Cognitive-based methods to facilitate learning of software applications via E-learning systems

E-learning systems, which are used for teaching complex software, can facilitate learning if they provide an appropriate teaching approach that decreases learners’ cognitive load in addition to providing practical knowledge. We believe there is lack of cognitively guided educational recommendations on how to effectively and efficiently design such learning platforms. We thus provide an integrative review paper that overviews relevant literature to cognitive load theory to provide practical solutions and an empirically validated framework to decrease learners’ cognitive load and improve the learning of complex software through E-learning systems. The solutions (which contain practical examples) are proposed based on different concepts of cognitive load theory including using analogies, worked examples and infographics to facilitate schema acquisition; keeping learners’ concentration on the target tools by preventing split-attention and redundancy effects and applying the training wheel method; using interactive videos based on embodied cognition theory and finally considering the modality and transient information effects in designing E-learning systems. These solutions are related to adapting the learning platform to human cognitive structures and can lead to increased learning performance by preventing working memory from being overwhelmed, thus facilitating the formation of schemas and resulting in more efficient and reliable learning with less effort

A review of Websites and Mobile Applications for People with Autism Spectrum Disorders: Towards Shared Guidelines

Many studies show the effective positive impact of using computer technologies to support the lives of users with autism spectrum disorders (ASD), for simplifying interaction with other people, for organising daily activities, for improving relation with family and friends. Despite that, only a restricted part of the current websites is accessible for people with ASD. In this paper, we discuss a set of guidelines that should be followed by designers while developing websites or mobile applications for users with ASD. We review many of the existing websites and applications in order to check which comply with all, or parts of these guidelines. We finally highlight current common limitations and address new challenging research directions. \ua9 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2017

Exploring the usability of a connected autonomous vehicle human machine interface designed for older adults

Users of Level 4–5 connected autonomous vehicles (CAVs) should not need to intervene with the dynamic driving task or monitor the driving environment, as the system will handle all driving functions. CAV human-machine interface (HMI) dashboards for such CAVs should therefore offer features to support user situation awareness (SA) and provide additional functionality that would not be practical within non-autonomous vehicles. Though, the exact features and functions, as well as their usability, might differ depending on factors such as user needs and context of use. The current paper presents findings from a simulator trial conducted to test the usability of a prototype CAV HMI designed for older adults and/or individuals with sensory and/or physical impairments: populations that will benefit enormously from the mobility afforded by CAVs. The HMI was developed to suit needs and requirements of this demographic based upon an extensive review of HMI and HCI principles focused on accessibility, usability and functionality [1, 2], as well as studies with target users. Thirty-one 50-88-year-olds (M 67.52, three 50–59) participated in the study. They experienced four seven-minute simulated journeys, involving inner and outer urban settings with mixed speed-limits and were encouraged to explore the HMI during journeys and interact with features, including a real-time map display, vehicle status, emergency stop, and arrival time. Measures were taken pre-, during- and post- journeys. Key was the System Usability Scale [3] and measures of SA, task load, and trust in computers and automation. As predicted, SA decreased with journey experience and although cognitive load did not, there were consistent negative correlations. System usability was also related to trust in technology but not trust in automation or attitudes towards computers. Overall, the findings are important for those designing, developing and testing CAV HMIs for older adults and individuals with sensory and/or physical impairments

Comparing static content, animation and interactive animation while teaching software through narrative-based e-Learning systems.

IntroductionHigh element interactivity software interfaces can increase cognitive load rendering them incomprehensible for users (Reis et al., 2012). In this study gamification was selected as a procedure to reduce users’ cognitive load (Darejeh & Salim, 2016). Previous research found that familiar narrative led to superior performance when compared to an unfamiliar narrative and no narrative (Darejeh, Marcus & Sweller, 2018). In the current experiment, different ways of delivering familiar narrative-based content were evaluated. Teaching software using e-learning systems including static content, animation and interactive animation, were compared. Static content involved using pictures and text, animation included video and audio, and interactive animation enables users to interact with the video content by clicking on elements, in the way users interact with web content. MethodSixty novice users were selected using a computer skill placement test form with 20 participants in each of the static, animation and interactive animation groups. Microsoft Access was taught with 1 topic from tools with low interactivity and 1 with high interactivity. Each participant read 2 tutorials and performed 2 tasks. During learning, time was measured and a subjective rating scale was administered afterwards. After each tutorial, one task in Microsoft Access was assigned to the participants. Time duration, mouse movement distance, and number of left and right clicks were measured. After performing each task, participants were asked to complete a subjective rating scale. ResultsA Linear Mixed Model test was conducted to test for interactions between the three groups (static, animation, and interactive animation) and the low and high interactivity tasks for each dependent variable. The results showed delivery method for the teaching material (static, animation, and interactive animation) influenced participants’ performance in learning low element interactivity materials versus high materials differently for a number of dependent variables including: task duration, F(2, 57)= 4.18, p < .05, tutorial duration, F(2, 57)= 59.67, p < .05, task confidence level questions, F(2, 57)= 4.36, p < .05, and the tutorial confidence level question, F(2, 57)= 4.72, p < .05. Post hoc analyses using a one-way ANOVA showed that animations versus statics could have significant positive effects on a high element interactivity task by increasing task completion rates, F(1, 38) = 5.43, p < .05, and decreasing duration, F(1, 38)= 6.55, p < .05, mouse movements, F(1, 38)= 5.67, p < .05, and left clicks, F(1, 38)= 6.26, p < .05. Additionally, participants reported significantly less difficulty, F(1, 38)= 5.10, p < .05 and more confidence, F(1, 38)= 5.37, p < .05 in performing the tasks. Comparing animation and interactive animation showed significant decreases in the number of right clicks for both low, F(1, 38)= 5.51, p < .05 and high, F(1, 38)= 5.14, p < .05 element interactivity tasks. Furthermore, participants reported significantly less difficulty, F(1, 38)= 4.89, p < .05, less stress, F(1, 38)= 4.84, p < .05 and more confidence, F(1, 38)=4.45, p < .05 for the high element interactivity tutorial.Discussion and ConclusionThe findings showed that, in comparison with static content, both animation and interactive animation can significantly decrease cognitive load and increase the ability of the users to complete different tasks using the target software, especially for high element interactivity tasks. In addition to increasing users’ performance in completing the tasks, the participant's response to the questionnaire showed that the interactive animation decreased the perceived difficulty level of the learning content more than the animation version and reduced the chance of unnecessary right clicks. It can be concluded that the animation version was superior to the static version and the interactive animation was superior to both the static and the animation-based version. ReferencesDarejeh, A., Marcus, N., & Sweller, J., 2018. The effect of gamification on novice users’ cognitive load while learning software applications in E-learning systems. 12th International Cognitive Load Theory Conference, Sep. 2018, Beijing, China.Darejeh, A., & Salim, S. S. (2016). Gamification solutions to enhance software user engagement—a systematic review. International Journal of Human-Computer Interaction, 32(8), 613-642.Reis, H. M., et al., (2012). Towards Reducing Cognitive Load and Enhancing Usability through a Reduced Graphical User Interface for a Dynamic Geometry System: An Experimental Study. Proceedings of IEEE International Symposium on Multimedia (ISM) (pp: 445 - 450). Irvine, CA: IEEE Xplore Press. DOI:10.1109/ISM.2012.9

An emerging framework to inform effective design of human-machine interfaces for older adults using connected autonomous vehicles

Connected autonomous vehicles (CAVs) represent an exciting opportunity for wider access to mobility; especially for individuals unable to drive manual vehicles. Interaction with CAVs will be through human-machine interfaces (HMIs) providing journey-related and other information with some interactivity. These should be designed with potential users as part of a co-design process to maximize acceptance, engagement, and trust. This paper presents an emerging framework to inform the design of in-vehicle CAV HMIs with a focus on older adults (70-years+). These could be amongst early adopters of CAVs and tend to have the highest level of cognitive, sensory, and physical impairments. Whilst there are numerous principles on HMI design for older adults there are fewer on HMIs for AVs, and a need for research on CAV HMI design principles for older adults. Our emerging framework is novel and important for designers of CAV HMIs for older adults and other potential users