Search

There is a considerable gap between many of the findings from educational psychology research and educational practice. This gap is especially notable in the field of science education. In this article, the implications of three categories of research and their findings for science educational policy in the USA and other jurisdictions were reviewed. We indicate that a particular category of research that we call “Program-Based Studies,” has dominated the formulation of educational standards while a large number of critical findings from randomized, controlled studies and correlational studies that overwhelmingly show minimal support for the suggested policy have been marked as irrelevant and excluded. The current blanket-emphasis on program-based studies at the expense of the other types of research is misplaced. Educational standards should represent a balanced view of the available data including findings from controlled and correlational studies. Finally, we indicate how these different forms of research might inform each other and provide coherent and consistent implications for educational procedures.

Cognitive load theory is an instructional design theory based on our knowledge of human cognitive architecture and evolutionary educational psychology. The theory assumes that curriculum areas covered in educational institutions are concerned with domain-specific, biologically secondary information that we have not specifically evolved to acquire rather than generic-cognitive, biologically primary skills that we have specifically evolved to acquire. There is a cognitive architecture associated with the acquisition, processing and use of domain-specific, biologically secondary information. That cognitive architecture can be specified by a series of principles. Those principles also apply to the information processing characteristics of evolution by natural selection and constitute a natural information processing system. The principles provide the core of cognitive load theory and have been used to generate instructional guidelines that facilitate knowledge acquisition. Using those guidelines, implications for practitioners are derived that indicate effective instructional procedures. Most of those procedures are concerned with reducing unnecessary cognitive load.

When novice users try to learn to use a software application that includes a variety of high element interactivity tools, the complex structure of the software can increase cognitive load and render the tools incomprehensible. Accordingly, there is a need for an efficient teaching approach that can provide practical knowledge to users while decreasing their cognitive load. In this study, the use and choice of narrative were selected as procedures that can provide practical knowledge to software learners in addition to impacting cognitive load through providing a familiar theme to worked-examples. We compared the effects of familiar and unfamiliar narratives versus a no-narrative condition on cognitive load of users while learning software applications with both low and high interactivity tools through e-learning platforms. The results showed that an e-learning system with a familiar narrative could decrease cognitive load in comparison to the no-narrative and unfamiliar narrative systems for both low and high interactivity materials. It was concluded that people can learn new software applications more easily when familiar context worked-examples are used to integrate novel material with their existing knowledge.

This study offers evidence of the impact of language background on the performance of students enrolled in an accounting study unit. It aims to quantify the effects of language background on perfor...

Spaced and interleaved practices have been identified as effective learning strategies which sometimes are conflated as a single strategy and at other times treated as distinct. Learning sessions in which studying information or practicing problems are spaced in time with rest-from-deliberate-learning periods between sessions generally result in better learning outcomes than massed practice without rest-from-deliberate-learning periods. Interleaved practice also consists of spaced sessions, but by interleaving topics rather than having rest-from-deliberate-learning periods. Interleaving is usually contrasted with blocking in which each learning topic is taught in a single block that provides an example of massed practice. The general finding that interleaved practice is more effective for learning than blocked practice is sometimes attributed to spacing. In the current paper, the presence of rest-from-deliberate-learning periods is used to distinguish between spaced and interleaved practice. We suggest that spaced practice is a cognitive load effect that can be explained by working memory resource depletion during cognitive effort with recovery during rest-from-deliberate-learning, while interleaved practice can be explained by the discriminative-contrast hypothesis positing that interleaving assists learners to discriminate between topic areas. A systematic review of the literature provides evidence for this suggestion.

Face-to-face and computer-mediated collaboration have been used extensively in educational practice. However, research on teaching writing skills for English as a foreign language under collaborati...

Human cognitive architecture indicates the manner in which cognitive structures and processes are organized. In turn, that architecture can be used to hypothesize the relative effectiveness of alternative instructional designs. Over several decades, cognitive load theory has simultaneously identified those aspects of human cognition relevant to instructional issues and tested the resultant hypotheses using randomized, controlled experiments. The cognitive architecture used by cognitive load theory has continually been developed and refined over this period. Currently, that architecture is based on evolutionary principles. This chapter outlines the cognitive architecture used by cognitive load theory and provides a general indicator of its relevance to instructional design issues associated with multimedia instruction.

Many large-scale, school-based interventions have attempted to improve academic performance through promoting students’ growth mindset, defined as the belief that one’s intellectual ability can increase with practice and time. However, most have shown weak to no effects. Thus, it is important to examine how growth mindset might affect retention and transfer of learning, as well as process-related variables such as cognitive load. In a double-blind, randomized controlled experiment based on 138 secondary school students, the effects of an experimentally induced growth mindset belief were examined during a learning phase in a classroom setting. Participants in the growth mindset condition perceived a lower intrinsic load and extraneous load and performed better on retention and transfer tests. Students with some prior knowledge also reported a higher mastery goal orientation. Supplementary mediation analysis suggested that the effect on transfer could be fully accounted for by changes in cognitive load perceptions. Future interventions may benefit from designs that promote motivational beliefs that reduce intrinsic and extraneous cognitive load perceptions. (PsycInfo Database Record (c) 2020 APA, all rights reserved)

Collaborative learning is a widely used instructional technique, but factors determining its effectiveness still are unclear. Cognitive load theory was used to examine the effects of prior collaborative experience and density of distribution of information amongst learners on short-term retention and delayed retention tests, as well as cognitive efficiency of collaborative learning and its outcomes. Data obtained with 240 secondary school students showed that groups with experience in collaboration outperformed and were more cognitively efficient than inexperienced groups, and low information density increased performance during the learning process. Also, when tasks required processing high information density, experienced groups were more cognitively efficient than inexperienced groups. For tasks with low information density no difference was found. These results provide instructional implications for designing effective collaborative learning environments.

The concept of productive failure posits that a problem-solving phase prior to explicit instruction is more effective than explicit instruction followed by problem-solving. This prediction was tested with Year 5 primary school students learning about light energy efficiency. Two, fully randomised, controlled experiments were conducted. In the first experiment (N = 64), explicit instruction followed by problem-solving was found to be superior to the reverse order for performance on problems similar to those used during instruction, with no difference on transfer problems. In the second experiment, where element interactivity was increased (N = 71), explicit instruction followed by problem-solving was found to be superior to the reverse order for performance on both similar and transfer problems. The contradictory predictions and results of a productive failure approach and cognitive load theory are discussed using the concept of element interactivity. Specifically, for learning where element interactivity is high, explicit instruction should precede problem-solving.

Cognitive load theory provides instructional recommendations based on our knowledge of human cognition. Evolutionary psychology is used to assume that knowledge should be divided into biologically primary information that we have specifically evolved to acquire and biologically secondary information that we have not specifically evolved to acquire. Primary knowledge frequently consists of generic-cognitive skills that are important to human survival and cannot be taught because they are acquired unconsciously while secondary knowledge is usually domain-specific in nature and requires explicit instruction in education and training contexts. Secondary knowledge is first processed by a limited capacity, limited duration working memory before being permanently stored in long-term memory from where unlimited amounts of information can be transferred back to working memory to govern action appropriate for the environment. The theory uses this cognitive architecture to design instructional procedures largely relevant to complex information that requires a reduction in working memory load. Many of those instructional procedures can be most readily used with the assistance of educational technology.

The testing effect occurs when students, given information to learn and then practice during a test, perform better on a subsequent content post-test than students who restudy the information as a substitute for the practice test. The effect is often weaker or reversed if immediate rather than delayed post-tests are used. The weakening may be due to differential working memory resource depletion on immediate post-tests with resource recovery due to rest following a delayed post-test. In three experiments, we compared an immediate post-test with a 1-week delayed post-test. Experiment 1 required the students to construct a puzzle poem and found working memory resource depletion occurred immediately after learning compared to a delay. Experiment 2 using text-based material tapping lower element interactivity information and experiment 3, again using a puzzle poem, compared study-only with the study and test groups. A disordinal interaction was obtained in both experiments with the study-only groups superior to the study–test groups on immediate content post-tests and reverse results on delayed tests. Working memory capacity tests indicated a non-significant increase in capacity after a delay compared to immediately after learning with medium size effects, but in experiment 2, there were no working memory differences between the study-only and the study and test groups. Experiment 3 increased element interactivity and found an increased memory capacity for the study-only group compared to the study and test group with the immediate test contributing more of the difference than the delayed test. It was concluded that increased working memory depletion immediately following learning with a test contributes to the failure to obtain a testing effect using immediate tests.

Based on cognitive load theory, this paper reports on two experiments investigating the variability effect that occurs when learners’ exposure to highly variable tasks results in superior test performance. It was hypothesised that the effect was more likely to occur using high rather than low levels of guidance and testing more knowledgeable than less knowledgeable learners. Experiment 1, which tested 103 adults studying pre-university mathematics, showed no interaction between levels of variability (high vs. low) and levels of instructional guidance (worked examples vs. unguided problem solving). The significant main effect of variability indicated a variability effect regardless of levels of instructional guidance. Experiment 2, which tested another group of 56 adults enrolled in the same mathematics program, showed an interaction between levels of variability (high vs. low) and levels of learner expertise (novices vs. experts). More experienced learners learned more from high rather than low variability tasks demonstrating the variability effect, while less experienced learners learned more from low rather than high variability tasks demonstrating a reverse variability effect. It was suggested that more experienced learners had sufficient available working memory capacity to process high variability information while less experienced learners were overwhelmed by high variability and learned more using low variability information. Subjective ratings of difficulty supported the assumptions based on cognitive load theory. The major educational implication is that learners should initially be presented with low variability or easier tasks, and as they gain more experience in the task domain, variability or task difficulty should increase.

Cognitive load theory has become a leading model in educational psychology and has started to gain traction in the medical education community over the last decade. The theory is rooted in our current understanding of human cognitive architecture in which an individual's limited working memory and unlimited long-term memory interact during the process of learning. Though initially described as primarily a theory of learning, parallels between cognitive load theory and broader aspects of medical education as well as clinical practice are now becoming clear. These parallels are particularly relevant and evident in complex clinical environments, like resuscitation medicine. The authors have built on these connections to develop a recontextualized version of cognitive load theory that applies to complex professional domains and in which the connections between the theory and clinical practice are made explicit, with resuscitation medicine as a case study. Implications of the new model for medical education are also presented along with suggested applications.

International audience

Depletion of limited working memory resources may occur following extensive mental effort resulting in decreased performance compared to conditions requiring less extensive mental effort. This “depletion effect” can be incorporated into cognitive load theory that is concerned with using the properties of human cognitive architecture, especially working memory, when designing instruction. Two experiments were carried out on the spacing effect that occurs when learning that is spaced by temporal gaps between learning episodes is superior to identical, massed learning with no gaps between learning episodes. Using primary school students learning mathematics, it was found that students obtained lower scores on a working memory capacity test (Experiments 1 and 2) and higher ratings of cognitive load (Experiment 2) after massed than after spaced practice. The reduction in working memory capacity may be attributed to working memory resource depletion following the relatively prolonged mental effort associated with massed compared to spaced practice. An expansion of cognitive load theory to incorporate working memory resource depletion along with instructional design implications, including the spacing effect, is discussed.

The expertise reversal effect occurs when instruction that is effective for novice learners is ineffective or even counterproductive for more expert learners. Four experiments designed to explore the expertise reversal effect in the field of teaching and learning foreign language listening skills were conducted. Three instructional formats (read-only, listen-only, and read-and-listen) were designed to teach native Chinese students English (experiments 1–3) or French (experiment 4) listening skills. Experiment 1 found a significant interaction with no effect for learners with lower levels of listening expertise but a significant effect for learners with higher levels of listening expertise favoring the read-only approach. The results of experiment 2 replicated the counterintuitive findings of experiment 1. Experiment 3 testing less knowledgeable students than experiments 1 and 2 indicated that the read-and-listen condition was more effective for novice learners. Experiment 4 testing beginner-level learners of French as a foreign language obtained results consistent with those of experiment 3 in that lower expertise learners gained greater benefits from the read-and-listen than the read-only or listen-only teaching approaches. It is concluded that the read-and-listen approach benefitted novice learners but more expert learners could benefit more from the read-only approach.

Research on either cognitive load theory or self-regulated learning usually proceeds without reference to the other theory. In this commentary, we have commented on the editorial introduction and the six papers included in this Special Issue intended to indicate possible links between the two theories. To assist in this process, we have analysed some of the characteristics of both theories that either facilitate or impede the establishment of links. We conclude that while links are possible, the many differences between the theories present considerable barriers that will need to be overcome.

Worked examples and collaborative learning have both been shown to facilitate learning. However, the testing of both strategies almost exclusively has been conducted independently of each other. The main aim of the current study was to examine interactions between these 2 strategies. Two experiments (N = 182 and N = 122) were conducted with Grade-7 Indonesian students, comparing learning to solve algebra problems, with higher and lower levels of complexity, collaboratively or individually. Results from both experiments indicated that individual learning was superior to collaborative learning when using worked examples. In contrast, in Experiment 2, when learning from problem solving using problem-solving search, collaboration was more effective than individual learning. However, again in Experiment 2, studying worked examples was overall superior to learning from solving problems, particularly for more complex problems. It can be concluded that while collaboration could be beneficial when learning under problem solving conditions, it may be counterproductive when studying worked examples. (PsycINFO Database Record (c) 2017 APA, all rights reserved)

A massive, open, online course (MOOC) is a form of computer-based learning that offers open access, internet-based education for unlimited numbers of participants. However, the general quality and utility of MOOCs has been criticized. Most MOOCs have been structured with minimal consideration of relevant aspects of human cognitive architecture and instructional design principles. This paper suggests cognitive load theory, with its roots embedded in our knowledge of human cognitive architecture and evolutionary educational psychology, is ideally placed to provide instructional design principles for all forms of computer-based learning, including MOOCs. The paper outlines the theory and indicates instructional design principles that could be used to structure online learning and to provide an appropriate base for instructional design when using computer-based learning.

Studying worked examples providing problem solutions to learners usually leads to better test performance than solving the equivalent problems without guidance, demonstrating the worked-example eff...

Cognitive load theory is used to design instruction. Several aspects of human cognition are critical to instructional design. First, the theory assumes we have not specifically evolved to learn the topics taught in educational and training institutions. Second, these topics require learners to acquire domain-specific rather than generic–cognitive knowledge. Third, while generic–cognitive knowledge does not require explicit instruction because we have evolved to acquire it, domain-specific concepts and skills do require explicit instruction. These factors interact with the capacity and duration constraints of working memory to delineate a cognitive architecture relevant to instructional design. The working memory limits do not apply to biologically primary, generic–cognitive knowledge acquired without explicit instruction but do apply to biologically secondary, domain-specific knowledge that requires explicit instruction. Accordingly, cognitive load theory has been developed to provide techniques that reduce unnecessary working memory load when dealing with explicitly taught, biologically secondary, domain-specific knowledge.

Cognitive load theory is an instructional theory based on our knowledge of human cognitive architecture. Current versions of the theory use evolutionary educational psychology to categorise the information that humans process and to provide a template for human cognitive architecture that is analogous to the information processes of evolutionary biology. That theoretical base can be used to generate instructional procedures. The theoretical base and its attendant instructional effects provide information on the characteristics and role of human problem solving in instructional design. It is concluded that teachable aspects of skilled problem solving are domain-specific rather than generic-cognitive in nature, and that those characteristics should determine what is taught and how it is taught.

Element interactivity is a measure of complexity that is central to cognitive load theory. It provides the ultimate determinant of both intrinsic and extraneous cognitive load. It differs from most other measures of complexity in that it not only takes into consideration the characteristics of the information being processed, but also simultaneously takes into consideration the knowledge base held in long-term memory of the person processing that information. By taking both factors into consideration, the concept of element interactivity is able to connect human cognitive architecture to cognitive load theory-generated instructional design with its emphasis on reducing working memory load to facilitate the transfer of information to long-term memory. Cognitive load theory is primarily concerned with high element interactivity information. Most cognitive load effects are likely to disappear or reverse using low element interactivity information. Since much work on instructional design ignores the concept of element interactivity, we run the risk of apparently contradictory experimental results. Some of those contradictory results and how they can be explained by cognitive load theory are discussed in this chapter.

Cognitive load theory was introduced in the 1980s as an instructional design theory based on several uncontroversial aspects of human cognitive architecture. Our knowledge of many of the characteristics of working memory, long-term memory and the relations between them had been well-established for many decades prior to the introduction of the theory. Curiously, this knowledge had had a limited impact on the field of instructional design with most instructional design recommendations proceeding as though working memory and long-term memory did not exist. In contrast, cognitive load theory emphasised that all novel information first is processed by a capacity and duration limited working memory and then stored in an unlimited long-term memory for later use. Once information is stored in long-term memory, the capacity and duration limits of working memory disappear transforming our ability to function. By the late 1990s, sufficient data had been collected using the theory to warrant an extended analysis resulting in the publication of Sweller et al. (Educational Psychology Review, 10, 251-296, 1998). Extensive further theoretical and empirical work have been carried out since that time and this paper is an attempt to summarise the last 20years of cognitive load theory and to sketch directions for future research.

There are basically two formats used in instructional visualizations, namely, static pictures and dynamic visualizations (e.g., animations and videos). Both can be engaging and fun for university students in the fields of health and natural sciences. However, engagement by itself is not always conducive to learning. Consequently, teachers, lecturers, and instructional designers need to utilize the cognitive processing advantages of visualizations as well as engagement to achieve full instructional effectiveness. A cognitive processing focus has outlined many ways in which instructional visualization can be optimized. Specifically, cognitive load theory and the cognitive theory of multimedia learning are two research paradigms that provide several methods for directing the design of visualizations by considering how learners process visuospatial information. In this chapter, we describe five methods based on these cognitive theories: (a) the split attention effect and spatial contiguity principle, (b) the modality effect, (c) the redundancy effect and coherence principle, (d) the signaling principle, and (e) the transient information effect. For each of these effects, examples of applications for education in health and natural sciences are provided, where the influence of visuospatial processing is also considered. We end this chapter by discussing instructional implications for science education and providing future directions for research.