Seminal Papers in Educational Psychology

Paul A. Kirschner

As an experienced researcher, reviewer, and supervisor/mentor of hundreds of young academic researchers, I have experienced a problem, namely that young academics often don’t “know the masters”. Without this knowledge, they often redesign many wheels and aren’t able to really stand on the shoulders of giants and bring the field further.

To this end, I crowdsourced a question a while ago to colleagues in the community, namely: What article or articles do you feel are seminal articles in our field that every (young) researcher should be aware of?

What follows is a cleaned-up, alphabetical list of what I received, each with an abstract or short annotation and where possible, a link to the document itself. It doesn’t pretend to be complete nor definitive. Maybe it’s better to call it an educated beginning.

 

Atkinson, R. C., & Shiffrin, R. M. (1968). Human memory: A proposed system and its control processes”. In K. W. Spence, & J. T. Spence (eds.), The psychology of learning and motivation (Volume 2, (pp. 89-195). New York: Academic Press.

This chapter presents a general theoretical framework of human memory and describes the results of a number of experiments designed to test specific models that can be derived from the overall theory. Available at: http://tinyurl.com/h5omtf7

Ausubel, D.P. (1960). The use of advance organizers in the learning and retention of meaningful verbal material. Journal of Educational Psychology, 51, 267-272.

David Ausubel suggests that advance organizers might foster meaningful learning by prompting the student regarding pre-existing superordinate concepts that are already in the student’s cognitive structure, and by otherwise providing a context of general concepts into which the student can incorporate progressively differentiated details. Ausubel claims that by presenting a global representation of the knowledge to be learned, advance organizers might foster “integrative reconciliation” of the subdomains of knowledge – the ability to understand interconnections among the basic concepts in the domain (http://edutechwiki.unige.ch/en/Advance_Organizer)

Ausubel, D. (1963). The psychology of meaningful verbal learning. New York: Grune & Stratton.

First and most important was the emphasis on meaningful learning, which he defined as non arbitrary, non verbatim, substantive incorporation of new symbolically expressed ideas into cognitive structure. The point here is that learners relate new information or ideas to relevant aspects of their current knowledge structure in a conscious manner. For meaningful learning to occur, three requirements must be met. First, the material to be learned must itself have potential meaning. For example, nonsense syllables or arbitrary lists of words have little inherent meaning and cannot be incorporated into cognitive structure in a non-arbitrary, substantive fashion. Secondly, the learner must possess relevant concepts and propositions that can serve to anchor the new learning and assimilate new ideas. Thirdly, the learner must choose to relate the new information to his/her cognitive structure in a non verbatim, substantive fashion. If any of these three elements are lacking, meaningful learning cannot occur, at least in initial stages of a given learning sequence. (From http://www.mlrg.org/proc3pdfs/Novak_Ausubel.pdf)

Baddeley, A. & Hitch, G. (1974). Working memory. In G.H. Bower (Ed.), The psychology of learning and motivation: Advances in research and theory (Vol. 8, pp. 47–89). New York: Academic Press.

Baddeley and Hitch’s (1974) model of WM as a multiple-component system consisting of a phonological loop, a visuospatial sketch pad, and a central executive started the age of decomposing WM into different components. The same idea is reflected in other WM models that followed. Although researchers differ in their specifications of WM subsystems, most agree that WM includes multiple subsystems working together to activate task-related information, maintain activation, and manipulate information during the performance of cognitive tasks (Miyake & Shah, 1999). The evolution of WM models shows that ideas about WM have shifted towards a more dynamic and systematic view. (From: https://web.stanford.edu/dept/SUSE/SEAL/Reports_Papers/YuanEtal_WorkingMemory.pdf)

Bandura, A. (1977) Self-efficacy: Toward a unifying theory of behavioral change. Psychological review, 84(2), 191-215. http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.315.4567&rep=rep1&type=pdf

The present article presents an integrative theoretical framework to explain and to predict psychological changes achieved by different modes of treatment. This theory states that psychological procedures, whatever their form, alter the level and strength of self-efficacy. It is hypothesized that expectations of personal efficacy determine whether coping behavior will be initiated, how much effort will be expended, and how long it will be sustained in the face of obstacles and aversive experiences. Persistence in activities that are subjectively threatening but in fact relatively safe produces, through experiences of mastery, further enhancement of self-efficacy and corresponding reductions in defensive behavior. In the propose model, expectations of personal efficacy are derived from four principal sources of information: performance accomplishments, vicarious experience, verbal persuasion, and physiological states. The more dependable the experiential sources, the greater are the changes in perceive self-efficacy. A number of factors are identified as influencing the cognitive processing of efficacy information arising from enactive, vicarious, exhortative, and emotive sources. The differential power of diverse therapeutic procedures is analyzed in terms of the postulated cognitive mechanism of operation. Findings are reported from microanalyses of enactive, vicarious, and emotive modes of treatment that support the hypothesized relationship between perceived self-efficacy and behavioral changes. Possible directions for further research are discussed. (Abstract of the article itself) Available at: https://www.uky.edu/~eushe2/Bandura/Bandura1977PR.pdf

Bandura, A. (1982). Self-efficacy mechanism in human agency. American Psychologist, 37, 122–147. http://doi.org/http://dx.doi.org/10.1037/0003-066X.37.2.122

Addresses the centrality of the self-efficacy mechanism (SEM) in human agency. SEM precepts influence thought patterns, actions, and emotional arousal. In causal tests, the higher the level of induced self-efficacy, the higher the performance accomplishments and the lower the emotional arousal. The different lines of research reviewed show that the SEM may have wide explanatory power. Perceived self-efficacy helps to account for such diverse phenomena as changes in coping behavior produced by different modes of influence, level of physiological stress reactions, self-regulation of refractory behavior, resignation and despondency to failure experiences, self-debilitating effects of proxy control and illusory inefficaciousness, achievement strivings, growth of intrinsic interest, and career pursuits. The influential role of perceived collective efficacy in social change and the social conditions conducive to development of collective inefficacy are analyzed. (Abstract of the article itself) Available at: https://www.uky.edu/~eushe2/Bandura/Bandura1982AP.pdf

Bandura, A., & Schunk, D. H. (1981). Cultivating competence, self-efficacy, and intrinsic interest through proximal self-motivation. Journal of Personality and Social Psychology, 41, 586-598.

Tested the hypothesis that self-motivation through proximal goal setting serves as an effective mechanism for cultivating competencies, self-percepts of efficacy, and intrinsic interest. 40 children (7.3–10.1 yrs of age) who exhibited gross deficits and disinterest in mathematical tasks pursued a program of self-directed learning under conditions involving either proximal subgoals, distal goals, or no goals. Results of the multifaceted assessment provide support for the superiority of proximal self-influence. Under proximal subgoals, Ss progressed rapidly in self-directed learning, achieved substantial mastery of mathematical operations, and developed a sense of personal efficacy and intrinsic interest in arithmetic activities that initially held little attraction for them. Distal goals had no demonstrable effects. In addition to its other benefits, goal proximity fostered veridical self-knowledge of capabilities as reflected in high congruence between judgments of mathematical self-efficacy and subsequent mathematical performance. Perceived self-efficacy was positively related to accuracy of mathematical performance and to intrinsic interest in arithmetic activities. (Abstract of the article itself) Available at: https://www.uky.edu/~eushe2/Bandura/Bandura1981JPSP.pdf

Bloom, B. (1984). The 2 Sigma Problem: The search for methods of group instruction as effective as one-to-one tutoring. Educational Researcher, 13(6), 4-16.

Bloom’s 2 sigma problem refers to an educational phenomenon observed by educational psychologist Benjamin Bloom and initially reported in 1984 in the journal “Educational Researcher”. Bloom found that the average student tutored one-to-one using mastery learning techniques performed two standard deviations better than students who learn via conventional instructional methods – that is, “the average tutored student was above 98% of the students in the control class”. Additionally, the variation of the students’ achievement changed: “about 90% of the tutored students … attained the level of summative achievement reached by only the highest 20%” of the control class.Bloom’s graduate students J. Anania and A. J. Burke conducted studies of this effect at different grade levels and in different schools, observing students with “great differences in cognitive achievement, attitudes, and academic self-concept. (Wikipedia: https://en.wikipedia.org/wiki/Bloom’s_2_Sigma_Problem) Available at: http://facultycenter.ischool.syr.edu/wp-content/uploads/2012/02/2-sigma.pdf

Brown, A. L. (1984). Metacognition, executive control, self-regulation and other more mysterious mechanisms. In F. E. Weinert & R. H. Kluwe (Eds.), Metacognition, motivation, and learning (pp. 60-108). West Germany: Kuhlhammer.

Metacognitive experiences involve the use of metacognitive strategies or metacognitive regulation. Metacognitive strategies are sequential processes that one uses to control cognitive activities, and to ensure that a cognitive goal (e.g., understanding a text) has been met. These processes help to regulate and oversee learning, and consist of planning and monitoring cognitive activities, as well as checking the outcomes of those activities. (http://gse.buffalo.edu/fas/shuell/cep564/metacog.htm)

In a thoughtful review, Ann Brown listed these separate areas of existing research that are kinds of metacognition:

  1. The status of verbal reports as data. When are and are not people aware of their own thoughts?
  2. Consciousness.
  3. Executive mechanisms (in Information Processing models of psychology): how is thinking controlled, decided upon as an action?
  4. Error correction in language, and its development.
  5. Self-regulation of action, and conceptual development of this in children. From Piagetian theory.
  6. Vygotsky: his notion of a transition (in each area learned) from Other-regulation to Self-regulation.

(http://www.psy.gla.ac.uk/~steve/small/metacognition.html)

Brown, A.L. (1992). Design experiments: Theoretical and methodological challenges in creating complex interventions in classroom settings. The Journal of the Learning Sciences, 2(2), 141-178.

The lion’s share of my current research program is devoted to the study of learning in the blooming, buzzing confusion of inner-city classrooms. My high-level goal is to transform grade-school classrooms from work sites where students perform assigned tasks under the management of teachers into communities of learning ( Bereiter & Scardamalia, 1989; Brown & Campione, 1990) and interpretation ( Fish, 1980), where students are given significant opportunity to take charge of their own learning. In my current work, I conduct what Collins (in press) refers to as design experiments, modeled on the procedures of design sciences such as aeronautics and artificial intelligence. As a design scientist in my field, I attempt to engineer innovative educational environments and simultaneously conduct experimental studies of those innovations. This involves orchestrating all aspects of a period of daily life in classrooms, a research activity for which I was not trained. My training was that of a classic learning theorist prepared to work with “subjects” (rats, children, sophomores), in strictly controlled labora­tory settings. The methods I have employed in my previous life are not readily transported to the research activities I oversee currently. (Abstract of the article itself) Available at: http://treeves.coe.uga.edu/EDIT9990/Brown_1992.pdf

Brown, A. L., & Campione, J. C. (1996). Psychological theory and the design of innovative learning environments: On procedures, principles, and systems. In L. Schauble & R. Glaser (Eds.), Contributions of instructional innovation to understanding learning. Hillsdale, NJ: Erlbaum.

Fostering Community of Learners (FCL) was a program launched by Brown along with her husband Joseph Campione at the University of California, Berkeley. The project was noted to be similar to earlier reform methods such as progressive education, and discovery learning. The approach to the project was to create a program that met between the theories of discovery learning and didactic learning. According to Brown and Campione, discovery learning that was unguided could potentially be dangerous, while didactic study led to passive learners. Therefore, Brown and Campione’s approach of “guided discovery” was the middle ground between the two.

In FCL, students were encouraged to design their own learning through a curriculum they prepared themselves therefore acting as collaborative researchers. A teacher, or guide, is then responsible for modeling, fostering, and guiding the process of discovery into forms of disciplined examination. The project also utilized reciprocal teaching, which allowed students to study and share their expertise with a group and discuss material they have prepared themselves. The curriculum of a FCL classroom was a key feature to the program. Depending on the curricula, the classroom activity fostered various themes and units that aided in the further development of the student. Biological themes included interdependence and adaptation while environmental science themes included balance, competition, and cooperation. (Wikipedia: https://en.wikipedia.org/wiki/Ann_Brown)

Brown, J. S., Collins, A., & Duguid, P. (1989). Situated cognition and the culture of learning. Educational Researcher, 18(1), 32-42.

Many teaching practices implicitly assume that conceptual knowledge can be abstracted from the situations in which it is learned and used. This article argues that this assumption inevitably limits the effectiveness of such practices. Drawing on recent research into cognition as it is manifest in everyday activity, the authors argue that knowledge is situated, being in part a product of the activity, context, and culture in which it is developed and used. They discuss how this view of knowledge affects our understanding of learning, and they note that conventional schooling too often ignores the influence of school culture on what is learned in school. As an alternative to conventional practices, they propose cognitive apprenticeship (Collins, Brown, & Newman, in press), which honors the situated nature of knowledge. They examine two examples of mathematics instruction that exhibit certain key features of this approach to teaching. (Abstract of the article itself) Available at: https://people.ucsc.edu/~gwells/Files/Courses_Folder/ED%20261%20Papers/Situated%20Cognition.pdf

Butler, D. L., & Winne, P. H. (1995). Feedback and self-regulated learning: A theoretical synthesis. Review of Educational Research, 65, 245-281.

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. (Abstract of the article itself) Available at: http://andrewvs.blogs.com/usu/files/feedback_and_selfregulated_learninga_theoretcial_synthesis.pdf

Campbell, D. & Stanley, J. (1959). Experimental and quasi-experimental designs for research. Chicago, IL: Rand-McNally.

This famous and foundational discussion of research design belongs high on the shelf of every social science researcher. It presents twelve factors that threaten the internal and external validity of research studies and three common “pre-experimental” that do not adequately control for these threats. The authors then review three “true experimental designs” which offer high control and increased interpretability of results. Finally, the book reviews a number of “quasi-experimental” research designs commonly used in educational research. These designs control for most threats to validity and can be used with some additional care. Statistical procedures used to analyze data resulting from each design are also discussed. (From: https://www.amazon.ca/Experimental-Quasi-Experimental-Designs-Research-Campbell/dp/0395307872) Available at: https://www.sfu.ca/~palys/Campbell&Stanley-1959-Exptl&QuasiExptlDesignsForResearch.pdf

Chi, M. (1997). Quantifying qualitative analyses of verbal data: A practical guide. The Journal of the Learning Sciences, 6, 271-315.

This article provides one example of a method of analyzing qualitative data in an objective and quantifiable way. Although the application of the method is illustrated in the context of verbal data such as explanations, interviews, problem-solving protocols, and retrospective reports, in principle, the mechanics of the method can be adapted for coding other types of qualitative data such as gestures and videotapes. The mechanics of the method we outlined in 8 concrete step. Although verbal analyses can be used for many purposes, the main goal of the analyses discussed here is to formulate an understanding of the representation of the knowledge used in cognitive performances and how that representation changes with learning This can be contrasted with another method or analyzing verbal protocols, the goal of which is to validate the cognitive processes of human performance, often as embodied in a computational model. (Abstract of the article). Available at: http://www.public.asu.edu/~mtchi/papers/Verbaldata.pdf

Chi, M. T. H., Feltovich, P. J., & Glaser, R. (1981). Categorization and representation of physics problems by experts and novices. Cognitive Science. 5(2), 121–152.

The representation of physics problems in relation to the organization of physics knowledge is investigated in experts and novices. Four experiments examine (a) the existence of problem categories as a basis for representation; (b) differences in the categories used by experts and novices; (c) differences in the knowledge associated with the categories; and (d) features in the problems that contribute to problem categorization and representation. Results from sorting tasks and protocols reveal that experts and novices begin their problem representations with specifiably different problem categories, and completion of the representations depends on the knowledge associated with the categories. For, the experts initially abstract physics principles to approach and solve a problem representation, whereas novices base their representation and approaches on the problem’s literal features. (Abstract of the article). Available at: http://tinyurl.com/z9fkjjj

Clark, R. E. (1983). Reconsidering research on learning from media. Review of Educational Research, 53, 445-459.

ecent meta-analyses and other studies of media’s influence on learning are reviewed. Consistent evidence is found for the generalization that there are no learning benefits to be gained from employing any specific medium to deliver instruction. Research showing performance or time-saving gains from one or another medium are shown to be vulnerable to compelling rival hypotheses concerning the uncontrolled effects of instructional method and novelty. Problems with current media attribute and symbol system theories are described and suggestions made for more promising research directions. (Abstract of the article). Available at: http://journals.sagepub.com/doi/pdf/10.3102/00346543053004445

Clark, R. E. (1989).When teaching kills learning: Research on mathemathantics. In H. N. Mandl, N. Bennett, E. de Corte, & H. F. Friedrich (Eds.), Learning and instruction: European research in an international context (Vol. 2, pp. 1–22). London, UK: Pergamon.

Instructional research is reviewed where teaching failures have produced students who seem to be less able to use learning skills or had less access to knowledge in some domain than before they were taught. Three general types of “mathemathantic” (i.e. where instruction “kills” learning) effects are hypothesized, theoretical explanations for each effect are examined and representative studies in each area are described. The three types of effects described are where instruction serves to: (1) substitute learning procedures (e.g. novel learning strategies are hypothesized to interfere with the learning of higher general ability learners and inadequate learning strategies are provided to those with lower general ability); (2) impose less desirable motivational goals on learners (e.g. when teaching methods lead constructively motivated learners to believe that failure avoidance has replaced achievement directed goals and, conversely, when defensively motivated students believe that achievement directed goals have replaced the opportunity to avoid failure); and (3) substitute student control for system control over instructional method (e.g. by allowing lower cognitive load instructional methods to be chosen by high general ability, constructive students and/or by allowing higher cognitive load methods to be chosen by defensive students who have low general ability). A four-page bibliography and an outline of situations when mathemathantic effects are more probable are attached. (Abstract of the article). Available at: https://www.researchgate.net/publication/234744652_When_Teaching_Kills_Learning_Types_of_Mathemathantic_Effects

Collins, A. (1992). Toward a design science of education. In E. Scanlon & T. O’Shea (Eds.), New directions in educational technology (pp. 15-22). New York: Springer-Verlag.

Noting some of the major problems with current design experiments in education, a project has been undertaken with the long-term goal of constructing a systematic science of how to design educational environments so that new technologies can be introduced successfully. This paper outlines several factors considered to be critical in developing a methodology for conducting design experiments and provides an example of a proposed application of the methodology to the development of a multimedia teaching unit about the seasons which would incorporate the film “The Voyage of the Mimi 2,” associated computer programs, a program for teaching students how to construct tables and graph data, a computer network, and application programs such as word processors and drawing programs. It is noted that the evaluation of the unit, through its reliance on multiple data collection methods–including pre- and post-tests, structured interviews, classroom observations, teachers’ comments, and follow-up studies–would avoid the shortcomings of current design experiments and would help determine the form that a design theory should take. Finally, the initial phases in constructing such a theory–i.e., identifying all relevant independent and dependent variables by which the success or failure of an innovation can be measured and specifying how these variables interact–are discussed. Factors affecting the success of technology in education are presented in two tables. (Abstract of the original paper). Available at: http://files.eric.ed.gov/fulltext/ED326179.pdf

Collins, A., Brown, J. S., & Newman, S. E. (1991). Cognitive apprenticeship: Making things visible. American Educator: The Professional Journal of the American Federation of Teachers, 15(3), 6-11, 38-46.

Cognitive apprenticeship is a theory of the process where a master of a skill teaches that skill to an apprentice. Constructivist approaches to human learning have led to the development of a theory of cognitive apprenticeship. This theory holds that masters of a skill often fail to take into account the implicit processes involved in carrying out complex skills when they are teaching novices. To combat these tendencies, cognitive apprenticeships “…are designed, among other things, to bring these tacit processes into the open, where students can observe, enact, and practice them with help from the teacher…”. (Wikipedia: https://en.wikipedia.org/wiki/Cognitive_apprenticeship)

The apprenticeship model can be adapted to teaching and learning cognitive skills in reading, writing, and mathematics, as illustrated by three successful examples. A cognitive apprenticeship framework is presented for the design of learning environments incorporating content taught, pedagogical methods, sequencing of learning activities, and sociology of learning. (Abstract of the article)

Craik, F. I. M., & Lockhart, R. S. (1972). Levels of processing: A framework for memory research. Journal of Verbal Learning and Verbal behavior, 11, 671-684.

This paper briefly reviews the evidence for multistore theories of memory and points out some difficulties with the approach. An alternative framework for human memory research is then outlined in terms of depth or levels of processing. Some current data and arguments are reexamined in the light of this alternative framework and implications for further research considered. (Abstract of the article) Available at: http://wixtedlab.ucsd.edu/publications/Psych%20218/Craik_Lockhart_1972.pdf

Craik, F.I.M., & Tulving, E. (1975). Depth of processing and the retention of words in episodic memory. Journal of Experimental Psychology: General, 104, 268-294.

The studies described in this section were undertaken to examine further aspects of depth of processing and to throw more light on the factors underlying good memory performance. (Author)

Conducted 10 experiments to evaluate the notion of “depth of processing” in human memory. Undergraduate Ss were asked questions concerning the physical, phonemic, or semantic characteristics of a long series of words; this initial question phase was followed by an unexpected retention test for the words. It was hypothesized that “deeper” (semantic) questions would take longer to answer and be associated with higher retention of the target words. These ideas were confirmed by the 1st 4 experiments. Exps V-X showed (a) it is the qualitative nature of a word’s encoding which determines retention, not processing time as such; and (b) retention of words given positive and negative decisions was equalized when the encoding questions were equally salient or congruous for both types of decision. While “depth” (the qualitative nature of the encoding) serves a useful descriptive purpose, results are better described in terms of the degree of elaboration of the encoded trace. Finally, results have implications for an analysis of learning in terms of its constituent encoding operations. (Abstract of the article) Available at: http://alicekim.ca/CraikTulving1975.pdf

Cronbach, L. J. (1957). The two disciplines of scientific psychology. American Psychologist, 12, 671-684.

No man can be acquainted with all of psychology today, as our convention program proves. The scene resembles that of a circus, but a circus grander and more bustling than any Barnum ever envisioned — a veritable week-long diet of excitement and pink lemonade. Three days of smartly paced performance are required just to display the new tricks the animal trainers have taught their charges. We admire the agile paper-readers swinging high above us in the theoretical blue, saved from disaster by only a few gossamer threads of fact, and we gasp as one symposiast thrusts his head bravely between another’s sharp toothed jaws. This 18-ring display of energies and talents gives plentiful evidence that psychology is going places. But whither?

I shall discuss the past and future place within psychology of two historic streams of method, thought, and affiliation which run through the last century of our science. One stream is experimental psychology; the other, correlational psychology. Dashiell optimistically forecast a confluence of these two streams, but that confluence is still in the making. Psychology continues to this day to be limited by the dedication of its investigators to one or the other method of inquiry rather than to scientific psychology as a whole. (Abstract of the article) Available at: http://psychclassics.yorku.ca/Cronbach/Disciplines/

Cronbach, L. & Snow, R. (1977). Aptitudes and instructional methods: A handbook for research on interactions. New York, NY: Irvington.

In education, the study of person-situation interaction translates into research on individual differences in student aptitudes for learning under differing instructional conditions. An old and vast literature in educational psychology attests to the fact that individual differences in learner aptitudes predict learning outcomes. But a substantial new body of literature also now demonstrates that aptitude variables often interact with instructional treatment variables in these predictions. These so-called aptitude-treatment interactions (ATI) have important implications for the development of instructional theory and research and for instructional improvement. They provide a powerful new means of testing the construct validity of aptitude constructs and of focusing task analyses of instructional situations. They suggest a systematic approach to the individualization of instruction. More than this, they signal that theories in educational research require constructs woven from an understanding of individual differences in psychological processes as these are influenced by differing situational demands; they prove the need for the unified psychological science envisioned by Cronbach (1957). (http://link.springer.com/chapter/10.1007%2F978-1-4613-3997-7_10)

Discusses educational, methodological, social, and philosophical investigations of aptitude and instruction; designs for research on interactions and methods of multivariate statistical analysis; interactions between aptitude and variations in programmed instruction and other curricula; and the effects of teacher behavior, classroom climate, college environment, and personality on response to instruction. (http://psycnet.apa.org/psycinfo/1978-11462-000)

Dweck, C. S., & Leggett, E. L. (1988). A social-cognitive approach to motivation and personality. Psychological review, 95(2), 256-273.

Past work has documented and described major patterns of adaptive and maladaptive behavior: the mastery-oriented and the helpless patterns. In this article, we present a research-based model that accounts for these patterns in terms of underlying psychological processes. The model specifies how individuals’ implicit theories orient them toward particular goals and how these goals set up the different patterns. Indeed, we show how each feature (cognitive, affective, and behavioral) of the adaptive and maladaptive patterns can be seen to follow directly from different goals. We then examine the generality of the model and use it to illuminate phenomena in a wide variety of domains. Finally, we place the model in its broadest context and examine its implications for our understanding of motivational and personality processes. (Abstract of the article) Available at: http://www.unco.edu/cebs/psychology/kevinpugh/motivation_project/resources/dweck_leggett88.pdf

Flavell, J. H. (1979). Metacognition and cognitive monitoring: A new area of cognitive–developmental inquiry. American Psychologist, 34, 906–911.

Studies suggest that young children are quite limited in their knowledge about cognitive phenomena—or in their metacognition—and do relatively little monitoring of their own memory, comprehension, and other cognitive enterprises. Metacognitive knowledge is one’s stored knowledge or beliefs about oneself and others as cognitive agents, about tasks, about actions or strategies, and about how all these interact to affect the outcomes of any sort of intellectual enterprise. Metacognitive experiences are conscious cognitive or affective experiences that occur during the enterprise and concern any aspect of it—often, how well it is going. Research is needed to describe and explain spontaneous developmental acquisitions in this area and find effective ways of teaching metacognitive knowledge and cognitive monitoring skills. (Abstract of the article) Available at: http://www.demenzemedicinagenerale.net/images/mens-sana/Metacognition_and_cognitive_monitoring.pdf

Gagne, R. (1985). The Conditions of Learning (4th. edition). New York, NY: Holt, Rinehart & Winston.

This theory stipulates that there are several different types or levels of learning. The significance of these classifications is that each different type requires different types of instruction. Gagne identifies five major categories of learning: verbal information, intellectual skills, cognitive strategies, motor skills and attitudes. Different internal and external conditions are necessary for each type of learning. For example, for cognitive strategies to be learned, there must be a chance to practice developing new solutions to problems; to learn attitudes, the learner must be exposed to a credible role model or persuasive arguments.

Gagne suggests that learning tasks for intellectual skills can be organized in a hierarchy according to complexity: stimulus recognition, response generation, procedure following, use of terminology, discriminations, concept formation, rule application, and problem solving. The primary significance of the hierarchy is to identify prerequisites that should be completed to facilitate learning at each level. Prerequisites are identified by doing a task analysis of a learning/training task. Learning hierarchies provide a basis for the sequencing of instruction.

In addition, the theory outlines nine instructional events and corresponding cognitive processes:

  1. Gaining attention (reception)
  2. Informing learners of the objective (expectancy)
  3. Stimulating recall of prior learning (retrieval)
  4. Presenting the stimulus (selective perception)
  5. Providing learning guidance (semantic encoding)
  6. Eliciting performance (responding)
  7. Providing feedback (reinforcement)
  8. Assessing performance (retrieval)
  9. Enhancing retention and transfer (generalization).

(http://www.instructionaldesign.org/theories/conditions-learning.html) For a synopsis see: http://lrc.binus.ac.id/downloads/TE/Gagne.pdf

Greeno, J.G. (1998). The situativity of knowing, learning, and research. American Psychologist, 53(1), 5-26.

The situative perspective shifts the focus of analysis from individual behavior and cognition to larger systems that include behaving cognitive agents interacting with each other and with other subsystems in the environment. The first section presents a version of the situative perspective that draws on studies of social interaction, philosophical situation theory, and ecological psychology. Framing assumptions and concepts are proposed for a synthesis of the situative and cognitive theoretical perspectives, and a further situative synthesis is suggested that would draw on dynamic-systems theory. The second section discusses relations between the situative, cognitive, and behaviorist theoretical perspectives and principles of educational practice. The third section discusses an approach to research and social practice called interactive research and design, which fits with the situative perspective and provides a productive, albeit syncretic, combination of theory-oriented and instrumental functions of research. (Abstract of the article) Available at: https://www.researchgate.net/publication/232563899_The_Situativity_of_Knowing_Learning_and_Research

Guilford, J. P. (1967). The Nature of Human Intelligence. McGraw-Hill Education.

In Guilford’s Structure of Intellect (SI) theory, intelligence is viewed as comprising operations, contents, and products. There are 5 kinds of operations (cognition, memory, divergent production, convergent production, evaluation), 6 kinds of products (units, classes, relations, systems, transformations, and implications), and 5 kinds of contents (visual, auditory, symbolic, semantic, behavioral). Since each of these dimensions is independent, there are theoretically 150 different components of intelligence. Guilford researched and developed a wide variety of psychometric tests to measure the specific abilities predicted by SI theory. These tests provide an operational definition of the many abilities proposed by the theory. Furthermore, factor analysis was used to determine which tests appeared to measure the same or different abilities.

See also: Guilford, J. P. (1988). Some changes in the structure-of-intellect model Educational and Psychological Measurement, 48, 1-4

Hatano, G. & Inagaki, K. (1986). Two courses of expertise. In H. A. H. Stevenson, & K. Hakuta (Ed.), Child development and education in Japan (pp. 262-272), New York, NY: Freeman.

Hatano and Inagaki, described two types of expertise: routine expertise, or classic expertise, and adaptive expertise. They defined routine expertise as involving mastering procedures in such a way as to become highly efficient and accurate, whereas developing adaptive expertise requires an individual to develop conceptual understanding that allows the “expert” to invent new solutions to problems and even new procedures for solving problems. To illustrate, imagine two sushi chefs: one who makes every piece perfectly but routinely makes the same few types over and over (routine, or classic, expertise), and one produces new menus frequently (adaptive expertise). (Wikipedia: https://en.wikipedia.org/wiki/Adaptive_expertise) Available at: http://eprints.lib.hokudai.ac.jp/dspace/bitstream/2115/25206/1/6_P27-36.pdf

Kirschner, P. A., & van Merriënboer, J. J. G. (2013). Do learners really know best? Urban legends in education. Educational Psychologist, 48(3), 1-15.

This article takes a critical look at three pervasive urban legends in education about the nature of learners, learning, and teaching and looks at what educational and psychological research has to say about them. The three legends can be seen as variations on one central theme, namely, that it is the learner who knows best and that she or he should be the controlling force in her or his learning. The first legend is one of learners as digital natives who form a generation of students knowing by nature how to learn from new media, and for whom “old” media and methods used in teaching/learning no longer work. The second legend is the widespread belief that learners have specific learning styles and that education should be individualized to the extent that the pedagogy of teaching/learning is matched to the preferred style of the learner. The final legend is that learners ought to be seen as self-educators who should be given maximum control over what they are learning and their learning trajectory. It concludes with a possible reason why these legends have taken hold, are so pervasive, and are so difficult to eradicate. (Abstract of the article) Available at: https://www.bvekennis.nl/Bibliotheek/16-1150.pdf

Kirschner, P. A., Sweller, J., & Clark, R. E. (2006). Why minimal guidance during instruction does not work: An analysis of the failure of constructivist, discovery, problem-based, experiential, and inquiry-based teaching. Educational Psychologist, 46(2), 75-86.

Evidence for the superiority of guided instruction is explained in the context of our knowledge of human cognitive architecture, expert–novice differences, and cognitive load. Although unguided or minimally guided instructional approaches are very popular and intuitively appealing, the point is made that these approaches ignore both the structures that constitute human cognitive architecture and evidence from empirical studies over the past half-century that consistently indicate that minimally guided instruction is less effective and less efficient than instructional approaches that place a strong emphasis on guidance of the student learning process. The advantage of guidance begins to recede only when learners have sufficiently high prior knowledge to provide “internal” guidance. Recent developments in instructional research and instructional design models that support guidance during instruction are briefly described. (Abstract of the article) Available at: https://dspace.library.uu.nl/bitstream/handle/1874/16899/kirschner_06_minimal_guidance.pdf?sequence=1&isAllowed=y

Mayer, R. E. (1997). Multimedia learning: Are we asking the right questions? Educational Psychologist, 32, 1-19.

How can we help students to understand scientific explanations of cause-and-effect systems, such as how a pump works, how the human respiratory system works, or how lightning storms develop? One promising approach involves multimedia presentation of explanations in visual and verbal formats, such as presenting computer-generated animations synchronized with computer-generated narration or presenting illustrations next to corresponding text. In a review of eight studies concerning whether multimedia instruction is effective, there was consistent evidence for a multimedia effect: Students who received coordinated presentation of explanations in verbal and visual format (multiple representation group) generated a median of over 75% more creative solutions on problem-solving transfer tests than did students who received verbal explanations alone (single representation group). In a review of 10 studies; concerning when multimedia instruction is effective, there was consistent evidence for a contiguity effect: Students generated a median of over 50% more creative solutions to transfer problems when verbal and visual explanations were coordinated (integrated group) than when they were not coordinated (separated group). Finally, in a review of six studies concerning for whom multimedia instruction is effective, Attribute x Treatment interactions indicated that multimedia and contiguity effects were strongest for low prior knowledge and high spatial ability students. Results are consistent with a generative theory of multimedia learning in which learners actively select, organize, and integrate verbal and visual information. (Abstract of the article) Available at: https://www.researchgate.net/publication/246899935_Multimedia_Learning_Are_We_Asking_the_Right_Questions

Newell, A. & Simon, H. (1972). Human problem solving. Englewood Cliffs, NJ: Prentice-Hall.

In 1972, Allen Newell and Herbert Simon published the book Human Problem Solving, in which they outlined their problem space theory of problem solving. In this theory, people solve problems by searching in a problem space. The problem space consists of the initial (current) state, the goal state, and all possible states in between. The actions that people take in order to move from one state to another are known as operators. (http://cognitivepsychology.wikidot.com/cognition:problem-solving)

Newell and Simon’s treatise by this name is described as “. . . perhaps the most important book on the scientific study of human thinking in the 20th century.” in Science [AAAS] magazine’s retrospective on Herbert Simon.

Nicholls, J. G. (1984). Achievement motivation: Conceptions of ability, subjective experience, task choice, and performance. Psychological Review, 91, 328–346.

Achievement behavior is denned as behavior directed at developing or demonstrating high rather than low ability. It is shown that ability can be conceived in two ways. First, ability can be judged high or low with reference to the individual’s own past performance or knowledge. In this context, gains in mastery indicate competence. Second, ability can be judged as capacity relative to that of others. In this context, a gain in mastery alone does not indicate high ability. To demonstrate high capacity, one must achieve more with equal effort or use less effort than do others for an equal performance. The conditions under which these different conceptions of ability function as individuals’ goals and the nature of subjective experience in each case are specified. Different predictions of task choice and performance are derived and tested for each case. (Abstract of the article) Available at: http://gribouts.free.fr/psycho/menace%20du%20st%E9r%E9o/nicholls%20-%20malleable.pdf

Palincsar, A. S. (1998). Social constructivist perspectives on teaching and learning. Annual Review of Psychology, 49, 345-375.

Social constructivist perspectives focus on the interdependence of social and individual processes in the co-construction of knowledge. After the impetus for understanding the influence of social and cultural factors on cognition is reviewed, mechanisms hypothesized to account for learning from this perspective are identified, drawing from Piagetian and Vygotskian accounts. The empirical research reviewed illustrates (a) the application of institutional analyses to investigate schooling as a cultural process, (b) the application of interpersonal analyses to examine how interactions promote cognition and learning, and (c) discursive analyses examining and manipulating the patterns and opportunities in instructional conversation. The review concludes with a discussion of the application of this perspective to selected contemporary issues, including: acquiring expertise across domains, assessment, educational equity, and educational reform. (Abstract of the article) Available at: https://gsueds2007.pbworks.com/f/Palinscar1998.pdf

Rogoff, B. (1994). Developing understanding of the idea of communities of learners. Mind, culture, and activity, 1(4), 209-229.

The idea of a community of learners is based on the premise that learning occurs as people participate in shared endeavors with others, with all playing active but often asymmetrical roles in sociocultural activity. This contrasts with models of learning that are based on one‐sided notions of learning— either that it occurs through transmission of knowledge from experts or acquisition of knowledge by novices, with the learner or the others (respectively) in a passive role. In this paper, I develop the distinction between the community of learners and one‐sided approaches from the perspective of a theory of learning as participation, and use two lines of research to illustrate the transitions in perspective necessary to understand the idea of communities of learners. One line of research examines differing models of teaching and learning employed by caregivers and toddlers from Guatemalan Mayan and middle‐class European‐American families; the other line of research involves a study of how middle‐class parents make a transition from their own schooling background to participate in instruction in a public US elementary school. (Abstract of the article) Available at: http://ase.tufts.edu/DevTech/courses/readings/Rogoff-DevelopingUnderstanding.pdf

Rothkopf, E. Z. (1970). The concept of mathemagenic activities. Review of Educational Research, 40, 325–336.

Mathemagenic activities are cognitive activities that give birth to learning (contrast mathemathantic; Clark). In 1966 he coined the term mathemagenic for behaviors that lead to learning, one of the first theories of learning that focused on internal processes. His ideas were based on his observation that what students learned from instruction is a transformed version of the knowledge their instructor intended to impart, we he thought required more than just the stimulus-response model of behaviorism. He wrote:

Psychologists write from time to time in human language. Some years ago, I submitted the report of an experiment about mathemagenic behavior to a journal. The article started with the sentence, “You can lead a horse to water but the only water that gets into his stomach is what he drinks.” The editor, probably judging this to be too alimentary, deleted the sentence. I regretted this not only because the little phrase pleased me but also because the problem of the not-drinking horse was and is a useful metaphor for explaining why the study of mathemagenic activities is a challenging enterprise for the educational psychologist. The proposition is simple. In most instructional situations, what is learned depends largely on the activities of the student. It therefore behooves those interested in the scientific study of instruction to examine these learning activities, i.e., the “drinking habits” of students.

Available at: https://www.jstor.org/stable/1169369?seq=1#page_scan_tab_contents

Schank, R.C. & Abelson, R. (1977). Scripts, Plans, Goals, and Understanding. Hillsdale , NJ: Earlbaum Assoc.

Script theory is a psychological theory which posits that human behaviour largely falls into patterns called “scripts” because they function analogously to the way a written script does, by providing a program for action. Silvan Tomkins created script theory as a further development of his affect theory, which regards human beings’ emotional responses to stimuli as falling into categories called “affects”: he noticed that the purely biological response of affect may be followed by awareness and by what we cognitively do in terms of acting on that affect so that more was needed to produce a complete explanation of what he called “human being theory”.

In script theory, the basic unit of analysis is called a “scene”, defined as a sequence of events linked by the affects triggered during the experience of those events. Tomkins recognized that our affective experiences fall into patterns that we may group together according to criteria such as the types of persons and places involved and the degree of intensity of the effect experienced, the patterns of which constitute scripts that inform our behavior in an effort to maximize positive affect and to minimize negative affect. (Wikipedia: https://en.wikipedia.org/wiki/Script_theory)

Skinner, B. F. (1958). Teaching machines. Science, 128 (3330), 969-977.

The teaching machine was a mechanical device whose purpose was to administer a curriculum of programmed learning. The machine embodies key elements of Skinner’s theory of learning and had important implications for education in general and classroom instruction in particular. In one incarnation, the machine was a box that housed a list of questions that could be viewed one at a time through a small window. There was also a mechanism through which the learner could respond to each question. Upon delivering a correct answer, the learner would be rewarded. Skinner advocated the use of teaching machines for a broad range of students (e.g., preschool aged to adult) and instructional purposes (e.g., reading and music). (Wikipedia: https://en.wikipedia.org/wiki/B._F._Skinner#Teaching_machine) Available at: http://svn.taupro.com/pub/Projects/TutorMe/trunk/docs/teachingmachines1958.pdf

Spearman, C. (1904). General intelligence, objectively determined and measured. American Journal of Psychology, 15, 201-293.

General intelligence, also known as g factor, refers to the existence of a broad mental capacity that influences performance on cognitive ability measures. Charles Spearman first described the existence of general intelligence in 1904. According to Spearman, this g factor was responsible for overall performance on mental ability tests. Spearman noted that while people certainly could and often did excel in certain areas, people who did well in one area tended also to do well in other areas. (https://www.verywell.com/what-is-general-intelligence-2795210) Available at: http://psychclassics.yorku.ca/Spearman/

Sweller, J: (1988). Cognitive load during problem solving: Effects on learning. Cognitive Science, 12, 257-285.

Considerable evidence indicates that domain specific knowledge in the form of schemas is the primary factor distinguishing experts from novices in problem-solving skill. Evidence that conventional problem-solving activity is not effective in schema acquisition is also accumulating. It is suggested that a major reason for the ineffectiveness of problem solving as a learning device, is that the cognitive processes required by the two activities overlap insufficiently, and that conventional problem solving in the form of means-ends analysis requires a relatively large amount of cognitive processing capacity which is consequently unavailable for schema acquisition. A computational model and experimental evidence provide support for this contention. Theoretical and practical implications are discussed. (Abstract of the article) Available at: https://pdfs.semanticscholar.org/d88c/481743db95687bf9d2861c16cd006f67a0a1.pdf

Sweller, J., van Merriënboer J. J., Paas F. G. (1998). Cognitive architecture and instructional design. Educational Psychology Review, 10, 251-296.

Cognitive load theory has been designed to provide guidelines intended to assist in the presentation of information in a manner that encourages learner activities that optimize intellectual performance. The theory assumes a limited capacity working memory that includes partially independent subcomponents to deal with auditory/verbal material and visual/2- or 3-dimensional information as well as an effectively unlimited long-term memory, holding schemas that vary in their degree of automation. These structures and functions of human cognitive architecture have been used to design a variety of novel instructional procedures based on the assumption that working memory load should be reduced and schema construction encouraged. This paper reviews the theory and the instructional designs generated by it. (Abstract of the article) Available at: http://portal.ou.nl/documents/40663120/0/Sweller+van+Merrienboer+%26%20Paas+1998+-+EPR.pdf

Thorndike, Edward L. (1910). The contribution of psychology to education. Journal of Educational Psychology, 1, 5-12.

Outlines the contributions of psychology to an understanding of the aims, materials, means and methods of education. The three ways in which psychology contributes to a knowledge of methods of teaching are delineated. The work done by psychologists which is of special significance to the theory and practice of education have also been discussed. Incidental contributions from studies of sensory and perceptual processes, imagery and memory, attention and distraction, facilitation, inhibition and fatigue, and the like have been enumerated. (http://psycnet.apa.org/psycinfo/1926-01409-001) Available at: http://psychclassics.yorku.ca/Thorndike/education.htm

Vygotsky, L. S. (1978). Interaction between learning and development. In M. Cole, V. John-Steiner, S. Scribner & E. Souberman (Eds.), Mind in Society: The development of higher psychological processes (pp. 79-91). Cambridge, MA: Harvard University Press.

Social Development Theory is the work of Russian psychologist Lev Vygotsky (1896-1934). Vygotsky’s work was largely unknown to the West until it was published in 1962. Vygotsky’s theory is one of the foundations of constructivism. It asserts three major themes regarding social interaction, the more knowledgeable other, and the zone of proximal development. (https://www.learning-theories.com/vygotskys-social-learning-theory.html) Available at: http://www.colorado.edu/physics/phys4810/phys4810_fa08/4810_readings/vygot_chap6.pdf

Weiner, B. (1974). Achievement motivation and attribution theory. Morristown, N.J.: General Learning Press.

Attribution theory is concerned with how individuals interpret events and how this relates to their thinking and behavior. Heider (1958) was the first to propose a psychological theory of attribution, but Weiner and colleagues (e.g., Jones et al, 1972; Weiner, 1974, 1986) developed a theoretical framework that has become a major research paradigm of social psychology. Attribution theory assumes that people try to determine why people do what they do, i.e., attribute causes to behavior. A person seeking to understand why another person did something may attribute one or more causes to that behavior. A three-stage process underlies an attribution: (1) the person must perceive or observe the behavior, (2) then the person must believe that the behavior was intentionally performed, and (3) then the person must determine if they believe the other person was forced to perform the behavior (in which case the cause is attributed to the situation) or not (in which case the cause is attributed to the other person).

Weiner focused his attribution theory on achievement (Weiner, 1974). He identified ability, effort, task difficulty, and luck as the most important factors affecting attributions for achievement. Attributions are classified along three causal dimensions: locus of control, stability, and controllability. The locus of control dimension has two poles: internal versus external locus of control. The stability dimension captures whether causes change over time or not. For instance, ability can be classified as a stable, internal cause, and effort classified as unstable and internal. Controllability contrasts causes one can control, such as skill/efficacy, from causes one cannot control, such as aptitude, mood, others’ actions, and luck.

Attribution theory is closely associated with the concept of motivation. It also relates the work done on script theory and inferencing done by Schank. (http://www.instructionaldesign.org/theories/attribution-theory.html)

Wenger, E. (2000). Communities of Practice and Social Learning Systems. Organization, 7, 225-246.

The concept of community of practice was not born in the systems theory tradition. It has its roots in attempts to develop accounts of the social nature of human learning inspired by anthropology and social theory (Lave, 1988; Bourdieu, 1977; Giddens, 1984; Foucault, 1980; Vygostsky, 1978). But the concept of community of practice is well aligned with the perspective of the systems tradition. A community of practice itself can be viewed as a simple social system. And a complex social system can be viewed as constituted by interrelated communities of practice. In this essay I first explore the systemic nature of the concept at these two levels. Then I use this foundation to look at the applications of the concept, some of its main critiques, and its potential for developing a social discipline of learning. The concept of community of practice does not exist by itself. It is part of a broader conceptual framework for thinking about learning in its social dimensions.1 It is a perspective that locates learning, not in the head or outside it, but in the relationship between the person and the world, which for human beings is a social person in a social world. In this relation of participation, the social and the individual constitute each other. When I refer to “the theory” in what follows, I refer to this version of social learning theory. (Abstract of the article) Available at: http://wenger-trayner.com/wp-content/uploads/2012/01/09-10-27-CoPs-and-systems-v2.01.pdf

Wood, D.J., Bruner, J.S. & Ross, G. (1976) The role of tutoring in problem solving. Journal of Child Psychology and Psychiatry, 17,2, 89–100.

Father of scaffolding. This paper is concerned with the nature of the tutorial process; the means whereby an adult or “expert” helps somebody who is less adult or less expert….3-, 4-, and 5-year olds were tutored in the task of constructing a pyramid from complex, interlocking constituent blocks. The results indicate some of the properties of an interactive system of exchange in which the tutor operates with an implicit theory of the learner’s acts in order to recruit his attention, reduces degrees of freedom in the task to manageable limits, maintains “direction” in the problem solving, marks critical features, controls frustration and demonstrates solutions when the learner can recognize them. The significance of the findings for instruction in general is considered. (Journal Extract). Available at: http://onlinelibrary.wiley.com/doi/10.1111/j.1469-7610.1976.tb00381.x/epdf

Zimmerman, B. J. (1983). Social learning theory: A contextualist account of cognitive functioning. In C. J. Brainerd (Ed.), Recent advances in cognitive developmental theory and practice (pp. 1 -49). New York: Springer.

Social learning theory grew out of the efforts of Bandura and Walters (1959, 1963) to explain how children acquired information and behavior by observing people in natural settings. Initially they investigated youngsters’ simple imitation of common responses, such as aggression, by a model. Favorable results of this research prompted study of more complex classes of social learning, such as the development of emotional reactions (attraction and avoidance), cognitive and linguistic rules, self-regulating responses, personal standards, expectations, and self-efficacy judgments. This social interactionist approach to development revealed a distinctive but widely underestimated feature of children’s knowledge: At all levels of complexity, it remained highly dependent on the social environmental context from which it sprang. This property of thought also became evident to other theorists as they began to study cognitive functioning in naturalistic settings. Several of these theorists have discussed the implications of their research on the basis of a general epistemology termed “contextualism. (http://link.springer.com/chapter/10.1007%2F978-1-4613-9490-7_1)

Zimmerman, B. J. (2013). From cognitive modeling to self-regulation: a social cognitive career path. Educational Psychologist, 48, 135–147.

My career path to understanding the source and nature of human learning started with an interest in social processes, especially cognitive modeling, and has led to the exploration of self-regulatory processes. My investigation of these processes has prompted the development of several social cognitive models: a triadic model that synthesized covert, behavioral, and environmental sources of personal feedback, a multilevel model of training that begins with observational learning and proceeds sequentially to self-regulation, and a cyclical phase model that depicts the interaction of metacognitive and motivational processes during efforts to learn. Empirical support for each of these models is discussed, including its implications for formal and informal forms of instruction. This self-regulation research has revealed that students who set superior goals proactively, monitor their learning intentionally, use strategies effectively, and respond to personal feedback adaptively not only attain mastery more quickly, but also are more motivated to sustain their efforts to learn. Recommendations for future research are made. (Abstract of the article). Available at: https://www.researchgate.net/publication/263080929_From_Cognitive_Modeling_to_Self-Regulation_A_Social_Cognitive_Career_Path

 

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