Multimodal Technol. Interact., Volume 8, Issue 4 (April 2024) – 11 articles

Software developers new to creating Augmented Reality (AR) experiences often gravitate towards simplified development environments, such as 3D game engines. While popular game engines such as Unity and Unreal have evolved to offer extensive support and functionalities for AR creation, many developers still find it difficult to realize their immersive development projects. We ran an observational study with 12 software developers to assess how they approach the initial AR creation processes using a simplified development framework, the information resources they seek, and how their learning experience compares to the more mainstream 2D development. We observed that developers often started by looking for code examples rather than breaking down complex problems, leading to challenges in visualizing the AR experience. They encountered vocabulary issues and found trial-and-error methods ineffective due to a lack of familiarity with 3D environments, physics, and motion. These observations highlight the distinct needs of emerging AR developers and suggest that conventional code reuse strategies in mainstream development may be less effective in AR. We discuss the importance of developing more intuitive training and learning methods to foster diversity in developing interactive systems and support self-taught learners. Full article

Recent evidence shows that physiological cues, such as pupil dilation (PD), heart rate (HR), skin conductivity (SC), and electroencephalography (EEG), can indicate cognitive load (CL) in users while performing tasks. This paper aims to investigate physiological (multimodal) measurement of CL in a Sternberg memory task as the difficulty level increases in both maintenance and probe phases. For this purpose, we designed a Sternberg memory test with four levels of difficulty determined by the number of letters in the words that need to be remembered. Our behavioral performance results show that the CL of the task is related to the number of letters in non-semantic words, which confirms that this task serves as an appropriate metric of CL (the task difficulty increases as the number of letters in words increases). We were interested in investigating the suitability of multimodal physiological measures as correlates of four CL levels for both the maintenance and probe phases in the Sternberg memory task. Our motivation was to: (1) design and create four levels of task difficulty with a gradual increase in CL rather than just high and low CL, (2) use the Sternberg test as our test bed, (3) explore both the maintenance and probe phases for measurement of CL, and (4) explore the correlation of physiological cues (PD, HR, SC, EEG) with CL in both phases. Testing with the system, we found that for both the maintenance and probe phases, there was a significant positive linear relationship between average baseline corrected PD and CL. We also observed that the average baseline corrected SC showed significant increases as the number of letters in the words increased for both the maintenance and probe phases. However, the HR analysis did not show any correlation with an increase in CL in either of the maintenance or probe phases. An additional analysis was conducted to investigate the correlation of these physiological signals for high (seven-letter words) versus low (four-letter words) CL loads. Our EEG analysis for the maintenance phase found significant positive linear relationships between the power spectral density (PSD) and CL for the upper alpha bands in the centrotemporal, frontal, and occipitoparietal regions of the brain and significant positive linear relationships between the PSD and CL for the lower alpha band in the frontal and occipitoparietal regions. However, our EEG analysis of the probe phase did not show any linear relationship between the PSD and CL in any region. These results suggest that PD, SC, and EEG could be used as suitable metrics for the measurement of cognitive load in Sternberg memory tasks. We discuss this, limitations of the study, and directions for future work. Full article

Fitness apps are persuasive tools developed to motivate physical activity. Despite their popularity, there is little work on how social-cognitive characteristics such as culture, household size, physical activity level, perceived self-efficacy and social support influence users’ willingness to use them and preference (personal vs. social). Knowing these relationships can help developers tailor fitness apps to different socio-cultural groups. Hence, we conducted two studies to address the research gap. In the first study (n = 194) aimed at recruiting participants for the second study, we asked participants about their app preference (personal vs. social), physical activity level and key demographic variables. In the second study (n = 49), we asked participants about their social-cognitive beliefs about exercise and their willingness to use a fitness app (presented as a screenshot). The results of the first study showed that, in the collectivist group (Nigerians), people in large households were more likely to be active and use the social version of a fitness app than those in small households. However, in the individualist group (Canadians/Americans), neither the preference for the social or personal version of a fitness app nor the physical activity level depended on the household size. Moreover, in the second study, in the individualist model, perceived self-efficacy and perceived self-regulation have a significant total effect on willingness to use a fitness app. However, in the collectivist model, perceived social support and outcome expectation have a significant total effect on the target construct. Finally, we found that females in individualist cultures had higher overall social-cognitive beliefs about exercise than males in individualist cultures and females in collectivist cultures. The implications of the findings are discussed. Full article

In the modern digital landscape, parental involvement in shaping children’s internet usage has gained unprecedented importance. This research delves into the evolving trends of parental mediation concerning children’s internet activities. As the digital realm increasingly influences young lives, the role of parents in guiding and safeguarding their children’s online experiences becomes crucial. The study addresses key research questions to explore the strategies parents adopt, the content they restrict, the rules they establish, the potential exposure to inappropriate content, and the impact of parents’ computer literacy on their children’s internet safety. Additionally, the research includes a thematic question that broadens the analysis by incorporating insights from studies not directly answering the primary questions but contributing valuable context and understanding to the digital parenting arena. Building on this, the findings from a systematic literature review, conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, highlight a shift towards more proactive parental involvement. Incorporating 49 studies from 11 databases, these findings reveal the current trends and methodologies in parental mediation. Active mediation strategies, which involve positive interactions and discussions about online content, are gaining recognition alongside the prevalent restrictive mediation approaches. Parents are proactively forbidding specific internet content, emphasizing safety and privacy concerns. Moreover, the emergence of parents’ computer literacy as a significant factor influencing their children’s online safety underlines the importance of digital proficiency. By shedding light on the contemporary landscape of parental mediation, this study contributes to a deeper understanding of how parents navigate their children’s internet experiences and the challenges they face in ensuring responsible and secure online engagement. The implications of these findings offer valuable insights for both practitioners and researchers, emphasizing the need for active parental involvement and the importance of enhancing parents’ digital proficiency. Despite limitations due to the language and methodological heterogeneity among the included studies, this research paves the way for future investigations into digital parenting practices. Full article

A growing number of higher-education institutions are implementing synchronous hybrid delivery, which provides both online and on-campus learners with simultaneous instruction, especially for facilitating discussions in Active Learning (AL) contexts. However, learners face difficulties in picking up social cues and gaining free access to speaking rights due to the geometrical misalignment of individuals mediated through screens. We assume that the cultivation of discussions is allowed by ensuring the spatial localization of learners similar to that in a physical space. This study aims to design a synchronous hybrid learning environment, called Mirror Campus (MC), suitable for the AL scenario that connects physical and cyberspaces by providing spatial localization of learners. We hypothesize that the MC promotes discussion-oriented behaviors, and eventually enhances applied skills for group tasks, related to discussion, creativity, decision-making, and interdependence. We conducted an experiment with five different groups, where four participants in each group were asked to discuss a given topic for fifteen minutes, and clarified that the occurrences of facing behaviors, intervening, and simultaneous utterances in the MC were significantly increased compared to a conventional video conferencing. In conclusion, this study demonstrated the significance of the spatial localization of learners to facilitate discussion-oriented behaviors such as facing and speech. Full article

To help young people understand socio-environmental systems and develop the confidence that meaningful action can be taken to address socio-environmental problems, young people need interactive simulations that enable them to take consequential actions in a familiar context and see the results. This can be achieved through reduced-form models with appropriate user interfaces, but it is a significant challenge to construct a system capable of producing educational models of socio-environmental systems that are localizable and customizable but accessible to educators and learners. In this paper, we present iPlan, a free, online educational software application designed to enable educators and middle- and high-school-aged learners to create custom, localized land-use simulations that can be used to frame, explore, and address complex land-use problems. We describe in detail the software application and its underlying computational models, and we present robust evidence that the accuracy of iPlan simulations is appropriate for educational contexts and preliminary evidence that educators are able to produce simulations suitable for their pedagogical goals and learner populations. Full article

In this paper, we present an approach to improve pointing methods and target selection on tactile human–machine interfaces. This approach defines a two-level highlighting technique (TLH) based on the direction of gaze for target selection on a touch screen. The technique uses the orientation of the user’s head to approximate the direction of his gaze and uses this information to preselect the potential targets. An experimental system with a multimodal interface has been prototyped to assess the impact of TLH on target selection on a touch screen and compare its performance with that of traditional methods (mouse and touch). We conducted an experiment to assess the effectiveness of our proposition in terms of the rate of selection errors made and time for completion of the task. We also made a subjective estimation of ease of use, suitability for selection, confidence brought by the TLH, and contribution of TLH to improving the selection of targets. Statistical results show that the proposed TLH significantly reduces the selection error rate and the time to complete tasks. Full article

As data-driven models gain importance in driving decisions and processes, recently, it has become increasingly important to visualize the data with both speed and accuracy. A massive volume of data is presently generated in the educational sphere from various learning platforms, tools, and institutions. The visual analytics of educational big data has the capability to improve student learning, develop strategies for personalized learning, and improve faculty productivity. However, there are limited advancements in the education domain for data-driven decision making leveraging the recent advancements in the field of machine learning. Some of the recent tools such as Tableau, Power BI, Microsoft Azure suite, Sisense, etc., leverage artificial intelligence and machine learning techniques to visualize data and generate insights from them; however, their applicability in educational advances is limited. This paper focuses on leveraging machine learning and visualization techniques to demonstrate their utility through a practical implementation using K-12 state assessment data compiled from the institutional websites of the States of Texas and Louisiana. Effective modeling and predictive analytics are the focus of the sample use case presented in this research. Our approach demonstrates the applicability of web technology in conjunction with machine learning to provide a cost-effective and timely solution to visualize and analyze big educational data. Additionally, ad hoc visualization provides contextual analysis in areas of concern for education agencies (EAs). Full article

This study investigates the integration of immersive technologies, primarily virtual reality (VR), in the domain of karate training and practice. The scoping review adheres to PRISMA guidelines and encompasses an extensive search across IEEE Xplore, Web of Science, and Scopus databases, yielding a total of 165 articles, from which 7 were ultimately included based on strict inclusion and exclusion criteria. The selected studies consistently highlight the dominance of VR technology in karate practice and teaching, with VR often facilitated by head-mounted displays (HMDs). The main purpose of VR is to create life-like training environments, evaluate performance, and enhance skill development. Immersive technologies, particularly VR, offer accurate motion capture and recording capabilities that deliver detailed feedback on technique, reaction time, and decision-making. This precision empowers athletes and coaches to identify areas for improvement and make data-driven training adjustments. Despite the promise of immersive technologies, established frameworks or guidelines are absent for their effective application in karate training. As a result, this suggests a need for best practices and guidelines to ensure optimal integration. Full article

Today, reinforcement learning is one of the most effective machine learning approaches in the tasks of automatically adapting computer systems to user needs. However, implementing this technology into a digital product requires addressing a key challenge: determining the reward model in the digital environment. This paper proposes a usability reward model in multi-agent reinforcement learning. Well-known mathematical formulas used for measuring usability metrics were analyzed in detail and incorporated into the usability reward model. In the usability reward model, any neural network-based multi-agent reinforcement learning algorithm can be used as the underlying learning algorithm. This paper presents a study using independent and actor-critic reinforcement learning algorithms to investigate their impact on the usability metrics of a mobile user interface. Computational experiments and usability tests were conducted in a specially designed multi-agent environment for mobile user interfaces, enabling the implementation of various usage scenarios and real-time adaptations. Full article

Running is a popular sport throughout the world. Breathing strategies like stable breathing and slow breathing can positively influence the runner’s physiological and psychological experiences. Sonic breathing instructions are an established, unobtrusive method used in contexts such as exercise and meditation. We argue sound to be a viable approach for administering breathing strategies whilst running. This paper describes two laboratory studies using within-subject designs that investigated the usage of sonic breathing instructions with novice female runners. The first study (N = 11) examined the effect of information richness of five different breathing instruction sounds on adherence and user experience. The second study (N = 11) explored adherence and user experience of sonically more enriched sounds, and aimed to increase the sonic experience. Results showed that all sounds were effective in stabilizing the breathing rate (study 1 and 2, respectively: mean absolute percentage error = 1.16 ± 1.05% and 1.9 ± 0.11%, percent time attached = 86.81 ± 9.71% and 86.18 ± 11.96%). Information-rich sounds were subjectively more effective compared to information-poor sounds (mean ratings: 7.55 ± 1.86 and 5.36 ± 2.42, respectively). All sounds scored low (mean < 5/10) on intention to use. Full article