Tamara van Gog

Instructional Efficiency: Revisiting the Original Construct in Educational Research

This article revisits Paas and Van Merriënboers (1993) measure of instructional efficiency, which can be applied by educational researchers to compare the effects of different instructional conditions on learning. This measure relied on performance and mental effort on the test, and as such gave an indication of the quality of learning outcomes. The acquisition of more (less) efficient cognitive schemata is indicated by combinations of high (low) performance and low (high) mental effort. This instructional efficiency measure has become widely adopted, but in an adapted form that incorporates mental effort invested in the learning phase instead of the test phase. This article demonstrates that the adaptation has important consequences for the construct of instructional efficiency and for the type of conclusions that can be drawn. Examples are given to illustrate the various implications of different combinations of mental effort and performance measures in the light of more contemporary developments in educational research.

Problem-Based Learning is Compatible with Human Cognitive Architecture: Commentary on Kirschner, Sweller, and Clark (2006)

Kirschner, Sweller, and Clark (2006) suggest that unguided or minimally guided instructional approaches are less effective and efficient for novices than guided instructional approaches because they ignore the structures that constitute human cognitive architecture. While we concur with the authors on this point, we do not agree to their equation of problem-based learning with minimally guided instruction. In this commentary, we argue that problem-based learning is an instructional approach that allows for flexible adaptation of guidance, and that, contrary to Kirschner et al.s conclusions, its underlying principles are very well compatible with the manner in which our cognitive structures are organized.

Development of an instrument for measuring different types of cognitive load

According to cognitive load theory, instructions can impose three types of cognitive load on the learner: intrinsic load, extraneous load, and germane load. Proper measurement of the different types of cognitive load can help us understand why the effectiveness and efficiency of learning environments may differ as a function of instructional formats and learner characteristics. In this article, we present a ten-item instrument for the measurement of the three types of cognitive load. Principal component analysis on data from a lecture in statistics for PhD students (n = 56) in psychology and health sciences revealed a three-component solution, consistent with the types of load that the different items were intended to measure. This solution was confirmed by a confirmatory factor analysis of data from three lectures in statistics for different cohorts of bachelor students in the social and health sciences (ns = 171, 136, and 148), and received further support from a randomized experiment with university freshmen in the health sciences (n = 58).

Instructional Design for Advanced Learners: Establishing Connections between the Theoretical Frameworks of Cognitive Load and Deliberate Practice

Cognitive load theory (CLT) has been successful in identifying instructional formats that are more effective and efficient than conventional problem solving in the initial, novice phase of skill acquisition. However, recent findings regarding the “expertise reversal effect” have begun to stimulate cognitive load theorists to broaden their horizon to the question of how instructional design should be altered as a learners knowledge increases. To answer this question, it is important to understand how expertise is acquired and what fosters its development. Expert performance research, and, in particular, the theoretical framework of deliberate practice have given us a better understanding of the principles and activities that are essential in order to excel in a domain. This article explores how these activities and principles can be used to design instructional formats based on CLT for higher levels of skills mastery. The value of these formats for e-learning environments in which learning tasks can be adaptively selected on the basis of online assessments of the learners level of expertise is discussed.

Uncovering cognitive processes: Different techniques that can contribute to cognitive load research and instruction

This article discusses the use of different techniques for uncovering cognitive processes, for research and instructional purposes: verbal reporting, eye tracking, and concept mapping. It is argued here that applying these techniques in research inspired by cognitive load theory may increase our understanding of how and why well-known effects of instructional formats come about (e.g., split-attention, redundancy, or worked example effects) and refine or corroborate the proposed theoretical underpinnings of such effects. This knowledge can inform instructional design, and moreover, the effects of these techniques on learning can also be direct, by embedding the techniques in instruction.

An expertise reversal effect of segmentation in learning from animated worked-out examples

Many animations impose a high cognitive load due to the transience of information, which often hampers learning. Segmentation, that is presenting animations in pieces (i.e., segments), has been proposed as a means to reduce this high cognitive load. The expertise reversal effect shows, however, that design measures that have a positive effect on cognitive load and learning for students with lower levels of prior knowledge, might not be effective, or might even have a negative effect on cognitive load and learning for students with higher levels of prior knowledge. This experiment with animated worked-out examples showed an expertise reversal effect of segmentation: segmented animations were more efficient than continuous animations (i.e., equal test performance with lower investment of mental effort during learning) for students with lower levels of prior knowledge, but not for students with higher levels of prior knowledge.

Reflection as a strategy to foster medical students' acquisition of diagnostic competence

Medical Education 2012: 46: 464–472

Editorial: State of the art research into Cognitive Load Theory

Ayres, P., & Van Gog, T. (2009). Editorial: State of the art research into Cognitive Load Theory. Computers in Human Behavior, 25, 253-257.

Self-assessment and task selection in learner-controlled instruction: Differences between effective and ineffective learners

Learner-controlled instruction is often found to be less effective for learning than fixed or adaptive system-controlled instruction. One possible reason for that finding is that students - especially novices - might not able to accurately assess their own performance and select tasks that fit their learning needs. Therefore, this explorative study investigated the differences in self-assessment and task-selection processes between effective and ineffective learners (i.e., in terms of learning gains) studying in a learner-controlled instructional environment. Results indicated that although effective learners could more accurately assess their own performance than ineffective learners, they used the same task aspects to select learning tasks. For effective learners, who were also more accurate self-assessors, the self-assessment criteria predicted subsequent task selection. The results are discussed, particularly with regard to their potential to provide guidelines for the design of a self-assessment and task-selection training.

The signaling (or cueing) principle in multimedia learning

This chapter is a cautionary description of 10 of the questionable principles that have developed and seem to be widely shared about multimedia learning. The updated questionable beliefs include the expectations that multimedia instruction: yields more learning than live instruction or older media; is more motivating than other instructional media; provides animated pedagogical agents that aid learning; accommodates different learning styles and so maximizes learning for more students; and facilitates student-managed constructivist and discovery approaches that are beneficial to learning. The more recent additions and the focus of this discussion are expectations that multimedia instruction benefits learning by providing autonomy and control over the sequencing of instruction; higher-order thinking skills; incidental learning of enriching information; interactivity; and an authentic learning environment and activities. Finally, multimedia is confounded with the content of instruction, such as critical and higher-order thinking skills.