Are there nonverbal cues to commitment? An exploratory study using the zero-acquaintance video presentation paradigm

Altruism is difficult to explain evolutionarily if subtle cheaters exist in a population (Trivers, 1971). A pathway to the evolutionary maintenance of cooperation is nonverbal altruist-detection. One adaptive advantage of nonverbal altruist-detection is the formation of trustworthy division of labour partnerships (Frank, 1988). Three studies were designed to test a fundamental assumption behind altruistic partner preference models. In the first experiment perceivers (blind with respect to target altruism level) made assessments of video-clips depicting self-reported altruists and self-reported non-altruists. Video-clips were designed with attempts to control for attractiveness, expressiveness, role-playing ability, and verbal content. Overall perceivers rated altruists as more “helpful” than non-altruists. In a second experiment manipulating the payoffs for cooperation, perceivers (blind with respect to payoff condition and altruism level) assessed altruists who were helping others as more “concerned” and “attentive” than non-altruists. However perceivers assessed the same altruists as less “concerned” and “attentive” than non-altruists when the payoffs were for self. This finding suggests that perceivers are sensitive to nonverbal indicators of selfishness. Indeed the self-reported non-altruists were more likely than self-reported altruists to retain resources for themselves in an objective measure of cooperative tendencies (i.e. a dictator game). In a third study altruists and non-altruists’ facial expressions were analyzed. The smile emerged as a consistent cue to altruism. In addition, altruists exhibited more expressions that are under involuntary control (e.g., orbicularis oculi) compared to non-altruists. Findings Are there nonverbal cues to commitment? suggest that likelihood to cooperate is signaled nonverbally and the putative cues may be under involuntary control as predicted by Frank (1988)

ENHANCING THE MOTIVATION AND LEARNING PERFORMANCE IN AN ONLINE CLASSROOM WITH THE USE OF NEUROMARKETING

In recent years, the newly emerging discipline of neuromarketing, which employs brain (emotions and behaviour) research in an organisational context, has grown in prominence in academic and practice literature. With the increasing growth of online teaching, COVID-19 left no option for higher education institutions to go online. As a result, students who attend an online course are more prone to lose focus and attention, resulting in poor academic performance. Therefore, the primary purpose of this study is to observe the learner's behaviour while making use of an online learning platform. This study presents neuromarketing to enhance students' learning performance and motivation in an online classroom. Using a web camera, we used facial coding and eye-tracking techniques to study students' attention, motivation, and interest in an online classroom. In collaboration with Oxford Business College's marketing team, the Institute for Neuromarketing distributed video links via email, a student representative from Oxford Business College, the WhatsApp group, and a newsletter developed explicitly for that purpose to 297 students over the course of five days. To ensure the research was both realistic and feasible, the instructors in the videos were different, and students were randomly allocated to one video link lasting 90 seconds (n=142) and a second one lasting 10 minutes (n=155). An online platform for self-service called Tobii Sticky was used to measure facial coding and eye-tracking. During the 90-second online lecture, participants' gaze behaviour was tracked overtime to gather data on their attention distribution, and emotions were evaluated using facial coding. In contrast, the 10-minute film looked at emotional involvement. The findings show that students lose their listening focus when no supporting visual material or virtual board is used, even during a brief presentation. Furthermore, when they are exposed to a single shareable piece of content for longer than 5.24 minutes, their motivation and mood decline; however, when new shareable material or a class activity is introduced, their motivation and mood rise. JEL: I20; I21 Article visualizations

The Interaction Between Global Task Motivation and the Motivational Function of Events on Self-Regulation: Is Sauce for The Goose, Sauce for The Gander?

An experiment was conducted to assess (1) the interaction between global task motivation and motivational aspects of the environment (level of controls and autonomy-support present in the environment) and (2) gender differences with regard to this interaction. Forty male and forty female participants with high and low levels of self-determination towards relaxation attempted to learn relaxation using biofeedback in an either controlling or autonomy-supportive environment. The results confirm the notion that global task motivation and intervention style interact. Further, this interaction is qualified by a gender effect. The resulting triple interaction suggests that a different pattern of relations between the motivational aspects of the environment and level of self-determination emerges for men and women. Une expérimentation a été réalisée afin d'évaluer (1) l'interaction entre la motivation globale vis-à-vis une tâche et différents styles de mobilisation (degré d'un style d'intervention contrôlant et de soutien à l'autonomie) et (2) le rôle du genre dans cette interaction. Quarante hommes et quarante femmes ayant un niveau soit élevé ou faible d'autodétermination envers une tâche de relaxation ont participé à une tâche d'apprentissage à la relaxation à l'aide de biofeedback avec un intervenant qui présentait un style soit contrôlant soit de soutien à l'autonomie. Les résultats confirment la présence d'effets d'interactions entre le niveau d'autodétermination (motivation globale) et le style de l'intervention. Le genre du participant qualifie également cette interaction. L'interaction triple suggère l'existence de différentes formes de relations entre les aspects mobilisateurs de l'environnement et le niveau d'autodétermination pour les hommes et les femmes.Controlling and autonomy-supportive intervention style, global-state task motivation, self-determination theory, gender, person-environment interactions, physiological responses, self-regulation learning, Style d'intervention contrôlant-soutien à l'autonomie, motivation globale-d'état vis-à-vis une tâche, théorie de l'autodétermination, interaction environnement-personne, genre, réactions physiologiques, apprentissage auto-régulation

Modelling human teaching tactics and strategies for tutoring systems

One of the promises of ITSs and ILEs is that they will teach and assist learning in an intelligent manner. Historically this has tended to mean concentrating on the interface, on the representation of the domain and on the representation of the student’s knowledge. So systems have attempted to provide students with reifications both of what is to be learned and of the learning process, as well as optimally sequencing and adjusting activities, problems and feedback to best help them learn that domain. We now have embodied (and disembodied) teaching agents and computer-based peers, and the field demonstrates a much greater interest in metacognition and in collaborative activities and tools to support that collaboration. Nevertheless the issue of the teaching competence of ITSs and ILEs is still important, as well as the more specific question as to whether systems can and should mimic human teachers. Indeed increasing interest in embodied agents has thrown the spotlight back on how such agents should behave with respect to learners. In the mid 1980s Ohlsson and others offered critiques of ITSs and ILEs in terms of the limited range and adaptability of their teaching actions as compared to the wealth of tactics and strategies employed by human expert teachers. So are we in any better position in modelling teaching than we were in the 80s? Are these criticisms still as valid today as they were then? This paper reviews progress in understanding certain aspects of human expert teaching and in developing tutoring systems that implement those human teaching strategies and tactics. It concentrates particularly on how systems have dealt with student answers and how they have dealt with motivational issues, referring particularly to work carried out at Sussex: for example, on responding effectively to the student’s motivational state, on contingent and Vygotskian inspired teaching strategies and on the plausibility problem. This latter is concerned with whether tactics that are effectively applied by human teachers can be as effective when embodied in machine teachers

Analysis of learners' emotions in e-learning environments based on cognitive sciences

The present study aimed to examine students’ emotions in e-learning classes through facial expressions and investigate the influence of different instructional methods on students’ emotional responses. In this study, we examined the facial expressions of 17 undergraduate students using three different methods of presenting educational content (PowerPoint, video, and Kahoot) in online classes and analyzed the data with face reader software. The findings demonstrated that students experienced various positive and negative emotions with different methods of content delivery. Furthermore, comparing the three methods revealed that the Kahoot method elicited the highest average of positive emotions among students compared to the other two methods. This difference can be attributed to the visual attractiveness and interactive nature of the Kahoot environment. Additionally, this study highlights that simply incorporating multimedia materials, such as PowerPoint presentations and videos, is not sufficient to enhance effectiveness and cultivate positive emotions in e-learning. While multimedia materials serve as supportive tools and enhance visualization, interaction at various levels (content, teacher, peers, etc.) is necessary. Nevertheless, the significance of this research lies in the innovative application of a tool for analyzing emotions in online learning classrooms, thereby enhancing the measurement of genuine and objective emotional responses in e-learning environments

Enriching remote labs with computer vision and drones

165 p.With the technological advance, new learning technologies are being developed in order to contribute to better learning experience. In particular, remote labs constitute an interesting and a practical way that can motivate nowadays students to learn. The studen can at anytime, and from anywhere, access the remote lab and do his lab-work. Despite many advantages, remote tecnologies in education create a distance between the student and the teacher. Without the presence of a teacher, students can have difficulties, if no appropriate interventions can be taken to help them. In this thesis, we aim to enrich an existing remote electronic lab made for engineering students called "LaboREM" (for remote Laboratory) in two ways: first we enable the student to send high level commands to a mini-drone available in the remote lab facility. The objective is to examine the front panels of electronic measurement instruments, by the camera embedded on the drone. Furthermore, we allow remote student-teacher communication using the drone, in case there is a teacher present in the remote lab facility. Finally, the drone has to go back home when the mission is over to land on a platform for automatic recharge of the batteries. Second, we propose an automatic system that estimates the affective state of the student (frustrated/confused/flow) in order to take appropriate interventions to ensure good learning outcomes. For example, if the studen is having major difficulties we can try to give him hints or to reduce the difficulty level of the lab experiment. We propose to do this by using visual cues (head pose estimation and facil expression analysis). Many evidences on the state of the student can be acquired, however these evidences are incomplete, sometims inaccurate, and do not cover all the aspects of the state of the student alone. This is why we propose to fuse evidences using the theory of Dempster-Shafer that allows the fusion of incomplete evidence

Incorporating Learner Emotions through Sentiment Analysis in Adaptive E-learning Systems: A Pilot Study

This research delves into the exciting avenue of incorporating learner emotions into adaptive E-learning systems through sentiment analysis techniques. Utilizing a pilot study with 40 undergraduate computer science students, we investigated the ability of an adaptive system to detect boredom and frustration in learner forum posts and subsequently personalize content or offer support based on these emotional states. This approach proved demonstrably successful, as learners in the experimental group who received emotion-based adaptation exhibited both increased engagement (reflected in higher time spent on tasks) and improved learning outcomes (evidenced by higher post-test scores). Furthermore, qualitative feedback revealed positive responses to the personalized interventions, indicating that learners appreciated the tailored support provided by the system. While acknowledging limitations such as the small sample size and single subject area, this study firmly establishes the promising potential of emotion-aware adaptive systems. By addressing the emotional dynamics of the learning process, such systems can pave the way for truly personalized and responsive E-learning environments that cater to individual learner needs and foster deeper engagement, positive learning experiences, and ultimately, success for all students

Affective e-learning approaches, technology and implementation model: a systematic review

A systematic literature study including articles from 2016 to 2022 was done to evaluate the various approaches, technologies, and implementation models involved in measuring student engagement during learning. The review’s objective was to compile and analyze all studies that investigated how instructors can gauge students’ mental states while teaching and assess the most effective teaching methods. Additionally, it aims to extract and assess expanded methodologies from chosen research publications to offer suggestions and answers to researchers and practitioners. Planning, carrying out the analysis, and publishing the results have all received significant attention in the research approach. The study’s findings indicate that more needs to be done to evaluate student participation objectively and follow their development for improved academic performance. Physiological approaches should be given more support among the alternatives. While deep learning implementation models and contactless technology should interest more researchers. And, the recommender system should be integrated into e-learning system. Other approaches, technologies, and methodology articles, on the other hand, lacked authenticity in conveying student feeling