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

Combining shared control with variability over surface features: Effects on transfer test performance and task involvement

Corbalan, G., Kester, L., & Van Merriënboer, J. J. G. (2009). Combining shared control with variability over surface features: Effects on transfer test performance and task involvement. Computers in Human Behavior, 25, 290-298.Positive effects of learner control decrease when learners do not perceive the control given to them, make suboptimal choices, or are cognitively overloaded by the amount of choice. This study proposes shared control (i.e., learners choose from a pre-selection of suitable tasks) over highly variable tasks to tackle these problems. Ninety-four students participated in a 2 x 2 factorial experiment with the factors control (system, shared) and variability of surface features (low, high). Results show superior effects on training performance, transfer test performance, and task involvement of shared control when learners can choose from pre-selected tasks with surface features that are different from the surface features of previous tasks

Designing Support to Facilitate Learning in Powerful Electronic Learning Environments

This themed issue reflects current developments in instructional design for powerful electronic learning environments. It presents a compilation of contributions to a combined special interest group (sig) meeting (2006) of Instructional Design and Learning and Instruction with Computers. Both sigs are part of the European Association for Research on Learning and Instruction (EARLI). The sig-meeting focused on the design of powerful electronic learning environments for complex learning. The articles in this issue describe how to design support to help learners during complex individual or collaborative learning. This introduction provides the context for the issue and a short overview of the contributions

Selecting Learning Tasks: Effects of Adaptation and Shared Control on efficiency and task involvement

Corbalan, G., Kester, L., & Van Merriënboer, J.J.G. (2008). Selecting learning tasks: Effects of adaptation and shared control on efficiency and task involvement. Contemporary Educational Psychology, 33(4), 733-756.Complex skill acquisition by performing authentic learning tasks is constrained by limited working memory capacity (Baddeley, 1992). To prevent cognitive overload, task difficulty and support of each newly selected learning task can be adapted to the learner’s competence level and perceived task load, either by some external agent, the learner herself, or both. Health sciences students (N = 55) participated in a study using a 2x2 factorial design with the factors adaptation (present or absent) and control over task selection (program control or shared control). As hypothesized, adaptation led to more efficient learning; that is, higher learning outcomes combined with less effort invested in performing the learning tasks. Shared control over task selection led to higher task involvement, that is, higher learning outcomes combined with more effort directly invested in learning. Adaptation also produced greater task involvement

Learner-controlled selection of tasks with different surface and structural features: Effects on transfer and efficiency

Surface task features are more salient than structural task features and thus easier to recognize for novices. It is predicted that the more salient the task features the better learners can choose personally relevant and varied tasks, which enhances learning transfer. To investigate this prediction, a 2 x 2 factorial experiment with 72 participants studied the effects of control over tasks that differ in their surface features (learner, program) and in their structural features (learner, program). Learner control over the selection of tasks with salient surface features enables learners to select personally relevant and varied tasks. This is believed to yield higher effectiveness (i.e., higher near and far transfer test performance) as well as higher efficiency (i.e. higher transfer test performance combined with lower associated mental effort). Learner control over the selection of tasks with non-salient structural features does not enable learners to select personally relevant and varied tasks and is therefore not expected to yield beneficial effects on learning. The results show positive effects of learner control over the selection of tasks with salient surface features for efficiency on the far transfer test but not for effectiveness. Theoretical and practical implications are discussed

Procedural advice on self-assessment and task selection in learner-controlled education

Taminiau, E. M. C., Corbalan, G., Kester, L., Van Merriënboer, J. J. G., & Kirschner, P. A. (2010, March). Procedural advice on self-assessment and task selection in learner-controlled education. Presentation at the ICO Springschool, Niederalteich, Germany.Learner-controlled education gives learners control over their learning pathways. They assess their own performance and select a task out of a large set of learning tasks, accommodating their own learning needs. However, novice learners often do not possess the self-assessment and task-selection skills necessary for determining an appropriate path. Especially if they are novices in the learning domain too, it is even harder to set an appropriate path. They will be overloaded by both the unfamiliar learning environment and the unfamiliar domain. Moreover, they will not know what performance standards are relevant for performance assessment, and what task characteristics to take into account for task selection. Consequently, they probably will neither gain a great deal of knowledge nor improve domain-specific skills. This is an explorative study to test the effect of a procedural advisory model providing self-assessment and task-selection advice, and if it helps learners in learner-controlled education to determine an appropriate learning pathway. The self-assessment advice provides a scoring rubric for assessing performance. The task-selection advice provides a rule for an appropriate task-selection which is based on the learner’s self-assessment, learner’s mental effort, and the task aspects of the prior task. These learners might be better able to determine their own learning pathway, in turn enhancing learning performance. It will be explored if the model benefits the learners’ development of self-assessment and task-selection skills, and, in addition, positively affect the acquisition of the learners’ domain-specific skills. This experiment will be followed by a second one, which will not be discussed in this paper, testing another advisory model. This second advisory model extends the procedural advisory model with more advice on self-assessment and task-selection. In order to test the effects of providing more advice on the development of self-assessment and task-selection skills, and, in addition, on the acquisition of domain-specific skills

Designing for scale: How relationships shape curriculum change

Pareja Roblin, N., Corbalan Perez, G., McKenney, S., Nieveen, N., & Van den Akker, J. (2012, 13-17 April). Designing for scale: How relationships shape curriculum change. Paper presentation at the AERA annual meeting, Vancouver, Canada. Please see also: http://hdl.handle.net/1820/4678While much is known about factors affecting curriculum change, much less knowledge is available to guide the process of designing for change on a large scale. This study explores how large scale innovations can achieve alignment between curricular components through interactions among various system actors. Eight prominent large-scale curriculum innovation projects were analyzed. Six key themes emerged from interview and document analysis data. Three themes related to salient relationships -i.e. strategic partnerships with (local/national) organizations; identification of individuals acting as linking pins; teacher involvement in design. Three other themes pertained to the relationships’ maintenance -i.e. visible presence; aligning goals; acknowledging the complex and interpersonal nature of relationships. Findings suggest that attending to relationships (professional and personal; strategic and unplanned; formal and informal) should be a key consideration in shaping the process of designing large scale curriculum innovations, and offer examples of how this has been accomplished

Designing on-demand education for simultaneous development of domain-specific and self-directed learning skills

On-demand education enables individual learners to choose their learning pathways according to their own learning needs. They must use self-directed learning (SDL) skills involving self-assessment and task selection to determine appropriate pathways for learning. Learners who lack these skills must develop them because SDL skills are prerequisite to developing domain-specific skills. This article describes the design of an on-demand learning environment developed to enable novices to simultaneously develop their SDL and domain-specific skills. Learners received advice on their self-assessments and their selections of subsequent learning tasks. In the domain of system dynamics – a way to model a dynamic system and draw graphs depicting the system’s behaviour over time – advice on self-assessment is provided in a scoring rubric containing relevant performance standards. Advice on task selection indicates all relevant task aspects to be taken into account, including recommendations for suitable learning tasks which meet the individual learner’s needs. This article discusses the design of the environment and the learners’ perceptions of its usefulness. Most of the times, the learners found the advice appropriate and they followed it in 78% of their task selections

Why Advice on Task Selection May Hamper Learning in On-Demand Education

Taminiau, E. M. C., Kester, L., Corbalan, G., Alessi, S. M., Moxnes, E., Gijselaers, W. H., Kirschner, P. A., & Van Merriënboer, J. J. G. (2013). Why advice on task selection may hamper learning in on-demand education. Computers in Human Behavior, 29, 145-154. doi: 10.1016/j.chb.2012.07.028In on-demand education, learners are required to plan their own learning trajectory by selecting suitable learning tasks. A positive effect on learning is expected when learners select tasks that help them fulfil their individual learning needs. However, the selection of suitable tasks is a difficult process for learners with little domain knowledge and suboptimal task-selection skills. A common solution for helping learners deal with on-demand education and develop domain-specific skills is to give them advice on task selection. In a randomized experiment, learners (N = 30) worked on learning tasks in the domain of system dynamics and received either advice or no advice on the selection of new learning tasks. Surprisingly, the no-advice group outperformed the advice group on a post-test measuring domain-specific skills. It is concluded that giving advice on task selection prevents learners from thinking about how the process of task selection works. The advice seems to supplant rather than support their considerations why they should perform the advised task, which results in negative effects on learning. Implications for future research on giving advice in on-demand education are discussed