Contemporary cognitive load theory research: The good, the bad and the ugly

Kirschner, P. A., Ayres, P., & Chandler, P. (2011). Contemporary cognitive load theory research: The good, the bad and the ugly. Computers in Human Behavior, 27(1), 99-105. doi:10.1016/j.chb.2010.06.025This paper reviews the 16 contributions of the special issue entitled Current Research in Cognitive Load Theory. Each paper is briefly summarized and some critical comments made. The overall collection is then discussed in terms of the positive contributions they make to the field of learning and instruction, and cognitive load theory in particular (the good), as well as problematical issues such as unresolved explanations and conflicting results (the bad) and the special case of measuring cognitive load (the ugly)

Shared control over task selection:Helping students to select their own learning tasks

PhD Thesi

Cognitive load theory and multimedia learning, task characteristics, and learning engagement: The current state of the art

Kirschner, F., Kester, L., & Corbalan, G. (2011). Cognitive load theory and multimedia learning, task characteristics, and learner engagement: The current state of the art. Computers in Human Behavior, 27, 1-4. doi:10.1016/j.chb.2010.05.003This special issue consists of 16 empirical papers, as well as a discussion based on the Third International Cognitive Load Theory Conference held at the Open Universiteit (Heerlen, The Netherlands) in 2009. All papers focus on improving instructional design from a cognitive load theory (CLT: Sweller, 1988; Sweller, Van Merriënboer, & Paas, 1998; Van Merriënboer & Sweller, 2005) perspective. They cover a wide variety of topics in which learner characteristics, tasks characteristics, and the interaction between both are studied in, new, innovative, but also traditional ways, thereby providing an overview of the current state of the art on CLT research. The overarching goal of all studies is to gain more understanding and insight into the optimal conditions under which learning can be successful, and students will be able to apply their acquired knowledge and skills in new or familiar problem solving situations. Together, the papers comprise three ways in which this overarching goal is reached: (1) by studying multimedia learning environments, (2) by studying different characteristics of a learning task and, (3) by studying how learners can be actively engaged in the learning process. Although, the research focus of most papers fit nicely within these research topics, some overlap is inevitable. The categorization has been made on the basis of the most prominent research focus and findings of each study

Self-Efficacy Change Associated with a Cognitive Load-Based Intervention in an Undergraduate Biology Course

Cognitive load theory (CLT) holds that discovery learning and other instructional strategies imposing high levels of extraneous load on novice learners hinder learning. Such learning conditions are also associated with significant drops in persistence, a key measure of motivation. However, research within the CLT framework typically engages motivation as a necessary precursor to learning, rather than as an outcome of instruction. In this study, we examine changes in motivational beliefs as outcomes of learners\u27 cognitive processes through a CLT lens as they engage with instruction. Using a double-blind quasi-experimental design, we manipulate the level of cognitive load imposed on participants through instruction and assess changes in self-efficacy from pre-to post-intervention. In an analysis of data from students enrolled in an undergraduate biology course (n = 2078), students in the treatment condition demonstrated significantly higher performance on end-of-semester lab reports and self-efficacy measures. However, post-instruction self-efficacy was not significantly related to performance, controlling for pre-instruction self-efficacy, gender, and scientific reasoning ability. These findings introduce the possibility that the cognitive load imposed on working memory during instruction may affect motivational beliefs and provides a foundation to further explore connections between historically distinct theoretical frameworks such as CLT and social cognitive theory

The Impact of Learner Control on E-Learning Effectiveness: Towards a Theoretical Model

E-learning systems are changing education and organizational training considerably. With the advancement of online-based learning systems, learner control of the instructional process has emerged as a decisive factor inherent to technology-based learning. However, the conceptual work on the role of learner control in e-learning has not advanced sufficiently to predict how learner control impacts e-learning effectiveness. To extend the research on the role of learner control in e-learning, we derive a conceptual framework as a reference model, which is based on cognitive and motivational learning theories. We then apply our framework to review 58 articles on learner control during the period 1996-2013. Our findings reveal how different individual characteristics, as well as the characteristics of the course and learning environment moderate the impact of learner control on learning effectiveness. Our analysis provides new insight into the role of learner control for e-learning effectiveness, as well as directions for further research

A Longitudinal Study on the Effect of Hypermedia on Learning Dimensions, Culture and Teaching Evaluation

Earlier studies have found the effectiveness of hypermedia systems as learning tools heavily depend on their compatibility with the cognitive processes by which students perceive, understand and learn from complex information\ud sources. Hence, a learner’s cognitive style plays a significant role in determining how much is learned from a hypermedia learning system. A longitudinal study of Australian and Malaysian students was conducted over two semesters in 2008. Five types of predictor variables were investigated with cognitive style: (i) learning dimensions (nonlinear learning, learner control, multiple tools); (ii)\ud culture dimensions (power distance, uncertainty avoidance, individualism/collectivism, masculinity/femininity, long/short term orientation); (iii) evaluation of units; (iv) student demographics; and (v) country in which students studied. This study uses both multiple linear regression and linear mixed effects to model the relationships among the variables. The results from this study support the findings of a cross-sectional study conducted by Lee et al. (2010); in particular, the predictor variables are significant to determine students’ cognitive style

Content and Timing of Feedback in a Web-based Learning Environment::Effects on Learning as a function of prior knowledge

This study investigated the effectiveness of different types of feedback content (elaborate vs. global) and feedback timing (immediate vs. delayed) for learning about genetics in a webbased learning environment as a function of learners’ prior knowledge. It was hypothesized that learning outcomes of students with low prior knowledge would be fostered by immediate elaborate feedback, whereas those of students with more prior knowledge would be enhanced by delayed global feedback. Students’ perceptions of the feedback they received were explored. Results showed a significant positive effect of global feedback on learning outcomes for higher prior knowledge learners, although those who received elaborate feedback gave a higher appreciation rating. The findings are discussed in terms of implications for the design and delivery of feedback in web-based learning environments

Facilitating flexible problem solving: A cognitive load perspective

The development of flexible, transferable problem-solving skills is an important aim of contemporary educational systems. Since processing limitations of our mind represent a major factor influencing any meaningful learning, the acquisition of flexible problem-solving skills needs to be based on known characteristics of our cognitive architecture in order to be effective and efficient. This paper takes a closer look at the processes involved in the acquisition of flexible problem-solving skills within a cognitive load framework. It concludes that (1) cognitive load theory can benefit from putting more emphasis on generalized knowledge structures; (2

Applying science of learning in education: Infusing psychological science into the curriculum

The field of specialization known as the science of learning is not, in fact, one field. Science of learning is a term that serves as an umbrella for many lines of research, theory, and application. A term with an even wider reach is Learning Sciences (Sawyer, 2006). The present book represents a sliver, albeit a substantial one, of the scholarship on the science of learning and its application in educational settings (Science of Instruction, Mayer 2011). Although much, but not all, of what is presented in this book is focused on learning in college and university settings, teachers of all academic levels may find the recommendations made by chapter authors of service. The overarching theme of this book is on the interplay between the science of learning, the science of instruction, and the science of assessment (Mayer, 2011). The science of learning is a systematic and empirical approach to understanding how people learn. More formally, Mayer (2011) defined the science of learning as the “scientific study of how people learn” (p. 3). The science of instruction (Mayer 2011), informed in part by the science of learning, is also on display throughout the book. Mayer defined the science of instruction as the “scientific study of how to help people learn” (p. 3). Finally, the assessment of student learning (e.g., learning, remembering, transferring knowledge) during and after instruction helps us determine the effectiveness of our instructional methods. Mayer defined the science of assessment as the “scientific study of how to determine what people know” (p.3). Most of the research and applications presented in this book are completed within a science of learning framework. Researchers first conducted research to understand how people learn in certain controlled contexts (i.e., in the laboratory) and then they, or others, began to consider how these understandings could be applied in educational settings. Work on the cognitive load theory of learning, which is discussed in depth in several chapters of this book (e.g., Chew; Lee and Kalyuga; Mayer; Renkl), provides an excellent example that documents how science of learning has led to valuable work on the science of instruction. Most of the work described in this book is based on theory and research in cognitive psychology. We might have selected other topics (and, thus, other authors) that have their research base in behavior analysis, computational modeling and computer science, neuroscience, etc. We made the selections we did because the work of our authors ties together nicely and seemed to us to have direct applicability in academic settings

A MODEL OF ADAPTIVE LEARNING IN SMART CLASSROOMS BASED ON THE LEARNING STRATEGIES

The paper presents a proposal of a model of adaptive learning. The model takes the advantage of a smart classroom environment for the realization of adaptive learning. As adaptation criteria, it uses parameters of motivation, student’s prior knowledge, cognitive load and a dynamic environmental parameter. The dynamic environmental parameter is a parameter which is obtained by evaluating physical parameters of working environment in a smart classroom. The learning process is carried out through different learning strategies grouped in learning categories. The model  dedicates a learning category  to a student based on a formula which takes in consideration above mentioned adaptation criteria  The proposed model has been tested. The assessment test scores at the end of a learning process showed that student’s in the experimental group achieved better learning outcomes than the student’s who learned in a traditional manner. The obtained results are encouraging and lay a sound foundation for the application and further development of the model