising partially due to SRL and capitalizing on software technologies that massively increase access to data about how and to what effects learners self-regulate learning.

This chapter sketches an intellectual and empirical trajectory of the construct of self-regulated learning (SRL) and forecasts a path for its near-term evolution within learning science and as applied in education. After presenting a varied but brief perspective about work on SRL and a terse summary of the state-of-the-field as of today, grounded speculations are offered about what may occupy studies of SRL in the near future. Attention is given to how theorizing about SRL and its associated research methods may shape future educational practices.


By various labels, “education for the 21st century” has acquired an urgency unlike any earlier era. When learners’ curiosity is sparked or they are confronted with an issue, they can roam global information resources that span topics far more extensive and points of view greatly more varied than any available in a local bricks-and-mortar library. The breadth and depth of this information and the complexities it presents often exceed what any particular teacher knows and, perhaps, what a school’s staff knows.

In this context, a new line of scholarly inquiry has been born. It strives to describe, understand, and promote better “information problem solving”—how people frame their needs for information, how they locate and sort information they find, and how they analyze and assemble nuggets of information to learn, to persuade, and to prosper. Students working in this way inherently stretch their capabilities for learning. The tactics and strategies they have used to learn previously are challenged. Consequently, as they wrestle with an abundance of information, they also must adapt how they learn. They must productively self-regulate learning.

You might thus imagine that scholarly address of self-regulated learning (SRL) is a relatively recent topic of inquiry. That musing is a misconception. Today’s energetic programs of research investigating SRL and constructs closely related to it are rooted in history.

In his book about self-education published in 1847, William Hosmer sowed a seed for thinking and research about SRL in elaborating one of the mental characteristics he ascribed to a self educated person, firmness of purpose:

It is inevitable that the regulation of every man’s plan must greatly depend on the course of events . . . in accommodating the plans of conduct to the train of events, the difference between two men may be no less than that, in the one instance the man is subservient to the events, and in the other, the events are made subservient to the man. (p. 209)

Forty-four years later, Charles Carroll Everett (1891) opined in his chapter titled “Self-education as a duty,”

But, in fact, all men who amount to anything are in a sense self-made men. The best teachers in the world cannot make a youth amount to anything, unless [the youth] takes the matter into his own hands, and works with them, as well as in ways that lie outside their teaching. . . . Treat yourself as if you were somebody else that you had charge of, and see what a good training-master you can be. (pp. 64, 66)

Hosmer and Everett were concerned with a stance where one took responsibility to seek betterment through education. Their views foreshadow today’s notions of SRL. In parallel, theorizing and empirical research into processes directly responsible for improving oneself through education—that is, learning—were rapidly expanding enterprises in latter half of the 19th century and the early 20th century. But a keystone to conceptualizing and then researching SRL, the construct of metacognition, was submerged and subtle, and eluded direct address for another half-century.

As will be examined later, metacognition is a keystone in the arc of SRL as a process. In brief, metacognition is mentally inspecting cognition and its attributes—how one thinks and with what information one thinks—and mentally charting and then following a path of action toward achieving a goal. The prefix meta originates in Greek, referring to something beyond, across, or after the focal concept per se. That metacognition was submerged is not surprising. For example, the developmental psychologist G. Stanley Hall investigated children’s ignorance about a quite wide array of topics upon entering public schools in Boston (Hall, 1893). Topics such as beehives, the source of milk, and islands were on his list. Yet, even the very process responsible for becoming educated, that is, learning, was not.

Over the next half-century, it was almost in passing that research observed learners and gave considerations to their cognition. For example, Tinker (1939) explored readers’ comprehension when texts they read varied in difficulty. He noted readers adjusted their rate of reading in proportion to difficulty. In modern terms, readers in his study engaged in metacognitive monitoring of their comprehension, and, when comprehension faltered relative to their standards, the readers selected a means—pace—and adjusted how they read. As Hosmer phrased it, they changed reading in response to “the course of events.” Had Tinker explored how his participants treated themselves, in his words, “as if you were somebody else that you had charge of, and see what a good training-master you can be” to find the most productive match of reading pace to text difficulty, his study might have been the first empirical study of SRL.


On perceiving that he was able to engage in metacognition, Descartes (1637/1999) recognized his existence and famously declared, “I doubt, therefore I think; therefore I am.” Nearly three centuries later, although he did not use the term metacognition, John Dewey (1910) characterized reflective thought as “purposeful. It goes in steps with each being utilized in the next” (p. 5) to “transform a situation in which there is experienced obscurity, doubt, conflict . . . into a situation that is clear, coherent, settled, harmonious” (pp. 100–101). But it was not until the last half of the 1970s that research on metacognition burst forth, setting a stage for the emergence of SRL as a focus in research.

In 1970, Flavell, Friedrichs, and Hoyt explored young children’s strategic use of plans for memorizing information and what the children described about their strategies. Older children in Grade 4 were more strategic and could better describe their strategies than younger children in nursery school, in kindergarten and in Grade 2. The abstract preceding their publication observed that a learner’s “knowledge and awareness of his own memory system is a particularly important and timely research problem” (p. 324). In the second half of the 1970s, seminal reviews by Flavell and colleagues (see Flavell, 1970; Flavell & Wellman, 1977) and Brown (1978) synthesized studies investigating children’s development of metamemory, that is, what the children knew about memory and how they attempted to manage factors they perceived to affect memory. Learning as a process and qualities of learning processes might then have been added to Hall’s (1893) list of what children knew about upon entering school.

Research on metamemory and metacognition accelerated in the 1980s. Searching in that decade for the terms metacognition or metamemory in PsycINFO yields 494 publications about these topics. Domains in which meta-processes were explored covered a broad span, including reading, impulsivity, motivation, lifespan development, academic as compared with everyday life settings, and mental retardation. Among these basic investigations emerged work on designs for instructional activities and teaching to elicit and sharpen metacognition. In the 1990s, metacognition research blossomed to 1,651 publications in PsycINFO, then to 2,739 publications in the following decade, and almost that same number (2,428) in just the first half of the present decade. Scope markedly widened and deepened.

Why is metacognition a key to SRL? The case was compellingly presented by Nelson and Narens in their 1990 chapter, “Metamemory: A Theoretical Framework and New Findings.” They synthesized principles apparent in the literature but not yet articulated:

Principle 1. The cognitive processes are split into two or more specific interrelated levels . . . the meta-level and the object-level.
Principle 2. The meta-level contains a dynamic model (e.g., a mental simulation) of the object-level.
Principle 3. There are two dominance relations, called “control” and “monitoring,” which are defined in terms of the direction of the flow of information between the meta-level and the object-level. (pp. 126–127)

These principles are the essence of self-regulation of any process, including learning processes. The object level is a description of a learning process. This description addresses the elements or steps involved in learning. At the meta-level is an extensive array of qualities that describe a learning process. A brief list includes: the effort required to carry out the process, the probability the process is estimated to be effective, reasons why the learner believes the process will be effective or may falter, awareness of influences on executing the process present in the external environment (e.g., time limits, access to information resources) and the learner’s internal mental environment (e.g., intrinsic and extrinsic interest in information being processed), and, of course, the perceived effectiveness of the learning process.

Merely reflecting on learning processes—monitoring the profile of multiple qualities a process has relative to an ideal profile of standards or even a profile that reflects only a satisficing result—is the beginning of an SRL event. Complete SRL entails more. Having monitored a learning process and judged it against standards, the learner is afforded a choice— persist, adapt, or replace the learning process. Exercising that choice is metacognitive control. It can alter the level, kind, and even the set of qualities the learner considers to matter.

In short, metacognitive monitoring creates a context for metacognitive control; metacognitive control sets the cognitive system along a new path that, in turn, invites further metacognitive monitoring for changes in qualities of the learning process and results of those changes. Metacognition in the form of these serial and unfolding links between metacognitive monitoring and metacognitive control is the “hub” of dynamic SRL (Winne, 2001).


In 1948, B. F. Skinner published Walden Two, a work of fiction describing a utopian society in which learning was shaped by positive rather than negative reinforcement, advancement through learning was grounded in readiness rather than the passage of time (age), and teaching was grounded in empiricism beyond rational design. His message for education was that others—teachers and school staff—could promote learners’ knowledge and well-being by focusing on the function of learners’ behaviors. Although the phrasing I use here plays a bit loose with Skinner’s theory, a question of interest when learners behaved as they did while learning was, “What’s in it for the learner?” Evident in this perspective is that learners choose how they behave. They have goals.

Another significantly influential theory began to emerge nearly a decade and a half later in work initiated by Albert Bandura. Building on an insightful mix of theory and empirical studies (see Zimmerman & Schunk, 2003), Bandura and Kupers (1964) showed that children who observed models with high standards for success would subsequently adopt those same high standards. Shortly following, Bandura and Perloff (1967) showed that self-reward could sustain children’s performance better than external reward. These seminal studies invite a conceptualization that self-regulating learners scan their environment for standards to use in metacognitive monitoring, incorporate and perhaps adapt those standards, and then monitor their behavior as prelude to future behavior.

Aggregating across Bandura’s and several other lines of research, Thomas (1980) expressly introduced the concept of learners’ agency, noting “instructional strategies designed to enhance a sense of agency tend also to enhance academically engaged time, achievement, and achievement related behavior” (p. 216). Thomas bridged research on learning strategies to both Bandura’s concept of self-efficacy and the construct of agency in a conjecture explaining the production deficiency, a case where a learner well trained and competent in carrying out a learning strategy can do so when instructed but misses opportunities to apply the strategy when explicit prompting is absent. Thomas’s bridge was “the spontaneous use of learning strategies is a matter of disposition: the disposition to perceive a learning task as controllable” (pp. 235–236). Corno (1986) added a critical ingredient to Thomas’s view, learners’ capability to exercise volition. Volition is learners’ commitment to, and capabilities they need to persist at, tasks, both challenging and tedious, in the face of distractions and setbacks on their path to achievements.

Zimmerman synthesized these works in his lead article for a special issue of Contemporary Educational Psychology, “Becoming a self-regulated learner: Which are the key subprocesses?” (1986). Christening SRL as “an important new approach to the study of student academic achievement,” Zimmerman observed this new view of learning

focuses attention on how students personally activate, alter, and sustain their learning practices in specific contexts [where] even high-“ability” students often do not achieve optimally because of their failure to use or control contextually specific cognitive, affective, and motoric learning processes. Furthermore, self-regulation theorists assume that no environment ensures learning. Even “advantaged” settings require [learners to exercise] varying amounts of selectivity and structuring . . . to learn. (p. 307)


Research on SRL has the interesting feature that researchers who study it and learners who engage in SRL have approximately the same goal—to investigate adaptations of learning processes that can confer benefits. Both researchers and self-regulating learners share a need for data that can helpfully inform those investigations.

In the 1980s, researchers developed two main approaches to reveal how students engaged in SRL: interviews and self-report questionnaires. In an early and highly cited study, Zimmerman and Pons (1986) assembled a structured interview schedule, the Self-Regulated Learning Interview Schedule (SRLIS), to elicit high school students’ reports about their uses of tactics1 when they were engaged with learning across six contexts: “in classroom situations, at home, when completing writing assignments outside class, when completing mathematics assignments outside class, when preparing for and taking tests, and when poorly motivated” (p. 617). The students were asked, for example, “Teachers often assign their class the task of writing a short paper outside class on a topic such a one's family history. They frequently use one’s scores as a major part of one’s grade. In such cases, do you have any particular methods to help you plan and write the paper?” (Table II, p. 619). Their descriptions were coded into one or more of 15 categories of tactics, one of which was “other.” Offshoots of this interview protocol have appeared widely in the literature.

In this same time period, self-report surveys were developed. Perhaps the most widely cited is a result of more than a decade’s synthesis of work (see Garcia Duncan & McKeachie, 2005), the Motivated Strategies for Learning Questionnaire (MSLQ; Pintrich, Smith, Garcia, & McKeachie, 1991). In the subscale for learning “strategies,” for example, learners were invited to respond on a 7-point scale anchored by not at all true of me to very true of me to items such as “When studying for this course, I often try to explain the material to a classmate or friend” and “When reading for this course, I make up questions to help focus my reading.”

A variant of self-reports, the think-aloud protocol, also was used in this period’s research on SRL. Within this technique, learners are encouraged at the beginning of work on a task to verbalize their thoughts about how they work as they work. An advantage of the think-aloud protocol is that the researcher does not prime the learner to consider tactics that, without a researcher’s prompt, the learner might never have considered. Disadvantages, however, are that the learner forgets to talk while working; consequently, the representativeness of the sample of utterances revealed as the learner thinks aloud is indeterminate. Also, like open-ended responses to probes in an interview, the learner’s descriptions may be ambiguous because learners lack precise terminology that is introduced and honed through successive work in learning science.

Much more important than the issue of whether to interpret learners' responses as reflections on strategies or tactics is the capacity of such methodologies to reflect SRL. As research using data collected through interviews and self-report surveys began to amass, colleagues and I (e.g., Winne, 2010a; Winne, Jamieson-Noel, & Muis, 2002; Winne & Perry, 2000; Winne, Zhou, & Egan, 2011) posed questions. Central among these were concerns about potential distortions of actual SRL behavior in self-reports due to the framework for the response (e.g., usually vs. this class vs. this study session) and inherent imperfections of human memory (e.g., forgetting, leveling, availability, construction).

Another methodology used in SRL research in the late 1990s and later was observation of learners’ behavior. In the running record approach used in Perry’s research program (Perry, 1998; Perry, VandeKamp, Mercer, & Nordby, 2002), an observation schedule included three successively completed sections: demographic data to identify the date, classroom, and activity; a running record of events that encapsulated events or, as possible, recorded verbatim transcripts about “what was going on”; and a set of categorical descriptions of SRL to be checked off that were derived from others’ research. A notable feature of this observational methodology is its “mix of analytic and emergent categories” (Perry et al., 2002, p. 8). This recognizes that, as agents, learners (and their teachers) may well manifest SRL in forms that lie at the edges of and beyond static terms and lists that researchers devise.

Yet another approach arising at about this time for gathering data about SRL is traces. A trace is an observable record of an event that strongly supports an inference about underlying constructs that can account for the event (Winne, 1982). For example, if a learner highlights when studying a text, the mark generated in that event traces an instance of metacognitive monitoring—the content highlighted was judged to be of some importance to the learner. The highlighting event also traces metacognitive control. The learner chose to apply a permanent mark to the text as opposed to, for example, making a note in a notebook. Presumably, the highlight better serves a plan the learner has, for example, to minimize effort (writing notes takes more effort) while ensuring ease of reviewing, by distinct visual markings, what was judged to be important content. Standards the learner used in metacognitive monitoring could be explicitly revealed if the highlight was supplemented with a brief, low effort marginal notation, for example, “!”. The ! traces the learner perceived the content to be significant, as opposed to, for example, vague or confusing (a mark of “?”) or confirming a belief or hypothesis (e.g., “”).

An important concern about all forms of data is what they represent about SRL. Do data lead to characterizing SRL as an aptitude that predicts behavior (to some extent in some context) or as a serial cascade of events (Winne et al., 2011) that are behavior in a particular context?

Because self-report surveys and interview responses are a learner’s reflection on a relatively unknown aggregate past activities, and because these responses commonly generalize over specific instances of metacognition, it is an open question whether they are strong predictors of SRL “in action.” (This is a different question than whether self-report and interview data predict achievement.) Think-aloud data characterize events “in some of the moments” of learning but are gathered in “free form” where learners speak in their own terms. Interpreting data can be challenging, and the “listener” can never be assured the learner’s sample of utterances is complete or even representative.

In contrast, ambient trace data may offer a nearly complete, unfiltered, and straightforward sample of when the learner metacognitively monitors information and judges it appropriate to act by exercising metacognitive control. For example, software can gather traces of highlighting in the course of everyday studying activities (e.g., see Winne, 2013b, 2016). Gathering ambient trace data neither primes the learner with a leading prompt nor disengages the learner from studying to respond to interview or survey prompts. Traces that match a learner’s already facile study tactics do not intrude on studying by talking aloud. A challenge facing those who use trace data is designing the trace so valid interpretations can be made about how a trace datum reflects features of SRL.


Scholarship about self-regulated learning has grown to occupy significant territory in the fields of education and psychology. Over the past decade, approximately 125 items were published each year that have some connection to SRL. Their scope is broad, ranging over cross-cultural studies, development, education in a plethora of subject areas, learning environments, life-long learning, methodological matters, metacognition, choices learners make about when and how to review, motivation, and special populations. Applied researchers and educators have profitably mined the field to develop a range of frameworks and teaching programs to encourage and support SRL and enhance its productive value (e.g., see Butler, Schnellert, & Perry, 2016). In these venues, it has been well acknowledged that, although self-regulation is ubiquitous (Winne, 1995b), it is complex (Winne, 1995a), context sensitive, and very challenging for learners to accomplish with productive outcomes (Winne, 2010b).

Notwithstanding, it is now clear that interventions carefully designed to promote the constituent elements of SRL—metacognition coupled to skills for cognitively operating on information—have benefit. Donker, de Boer, Kostons, Dignath van Ewijk, and van der Werf’s (2014) meta-analysis of 95 studies providing 180 effect sizes found “substantial effects in the domains of writing (Hedges’ g = 1.25), science (.73), mathematics (.66) and comprehensive reading (.36)” (p. 1). This spread of findings documents ground gained and will spur further research that melds SRL per se with other key variables such as motivation, transfer, and goal setting.


Conceptual foundations for SRL are extensive, multifaceted, and deep. Hosmer’s conception of a self-educated person noted the need to be attentive to context and to plan. Everett foreshadowed agency as inherent with nuance the person needed to exercise agency to make progress on a path toward self-improvement. Adding the critical ingredient of metacognition—cognition about processes and states of cognition—set a stage for explicit considerations of learning as a key process in becoming educated and governing one’s education.

The rapid growth of research on metacognition and the wide scope of this work ranging across otherwise disparate domains, such as comprehension of text, impulse control, and motivation, widened the foundation on which to build models of SRL in their own right. Perhaps unexpectedly, Skinner’s operant psychology provoked further psychological theorizing about goals and how learners form them; and, having formed goals, why it matters that learners conceptualize a sense of Bandura’s construct of self-efficacy, that is, agency for a particular future task in a specific setting.

Thomas made perhaps the first strong extension of this tradition to situations in which an other, a teacher or the author of a curriculum, created a context that was planned to support learners’ SRL. In doing so, he noted that learners well prepared to exercise SRL might falter for reasons of motivation. Following on his heels, Zimmerman explicated a full model of SRL, and Corno added a key ingredient of the learner’s capacity to apply self-control to avoid obstacles and work through impediments. These significant psychological constructions appearing in the late 20th century fleshed out in more discerning and sophisticated forms the cornerstones for SRL seeded in writings of approximately 150 years ago.

What implications arise for teachers, teaching, and educational policy from this trajectory of the conceptualization of SRL? One is that students should be credited with agency. To exercise agency productively, students need options they can apply as tools for learning—study tactics and learning strategies. The literature on tactics and strategies is mixed. Although individual studies have reported benefits (e.g., Glaser & Brunstein, 2007), larger sets of studies have been less sanguine (Hadwin & Winne, 2007; Winne, 2013a). I conjecture what needs greater attention in the classroom and in research are key motivational facets of SRL, efficacy, and volition. These thrive when students’ environment for learning supplies incentives and leeway to experiment with tactics and strategies in a context of encouragement to set high standards for achievement. This reminds of Skinner’s notion to advance learners by readiness rather than proxies for it, such as age. As well, students need to be allowed responsibility for developing SRL. Paraphrasing Hosmer, students need opportunity to shape teaching to their needs, perhaps more so than teachers shaping learning environments for students.

Turning to the trajectory of empirical means for exploring SRL, early work used tools—interview schedules and self-report surveys—for gathering data about SRL. These data reflect students’ views and are apt because, ipso facto, a student’s view is the basis for the student’s metacognition. But data gathered in these ways may overly lead students. Although these methods also highlight that SRL is contextual, the scope of context was broad or too diffuse (writing assignments, “this course”). To compensate, think-aloud protocols focused on relatively minute segments of work carried out during a particular task but at cost to assurances that what students describe is a thorough and accurate representation of SRL and attendant motivational states. Observational schedules resituated data in specific tasks but removed the student as spokesperson about what was happening.

Many of these potential compromises can be offset by gathering traces (Winne, 1982), accretion data (Webb, Campbell, Schwartz, & Sechrest, 1966) that bind the information on which a student operates to a theory of cognitive operations engaged in the milieu of the student’s motivation. Traces are challenging to gather and process, but this may be easier to overcome as technology becomes more and more a part of schooling (Winne, 2006).

What implications arise from this trajectory of methodological approaches? First, teachers who teach problem solving have nearly universally been observed to ask, “Can you show me your work?” The same applies to SRL, where the “work” is represented as conditions that spur metacognitive monitoring, standards used in metacognitive monitoring, and students’ choices for learning processes in the context of a larger set of available processes. A catch phrase for teachers goes beyond “Show me. . .” to a blend of the structured interview and think-aloud protocol: “Think with me.”

Data generated in “think with me” sessions will be spotty in two senses. Teachers don’t have time or resources to think (a) with every student (b) in every learning episode. Although not a complete solution to this dilemma, again, technology may help significantly (Winne, 2013b, 2016). Opportunities to leverage learning technologies to gather big data (Roll & Winne, 2015) in ambient fashion, while students do what they do, should be exploited.

The future trajectory for research may have a steep upward slope. If students are afforded more opportunities to experiment with learning as a subject, and if big data about learning as SRL can be reaped, I surmise several significant effects (see Winne, 2017). First, a great proportion of what has heretofore necessarily been relegated to “error variance” or “random perturbation” in the experimental literature of SRL will, with massively increased and more frequent sampling of data, be amenable to modeling per se. Worries about generalizing from pseudo-random samples of minuscule size relative to the “population” will be greatly ameliorated. As a consequence, second, many more kinds of study tactics and learning strategies will be discovered “in the wild” than have been studied in difficult-to-carry-out controlled laboratory and field experiments. Because theory feeds on data, third, theory will very likely accelerate and sharpen in a technologically supported environment. And important, fourth, the lag between theoretical conjecture, experimentation, and distribution of findings will shrink from years to perhaps days.

These forecasts about the trajectory of future work on SRL grow from long-standing and deep-seated thinking and wide-ranging investigations about what is involved in becoming educated. I forecast this trajectory points toward a nexus in which the student reemerges as the central figure—the self—who investigates and is empowered to research what works. What may become the field’s most alluring challenge is accepting that students should teach us what works. I ground this view on the fact that more than a few learners are highly productive self-regulating learners. By documenting and sharing those learners’ contextualized practices, I believe the field can learn what works in a way that avoids the presumption of randomized controlled trials that individual differences should be viewed as error when estimating effects (Winne, 2006, 2017).


1. Zimmerman and Pons (1986), as well as hosts of other researchers in the field, use the term strategies to describe SRL-related activities such as self evaluating, goal setting planning, and rehearsing memorizing. I label basic IF-THEN structures (e.g., IF work is completed, THEN check it for completeness and accuracy) as tactics. I reserve the term strategy to cases where (a) tactics are arranged to offer branch points where the learner can choose, grounded in metacognitive monitoring of the current state of work on a task, among two or more following tactics, and (b) the learner exercises metacognitive control to choose one branch (a single tactic or a string of tactics) forecast to optimize goals, for example, maximize a grade while minimizing effort.


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Cite This Article as: Teachers College Record Volume 119 Number 13, 2017, p. 1-16 ID Number: 21920, Date Accessed: 5/27/2022 5:24:45 PM

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