Effects of digital dictionary format on incidental acquisition of spelling knowledge and cognitive load during second language learning: Click-on vs. key-in dictionaries

Recent research has shown that students involved in computer-based second language learning prefer to use a digital dictionary in which a word can be looked up by clicking on it with a mouse (i.e., click-on dictionary) to a digital dictionary in which a word can be looked up by typing it on a keyboard (i.e., key-in dictionary). This study investigated whether digital dictionary format also differentially affects students' incidental acquisition of spelling knowledge and cognitive load during second language learning. A comparison between a click-on dictionary condition, a key-in dictionary condition, and a non-dictionary control condition for 45 Taiwanese students learning English as a foreign language revealed that learners who used a key-in dictionary invested more time investment on dictionary consultation than learners who used a click-on dictionary. However, on a subsequent unexpected spelling test the key-in group invested less time investment and performed better than the click-on group. The theoretical and practical implications of the results are discussed.     

The influence of node sequence and extraneous load induced by graphical overviews on hypertext learning

The effects of four hypertext learning environments with a hierarchical graphical overview were studied on the coherence of the node sequence, extraneous load and comprehension. Navigation patterns were influenced by the type of overview provided (i.e., dynamic, static) and whether navigation was restricted (i.e., restricted, non-restricted). It was hypothesised that redundant use of the overview for inducing a high-coherence reading sequence would result in high extraneous load and low comprehension. Coherence was higher in the dynamic than in the static conditions. Coherence was also higher in the restricted than in the non-restricted conditions. Mental effort as a measure of extraneous load was higher at the end than at the beginning of the learning phase, especially in the dynamic restricted and the static non-restricted conditions, although there was no significant interaction. Comprehension was lowest in the dynamic restricted condition and highest in the dynamic non-restricted and static restricted conditions. Low comprehension in the dynamic restricted condition indicates that overviews can become redundant for reading sequence coherence, negatively impacting comprehension. The evidence suggests that severe restriction of navigation paths should be avoided and that continuous use of overviews such as in dynamic overviews may be detrimental to learning.     

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.     

A classification-oriented dictionary learning model: Explicitly learning the particularity and commonality across categories

Empirically, we find that despite the most exclusively discriminative features owned by one specific object category, the various classes of objects usually share some common patterns, which do not contribute to the discrimination of them. Concentrating on this observation and motivated by the success of dictionary learning (DL) framework, in this paper, we propose to explicitly learn a class-specific dictionary (called particularity) for each category that captures the most discriminative features of this category, and simultaneously learn a common pattern pool (called commonality), whose atoms are shared by all the categories and only contribute to representation of the data rather than discrimination. In this way, the particularity differentiates the categories while the commonality provides the essential reconstruction for the objects. Thus, we can simply adopt a reconstruction-based scheme for classification. By reviewing the existing DL-based classification methods, we can see that our approach simultaneously learns a classification-oriented dictionary and drives the sparse coefficients as discriminative as possible. In this way, the proposed method will achieve better classification performance. To evaluate our method, we extensively conduct experiments both on synthetic data and real-world benchmarks in comparison with the existing DL-based classification algorithms, and the experimental results demonstrate the effectiveness of our method.     

Learning programming via worked-examples: Relation of learning styles to cognitive load

This paper describes an experiment that compared learners with contrasting learning styles, Active vs. Reflective, using three different strategies for learning programming via worked-examples: Paired-method, Structure-emphasising, and Completion. The quality of the learners’ acquired cognitive schemata was assessed in terms of their post-test performance. The experiment investigated variations in learners’ cognitive load, taking both the learning strategies and the learners’ learning styles into account. Overall, the results of the experiment were inconsistent. In comparing the effects of the strategies during the learning phase, the study found significant differences in cognitive load. Unexpectedly, no differences were then detected either in cognitive load or in performance during the post-test (post-test). In comparing the effects of the learning styles during the learning phase and the transfer phase, medium effect sizes suggested that learning style may have had an effect on cognitive load. However, no significant difference was observed in performance during the post-test.     

First impressions last a lifetime: effect of interface type on disorientation and cognitive load

Today, technology users are faced with a multitude of different interfaces for computer applications, web sites, vehicle navigation, and cellular phones. In most cases, training to use these technologies is minimal or none and is left up to the user to learn the use of the technology at hand. Subsequently, their initial impression, which is dependent on how successful they can achieve simple tasks during their self-directed learning process, plays an important role in their intention to adopt the technology. Many users have trouble learning and remembering information presented on the screen. Disorientation and cognitive loading are two primary cognitive conditions that may be used to learn more about human behavior while using different type of interfaces. This paper presents the results of an experiment on computer user’s behavior while using one of two types of software interfaces: a menu-driven and an icon-based interfaces. Disorientation and cognitive loading theories are used to explain observations. A research model based on the technology acceptance model is used. Results show a strong relationship between performance and perceptions. The mediating effects on the different interfaces on perceptions are evident and significant considering that perceptions have been shown to predict computer user’s attitudes towards their intentions to use a technology. The experiment demonstrated the need to consider standard consistent interfaces when training is not provided.     

Examining different types of collaborative learning in a complex computer-based environment: A cognitive load approach

This study compared the effects of two collaborative learning strategies (Open-ended and Task-based) with an individualized learning strategy on individual learning in a computer-based environment. The experiment sought ecological validity by conducting it under real teaching and homework conditions. Ninety-four students from grade 9 participated in a webpage design task. Cognitive load theory was used to predict that the collaborative approaches would outperform the individualized approach due to reduced cognitive load. This hypothesis was confirmed by performance scores and cognitive load only in the case of the Open-ended collaborative learning condition. Evidence was also found that the Open-ended collaborative learning condition outperformed the Task-based collaborative one. It was concluded that in collaborative learning a more Open-ended task design together with moderate independent sub-task requirements leads to more effective learning.     

Dynamics of cognitive load theory: A model-based approach

Since its conception nearly two decades ago, cognitive load theory (CLT) has been a fertile ground for both empirical and theoretical investigations. The research accumulated over the years has contributed not only to the theory’s validation, but also generated new insights. These new insights helped to refine CLT, making it more precise, but also more complex. A formal (mathematical) simulation model is proposed as a new analytical tool for investigating CLT’s increasingly intricate postulates and their dynamic implications. This paper describes how the theoretical relationships between certain features of instruction and the cognitive capacities of learners can be expressed formally, and how the resulting model can help gain insights into the learning dynamics that arise from these relationships, providing a new aid for research, teaching and practice in the field of instructional design.     

A morphable template framework for robot learning by demonstration: Integrating one-shot and incremental learning approaches

Robot learning by demonstration is key to bringing robots into daily social environments to interact with and learn from human and other agents. However, teaching a robot to acquire new knowledge is a tedious and repetitive process and often restrictive to a specific setup of the environment. We propose a template-based learning framework for robot learning by demonstration to address both generalisation and adaptability. This novel framework is based upon a one-shot learning model integrated with spectral clustering and an online learning model to learn and adapt actions in similar scenarios. A set of statistical experiments is used to benchmark the framework components and shows that this approach requires no extensive training for generalisation and can adapt to environmental changes flexibly. Two real-world applications of an iCub humanoid robot playing the tic-tac-toe game and soldering a circuit board are used to demonstrate the relative merits of the framework.     

The influence of leads on cognitive load and learning in a hypertext environment

The purpose of this study was to determine the effect of leads (or hypertext node previews) on cognitive load and learning. Leads provided a brief summary of information in the linked node, which helped orient the reader to the linked information. Dependent variables included measures of cognitive load: self-report of mental effort, reading time, and event-related desynchronization percentage of alpha, beta and theta brain wave rhythms; and learning performance: a recall task, and tests of domain and structural knowledge. Results indicated that use of leads reduced brain wave activity that may reflect split attention and extraneous cognitive load, and improved domain and structural knowledge acquisition. Further, findings provide insights into differentiating the types of cognitive load apparent in hypertext-assisted learning environments. Use of EEG measures allowed examination of instantaneous cognitive load, which showed that leads may be influencing germane load—reducing mental burden associated with creating coherence between two linked node. The self-report of mental effort measure appears more closely associated with overall and intrinsic load.     

The impact of goal specificity and goal type on learning outcome and cognitive load

Two hundred and thirty three 15-year old students conducted experiments within a computer-based learning environment. They were provided with different goals according to an experimental 2 × 2 design with goal specificity (nonspecific goals versus specific goals) and goal type (problem solving goals versus learning goals) as factors. We replicated the findings of other researchers that nonspecific problem solving goals lead to lower cognitive load and better learning than specific problem solving goals. For learning goals, however, we observed this goal specificity effect only on cognitive load but not on learning outcome. Results indicate that the goal specificity affects the element interactivity of a task and cognitive load with both, problem solving goals or learning goals. But differences in overall cognitive load are not sufficient for explaining differences in learning outcome. Additionally, differences in strategy use come into play. Specific problem solving goals seem to restrict students to use a problem solving strategy whereas nonspecific problem solving goals or learning goals allow students to use a learning strategy. We conclude that in order to foster learning, students must be provided with goals that allow them to use a learning strategy. Additionally, providing them with nonspecific goals decreases cognitive load and, thus, enables students to learn with less effort.     

The influence of virtual presence: Effects on experienced cognitive load and learning outcomes in educational computer games

Does the immersive design of an educational gaming environment affect learners’ virtual presence and how much do they learn? Does virtual presence affect learning? This study tries to answer these questions by examining the differences in virtual presence and learning outcomes in two different computer-based multimedia environments: a gaming environment with high immersive design vs. hypertext learning environment with low immersive design. As the main focus, the effect of virtual presence on learning is also explained and tested. By identifying virtual presence as a variable that may determine learning, it is argued that computer gaming environments present a new challenge for researchers to investigate, particularly, the effects of virtual presence on the immersive design of games in order to help designers to predict which instructional configurations will maximize learning performance. In general, results revealed that the high-immersive gaming environment leads to the strongest form of virtual presence but also decreased learning. Although regression analyses indicate that virtual presence positively influences trivial- and non-trivial learning outcomes, learners who learned in a low-immersive environment outperformed the gaming group. A mediation analysis showed that the relation between virtual presence and non-trivial learning outcomes is partly mediated through increased cognitive load.     

The effects of time-compressed instruction and redundancy on learning and learners’ perceptions of cognitive load

Can increasing the speed of audio narration in multimedia instruction decrease training time and still maintain learning? The purpose of this study was to examine the effects of time-compressed instruction and redundancy on learning and learners’ perceptions of cognitive load. 154 university students were placed into conditions that consisted of time-compression (0%, 25%, or 50%) and redundancy (redundant text and narration or narration only). Participants were presented with multimedia instruction on the human heart and its parts then given factual and problem solving knowledge tests, a cognitive load measure, and a review behavior (back and replay buttons) measure. Results of the study indicated that participants who were presented 0% and 25% compression obtained similar scores on both the factual and problem solving measures. Additionally, they indicated similar levels of cognitive load. Participants who were presented redundant instruction were not able to perform as well as participants presented non-redundant instruction.     

Effects of simultaneously observing and making gestures while studying grammar animations on cognitive load and learning

This study examined whether simultaneously observing and making gestures while studying animations would lighten cognitive load and facilitate the acquisition of grammatical rules. In contrast to our hypothesis, results showed that children in the gesturing condition performed worse on the posttest than children in the non-gesturing, control condition. A more detailed analysis of the data revealed an expertise reversal effect, indicating that this negative effect on posttest performance materialized for children with lower levels of general language skills, but not for children with higher levels of general language skills. The finding that for children with lower language ability, cognitive load did not decrease as they saw more animations provided additional support for this expertise reversal effect. These findings suggest that the combination of observing and making gestures may have imposed extraneous cognitive load on the lower ability children, which they could not accommodate together with the relatively high intrinsic load imposed by the learning task.     

Design of adaptive hypermedia learning systems: A cognitive style approach

In the past decade, a number of adaptive hypermedia learning systems have been developed. However, most of these systems tailor presentation content and navigational support solely according to students’ prior knowledge. On the other hand, previous research suggested that cognitive styles significantly affect student learning because they refer to how learners process and organize information. To this end, the study presented in this paper developed an adaptive hypermedia learning system tailored to students’ cognitive styles, with an emphasis on Pask’s Holist–Serialist dimension. How students react to this adaptive hypermedia learning system, including both learning performance and perceptions, was examined in this study. Forty-four undergraduate and postgraduate students participated in the study. The findings indicated that, in general, adapting to cognitive styles improves student learning. The results also showed that the adaptive hypermedia learning system have more effects on students’ perceptions than performance. The implications of these results for the design of adaptive hypermedia learning systems are discussed.