The Cognitive-Affective-Motivation Model of Learning (CAMML): Standing on the Shoulders of Giants

2021 ◽  
pp. 082957352110542
Author(s):  
Kevin S. McGrew
Keyword(s):  
School Psychologists ◽  
Cognitive Abilities ◽  
Self Regulation ◽  
Chc Theory ◽  
Specific Domain ◽  
Self Regulated Learning ◽  
Domain Specific ◽  
Readiness To Learn ◽  
The Mind ◽  
Motivation Model

The Cognitive-Affective-Motivation Model of Learning (CAMML) is a proposed framework for integrating contemporary motivation, affective (Big 5 personality) and cognitive (CHC theory) constructs in the practice of school psychologists (SPs). The central tenet of this article is that SPs need to integrate motivation alongside affective and cognitive constructs vis-à-vis an updated trilogy-of-the-mind (cognitive, conative, affective) model of intellectual functioning. CAMML builds on Richard Snow’s seminal research on academic aptitudes—which are not synonymous with cognitive abilities. Learning aptitude complexes are academic domain-specific cognitive abilities and personal investment mechanisms (motivation and self-regulation) that collectively produce a student’s readiness to learn in a specific domain. CAMML incorporates the “crossing the Rubicon” commitment pathway model of motivated self-regulated learning. It is recommended SPs take a fresh look at motivation theory, constructs, and research, embedded in the CAMML aptitude framework, by going back-to-the-future guided by the wisdom of giants from the field of cognition, intelligence, and educational psychology.

scholarly journals L’autorégulation conjointe de la cognition et des émotions : quel impact sur les apprentissages ?

2015 ◽  
Vol 12 (1) ◽  
pp. 82-103 ◽  
Author(s):  
Bastien Wagener
Keyword(s):  
Problem Solving ◽  
Self Regulation ◽  
Global Scale ◽  
Specific Situation ◽  
Self Awareness ◽  
Self Regulated Learning ◽  
Positive Effects ◽  
Holistic Approaches ◽  
Key Aspects ◽  
The Mind

Les apprentissages consistent à résoudre des problèmes et à acquérir de nouvelles connaissances et compétences par le biais d’un ensemble de processus relevant de l’autorégulation. Deux aspects principaux rentrent en ligne de compte lorsque l’on cherche à améliorer la résolution de problèmes : la dimension émotionnelle et la métacognition. Les émotions, en tant que réactions organisées et utiles à une situation donnée, peuvent être tour à tour un atout ou un handicap lorsqu’il s’agit d’apprendre. Par ailleurs, la métacognition est constituée d’un ensemble de processus et de savoirs qui s’articulent autour de la prise de conscience et de la régulation de son propre fonctionnement, qu’il soit cognitif ou émotionnel. Grâce aux pratiques de l’attention (PA), issues de traditions permettant un travail sur la conscience et la régulation psychologique et physiologique, il est possible d’agir conjointement sur les cognitions et les émotions. Plusieurs travaux ont montré les nombreux bénéfices que présentent de telles approches et nous constatons également que les effets positifs sur l’autorégulation commencent à être de plus en plus étayés. Nous proposons donc de nouvelles approches holistiques permettant un travail global sur l’autorégulation qui prendraient en compte le traitement métacognitif des sphères cognitive et émotionnelle au bénéfice des apprenants. Simultaneous self-regulation of cognition and emotions and its consequences on learning Abstract: The learning process relies on problem-solving activities and the acquisition of knowledge and skills through self-regulation. Emotions and metacognitions are some of the key aspects that allow the improvement of problem-solving. The emotional dimension consists of structured and useful reactions in regard to a specific situation. Emotions can either be an asset or a disadvantage when one is involved in a learning situation. As for metacognition, it’s a compound of processes and knowledge (of cognitive or emotional nature) connected through self-regulation and self-awareness. Thanks to attentional practices (AP), one can regulate both cognitions and emotions. These AP come from various traditions focused on the exploration of the mind and self-regulation of psychological and physiological activities. Many studies show the positive effects of such practices on health, and some recent studies also report improvements in self-regulation thanks to AP. In this paper, we suggest that the creation of new holistic approaches would allow us to work on metacognition and emotions on a global scale, in order to improve the ability of individuals to engage in self-regulated learning efficiently.

Clarifying the Connections Among Giftedness, Metacognition, Self-Regulation, and Self-Regulated Learning: Implications for Theory and Practice

2018 ◽  
Vol 63 (2) ◽  
pp. 102-119 ◽  
Author(s):  
Ernestina Oppong ◽  
Bruce M. Shore ◽  
Krista R. Muis
Keyword(s):  
Gifted Education ◽  
Self Regulation ◽  
Theory And Practice ◽  
Social Emotional ◽  
Education Practice ◽  
Self Regulated Learning ◽  
Construction Of Knowledge ◽  
Regulated Learning ◽  
The Individual ◽  
The Mind

The concept of giftedness has historically been shaped by theories of IQ, creativity, and expertise (including early conceptions of metacognition). These theories focus within the mind of the individual learner. Social, emotional, and motivational qualities of giftedness were treated as add-ons, not part of the core construct. This created misalignment with the social construction of knowledge—a position widely supported in gifted education practice. Newer, broader conceptions of metacognitive, self-regulated, and self-regulated learning processes have garnered interest. However, because these theories borrowed language from each other and earlier theories, assigning new meanings to old constructs, confusion arose about how to distinguish each of these three theories from each other or apply them to instruction. This article distinguishes among metacognition, self-regulation, and self-regulated learning, relating each to notions of giftedness, highlighting implications for practice, and especially highlighting self-regulated learning as a valuable contributor to understanding giftedness and designing instruction in gifted education.

Development of A Self – Regulation Package For Academic Procrastination and Evaluation of Its Effectiveness

2013 ◽  
Vol 4 (1) ◽  
pp. 189-198
Author(s):  
Hoora Motie ◽  
Mahmood Heidari ◽  
Mansooreh Alsadat Sadeghi
Keyword(s):  
School Psychologists ◽  
Group Discussion ◽  
Self Regulation ◽  
The Self ◽  
Academic Procrastination ◽  
Self Regulated Learning ◽  
School Settings ◽  
Regulatory Failure ◽  
And Control ◽  
Experimental Group

Background: Procrastination is a common phenomenon that is mainly observed in school settings. Recognized as a self-regulatory failure, procrastination is believed to adversely affect students’ academic achievements. Aim: To develop a self-regulation package in order to predict academic procrastination, and to evaluate its effectiveness. The package was developed from 3 sources: Self-regulation components predicting academic procrastination developed in a previous study, opinions of psychologists and teachers contacted during the study, and the literature. The package helped students in the following ways: to recognize the reasons for their academic procrastination; to improve their motivation to decrease academic procrastination; to learn how to set goals and how. to organize their lessons; to use metacognitive strategies to manage time/ study environment and to regulate their efforts. Methods: Sixty-six students were randomly assigned to experimental (n=33) and control (n=33) groups. The students in the experimental group were taught the self-regulation package over ten sessions. To evaluate the effectiveness of the package, all students were asked to complete the Motivated Strategies For Learning questionnaire (MSLQ) and the Procrastination Assessment Scale-Student (PASS) before, immediately after and 21 days after instructions with the self-regulation package. Results: The mixed ANOVA showed statistically significant (p <0.001) effectiveness of self-regulation package for all subscales of academic procrastination in the experimental group. Discussion: The findings are discussed with regard to prior research on self-regulated learning and procrastination. Implications for school psychologists and teachers also are presented and discussed.

scholarly journals Undergraduate students’ metacognition of learning (with the main focus on students with different levels of mental self-regulation)

2020 ◽  
Vol 10 (5) ◽  
pp. 104-118
Author(s):  
Ekaterinа Igorevna Perikova ◽  
◽  
Valentina Mihailovna Byzova ◽  
Keyword(s):  
Undergraduate Students ◽  
Cognitive Abilities ◽  
Self Regulation ◽  
Metacognitive Awareness ◽  
Short Version ◽  
Self Regulated Learning ◽  
Wide Range ◽  
Emotional Intelligence Inventory ◽  
The Relationship ◽  
Different Levels

Introduction. A number of researchers have reported the influence of metacognition and self-regulation on learning and academic performance. However, to date there has been little agreement on how these processes are related to each other. This study is aimed at identifying the relationship between metacognition and mental self-regulation of learning, as well as comparing the components of metacognitive awareness among students with different levels of mental self-regulation. Materials and Methods. A theoretical framework of this study included J. Flavell and A. Brown’s Metacognition Theory; Konopkin’s Structural-Functional Approach to Studying Conscious Self-Regulation and B. Zimmerman’s Self-Regulated Learning Theory. The study used the following psychological testing techniques: (a) V. Morosanova’s Style of Behaviour self-regulation questionnaire, (b) G. Schraw & R. Dennison’s Metacognitive Awareness Inventory (short version) adapted by Perikova and Byzova, (c) E. Y. Mandrikova’s Self-regulation questionnaire, (d) D. V. Lyusin’s Emotional intelligence inventory, (e) D. A. Leontiev’s Differential reflexivity diagnostic. The sample consisted of 186 students of St. Petersburg State University aged 19,51±1,39 years. Results. The results indicate a wide range of relationships between mental self-regulation and metacognitive, cognitive, motivational and emotional components. Self-regulation is primarily linked with metacognitive processes of control and regulation of cognition, as well as cognition management. Metacognitive awareness of general and individual patterns, cognitive abilities and strategies are included in the process of self-regulation to a lesser extent. However, the results of factor analysis and regression analysis indicate that metacognition components did not affect self-regulation. Analysis of the variance confirmed that individuals with a low level of self-regulation demonstrate significantly less pronounced metacognitive, motivational and emotional components. Conclusions. The study demonstrates the systemic nature of the relationship between mental self-regulation and metacognitive components, as well as cognitive, motivational and emotional components.

Automatic construction of academic profile: A case of information science domain

2021 ◽  
pp. 016555152199804
Author(s):  
Qian Geng ◽  
Ziang Chuai ◽  
Jian Jin
Keyword(s):  
Information Science ◽  
Binary Classification ◽  
Learning To Rank ◽  
Semantic Distance ◽  
Background Information ◽  
Training Dataset ◽  
Initial Vector ◽  
Specific Domain ◽  
Adaboost Algorithm ◽  
Domain Specific

To provide junior researchers with domain-specific concepts efficiently, an automatic approach for academic profiling is needed. First, to obtain personal records of a given scholar, typical supervised approaches often utilise structured data like infobox in Wikipedia as training dataset, but it may lead to a severe mis-labelling problem when they are utilised to train a model directly. To address this problem, a new relation embedding method is proposed for fine-grained entity typing, in which the initial vector of entities and a new penalty scheme are considered, based on the semantic distance of entities and relations. Also, to highlight critical concepts relevant to renowned scholars, scholars’ selective bibliographies which contain massive academic terms are analysed by a newly proposed extraction method based on logistic regression, AdaBoost algorithm and learning-to-rank techniques. It bridges the gap that conventional supervised methods only return binary classification results and fail to help researchers understand the relative importance of selected concepts. Categories of experiments on academic profiling and corresponding benchmark datasets demonstrate that proposed approaches outperform existing methods notably. The proposed techniques provide an automatic way for junior researchers to obtain organised knowledge in a specific domain, including scholars’ background information and domain-specific concepts.

scholarly journals The Role of Mental Effort in Fostering Self-Regulated Learning with Problem-Solving Tasks

2020 ◽  
Vol 32 (4) ◽  
pp. 1055-1072 ◽  
Author(s):  
Tamara van Gog ◽  
Vincent Hoogerheide ◽  
Milou van Harsel
Keyword(s):  
Problem Solving ◽  
Self Regulation ◽  
Mental Effort ◽  
Future Research ◽  
Task Sequence ◽  
Self Monitoring ◽  
Self Regulated Learning ◽  
Regulated Learning ◽  
And Mathematics

Abstract Problem-solving tasks form the backbone of STEM (science, technology, engineering, and mathematics) curricula. Yet, how to improve self-monitoring and self-regulation when learning to solve problems has received relatively little attention in the self-regulated learning literature (as compared with, for instance, learning lists of items or learning from expository texts). Here, we review research on fostering self-regulated learning of problem-solving tasks, in which mental effort plays an important role. First, we review research showing that having students engage in effortful, generative learning activities while learning to solve problems can provide them with cues that help them improve self-monitoring and self-regulation at an item level (i.e., determining whether or not a certain type of problem needs further study/practice). Second, we turn to self-monitoring and self-regulation at the task sequence level (i.e., determining what an appropriate next problem-solving task would be given the current level of understanding/performance). We review research showing that teaching students to regulate their learning process by taking into account not only their performance but also their invested mental effort on a prior task when selecting a new task improves self-regulated learning outcomes (i.e., performance on a knowledge test in the domain of the study). Important directions for future research on the role of mental effort in (improving) self-monitoring and self-regulation at the item and task selection levels are discussed after the respective sections.

scholarly journals The Effect Of Problem Based Learning And Self-Assessment On Students’ Writing Competency And Self-Regulated Learningm

2018 ◽  
Vol 42 ◽  
pp. 00036
Author(s):  
I Putu Suyoga Dharma ◽  
Pande Agus Adiwijaya
Keyword(s):  
Significant Interaction ◽  
Self Regulation ◽  
Problem Based Learning ◽  
Teaching Model ◽  
Self Assessment ◽  
Significance Level ◽  
Self Regulated Learning ◽  
Writing Competency ◽  
Regulated Learning

This experimental study aimed at investigating the effect of Problem Based Learning (PBL) and self-assessment (SA) on students’ writing competency and self-regulated learning in Tabanan Regency. This research applied 2x2 factorial design. 96 students were selected as sample through random sampling. Data were collected by test (writing competency) and questionnaire (self-regulation). Students’ writings were scored by analytical scoring rubric. The obtained data were analyzed statistically by MANOVA at 5% significance level. This research discovers: 1) there is a significant effect of PBL which occurs simultaneously and separately on students’ writing competency and self-regulated learning, 2) there is a significant effect of SA which ocurs simultaneously and separately on students’ writing competency and self-regulated learning, 3) there is a significant interaction between teaching model and assessment type on students’ writing competency and self-regulated learning which occurs simultaneously, 4) there is no significant interaction between teaching model and assessment type on students’ writing competency, and 5) there is a significant interaction between teaching model and assessment type on students’ self-regulated learning. This research results implies that PBL and SA should be applied in instruction process as a way to improve the quality of students’ writing competency and self-regulated learning.

scholarly journals Training Self-Regulated Learning in the Classroom: Development and Evaluation of Learning Materials to Train Self-Regulated Learning during Regular Mathematics Lessons at Primary School

2012 ◽  
Vol 2012 ◽  
pp. 1-14 ◽  
Author(s):  
Manuela Leidinger ◽  
Franziska Perels
Keyword(s):  
Primary School ◽  
Self Regulation ◽  
The Self ◽  
Structured Learning ◽  
Process Data ◽  
Learning Materials ◽  
Self Regulated Learning ◽  
Powerful Learning ◽  
Regulated Learning ◽  
Evaluation Of Learning

The aim of the intervention based on the self-regulation theory by Zimmerman (2000) was to promote a powerful learning environment for supporting self-regulated learning by using learning materials. In the study, primary school teachers were asked to implement specific learning materials into their regular mathematics lessons in grade four. These learning materials focused on particular (meta)cognitive and motivational components of self-regulated learning and were subdivided into six units, with which the students of the experimental group were asked to deal with on a weekly basis. The evaluation was based on a quasiexperimental pre-/postcontrol-group design combined with a time series design. Altogether, 135 fourth graders participated in the study. The intervention was evaluated by a self-regulated learning questionnaire, mathematics test, and process data gathered through structured learning diaries for a period of six weeks. The results revealed that students with the self-regulated learning training maintained their level of self-reported self-regulated learning activities from pre- to posttest, whereas a significant decline was observed for the control students. Regarding students’ mathematical achievement, a slightly greater improvement was found for the students with self-regulated learning training.

Similarity of Computations Across Domains Does Not Imply Shared Implementation: The Case of Language Comprehension

2021 ◽  
Vol 30 (6) ◽  
pp. 526-534
Author(s):  
Evelina Fedorenko ◽  
Cory Shain
Keyword(s):  
Language Processing ◽  
Language Comprehension ◽  
Fluid Intelligence ◽  
Linguistic Knowledge ◽  
Domain Specific ◽  
Cognitive Operations ◽  
High Level ◽  
General Circuits ◽  
The Mind ◽  
Language Network

Understanding language requires applying cognitive operations (e.g., memory retrieval, prediction, structure building) that are relevant across many cognitive domains to specialized knowledge structures (e.g., a particular language’s lexicon and syntax). Are these computations carried out by domain-general circuits or by circuits that store domain-specific representations? Recent work has characterized the roles in language comprehension of the language network, which is selective for high-level language processing, and the multiple-demand (MD) network, which has been implicated in executive functions and linked to fluid intelligence and thus is a prime candidate for implementing computations that support information processing across domains. The language network responds robustly to diverse aspects of comprehension, but the MD network shows no sensitivity to linguistic variables. We therefore argue that the MD network does not play a core role in language comprehension and that past findings suggesting the contrary are likely due to methodological artifacts. Although future studies may reveal some aspects of language comprehension that require the MD network, evidence to date suggests that those will not be related to core linguistic processes such as lexical access or composition. The finding that the circuits that store linguistic knowledge carry out computations on those representations aligns with general arguments against the separation of memory and computation in the mind and brain.

Examining the role of passion in university students’ academic emotions, self-regulated learning and well-being

2021 ◽  
pp. 147797142110373
Author(s):  
Anna Sverdlik ◽  
Sonia Rahimi ◽  
Robert J Vallerand
Keyword(s):  
University Students ◽  
Adult Students ◽  
Self Regulation ◽  
Well Being ◽  
Future Research ◽  
Academic Emotions ◽  
Psychological Well Being ◽  
Self Regulated Learning ◽  
Regulated Learning

University students’ passion for their studies has been previously demonstrated to be important for both their academic performance and their personal well-being. However, no studies to date have explored the role of passion for one’s studies on both academic and personal outcomes in a single model. The present research sought to determine the role of passion in adult university students’ self-regulated learning and psychological well-being (Study 1), as well as the process by which passion shapes these outcomes, namely academic emotions, in Study 2. It was hypothesised that harmonious passion would positively predict both self-regulated learning and psychological well-being in Study 1. Furthermore, the mediating role of academic emotions between passion and outcomes was tested using a prospective design over time in Study 2. Results provided support for the proposed model. Implications for future research and practice focusing on the role of passion in facilitating adaptive emotions, use of self-regulation and well-being in adult students are discussed.

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