Nadine Marcus

Instructional animations can be superior to statics when learning human motor skills

Based on the assumption of a working memory processor devoted to human movement, cognitive load theory is used to explore some conditions under which animated instructions are hypothesised to be more effective for learning than equivalent static graphics. Using paper-folding tasks dealing with human movement, results from three experiments confirmed our hypothesis, indicating a superiority of animation over static graphics. These results are discussed in terms of a working memory processor that may be facilitated by our mirror-neuron system and may explain why animated instructional animations are superior to static graphics for cognitively based tasks that involve human movement.

Learning hand manipulative tasks: When instructional animations are superior to equivalent static representations

Cognitive load theory was used to argue why instructional animations are more effective in teaching human motor skills than static representations. A key aspect to this argument is the role played by the transitory nature of animation and the newly discovered human mirror-neuron system. In two experiments students were taught to tie knots or complete puzzle rings either through an animated presentation or an equivalent sequence of static diagrams. In both experiments students learnt more from the animation mode than the static one, thus supporting the general thesis of the paper.

Should hand actions be observed when learning hand motor skills from instructional animations

This study investigated whether the effectiveness of learning a hand-motor task through an instructional animation required observation of the hands or not. Cognitive load theory was used to predict that both animated conditions (with and without hands) would be equally effective, and that both animations would be superior to an equivalent static graphics presentation. 36 adults were randomly assigned to three groups (With-hands animation, No-hands animation, Statics graphics) and were required to learn how to tie two knots. Test results confirmed that both animations led to superior learning compared to the static presentation. However, the With-hands animation strategy had a further advantage in that it had higher instructional efficiency than the No-hands animation.

Analysis of Collaborative Communication for Linguistic Cues of Cognitive Load

Objective: Analyses of novel linguistic and grammatical features, extracted from transcribed speech of people working in a collaborative environment, were performed for cognitive load measurement. Background: Prior studies have attempted to assess users’ cognitive load with several measures, but most of them are intrusive and disrupt normal task flow. An effective measurement of people’s cognitive load can help improve their performance by deploying appropriate output and support strategies accordingly. Methods: The authors studied 33 members of bushfire management teams working collaboratively in computerized incident control rooms and involved in complex bushfire management tasks. The participants’ communication was analyzed for some novel linguistic features as potential indices of cognitive load, which included sentence length, use of agreement and disagreement phrases, and use of personal pronouns, including both singular and plural pronoun types. Results: Results showed users’ different linguistic and grammatical patterns with various cognitive load levels. Specifically, with high load, people spoke more and used longer sentences, used more words that indicated disagreement with other team members, and exhibited increased use of plural personal pronouns and decreased use of singular pronouns. Conclusion: The article provides encouraging evidence for the use of linguistic and grammatical analysis for measuring users’ cognitive load and proposes some novel features as cognitive load indices. Application: The proposed approach may be applied to many data-intense and safety-critical task scenarios, such as emergency management departments, for example, bushfire or traffic incident management centers; air traffic control rooms; and call centers, where speech is used as part of everyday tasks.

Measuring Cognitive Load Using Linguistic Features: Implications for Usability Evaluation and Adaptive Interaction Design

An intelligent adaptable system, aware of a user’s experienced cognitive load, may help improve performance in complex, time-critical situations by dynamically deploying more appropriate output strategies to reduce cognitive load. However, measuring a user’s cognitive load robustly, in real-time is not a trivial task. Many research studies have attempted to assess users’ cognitive load using different measurements, but these are often unsuitable for deployment in real-life applications due to high intrusiveness. Relatively novel linguistic behavioral features as potential indices of user’s cognitive load is proposed. These features may be collected implicitly and nonintrusively supporting real-time assessment of users’ cognitive load and accordingly allowing adaptive usability evaluation and interaction. Results from a laboratory experiment show significantly different linguistic patterns under different task complexities and cognitive load levels. Implications of the research for adaptive interaction are also discussed, that is, how the cognitive load measurement-based approach could be used for user interface evaluation and interaction design improvement.

Instructional Support for Teachers and Guided Feedback for Students in an Adaptive eLearning Environment

Adaptive Tutorials are Intelligent Tutoring Systems (ITS) in which students typically interact with a simulation towards a task-goal while being guided and remediated. Adaptive Tutorials can exhibit different kinds of feedback: students are given guidance based on their interaction, and teachers can also receive feedback on their own authoring choices to drive reflection and content adaptation. This paper will discuss different types of feedback which students are given within Adaptive Tutorials and their pedagogical utility. It will then look at providing teachers with timely support and feedback as well as post-hoc solution traces, to improve student learning. We suggest a refined ITS design and development lifecycle to better support teachers in the design of good pedagogy. We provide this in the form of the Adaptive eLearning Platform, which is a tool to support teachers in the adaptation of tutorials and the creation of customized student feedback. This in turn can result in an improved student experience, with more guidance and better learning.

Using Galvanic Skin Response (GSR) to Measure Trust and Cognitive Load in the Text-Chat Environment

Exchanging text messages via software on smart phones and computers has recently become one of the most popular ways for people to communicate and accomplish their tasks. However, there are negative aspects to using this kind of software, for example, it has been found that people communicating in the text-chat environment may experience a lack of trust and may face different levels of cognitive load [1, 11]. This study examines a novel way to measure interpersonal trust and cognitive load when they overlap with each other in the text-chat environment. We used Galvanic Skin Response (GSR), a physiological measurement, to collect data from twenty-eight subjects at four gradients and overlapping conditions between trust and cognitive load. The findings show that the GSR signals were significantly affected by both trust and cognitive load and provide promising evidence that GSR can be used as a tool for measuring interpersonal trust when cognitive load is low and also for measuring cognitive load when trust is high.

Trust and cognitive load in the text-chat environment: the role of mouse movement

This paper examines how different levels of cognitive load can affect trust in the text-chat environment. It also examines how the mouse movements of participants can indicate the level of cognitive load when they chat with each other. We designed two chat systems: one in which subjects chat under low mental load and the other in which subjects chat under high mental load. Twenty subjects participated in the study and the results showed significant differences in the level of trust between subjects under different cognitive loads; that is, subjects who chatted under low mental load showed more trust in their partners. Moreover, the mouse data obtained proved to be effective in indicating the level of cognitive load existing between the subjects. However, this work suggests that to establish trust in the chat environment, it is better to communicate under a low cognitive load. Our findings also show the ability of designed systems to measure cognitive load via tracking mouse events for the purpose of providing assistance to communicators.

Trust and cooperation in text-based computer-mediated communication

This study examines how different behaviours can affect trust in the text-chat environment. We designed two automated chat systems: one behaves cooperatively and the other behaves competitively. Thirty subjects participated in this study and the results revealed that the trust of subjects who chatted with a cooperative partner was significantly higher than the trust of subjects who chatted with a competitive partner. This study also examines the chat contents and the results show that subjects behave differently when they trust their partner, using more assent and positive emotion words.

Can More Become Less? Effects of an Intensive Assessment Environment on Students' Learning Performance.

Online interactive systems offer the beguiling prospect of an improved environment for learning at minimum extra cost. We have developed online interactive tutorials that adapt the learning environment to the current learning status of each individual student. These Adaptive Tutorials (ATs) modify the tasks given to each student according to their previous responses. Feedback, assessment and remediation are also adapted. Over a three-year period we progressively blended ATs into notoriously challenging courses in introductory Engineering Mechanics. We assessed the impact of this initiative by reviewing three lines of data: (i) the built-in diagnostics of the system, (ii) changes in student grades from year-to-year and (iii) supplementary surveys. Generally, students liked the new blended system and grades improved. Detailed analysis revealed nuances in the measures of student learning, such as differences between high-performing and low-performing students. With these insights we are able to further adapt the system to meet the learning needs of our students.