As driving functions become increasingly automated, motorists run the risk of becoming cognitively removed from the driving process. Psychophysiological measures may provide added value not captured through behavioral or self-report measures alone. This paper provides a selective review of the psychophysiological measures that can be utilized to assess cognitive states in real-world driving environments. First, the importance of psychophysiological measures within the context of traffic safety is discussed. Next, the most commonly used physiology-based indices of cognitive states are considered as potential candidates relevant for driving research. These include: electroencephalography and event-related potentials, optical imaging, heart rate and heart rate variability, blood pressure, skin conductance, electromyography, thermal imaging, and pupillometry. For each of these measures, an overview is provided, followed by a discussion of the methods for measuring it in a driving context. Drawing from recent empirical driving and psychophysiology research, the relative strengths and limitations of each measure are discussed to highlight each measures' unique value. Challenges and recommendations for valid and reliable quantification from lab to (less predictable) real-world driving settings are considered. Finally, we discuss measures that may be better candidates for a near real-time assessment of motorists' cognitive states that can be utilized in applied settings outside the lab. This review synthesizes the literature on in-vehicle psychophysiological measures to advance the development of effective human-machine driving interfaces and driver support systems.

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A Review of Psychophysiological Measures to Assess Cognitive States in Real-World Driving

Despite the importance of attention in user performance, current methods for attention classification do not allow to discriminate between different attention types. We propose a novel method that combines thermal imaging and eye tracking to unobtrusively classify four types of attention: sustained, alternating, selective, and divided. We collected a data set in which we stimulate these four attention types in a user study (N = 22) using combinations of audio and visual stimuli while measuring users' facial temperature and eye movement. Using a Logistic Regression on features extracted from both sensing technologies, we can classify the four attention types with high AUC scores up to 75.7% for the user independent-condition independent, 87% for the user-independent-condition dependent, and 77.4% for the user-dependent prediction. Our findings not only demonstrate the potential of thermal imaging and eye tracking for unobtrusive classification of different attention types but also pave the way for novel applications for attentive user interfaces and attention-aware computing.

Classifying Attention Types with Thermal Imaging and Eye Tracking

This study scrutinizes the existing literature regarding the use of augmented reality and gamification in education to establish its theoretical basis. A systematic literature review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement was conducted. To provide complete and valid information, all types of related studies for all educational stages and subjects throughout the years were investigated. In total, 670 articles from 5 databases (Scopus, Web of Science, Google Scholar, IEEE, and ERIC) were examined. Based on the results, using augmented reality and gamification in education can yield several benefits for students, assist educators, improve the educational process, and facilitate the transition toward technology-enhanced learning when used in a student-centered manner, following proper educational approaches and strategies and taking students’ knowledge, interests, unique characteristics, and personality traits into consideration. Students demonstrated positive behavioral, attitudinal, and psychological changes and increased engagement, motivation, active participation, knowledge acquisition, focus, curiosity, interest, enjoyment, academic performance, and learning outcomes. Teachers also assessed them positively. Virtual rewards were crucial for improving learning motivation. The need to develop appropriate validation tools, design techniques, and theories was apparent. Finally, their potential to create collaborative and personalized learning experiences and to promote and enhance students’ cognitive and social–emotional development was evident.

/pdf/augmented-reality-and-gamification-in-education-a-systematic-3ibvz126.pdf

Augmented Reality and Gamification in Education: A Systematic Literature Review of Research, Applications, and Empirical Studies

Augmented reality (AR) has the potential to support individuals with special needs and to enable their development of daily living skills. This meta-analysis study examined the effect of AR on func...

https://journals.sagepub.com/doi/pdf/10.1177/0162643420910413

Augmented Reality and Functional Skills Acquisition Among Individuals With Special Needs: A Meta-Analysis of Group Design Studies

Computer science is about learning how to think. It is applicable to everything. Most industries in the 21\(^{st}\) century are directed towards digitized processes using up-to-date technologies. This increases the need for students to know how these technologies work, especially with the availability of smart and handy devices. As a preliminary step to learning programming, students should learn basics of logical and computational thinking. Computational thinking compromises the skills, concepts, and behaviors used to solve problems. Some visual platforms, such as Scratch and Alice [6, 17], were introduced to teach children programming. The platform introduced in this paper aims at teaching young children (in the age range of 8–9 years old) the preliminary concepts of programming including sequential blocks, conditional blocks, and iterative blocks. This is achieved through an interactive, gesture-based game, where the Kinect Sensor device is used to control the gameplay instead of playing it using a normal PC. The game was tested using a between-group experimental model with two subgroups; an experimental group and a control group. The experimental group used the game whereas the control group was taught using a traditional educational method. The results showed a significant difference between the two groups with a P-value of < 0.05 for both the learning gain and the engagement level.

MiniColon; Teaching Kids Computational Thinking Using an Interactive Serious Game

Systems that adapt to the states of users show great potential for creating novel user experiences. However, most approaches in affective computing only rely on the current state of the user. Furthermore, personality computing has recently evolved, it shows a few examples of how personality traits can be inferred from different types of behavioral evidence. We envision introducing novel user experiences by learning more about the user through extracting the building blocks of their character including; morals, mentalities and believes. In this workshop we aim to introduce Character Computing, a novel approach to examine and leverage characters to build ubiquitous and non-obtrusive character-aware adaptive systems. This workshop aims at engaging participants in reflection and practical work exploring the evolving research strand in hand.

Character computing: challenges and opportunities

Now that most daily endeavors have migrated to computers and the Internet, having systems that adapt to users is a rising trend. By detecting and adapting to the user's traits and character instead of only the current states, there is great potential for novel user experiences. Character Computing which was introduced in [3] is now extended to the field of experimental psychology and psychological theorizing. Our approach integrates psychological and computational aspects of advanced sensing and processing technologies to detect the building blocks of a user's character traits and states which will allow computer systems to adapt to the user's behavior and his/her feelings more reliably and mimic them according to situational demands. Accordingly, in this workshop the different aspects of Character Computing are to be discussed from an interdisciplinary perspective taking computational and psychological accounts into consideration in order to strengthen already investigated and potential applications as well as the theoretical foundation and challenges of Character Computing.

Character Computing: Computer Science meets Psychology

Most of the typical digital systems are not fully aware of the users' affect states. Adapting to the users' state showed great potential for enhancing user experiences. However, most approaches for sensing affective states, specifically arousal and valence, involve expensive and obtrusive technologies, such as physiological sensors attached to users' bodies. This paper present an indicator of the users' affect based on eye tracking. We use a commercial eye tracker to monitor the user's pupil size to estimate their arousal and valence in response to videos of different content. To assess the effect of different content (namely pleasant and unpleasant) influencing the arousal and valence on the pupil diameter, we conducted a user study with 25 participants. The study showed that different content of videos affect the pupil diameter, thereby giving an indicator about the user's state. We provide empirical evidence showing how to unobtrusively detect changes in users' state. Our initial investigation gives rise to eye-based user's tracking, which introduces the potential of new applications in the field of affect-aware computing.

DiVA: exploring the usage of pupil diameter to elicit valence and arousal

Brain signals are a reliable information source because human beings have limited voluntary control over. We examine EEG readings as a reporting tool concerning human emotions. We examine whether readings from an eye tracker, can enhance the results. We conducted an experiment on 25 users to measure their EEG signals in response to emotional stimuli. All sensors used were off-the-shelf, to test our method using cheap sensors. We used pleasant and unpleasant videos content to elicit emotional responses. Along with Self-Assessment Mannequin (SAM), Alpha symmetry index readings, and pupil diameter, were recorded. Our results show a significant difference in the video clips eliciting different emotions. This implies that EEG can be a valid way to detect emotional state, especially when combined with eye-tracker. We conclude from our findings that EEG can be used as a platform, upon which reliable affect-aware systems and applications can be built.

Exploring the Usage of EEG and Pupil Diameter to Detect Elicited Valence

Teenagers with Down syndrome face difficulties in acquiring new skills specially in the tasks that need high cognitive abilities. In the recent years, serious games showed to be a promising assistive mean in the field of education. Augmented Reality (AR) technology is a growing research area that could be achieved by different ways for many purposes. The main focus of this study is investigating the effect of using a projection based game for Down syndrome teenagers in an educational context. This was done through implementing a game that aims at enhancing their numeracy skills for financially independent living. The developed interactive surface game was tested with a number of Down syndrome teenagers, and its effect on their learning outcomes was compared to the effect of the same game played on the normal technological mean they receive, namely the personal computers.

Jailan Salah

Papers

Character computing: challenges and opportunities

Character Computing: Computer Science meets Psychology

DiVA: exploring the usage of pupil diameter to elicit valence and arousal

Exploring the Usage of EEG and Pupil Diameter to Detect Elicited Valence

Galaxy Shop: Projection-Based Numeracy Game for Teenagers with Down Syndrome