Bio: Eduardo Cascallar is an academic researcher from Katholieke Universiteit Leuven. The author has contributed to research in topics: Psychology & Academic achievement. The author has an hindex of 12, co-authored 22 publications receiving 1296 citations.
Abstract: In this article, we address four main questions, including: What is self-regulated learning for? What key strategies do students need to guide and direct their own learning process? What cues in the learning environment trigger self-regulation strategies? What can teachers do to help student to self-regulate their learning, motivation, and effort in the classroom? We illustrate that answers to these questions have changed over time and that changing conceptualizations of the self-regulation process have influenced the assessment tools that were used. We also point to changing classroom conditions as a factor that has affected the assessment of self-regulation. Finally, we formulate some questions that need to be tackled in research on self-regulation and introduce the articles and commentaries in the special issue that provide some cutting-edge work on the use of assessment to register self- regulation over time.
TL;DR: In this paper, a meta-analysis reveals a positive effect of cooperative learning on achievement and attitudes in primary, secondary or tertiary education conducted in real-life classrooms, and the authors investigate the effect of the study domain, the age level of the students and the culture in which the study took place.
Abstract: One of the major conclusive results of the research on learning in formal learning settings of the past decades is that cooperative learning has shown to evoke clear positive effects on different variables. Therefore this meta-analysis has two principal aims. First, it tries to replicate, based on recent studies, the research about the main effects of cooperative learning on three categories of outcomes: achievement, attitudes and perceptions. The second aim is to address potential moderators of the effect of cooperative learning. In total, 65 articles met the criteria for inclusion: studies from 1995 onwards on cooperative learning in primary, secondary or tertiary education conducted in real-life classrooms. This meta-analysis reveals a positive effect of cooperative learning on achievement and attitudes. In the second part of the analysis, the method of cooperative learning, study domain, age level and culture were investigated as possible moderators for achievement. Results show that the study domain, the age level of the students and the culture in which the study took place are associated with variations in effect size.
01 Jan 2003
TL;DR: In this article, a framework for Project-Based Assessment in Science Education is presented, along with a review of the role of self-and peer-assessment in higher education.
Abstract: Contributors. Acknowledgements. Preface. The Era of Assessment Engineering: Changing Perspectives on Teaching and Learning and the Role of New Modes of Assessment M. Segers, F. Dochy, E. Cascallar. New Insights into Learning and Teaching and their Implications for Assessment M. Birenbaum. Evaluating the Consequential Validity of New Modes of Assessment: The Influence of Assessment on Learning, Including Pre-, Post-, and True Assessment Effects S. Gielen, F. Dochy, S. Dierick. Self and Peer Assessment in School and University: Reliability, Validity and Utility K. Topping. A framework for Project-Based Assessment in Science Education Y. Dori. Evaluating the OverAll Test: Looking for Multiple Validity Measures M. Segers. Assessment for Learning: Reconsidering Portfolios and Research Evidence A. Davies, P. LeMahieu. Students' Perceptions about New Modes of Assessment in Higher Education: a Review K. Struyven, F. Dochy, S. Janssens. Assessment of Students' Feelings of Autonomy, Competence and Social Relatedness: A New Approach to Measuring the Quality of the Learning Process through self- and Peer Assessment M. Boekaerts, A. Minnaert. Setting Standards in the Assessment of Complex Performances: The Optimized Extended-Response Standard Setting Method A. Cascallar, E. Cascallar. Assessment and Technology. H. Braun. Index.
TL;DR: In this paper, the authors investigated the direct and indirect influence of motivation for learning on students' approaches to learning and found that the greater the extent to which students are autonomously motivated, the less they perceive that they have a lack of information and the less inclined they are inclined to adopt a surface approach to learning.
Abstract: The present study investigates the direct and indirect influence of motivation for learning, as understood by the self‐determination theory, on students' approaches to learning. Concerning the direct influence of motivation, results show that autonomous motivation is positively related to a deep approach to learning and negatively to a surface approach. Motivation also has an indirect effect on students' approaches to learning through the perceptions of workload and task complexity, in particular through the perception of a lack of information. The greater the extent to which students are autonomously motivated, the less they perceive that they have a lack of information and the less they are inclined to adopt a surface approach to learning.
TL;DR: A review of the literature reveals a very diverse set of models and assessment instruments, many attempting to establish constructs with serious definitional problems, and conceptual overlaps as discussed by the authors, and it is necessary then to establish their validity and the exact nature of their participation, as well as a clear differentiation between them.
Abstract: The role of assessment is central to the current work in the field of self-regulation research, to the conceptualizations derived from empirical work, and to the operationalisation of its concepts in individual and classroom implementations. The various instantiations of the concept of self-regulation, all presuppose a detailed accounting of many different components, with each of them being represented by a variety of proxy variables which can be measured to establish the appropriate level at which the individual or group in question is functioning or performing. A review of the literature reveals a very diverse set of models and assessment instruments, many attempting to establish constructs with serious definitional problems, and conceptual overlaps. It is necessary then to establish their validity and the exact nature of their participation, as well as a clear differentiation between them. The assessment instruments which have been used so far are equally diverse, addressing the demands of the various components of the self-regulation models used and the different aspects emphasized in the research, including socio-cultural, cognitive, and volitional aspects. It is essential, to study carefully the relationship between assessment and the elements of the self-regulation process. This careful analysis will lead to a refinement of the instruments used, to the development of appropriate assessment methodologies and strategies, and to a richer conceptualization of the self-regulatory process (SR) based on empirical assessment data to inform the theory and model construction.
01 Jan 2006
TL;DR: For example, Standardi pružaju okvir koje ukazuju na ucinkovitost kvalitetnih instrumenata u onim situacijama u kojima je njihovo koristenje potkrijepljeno validacijskim podacima.
Abstract: Pedagosko i psiholosko testiranje i procjenjivanje spadaju među najvažnije doprinose znanosti o ponasanju nasem drustvu i pružaju temeljna i znacajna poboljsanja u odnosu na ranije postupke. Iako se ne može ustvrditi da su svi testovi dovoljno usavrseni niti da su sva testiranja razborita i korisna, postoji velika kolicina informacija koje ukazuju na ucinkovitost kvalitetnih instrumenata u onim situacijama u kojima je njihovo koristenje potkrijepljeno validacijskim podacima. Pravilna upotreba testova može dovesti do boljih odluka o pojedincima i programima nego sto bi to bio slucaj bez njihovog koristenja, a također i ukazati na put za siri i pravedniji pristup obrazovanju i zaposljavanju. Međutim, losa upotreba testova može dovesti do zamjetne stete nanesene ispitanicima i drugim sudionicima u procesu donosenja odluka na temelju testovnih podataka. Cilj Standarda je promoviranje kvalitetne i eticne upotrebe testova te uspostavljanje osnovice za ocjenu kvalitete postupaka testiranja. Svrha objavljivanja Standarda je uspostavljanje kriterija za evaluaciju testova, provedbe testiranja i posljedica upotrebe testova. Iako bi evaluacija prikladnosti testa ili njegove primjene trebala ovisiti prvenstveno o strucnim misljenjima, Standardi pružaju okvir koji osigurava obuhvacanje svih relevantnih pitanja. Bilo bi poželjno da svi autori, sponzori, nakladnici i korisnici profesionalnih testova usvoje Standarde te da poticu druge da ih također prihvate.
01 Jan 2009
17 Jun 2005
TL;DR: In this paper, the authors present a data processing system having a business object model reflecting the data used during a business transaction, which is suitable for use across industries, across businesses, and across different departments within a business within a transaction.
Abstract: Methods and systems consistent with the present invention provide a data processing system having a business object model reflecting the data used during a business transaction. Consistent interfaces are generated from the business object model. These interfaces are suitable for use across industries, across businesses, and across different departments within a business during a business transaction.
TL;DR: The SRL models form an integrative and coherent framework from which to conduct research and on which students can be taught to be more strategic and successful in order to enhance students’ learning and SRL skills.
Abstract: Self-regulated learning (SRL) includes the cognitive, metacognitive, behavioral, motivational, and emotional/affective aspects of learning. It is, therefore, an extraordinary umbrella under which a considerable number of variables that influence learning (e.g., self-efficacy, volition, cognitive strategies) are studied within a comprehensive and holistic approach. For that reason, SRL has become one of the most important areas of research within educational psychology. In this paper, six models of SRL are analyzed and compared; that is, Zimmerman; Boekaerts; Winne and Hadwin; Pintrich; Efklides; and Hadwin, Jarvela and Miller. First, each model is explored in detail in the following aspects: (a) history and development, (b) description of the model (including the model figures), (c) empirical support, and (d) instruments constructed based on the model. Then, the models are compared in a number of aspects: (a) citations, (b) phases and subprocesses, (c) how they conceptualize (meta)cognition, motivation and emotion, (d) top–down/bottom–up, (e) automaticity, and (f) context. In the discussion, the empirical evidence from the existing SRL meta-analyses is examined and implications for education are extracted. Further, four future lines of research are proposed. The review reaches two main conclusions. First, the SRL models form an integrative and coherent framework from which to conduct research and on which students can be taught to be more strategic and successful. Second, based on the available meta-analytic evidence, there are differential effects of SRL models in light of differences in students’ developmental stages or educational levels. Thus, scholars and teachers need to start applying these differential effects of the SRL models and theories to enhance students’ learning and SRL skills.
15 May 2011
TL;DR: Self-Regulation of learning and performance has been studied extensively in the literature as mentioned in this paper, with a focus on the role of self-regulation in the development of learners' skills and abilities.
Abstract: Contents Historical, Contemporary, and Future Perspectives on Self-Regulated Learning and Performance Dale H. Schunk and Jeffrey A. Greene Section I. Basic Domains of Self-Regulation of Learning and Performance Social Cognitive Theoretical Perspective of Self-Regulation Ellen L. Usher and Dale H. Schunk Cognition and Metacognition Within Self-Regulated Learning Philip H. Winne Developmental Trajectories of Skills and Abilities Relevant for Self-Regulation of Learning and Performance Rick H. Hoyle and Amy L. Dent Motivation and Affect in Self-Regulated Learning: Does Metacognition Play a Role? Anastasia Efklides, Bennett L. Schwartz, and Victoria Brown Self-Regulation, Co-Regulation and Shared Regulation in Collaborative Learning Environments Allyson Hadwin, Sanna Jarvela, and Mariel Miller Section II. Self-Regulation of Learning and Performance in Context Metacognitive Pedagogies in Mathematics Classrooms: From Kindergarten to College and Beyond Zemira R. Mevarech, Lieven Verschaffel, and Erik De Corte Self-Regulated Learning in Reading Keith W. Thiede and Anique B. H. de Bruin Self-Regulation and Writing Steve Graham, Karen R. Harris, Charles MacArthur, and Tanya Santangelo The Self-Regulation of Learning and Conceptual Change in Science: Research, Theory, and Educational Applications Gale M. Sinatra and Gita Taasoobshirazi Using Technology-Rich Environments to Foster Self-Regulated Learning in the Social Studies Eric G. Poitras and Susanne P. Lajoie Self-Regulated Learning in Music Practice and Performance Gary E. McPherson, Peter Miksza, and Paul Evans Self-Regulation in Athletes: A Social Cognitive Perspective Anastasia Kitsantas, Maria Kavussanu, Deborah B. Corbatto, and Pepijn K. C. van de Pol Self-Regulation: An Integral Part of Standards-Based Education Marie C. White and Maria K. DiBenedetto Teachers as Agents in Promoting Students' SRL and Performance: Applications for Teachers' Dual-Role Training Program Bracha Kramarski Section III. Technology and Self-Regulation of Learning and Performance Emerging Classroom Technology: Using Self-Regulation Principles as a Guide for Effective Implementation Daniel C. Moos Understanding and Reasoning About Real-Time Cognitive, Affective, and Metacognitive Processes to Foster Self-Regulation With Advanced Learning Technologies Roger Azevedo, Michelle Taub, and Nicholas V. Mudrick The Role of Self-Regulated Learning in Digital Games John L. Nietfeld Self-Regulation of Learning and Performance in Computer-Supported Collaborative Learning Environments Peter Reimann and Maria Bannert Section IV. Methodology and Assessment of Self-Regulation of Learning and Performance Validity and the Use of Self-Report Questionnaires to Assess Self-Regulated Learning Christopher A. Wolters and Sungjun Won Capturing and Modeling Self-Regulated Learning Using Think-Aloud Protocols Jeffrey A. Greene, Victor M. Deekens, Dana Z. Copeland, and Seung Yu Assessing Self-Regulated Learning Using Microanalytic Methods Timothy J. Cleary and Gregory L. Callan Advancing Research and Practice About Self-Regulated Learning: The Promise of In-Depth Case Study Methodologies Deborah L. Butler and Sylvie C. Cartier Examining the Cyclical, Loosely Sequenced, and Contingent Features of Self-Regulated Learning: Trace Data and Their Analysis Matthew L. Bernacki Data Mining Methods for Assessing Self-Regulated Learning Gautam Biswas, Ryan S. Baker, and Luc Paquette Section V. Individual and Group Differences in Self-Regulation of Learning and Performance 26. Calibration of Performance and Academic Delay of Gratification: Individual and Group Differences in Self-Regulation of Learning Peggy P. Chen and Hefer Bembenutty 27. Academic Help Seeking as a Self-Regulated Learning Strategy: Current Issues, Future Directions Stuart A. Karabenick and Eleftheria N. Gonida 28. The Three Faces of Epistemic Thinking in Self-Regulated Learning Krista R. Muis and Cara Singh 29. Advances in Understanding Young Children's Self-Regulation of Learning Nancy E. Perry, Lynda R. Hutchinson, Nikki Yee, and Elina Maatta 30. Self-Regulation: Implications for Individuals With Special Needs Linda H. Mason and Robert Reid 31. Culture and Self-Regulation in Educational Contexts Dennis M. McInerney and Ronnel B. King