Cognitive Load Theory: Advances in Research on Worked Examples, Animations, and Cognitive Load Measurement

The contributions to this special issue document some recent advances of cognitive load theory, and are based on contributions to the Third International Cognitive Load Theory Conference (2009), Heerlen, The Netherlands. The contributions focus on developments in example-based learning, amongst others on the effects of integrating worked examples in cognitive tutoring systems; specify the effects of transience on cognitive load and why segmentation may help counteract these effects in terms of the role of time in working memory load; and discuss the possibilities offered by electroencephalography (EEG) to provide a continuous and objective measure of cognitive load. This article provides a short introduction to the contributions in this issue.     

Managing cognitive load during document-based learning

Designers of interactive learning environments face the issue of managing the learner's cognitive load, reducing irrelevant sources while optimizing useful sources of load. I propose a conceptual framework aimed at organizing the contributions of the papers presented in this special issue. The framework identifies three main dimensions, namely individual, task and environment, which may have specific or combined effects on the amount and type of cognitive load experienced during learning activities. I summarize some of the findings presented in the special issue with respect to each of these dimensions. Then I discuss some limitations of the studies and some perspectives for further research in the domain. I emphasize the need to control learners’ level of familiarity with the task setting and environment features, not just their prior knowledge of the content area, in order to obtain reliable assessments of cognitive load and learning outcomes.     

Advances in research on classroom dialogue: learning outcomes and assessments

The goal of this special issue is to examine how certain modes of classroom dialogue might contribute to students' learning outcomes. The articles in this special issue share the idea of classroom talk as a problem-oriented dialogue. In other words, an interactional configuration based on exchanges among students and teachers that go beyond the predominantly monologic approaches of classroom talk. In each of the contributions to this special issue, different types of learning outcomes were studied as a result of specific ways of orchestrating classroom dialogue. All in all, the studies in this special issue yield a picture of the field as a productive research area: they provide evidence for the plausibility of the assumption that dialogic orchestrations of classroom talk may produce various desired learning and developmental outcomes in students, depending on what outcomes we want to articulate, and how they are assessed. Although the studies in this special issue yield promising results for future improvements of classroom practice more (preferably longitudinal) research is required.     

Measuring Reading Comprehension

The five articles in this special issue are a blend of experimental and correlational approaches that exemplify advances in contemporary approaches to assessment of reading comprehension. They illustrate how inferences about reading comprehension are determined in part by the material presented for comprehending and the format that is used for assessing comprehension of the material. In the future, the approaches to measuring reading comprehension in these articles could be further integrated by perspectives that cut across particular approaches to measurement and begin to utilize multimethod modeling of the latent variables that underlie different tests of reading comprehension.     

Editorial: e‐Research for education: Applied,methodological and critical perspectives

This special issue brings together a set of contributions that represent and explore the state of the art regarding the development and application of digital technology‐enhanced research approaches in educational research—e‐research for education. Over the recent years, digital technologies have enhanced various aspects of scholarly practices, such as data collection and analysis, research collaboration, and publishing. New technology‐enhanced research approaches have been emerging in a number of educational research domains, such as learning analytics, educational data mining, digital ethnography and educational informatics. Although the potential of digital approaches has been generally acknowledged, many overarching conceptual and methodological questions remain unexplored and under‐theorised. This special issue provides a landmark collection that synthesises some important empirical and methodological advances in this research field, including methodologically innovative case studies and critical analyses of overarching epistemological, methodological and practical issues that inevitably will shape future developments of this research field.     

Defining and Measuring Engagement and Learning in Science: Conceptual,Theoretical, Methodological,and Analytical Issues

Engagement is one of the most widely misused and overgeneralized constructs found in the educational, learning, instructional, and psychological sciences. The articles in this special issue represent a wide range of traditions and highlight several key conceptual, theoretical, methodological, and analytical issues related to defining and measuring engagement. All the approaches exemplified by the contributors show different ways of conceptualizing and measuring engagement and demonstrate the strengths and weaknesses of each method to significantly augment our current understanding of engagement. Despite the numerous issues raised by the authors of this special issue and in my commentary, I argue that focusing on process data will lead to advances in models, theory, methods, analytical techniques, and ultimately instructional recommendations for learning contexts that effectively engage students.     

Design,development, and implementation of electronic learning environments for collaborative learning

Developments in society and business, and related changes in higher education and lifelong learning, require educators and educational designers or technologists to rethink education. Examples of such changes are the growing importance of achieving complex learning, the integration of learning and work in education, and the need for improved flexibility with regard to time, place, and individual needs. These changes cannot simply be responded to by adding technological solutions implemented according to existing educational approaches. Instead, an integrated view of e-learning is necessary, characterized by the combination of pedagogical, technical, social, and organizational factors. This two-part special issue elaborates on the different characteristics of integrated e-learning, from design through future topics for research. He would like to give special thanks to Jan Elen and Brent Wilson, who took on the task of reviewing and discussing all of the contributions, both at AECT 2003 in Anaheim and for this issue, and J. Michael Spector, Development Editor of this journal, for his faith in all of us.     

Complex Systems Approaches to Educational Research: Introduction to the Special Issue

Abstract

To explore the movement toward increased complex systems (CS) research in education, this special issue of the Journal of Experimental Education was developed to identify some under-examined places where CS approaches have advanced research. The articles provide empirical examples of research leveraging methods and analyses from complexity science. In this introduction article to the special issue, we discuss the authors’ contributions to defining and explicating concepts and methods that fall under the umbrella of CS perspectives and how these methods were used to investigate complex processes in their topics of study. The articles capture the goal of the special issue to demonstrate how the research questions framed by CS assumptions can change our expectations about the very nature of the processes under study in education. We then take a more global perspective and acknowledge the commonalities amongst the papers, including (a) the reliance on intensive data to answer research questions, and (b) the use of dynamic approaches that yield findings about the stability and change of these systems and phenomena.     

Mobile technology,learning, and achievement: Advances in understanding and measuring the role of mobile technology in education

Studying mobile learning – the use of personal electronic devices to engage in learning across multiple contexts via connections to media, educators, peers, experts, and the larger world – is a relatively new academic enterprise. In this special issue, we interrogated the promise and unexamined expectations of mobile learning, the theories and ideas developing around it, and the devices that afford it. The articles introduce mobile and wearable technologies as key components of empirical research and demonstrate ways that learning conducted with such devices (1) affects the process and products of learning via interactions with other psychological constructs; (2) affords new opportunities to directly influence learning process or outcomes; and (3) provides opportunities to collect previously unobtainable data that improve understanding and modeling of the learning process. In this introduction, we overview the emergence of mobile learning theory and its contemporary conceptualization. Then we highlight ways that mobile technologies can be used to enhance learning processes and an understanding of them. All special issue contributors conceptualize and align their work with both psychological theories of learning and instruction as well as emerging theories of mobile learning. The commentary authors appraise mobile learning research critically and analytically, and recommend ways mobile learning theory might build upon research methodology and knowledge grounded empirically in psychological and sociocultural theories of learning. Overall, we believe this special issue achieved our goal to produce a balanced consideration that highlights the advancements in learning and learning theory mobile devices might afford, and to temper any premature enthusiasm about these potential benefits.     

Bridging Cognitive Load and Self-Regulated Learning Research: A complementary approach to contemporary issues in educational research

The aim of this Introduction to the Special Issue ‘Bridging Cognitive Load and Self-Regulated Learning Research’ is to explore how cognitive load theory, which is particularly relevant for how learners deal with complex information, and self-regulated learning theory, which is particularly relevant for how learners use information to monitor and control their learning, can be combined into one joint research paradigm that is relevant for contemporary and future developments in education. The first two sections introduce cognitive load theory and self-regulated learning theory. The third section discusses the main similarities and differences between the theories, and describes how the cue-utilization framework can be used as the basis for a joint research paradigm. The main idea postulated is that new instructional methods should help learners identify diagnostic cues in available information that provide an accurate indication of where learners stand in relation to criterion task performance. Use of these diagnostic cues when monitoring learning will lead to better regulation of learning activities and of mental resources allocated, and thus to more efficient learning and higher learning outcomes.In the fourth section, the six studies and two commentaries presented in this special issue are positioned within this paradigm. In the fifth and final section, a common research agenda based on the joint CLT-SRL paradigm is sketched and its relevance for future developments is explained. The studies presented in this special issue and the two commentaries, which complete the Special Issue, should be seen as a very first step in executing this research agenda.     

Co-regulation of learning in computer-supported collaborative learning environments: a discussion

This discussion paper for this special issue examines co-regulation of learning in computer-supported collaborative learning (CSCL) environments extending research on self-regulated learning in computerbased environments. The discussion employs a socio-cognitive perspective focusing on social and collective views of learning to examine how students co-regulate and collaborate in computer-supported inquiry. Following the review of the articles, theoretical, methodological and instructional implications are discussed: Future research directions include examining the theoretical nature of collective regulation and social metacognition in building models of co-regulated learning; expanding methodological approaches using trace data and multiple measures for convergence and construct validity; and conducting instructional experiments to test and to foster the development of co-regulated learning in computer-supported collaborative inquiry.     

Toward an Integrated Model of Student Learning in the College Classroom

In the last special issue devoted to this topic, Pintrich (Educ Psychol Rev 16:385–407, 2004) provided an in-depth critique of his conceptual framework on self-regulated learning (SRL), comparing and contrasting it to Biggs’ student approaches to learning (SAL) perspective. Since then, there have been a number of advances in the study of learning in higher education. To that end, the purpose of this article is to provide a critical analysis of three distinct yet overlapping streams of research in higher education, namely SRL, patterns of learning (including SAL), and student engagement. The theoretical bases of each of these approaches are outlined followed by a review of recent trends. Finally, an integrative model of student learning is proposed, which draws on the strengths of each of these traditions.     

Theory,Method, and Analysis in Research on the Relations Between Peer Collaboration and Cognitive Development

It is important to make explicit the theoretical framework within which research is conducted because one's choice of theory constrains the choice of what to study and which methods to use for doing research. From a perspective informed by the writings of T. Kuhn (1962), S. C. Pepper (1942), and L. T. Winegar (1997), the author assessed the extent to which each of the articles in this special issue related theory to methods and to analysis. The author identified limitations in each of the articles, caused primarily by the use of methods or analyses that did not seem well suited to the theory of choice. However, each of the articles also had great strengths, and, taken together, they further our understanding of the complexity of the relationships between peer collaboration and cognitive development. They also provide some stimulating and productive ways of studying the collaborative processes themselves.     

The Challenges of Defining and Measuring Student Engagement in Science

Engagement is one of the hottest research topics in the field of educational psychology. Research shows that multifarious benefits occur when students are engaged in their own learning, including increased motivation and achievement. However, there is little agreement on a concrete definition and effective measurement of engagement. This special issue serves to discuss and work toward addressing conceptual and instrumentation issues related to engagement, with particular interest in engagement in the domain of science learning. We start by describing the dimensional perspective of engagement (behavioral, cognitive, emotional, agentic) and suggest a complementary approach that places engagement instrumentation on a continuum. Specifically, we recommend that instrumentation be considered on a “grain-size” continuum that ranges from a person-centered to a context-centered orientation to clarify measurement issues. We then provide a synopsis of the articles included in this special issue and conclude with suggestions for future research.     

Explorations of relationships among learners, tasks, and learning

Based on a critical re-analysis of cognitive load theory (CLT), Schnotz and Kürschner identified the need for research on more sensitive ways of assessing learner characteristics, both prior to and during instruction, in order to understand learning processes and outcomes. One emergent theme of the papers in this special issue is that the “same” learning environment is differentially demanding and produces different results depending on characteristics of the learners, most importantly their knowledge in the task domain. These findings indicate that to optimize learning outcomes, theories of instructional design and learning need to be more adaptive and reflect the nuances of interactions among learners, tasks, and instructional supports.     

Mathematical disabilities: Reflections on cognitive,neuropsychological, and genetic components

The collection of articles in this special issue and related studies over the past decade provides a fine example of the substantial progress that has been made in our understanding and remediation of mathematical learning disabilities and difficulties since 1993 (Geary, 1993). The originally proposed procedural and retrieval deficits have been supported and a number sense deficit has been identified. There is evidence for visuospatial contributions to some aspects of mathematical learning, but identification of a core visuospatial deficit underlying some forms of mathematical learning disabilities and difficulties has been elusive. The contributions of working memory to the development and expression of these deficits is more nuanced than I originally proposed as are the brain systems supporting mathematical learning. Although much has been learned about children's difficulties in learning mathematics, but there is just as much and likely more than remains to be discovered.     

Cognitive and affective processes in multimedia learning

This special section focuses on cognitive and affective processes in multimedia learning in a range of learning domains. Expanding previous research that has taken a predominantly cognitive perspective of multimedia learning, recent studies have begun to consider affective aspects of multimedia learning with the aim of integrating emotion, motivation, and other affective variables into cognitive processing models. The articles included in this special section are examples of the various ways in which the cognitive perspective can be enhanced by taking affective aspects of learning into account. Investigations range from the study of confusion as an affective state that can be beneficial to learning, and the consideration of the potential distracting or motivating function of decorative illustrations, to an inquiry into how visual design can induce positive emotions in learners. The results of the studies included in this section are in line with Moreno's Cognitive-Affective Theory of Learning with Media (CATLM; Moreno, 2006) and show how emotion and interest facilitate cognitive processing and improve cognitive and affective outcomes.     

Cognitive Load Theory: A Broader View on the Role of Memory in Learning and Education

According to cognitive load theory (CLT), the limitations of working memory (WM) in the learning of new tasks together with its ability to cooperate with an unlimited long-term memory (LTM) for familiar tasks enable human beings to deal effectively with complex problems and acquire highly complex knowledge and skills. With regard to WM, CLT has focused to a large extent on learning task characteristics, and to a lesser extent on learner characteristics to manage WM load and optimize learning through instructional design. With regard to LTM, explanations of human learning and cognition have mainly focused on domain-general skills, instead of domain-specific knowledge held in LTM. The contributions to this special issue provide a broader cognitive load view on the role of memory in learning and education by presenting the historical roots and conceptual development of the concept of WM, as well as the theoretical and practical implications of current debates about WM mechanisms (Cowan 2014), by presenting an updated model of cognitive load in which the physical learning environment is considered a distinct causal factor for WM load (Choi et al. 2014), by an experimental demonstration of the effects of persistent pain on the available WM resources for learning (Smith and Ayres 2014), and by using aspects of evolutionary educational psychology to argue for the primacy of domain-specific knowledge in human cognition (Tricot and Sweller 2014).     

The effects of constructivist learning environments: a commentary

This special issue on the effects of constructivist learning environments is based on a symposium organized during the last annual meeting of the American Educational Research Association in Chicago. The studies in this issue not only provide an overview of the multitude of forms a constructivist learning environment can take, they also provide the reader with an overview of recent advances in this domain of research. The present discussion article provides a critical reflection on the studies in this special issue and tries to identify their prospects and limitations.