Measuring cognitive load in test items: static graphics versus animated graphics

The majority of multimedia learning studies focus on the use of graphics in learning process but very few of them examine the role of graphics in testing students' knowledge. This study investigates the use of static graphics versus animated graphics in a computer‐based English achievement test from a cognitive load theory perspective. Three hundred and three 7th‐grade students were randomly split into two groups and given the test questions either with static graphics or with animated graphics accompanied with text. Students' response time, response accuracy, self‐reported ratings on cognitive load and secondary task approach were used to measure their cognitive load. Findings revealed that animating graphics increased the response time and secondary task scores of the students but did not have any significant effect on their test success. Furthermore, no difference was observed in self‐reported cognitive loads. The relationship between the four different cognitive load measures was also examined in the study. No direct relation was found between self‐reported ratings and secondary task scores. On the other hand, self‐ratings and response accuracy were found to be more sensitive to intrinsic cognitive load, whereas response time and secondary task measures were found to be more sensitive to extraneous cognitive load in our testing environment.     

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.     

Does instructor's image size in video lectures affect learning outcomes?

One of the most commonly used forms of video lectures is a combination of an instructor's image and accompanying lecture slides as a picture‐in‐picture. As the image size of the instructor varies significantly across video lectures, and so do the learning outcomes associated with this technology, the influence of the instructor's image size should be evaluated. This study tested the effect of image size of the instructor on learners' experience of social presence, cognitive load, learning performance and satisfaction. In the study, 87 Chinese undergraduates were randomly assigned to view a video lecture with a small image of the instructor, with a medium image size of the instructor or with a large image of the instructor. The results of analyses of variances and analysis of covariance suggested that learners perceived the same level of social presence and cognitive load across video lectures with different image sizes of the instructor; learners who watched the video lecture with the small image of the instructor learned better than those who watched the video lectures with the medium and the large images of the instructors. Furthermore, learners who watched the video lecture with the small image and medium image of the instructor experienced more learning satisfaction. The findings highlight the importance of image size of the instructor in video lecture learning.     

The effects of a theory‐based summary writing tool on students' summary writing

This paper focuses on the design and evaluation of a theory‐based computer‐assisted summary writing learning environment called Summary Writing‐PAL (SW‐PAL). The SW‐PAL was developed based on four aspects: summarizing strategies, learning theories, prior knowledge, and cognitive load. A quasi‐experiment that involved 58 undergraduates majoring in Computer Science was conducted to examine the effectiveness of SW‐PAL in writing summaries. Two intact classes were selected with 28 and 30 students in control and experimental groups, respectively. The conventional teaching approach was employed in the control group, whereas the SW‐PAL was introduced to the experimental group. Pretest and posttest were administrated to both groups. The findings indicated that SW‐PAL improved students' summary writing performance. A significant variance was noted between intrinsic and extraneous cognitive load among students with varying levels of English proficiency in the experimental group, signifying that the SW‐PAL is more suitable for students with lower language proficiency.     

How flipped learning based on the cognitive theory of multimedia learning affects students' academic achievements

The study aims to identify the effect of a flipped classroom approach designed according to the cognitive theory of multimedia learning on the academic achievements of eighth‐grade students (aged 14 years) in Saudi Arabia in computer science. To this end, a quasi‐experimental design was used, with a sample of 67 students; 33 students were assigned to the experimental group, whereas 34 comprised the control group. The experimental group was subjected to the flipped classroom approach, whereas the control group was given direct instruction. To measure student achievements, an instrument that measures cognitive skills based on Revised Bloom's taxonomy levels was designed. Findings revealed a positive effect on the experimental group's achievement levels with respect to Bloom's higher order thinking skills, that is, applying, analysing, and evaluating. No difference was found between the two groups in terms of academic achievements at the remembering and understanding levels of Bloom's taxonomy. Moreover, learners with low prior knowledge showed a higher improvement in academic achievements compared with those with high prior knowledge. This corresponds to the assumption of the cognitive theory of multimedia learning that learners with low prior knowledge would benefit from its principles more than learners with high prior knowledge.     

Do students benefit equally from interactive computer simulations regardless of prior knowledge levels?

The purposes of this study were to examine the effects of two types of interactive computer simulations and of prior knowledge levels on concept comprehension, cognitive load, and learning efficiency. Seventy-two 5th grade students were sampled from two elementary schools. They were divided into two groups (high and low) based on prior knowledge levels, and each group was divided into two treatment groups (a low-interactive simulation group and a high-interactive simulation group). The dependent variables were concept comprehension, cognitive load, and learning efficiency. The results showed that, for students with high prior knowledge levels, high-interactive simulations, rather than low-interactive simulations, resulted in significantly increased comprehension scores, decreased cognitive load scores, and higher learning efficiency. On the other hand, among students with low prior knowledge levels, the low-interactive simulation group did not demonstrate significantly increased comprehension scores, but they did show lower cognitive load scores and higher learning efficiency than the high-interactive simulation group.     

Effects on learning of time spent by university students attending lectures and/or watching online videos

We apply Carroll's model of school learning, which theorizes about the relationship between time and learning, to motivate the design of a large, first‐year, university mathematics course, where students have the choice to attend lectures and/or watch online videos. The theoretical model informs how the course and resources are designed in order to assist students to spend the time they need to master a task in an efficient manner. We examine the relationship between learning and time spent on lectures and/or videos, by analysing data collected on lecture attendance, videos accessed, and mathematical achievement, prior to, and at the end of, the course. Findings show that students use videos as either a complement to, or substitute for, the lecture, and time spent using either or both resources has a significant impact on learning.     

Cognitive learning efficiency through the use of design patterns in teaching

Nowadays we need to teach students how to become flexible problem solvers in a dynamic world. The pace in which technology changes and complexity increases requires increased efficiency in learning and understanding. This requires the engineers of tomorrow to quickly gain knowledge and insight outside their prime area of expertise. To transfer practical, how-to knowledge, to re-use design solutions and to teach students design solutions in the context of a specific domain, design patterns can be used. Design patterns offer a way to transfer knowledge that is more practical and ‘ready for use’ than a generic theory-based transfer of knowledge. However, the advantage of design patterns might go beyond re-use, design efficiency and flexibility. This paper argues that in addition to the benefits described above, there is a specific added value for the use of design patterns by students to acquire design skills and domain knowledge. To analyze this proposition we will analyze the literature on cognitive load and cognitive learning processes, and relate this to experiences from three case studies in which novices and experts were offered design patterns to develop and implement systems and processes. We will reflect on implications of the use of design patterns in computer-based teaching as well as on a potential support tool to improve the accessibility of pattern languages.     

The interplay between cognitive task complexity and user interaction in mobile collaborative training

Mobile collaborative training is increasingly crucial in today's mobile world, in that much complicated collaborative professional work is being conducted in the field and globally. Nevertheless, this field is lacking in holistic empirical studies to effectively understand this important phenomenon and its challenges. Accordingly, grounded upon cognitive load theory and Bloom's taxonomy, we designed and conducted a set of mobile collaborative training field experiments with 364 participants to examine the impact of the various complexities of cognitive tasks on user performance and perceptions, using a non-interactive vs. interactive mobile training app in both individual and group settings. The study findings provide useful insights into the interplay between cognitive task complexity and user interactions with both peers and technologies in a mobile collaborative training. We found that at the lowest level of cognitive complexity, user performance and perceptions of mobile training achieved the desirable improved results between non-interactive and interactive mobile app use. At the middle level of complexity, no significant differences were found. Surprisingly, at the highest level of complexity, the results indicate that cognitive task complexity and user interactions with both peers and technology significantly decreased user performance and user perceptions of mobile training. This study also offers practical implications whereby educators and training practitioners need to clearly balance the interface design of mobile training systems and different complexity levels of cognitive tasks in various training domains, in order to to achieve the desired training outcomes.     

A blended learning lecture delivery model for large and diverse undergraduate cohorts

A blended learning model was developed to enhance lecture delivery in a large, diverse introductory psychology unit, introducing the use of an online, personalized learning system for lecture preparation and using lecture time to extend students' understanding. Changes to the assessment included diagnostic, formative and summative online quizzes. Using hierarchical multiple regression to account for the variance associated with prior achievement and background knowledge, the results show that students who completed the online formative assessments had significantly higher scores on summative assessment tasks, and that scores were even higher for students who used these resources repeatedly. Changes to future implementations of the model are suggested to improve student engagement in formative assessment, and to facilitate lecturer's use of reports on student progress to focus and improve the quality of discussion in the face-to-face lectures.     

Generating a two-phase lesson for guiding beginners to learn basic dance movements

In this paper, an automated lesson generation system for guiding beginners to learn basic dance movements is proposed. It analyzes the dance to generate a two-phase lesson which can provide a suitable cognitive load thus offering an efficient learning experience. In the first phase, the dance is divided into small pieces which are patterns, and then those patterns are arranged to form an easy-to-complex learning path according to the prerequisite relations. The courseware of the second phase is responsible for guiding students to assemble all the patterns into the full dance. The learning process of the second phase adapts to the student's background knowledge and preference. It keeps monitoring the students' performances during the learning process, and adaptively adding new patterns for the students to learn. A user study which involved 52 college students who had never been trained to dance before was conducted and the results are optimistic implying that the two-phase lesson is a practical way for people to learn dance.     

Facilitating collaboration in lecture‐based learning through shared notes using wireless technologies

This paper reports a case study for developing lecture teaching in higher education by connecting simultaneously the benefits of face‐to‐face teaching and social software for capturing and sharing students' lecture notes. The study was conducted with 12 university students taking a degree course on pre‐primary education. Data were collected on (1) the nature of the shared lecture notes produced by the students; and (2) their experiences in creating and sharing lecture notes. Students wrote 367 notes in eight lecture sessions. Discourse analysis revealed five types of notes: reproducing lecture content; summarizing lecture content; connecting key concepts; developing lecture content; questions arising from lecture content. Content analysis revealed those aspects of the lectures developed through the shared notes. Discussions with four students at the end of the course explored their experiences of using the shared notes. The results are discussed in the context of changes to the cultural ecology of learning.     

A comparative simulation study of work processes in autonomous production cells

An approach to human‐centered design and assessment of work processes in flexible manufacturing systems with the help of dynamic task networks is presented. To model and simulate the task networks, the method of timed colored Petri Nets is used. Two task networks are developed. The first task network is a model of work processes in Autonomous Production Cells (APCs). The second task network represents work processes in conventional Computer Numerically Controlled (CNC)‐based manufacturing systems. The material processing technology is associated with 5‐axis milling. The values of attributes of task elements were acquired empirically on a fine‐grained level with reference to a sample milling order. Comparative hypotheses regarding time‐on‐task, supervisory control functions, levels of cognitive control, human error (HE), and labor division were then formulated. To test these hypotheses, several simulation experiments were conducted. The results from inferential statistics show that single‐operator APCs have a 30% higher efficiency in relation to total time‐on‐task. Moreover, the level of cognitive control is significantly shifted toward rule‐ and knowledge‐based behavior. Surprisingly, the simulation of minor HE does not demonstrate a significantly worse performance from APCs. A simulated labor division among central process planner and production operator allows an additional efficiency improvement of approximately 15%. However, the labor division has two important drawbacks: first, a sequential incompleteness of operators' task spectrum occurs; second, the operator has to cope with hierarchical task incompleteness. Finally, a sensitivity analysis was carried out to investigate the effects of varying lot sizes and number of processed orders. © 2002 John Wiley & Sons, Inc.     

Effects of different video lecture types on sustained attention,emotion, cognitive load,and learning performance

Although online courseware often includes multimedia materials, exactly how different video lecture types impact student performance has seldom been studied. Therefore, this study explores how three commonly used video lectures styles affect the sustained attention, emotion, cognitive load, and learning performance of verbalizers and visualizers in an autonomous online learning scenario by using a two-factor experimental design, brainwave detection, emotion-sensing equipment, cognitive load scale, and learning performance test sheet. Analysis results indicate that, while the three video lecture types enhance learning performance, learning performance with lecture capture and picture-in-picture types is superior to that associated with the voice-over type. Verbalizers and visualizers achieve the same learning performance with the three video types. Additionally, sustained attention induced by the voice-over type is markedly higher than that with the picture-in-picture type. Sustained attention of verbalizers is also significantly higher than that of visualizers when learning with the three video lectures. Moreover, the positive and negative emotions induced by the three video lectures do not appear to significantly differ from each other. Also, cognitive load related to the voice-over type is significantly higher than that with by the lecture capture and picture-in-picture types. Furthermore, the cognitive load for visualizers markedly exceeds that of verbalizers who are presented with the voice-over type. Results of this study significantly contribute to efforts to design of video lectures and also provide a valuable reference when selecting video lecture types for online learning.     

The learning kit project: Software tools for supporting and researching regulation of collaborative learning

Computer-supported collaborative learning (CSCL) is a dynamic and varied area of research. Ideally, tools for CSCL support and encourage solo and group learning processes and products. However, most CSCL research does not focus on supporting and sustaining the co-construction of knowledge. We identify four reasons for this situation and identify three critical resources every collaborator brings to collaborations that are underutilized in CSCL research: (a) prior knowledge, (b) information not yet transformed into knowledge that is judged relevant to the task(s) addressed in collaboration, and (c) cognitive processes used to construct these informational resources. Finally, we introduce gStudy, a software tool designed to advance research in the learning sciences. gStudy helps learners manage cognitive load so they can re-assign cognitive resources to self-, co-, and shared regulation; and it automatically and unobtrusively traces each user′s engagement with content and the means chosen for cognitively processing content, thus generating real-time performance data about processes of collaborative learning.     

Extracting bottlenecks for reinforcement learning agent by holonic concept clustering and attentional functions

Reinforcement learning is not well scalable in state spaces with high-dimensions. The hierarchical reinforcement learning resolves this problem by task decomposition. Task decomposition is done by extracting bottlenecks, which is in turn another challenging issue, especially in terms of time and memory complexity and the need to the prior knowledge of the environment. To alleviate these issues, a new approach is proposed toward the problem of extracting bottlenecks. Holonic concept clustering and attentional functions are proposed to extract bottleneck states. To this end, states are organized based on the effects of actions by means of a holonic clustering to extract high-level concepts. High-level concepts are used as cues for controlling attention. The proposed mechanism has a better time complexity and fewer requirements to the designer's help. The experimental results showed a considerable improvement in the precision of bottleneck detection and agent's performance for traditional benchmarks comparing to other similar methods.     

Manipulation of mental models of anatomy in interventional radiology and its consequences for design of human–computer interaction

Interventional radiology procedures require extensive cognitive processing from the physician. A set of these cognitive functions are aimed to be replaced by technology in order to reduce the cognitive load. However, limited knowledge is available regarding mental processes in interventional radiology. This research focuses on identifying mental model–related processes, in particular during percutaneous procedures, useful to improve image guidance during interventions. Ethnographic studies and a prototype-based study were conducted in order to perform a task analysis and to identify working strategies and cognitive processes. Data were compared to theories from visual imagery. The results indicate a high level of complexity of mental model construction and manipulation, in particular when mentally comparing mental model knowledge with radiology images on screen (e.g., to steer a needle correctly). Regarding current interface support, most difficult is the interpretation and selection of oblique views. New interface principles are needed to bring cognitive demands within reasonable human range, and also accompanying cognitive work strategies should be developed.     

Time identification of design knowledge push based on cognitive load measurement

The reuse of multidisciplinary design knowledge is pivotal in product development because of the increasingly fierce market competition. It can assist designers, particularly those who lack sufficient experience, in making correct decisions and achieving rapid design. Traditionally, designers primarily acquire design knowledge through information retrieval, which is typically time-consuming and inefficient. A solution that is widely considered to overcome the deficiencies of traditional knowledge retrieval approaches and actively provide designers with necessary knowledge is knowledge push. However, achieving the timely push of required knowledge to designers during the design process remains a challenging task. Accordingly, this paper presents a time identification method based on cognitive load measurement to identify the suitable time for design knowledge push. First, behavioral indicators related to the changes in cognitive load are identified by investigating the influence of the load on three types of behaviors: mouse dynamics, keystroke dynamics, and emotional states. Second, the possibility and efficacy of inferring the cognitive load by simultaneously and unobtrusively tracking the three aforementioned behaviors are considered through behavioral observations. Finally, predicting the knowledge push time based on the cognitive load using classification algorithms is investigated. The experimental results indicate that the accuracy of the proposed method in inferring the cognitive load is 55%, and that of push time is 83%.     

How a semantic diagram tool influences transaction costs during collaborative problem solving

A semantic diagram tool is proposed in this study in order to structure collaborative problem solving (CPS) based on cognitive load theory (CLT). To investigate its effects on transaction cost and the deepening of user understandings, a comparative quasi‐experiment was designed and conducted with 49 participants from a university in East China. Analysis of group dialogic acts and self‐reported cognitive load showed that a semantic diagram tool can decrease transaction costs during CPS. It can thereby help collaborators invest less effort into those procedural conversations that are necessary for managing social interaction but which do not directly contribute to deepening collaborative learning in the task domain. Data analysis of pretested and posttested domain understanding suggested that learners achieved a greater depth of understanding after CPS supported by the semantic diagram tool. These findings are interpreted in terms of CLT. A semantic diagram tool can release the learner's limited working memory from procedural conversation, creating more working memory capacity for deepening problem understanding. Therefore, this study demonstrates one means whereby a semantic diagram tool functions as a promising technological support to structure CPS.     

Modeling the cognitive content of displays

An approach for measuring the cognitive complexity of visual displays is discussed and applied to a dynamic display of avionic information. A semantic network formalism is used to model two interrelated knowledge systems, world knowledge and display knowledge. The information the operator receives during training about the general display format characteristics and the task requirements, along with other previously stored information, constitutes world knowledge. The semantic content of a particular configuration of information encountered during task performance constitutes display knowledge. Four orthogonal predictor measures of cognitive complexity were derived from the networks. In an experiment three of the orthogonal predictors were significantly correlated with task performance. After averaging across operators, the three significant predictors accounted for 99% of the variation of display effectiveness. Results indicate that a model of cognitive complexity based on a semantic network formalism may provide a useful technique for quantitatively evaluating the quality of competing display format concepts.