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.     

Medical students' cognitive load in volumetric image interpretation: Insights from human-computer interaction and eye movements

Medical image interpretation is moving from using 2D- to volumetric images, thereby changing the cognitive and perceptual processes involved. This is expected to affect medical students' experienced cognitive load, while learning image interpretation skills. With two studies this explorative research investigated whether measures inherent to image interpretation, i.e. human-computer interaction and eye tracking, relate to cognitive load. Subsequently, it investigated effects of volumetric image interpretation on second-year medical students' cognitive load. Study 1 measured human-computer interactions of participants during two volumetric image interpretation tasks. Using structural equation modelling, the latent variable ‘volumetric image information’ was identified from the data, which significantly predicted self-reported mental effort as a measure of cognitive load. Study 2 measured participants' eye movements during multiple 2D and volumetric image interpretation tasks. Multilevel analysis showed that time to locate a relevant structure in an image was significantly related to pupil dilation, as a proxy for cognitive load. It is discussed how combining human-computer interaction and eye tracking allows for comprehensive measurement of cognitive load. Combining such measures in a single model would allow for disentangling unique sources of cognitive load, leading to recommendations for implementation of volumetric image interpretation in the medical education curriculum.     

Exploring the cognitive loads of high-school students as they learn concepts in web-based environments

This study measured high-school learners' cognitive load as they interacted with different web-based curriculum components, and examined the interactions between cognitive load and web-based concept learning. Participants in this study were 105 11th graders from an academic senior high school in Taiwan. An online, multimedia curriculum on the topic of global warming, which lasted for four weeks, provided the learning context. After students worked through the curriculum, their feelings about the degree of mental effort that it took to complete the learning tasks were measured by self-report on a 9-point Likert scale. An online test and the flow-map method were applied to assess participants' concept achievements. The results showed that curriculum components such as scientific articles, online notebooks, flash animations and the online test induced a relatively high cognitive load, and that a lower cognitive load resulted in better concept achievement. Also, students appeared to adopt different learning approaches that were corresponding to different levels of cognitive load.     

Cognitive load and science text comprehension: Effects of drawing and mentally imagining text content

One hundred and eleven 10th graders read an expository science text on the dipole character of water molecules (ca. 1600 words). Reading instruction was varied according to a 2 × 2 experimental design with factors ‘drawing pictures of text content on paper’ (yes, no) and ‘mentally imagining text content while reading’ (yes, no). The results indicate that drawing pictures, mediated through increased cognitive load, decreased text comprehension and, thus, learning (d = −0.37), whereas mental imagery, although decreasing cognitive load, increased comprehension only when students did not have to draw pictures simultaneously (d = 0.72). No evidence was found that the effects were moderated by domain-specific prior knowledge, verbal ability, or spatial ability. The results are in line with cognitive theories of multimedia learning, self-regulated learning, and mental imagery as well as conceptions of science learning that focus on promoting mental model construction by actively visualizing the content to be learned. Constructing mental images seems to reduce cognitive load and to increase comprehension and learning outcome when the mental visualization processes are not disturbed by externally drawing pictures on paper, whereas drawing pictures seems to increase cognitive load resulting in reduced comprehension and learning outcome.     

Cognitive load and instructionally supported learning with provided and learner-generated visualizations

This study investigated, whether learning from science texts can be enhanced by providing learners with different forms of visualizations (pictures) in addition to text. One-hundred-two 9th and 10th graders read a computer-based text on chemical processes of washing and answered questions on cognitive load (mental effort, perceived difficulty) and comprehension (retention, transfer, drawing). Instruction varied according to a 2 × 2-factorial design with ‘learner-generated pictures’ (yes, no) and ‘provided pictures’ (yes, no) as factors. Results indicate positive main effects of provided pictures on all three comprehension measures and negative main effects on both cognitive load measures. Additional analyses revealed a mediation effect of perceived difficulty on retention and transfer, that is learning with provided pictures decreased cognitive load and enhanced comprehension. Furthermore, results show a positive main effect of learner-generated pictures on drawing and mental effort, but no mediation effect. Taken together, computer-based learning with provided pictures enhances comprehension as it seems to promote active processing while reducing extraneous cognitive processing. Learners, generating pictures, however, seem to have less cognitive resources available for essential and generative processing, resulting in reduced comprehension. These results are in line with cognitive load theory, cognitive theories of multimedia learning, and generative theories of learning.     

Just-in-time information presentation and the acquisition of complex cognitive skills

This paper describes a model for just-in-time (JIT) presentation of information. Learners receive the information needed to carry out a task precisely at the time it is needed. The model is twofold: supportive information is best presented before practising task clusters while prerequisite information is best presented during practice on learning tasks. JIT supportive information presentation promotes schema construction through meaningful learning or elaboration. JIT prerequisite information presentation promotes schema automation through proceduralization or restricted encoding while learning the recurrent aspects of a task. It leads to a reduction in extraneous cognitive load because temporal split attention is avoided. This frees up cognitive capacity for learning the non-recurrent aspects of a complex cognitive skill and so enhances transfer performance. An exploratory, empirical study is described that supports our model. Implications for teaching and teacher training are discussed.     

The impact of study load on the dynamics of longitudinal email communications among students

With the advent of information technology, emails have gained wide acceptability among students as an asynchronous communication tool. According to the current pedagogy literature the overall trend of the use of email communication by university students has been increasing significantly since its inception, despite the rapid growth of the popularity and acceptability of other social mediums (e.g. Mobile phone and Facebook). In this study, we explore a longitudinal email communication network, which evolved under an increasing study load among 38 students throughout a university semester, using measures of social network analysis (SNA) and exponential random graph (ERG) models. This longitudinal network was divided into three waves, where each wave represents the portion of the complete longitudinal network that evolves between two consecutive observations. An increased study load was imposed through the assessment components of the course. SNA measures of degree centrality (i.e. the activity of an actor or actor popularity), betweenness centrality (i.e. the capacity to control the flow of information in a network), closeness centrality (i.e. reachable to other nodes) and reciprocity (i.e. tendency to make reciprocal links) are considered to explore this longitudinal network. ERG models are probabilistic models that are presented by locally determined explanatory variables and can effectively identify structural properties of networks. From the analysis of this email communication network, we notice that students' network positions and behaviours change with the changes in their study load. In particular, we find that (i) students make an increased number of email communications with the increase of study load; (ii) the email communication network become sparse with the increase of study load; and (iii) the 2-star parameter (a subset of three nodes in which one node is connected to each of the other two nodes) and the triangle parameter (a subset of three nodes in which each node is connected to the other two nodes) can effectively explain the formation of network in wave3; whereas, the 3-star parameter (a subset of four nodes in which one node is connected to each of other three nodes) can effectively explain the formation of network in wave1 and wave2. Interpretations of these findings for the monitoring of student behaviour in online learning environments, as well as the implications for the design of assessment and the use of asynchronous tools are discussed in this paper.     

Individual and group-based learning from complex cognitive tasks: Effects on retention and transfer efficiency

The effects of individual versus group learning (in triads) on efficiency of retention and transfer test performance in the domain of biology (heredity) among 70 high-school students were investigated. Applying cognitive load theory, the limitations of the working memory capacity at the individual level were considered an important reason to assign complex learning tasks to groups rather than to individuals. It was hypothesized that groups will have more processing capacity available for relating the information elements to each other and by doing so for constructing higher quality cognitive schemata than individuals if the high cognitive load imposed by complex learning tasks could be shared among group members. In contrast, it was expected that individuals who learn from carrying out the same complex tasks would need all available processing capacity for remembering the interrelated information elements, and, consequently, would not be able to allocate resources to working with them. This interaction hypothesis was confirmed by the data on efficiency of retention and transfer test performance; there was a favorable relationship between mental effort and retention test performance for the individual learners as opposed to a favorable relationship between transfer test performance and mental effort for the students who learned in groups.     

The effects of visual metaphor and cognitive style for mental modeling in a hypermedia-based environment

With the exponential growth of Internet technology, the notion of users’ cognition when navigating such a vast information space has gained prominence. Studies suggest that metaphors can serve as effective tools to scaffold users’ mental modeling processes. However, how users conceive of the metaphorical aid (as opposed to simply how they perceive it) remains questionable. Cognitive style, or the user’s preferred way of information processing, has thus been posited as a possible factor affecting the success of the metaphorical approach in a hypermedia environment.

This study explores the effects of visual metaphors and cognitive styles on users’ learning performances in terms of structural knowledge and feelings of disorientation. The results indicate that a visual metaphor could improve the quality of mental formation, yet simultaneously increase users’ mental load during navigation. In addition, cognitive style is a crucial factor that can significantly affect users’ learning performance.     

The effects of video on cognitive load and social presence in multimedia-learning

Two studies examined the use of video in multimedia learning environments. In Study 1, participants (N = 26) viewed one of two versions of a computer-based multimedia presentation: video, which included a video of a lecture with synchronized slides, or no video, which included the slides but only an audio narration of the lecture. Learning, cognitive load and social presence were assessed, but a significant difference was found only for cognitive load, with video experiencing greater cognitive load, t (24) = 2.45, p < .05. In Study 2, students (N = 25) were randomly assigned to either video or no video condition. Background knowledge and visual/verbal learning preference were assessed before viewing the presentation, and learning, cognitive load, and social presence were assessed after viewing. No significant differences were found for learning or social presence. However, a significant visual/verbal learning preference by condition interaction was found for cognitive load, F (1,21) = 4.51, p < .05: low visual-preference students experienced greater cognitive load in the video condition, while high visual-preference students experienced greater cognitive load in the no video condition.     

RoLo: A dictionary interface that minimizes extraneous cognitive load of lookup and supports incidental and incremental learning of vocabulary

Dictionary use can improve reading comprehension and incidental vocabulary learning. Nevertheless, great extraneous cognitive load imposed by the search process may reduce or even prevent the improvement. With the help of technology, dictionary users can now instantly access the meaning list of a searched word using a mouse click. However, they must spend great cognitive effort identifying the most appropriate meaning for a given context, contributing to the disruption of the flow of reading and decreasing the positive effect of dictionary use. Furthermore, dictionary users face difficulty in exploiting accumulative illustrations from multiple contexts to understand obscure words whose appropriate meanings are not in the dictionary or are difficult to identify. To address these issues and to offer language learners, especially lifelong learners, effective support for incremental and incidental learning of vocabulary through reading, this research proposes a dictionary interface named RoLo (Remind on Lookup). Each time an unfamiliar word is re-looked up, RoLo reminds users about contextual information and word knowledge learned in previous encounters of the word in an appropriate manner. Two studies were conducted to evaluate RoLo. The first study, with 34 participants, examined the effect of RoLo use on incidental vocabulary learning. The second examination, involving 43 participants who used the prototype of RoLo for one month, investigated dictionary users' evaluation of RoLo. The results show that RoLo helps dictionary users enhance vocabulary learning and text comprehension and search for unfamiliar words more easily and faster.     

Superiority of collaborative learning with complex tasks: A research note on an alternative affective explanation

Kirschner, Paas, and Kirschner (2009c) used the theoretical framework of cognitive load to explain why the learning of a group of collaborating individuals was more efficient than that of individuals learning alone with high-complexity tasks but not with low-complexity tasks. The authors argued that collaboration circumvented the limitations of an individual’s working memory by creating an expanded cognitive capacity and by allowing for the distribution of cognitive load among group members. Inspired by research on efficacy, this study explored an alternative affective explanation of the results. By measuring the amount of mental effort learners expected to invest in working on a learning task before actually carrying out the task, this study showed that learners who had to collaboratively solve a high-complexity problem expected to invest less mental effort than learners who had to solve the problem alone. When confronted with low-complexity tasks, the expected amount of mental effort did not differ.     

The double-edged effects of explanation prompts

Explanation prompts usually foster conceptual understanding. However, it has been claimed within cognitive load theory that prompts can take cognitive load to the upper limit when learning complex contents. Under such circumstances, prompts focusing the learners’ attention on specific aspects (e.g., conceptual aspects such as elaborations on domain principles) might have some costs: Other important aspects (e.g., procedural aspects such as how to calculate) cannot be processed deeply. Thus, we expected that conceptually-oriented explanation prompts would foster the detailedness of explanations, the number of elaborations on domain principles, and conceptual knowledge. In addition, we tested the influence of such prompts on the number of calculations performed during learning and procedural knowledge. We conducted an experiment in which we employed conceptually-oriented explanation prompts in a complex e-learning module on tax law. Tax law university students (N = 40) worked on this e-learning module under two conditions: (a) conceptually-oriented explanation prompts, (b) no prompts. The prompts led to double-edged effects: positive effects on the detailedness of explanations and on the number of elaborations on domain principles, as well as on conceptual knowledge and simultaneously negative effects on the number of calculations performed during learning as well as on procedural knowledge.     

Process-mining enabled feedback: “Tell me what I did wrong” vs. “tell me how to do it right”

Fast advancement of technology has led to an increased interest for using information technology to provide feedback based on learning behavior observations. This work outlines a novel approach for analyzing behavioral learner data through the application of process mining techniques specifically targeting a complex problem solving process. We realize this in the context of one particular learning case, namely, domain modeling. This work extends our previous research on process-mining analysis of domain modeling behavior of novices by elaborating with new insights from a replication study enhanced with an extra observation on how novices verify/validate models. The findings include a set of typical modeling and validation patterns that can be used to improve teaching guidance for domain modeling courses. From a scientific viewpoint, the results contribute to improving our knowledge on the cognitive aspects of problem-solving behavior of novices in the area of domain modeling, specifically regarding process-oriented feedback as opposed to traditional outcome feedback (is a solution correct? Why (not)?) usually applied in this type of courses. Ultimately, the outcomes of the work can be inspirational outside of the area of domain modeling as learning event data is becoming readily available through virtual learning environments and other information systems.     

Note-taking while learning hypermedia: Cognitive and motivational considerations

The non-linear format of hypermedia requires the use of self-regulated learning (SRL) processes, including making decisions about which representation to access. The design of hypermedia environments can make these decisions difficult, and may result in extraneous cognitive load. Note-taking, a SRL strategy may offload extraneous cognitive load while learning with hypermedia. This study examined factors related to undergraduate students’ note-taking while learning with hypermedia. Think-aloud, self-report, pretest, and posttest data were collected from 53 undergraduates while they learned about a challenging science topic for 30 min with hypermedia. Results indicated that participants’ prior domain knowledge, as measured by the pretest, did not significantly predict the content of their notes. However, motivation, as measured by a self-report questionnaire, had a significant relationship with the content of the participants’ notes. Specifically, intrinsic motivation had a significant negative relationship while extrinsic motivation had a significant positive relationship with the content of notes. Additionally, there was a significant interaction between the content of the participants’ notes and their use of self-regulatory processes while learning with hypermedia.     

Benefits of adding anxiety-reducing features to a computer-based multimedia lesson on statistics

The present study examined the effectiveness of techniques intended to reduce anxiety as students learn mathematical content from a computer-based lesson. In a between-subjects experiment, students learned statistical rules through worked examples in a computer-based learning environment that either did (treatment group) or did not (control group) include anxiety reducing features—a coping message delivered through the lesson by an online pedagogical agent concerning how to manage feelings of anxiety, and prompts for expressive writing, in which students summarize their thoughts and feelings. An independent samples t-test showed that the treatment group, which received added anxiety-reducing features, showed higher accuracy than the control group on solving practice problems (d = 0.71) and retention problems (d = 0.63) and reported higher perceived effort on learning the multimedia lesson (d = 0.66). In addition, a standard multiple linear regression found that anxiety, self-efficacy, and cognitive load as a set predicted performance (R² = 0.56), with self-efficacy as the strongest predictor (β = 0.63). Adding anxiety-reducing features to an online lesson may encourage greater effort, which leads to better learning outcomes.     

Effects of stress and effort on self-rated reports in experimental study of design activities

This paper investigates the relationships between subjective rating measure and physiological measure of mental stress and mental effort during design activities. Mental stress and mental effort were captured by skin conductance and EEG beta2 power (20–30 Hz) whereas self-rated mental stress and self-rated mental effort were obtained using the NASA Task Load Index. A strong association between self-rated effort and EEG beta2 power was found in several design tasks. The analysis shows that self-rating is by itself a mental activity which may be affected by psychological stress and may be influenced by the amount of cognitive effort allocated. Researchers who rely on subjective rating should take into account the stress and effort of respondents during the rating activities to ensure the validity of the self-report measures. The study also demonstrated that design tasks induced mental stress that continued to stay above the baseline even after the tasks were completed.     

The cognitive impact of interactive design features for learning complex materials in medical education

To identify the most effective way for medical students to interact with a browser-based learning module on the symptoms and neurological underpinnings of stroke syndromes, this study manipulated the way in which subjects interacted with a graphical model of the brain and examined the impact of functional changes on learning outcomes. It was hypothesized that behavioral interactions that were behaviorally more engaging and which required deeper consideration of the model would result in heightened cognitive interaction and better learning than those whose manipulation required less deliberate behavioral and cognitive processing. One hundred forty four students were randomly assigned to four conditions whose model controls incorporated features that required different levels of behavioral and cognitive interaction: Movie (low behavioral/low cognitive, n = 40), Slider (high behavioral/low cognitive, n = 36), Click (low behavioral/high cognitive, n = 30), and Drag (high behavioral/high cognitive, n = 38). Analysis of Covariates (ANCOVA) showed that students who received the treatments associated with lower cognitive interactivity (Movie and Slider) performed better on a transfer task than those receiving the module associated with high cognitive interactivity (Click and Drag, partial eta squared = .03). In addition, the students in the high cognitive interactivity conditions spent significantly more time on the stroke locator activity than other conditions (partial eta squared = .36). The results suggest that interaction with controls that were tightly coupled with the model and whose manipulation required deliberate consideration of the model's features may have overtaxed subjects' cognitive resources. Cognitive effort that facilitated manipulation of content, though directed at the model, may have resulted in extraneous cognitive load, impeding subjects in recognizing the deeper, global relationships in the materials. Instructional designers must, therefore, keep in mind that the way in which functional affordances are integrated with the content can shape both behavioral and cognitive processing, and has significant cognitive load implications.     

Cognitive load in hypermedia reading comprehension: Influence of text type and linearity

In this paper the assumption of cognitive overhead in hypermedia learning is specified by cognitive load theory. This analysis is based on different types of cognitive load, the dimension of linearity/non-linearity as well as text characteristics. We propose a model stating that extraneous cognitive load in hypermedia learning is basically determined by the interaction of text presentation format (linear/non-linear) with text type (text with and without narrative structures). This assumption was tested by means of a 2 × 2 experimental design. Sixty participants completed a computer-based learning program that contained a narrative text or an encyclopaedia text in either linear or non-linear presentation format. Results confirm the suggested interaction hypothesis postulating that non-linear information presentation of narrative text structure increases cognitive load and decreases knowledge acquisition. However, for encyclopaedia text participants’ knowledge acquisition was not affected by linear or non-linear presentation format. Furthermore, results suggest a cross-validation of cognitive load measures and propositional analysis.     

Just-in-time,schematic supportive information presentation during cognitive skill acquisition

Cognitive load theory states that well-designed learning material minimizes extraneous cognitive load and optimizes germane cognitive load within the thresholds of available cognitive resources. In this study, the extraneous cognitive load is minimized by avoiding temporal split attention with regard to supportive information (i.e., conceptual models or ‘theory’) and the germane cognitive load is optimized by using schematic representations of this information to direct learner’s attention to concepts relevant for learning. A 2 × 2 between-groups design with the factors supportive information (before or during practice) and schematic representation (before or during practice) was used to investigate whether this balance between extraneous and germane load leads to more effective and efficient learning. It was found that the ‘supportive during, schema before’ format indeed yielded a higher learning efficiency than the ‘supportive before, schema before’ and the supportive during, schema during’ format but no differences were found for learning effectiveness (i.e., test performance).