Tutoring systems that are sensitive to affect show considerable promise for enhancing student learning experiences. Creating successful affective responses requires considerable effort both to detect student affect and to design appropriate responses to affect. Recent work has suggested that affect detection is more effective when both physical sensors and interaction logs are used, and that context-sensitive design of affective feedback is necessary to enhance engagement and improve learning. In this paper, we provide a comprehensive report on a multi-part study that integrates detection, validation, and intervention into a unified approach. This paper examines the creation of both sensor-based and interaction-based detectors of student affect, producing successful detectors of student affect. In addition, it reports results from an investigation of motivational feedback messages designed to address student frustration, and investigates whether linking these interventions to detectors improves outcomes. Our results are mixed, finding that self-efficacy enhancing interventions based on interaction-based affect detectors enhance outcomes in one of two experiments investigating affective interventions. This work is conducted in the context of the GIFT framework for intelligent tutoring, and the TC3Sim game-based simulation that provides training for first responder skills.

Significant research has confirmed the necessity to better comprehend psychological constructs that are essential in predicting and influencing human performance, in particular, assessing expressive flexibility and resilience. However, limited research has investigated the relationships that exist between these two constructs that are critical protective factors in facilitating the mental health and the well-being of individuals. Through a number of structural equation modeling (SEM) techniques, the current endeavor evaluates this gap to assess the relationship between these two constructs. Utilizing a military student sample from a private U.S. military university (N = 107), participants completed the Resilience Scale for Adults (RSA) and the Flexible Regulation of Emotional Expression (FREE) scale. Correlations matrixes reported positive relationships between expressive flexibility and resilience. Confirmatory factor analyses (CFAs) revealed a bi-factor models of expressive flexibility and resilience. Additional CFAs revealed a two-factor model structure between expressive flexibility and resilience. Implications for future work are offered.

Introduction: Character strengths and virtues are greatly revered in military leadership. However, there is no empirical work assessing the relationship of resilience and expressive flexibility, two essential psychological constructs crucial in nurturing mentally healthy individuals, also for successful officer development and military leadership. Methods: Employing a cross-sectional design, this study recruited 107 participants (ages 18 to 22) from a private U.S. Military university. McGrath, Rashid, Park, and Peterson’s and Peterson and Seligman’s taxonomies of character strengths and virtues were measured. Self-reported resilience and expressive flexibility were additionally assessed. Results: Results revealed McGrath et al.’s virtue of self-control and Peterson and Seligman’s virtues of temperance, wisdom and knowledge, and humanity as the top ranked virtues for an effective military leader. In terms of character strengths, judgment ranked the highest, with perspective and fairness, second and third. Additional results showed a model suggesting that resilience and expressive flexibility explained 45.9% of variance suggesting that resilience and expressive flexibility significantly (p < .001) predicted leadership. Regression models that included honesty, social intelligence, and hope also offered significant predictive outcomes on leadership (p < .001). Furthermore, results revealed that expressive flexibility predicted the character strengths of creativity (p = .001), bravery (p = .045), love (p = .044), hope (p = .016), teamwork (p = .013), appreciation of beauty (p = .016), curiosity (p = .044), prudence (p = .034), love of learning (p = .020), zest (p = .017), humor (p = .018), and perspective (p = .003). Conclusions: Understanding the relationships amongst these constructs will help in better cultivating protective mechanisms that safeguard from adversity, in encouraging wellness and health, and in supporting healthy human performance and development.

The effect of the novel coronavirus (SARS-CoV-2) pandemic has produced significant health concerns negatively impacting individuals. As the ongoing and constantly changing nature of SARS-CoV-2 continues, the unique characteristics of this pandemic trend toward anxiety and loneliness as significant behavioral health outcomes. Furthermore, the SARS-CoV-2 pandemic has significantly impacted the utilization of social media platforms such as Twitter. Utilizing over 1.6 million tweets from approximately 988,760 Twitter users geolocated in Washington state from the University of Pennsylvania’s publicly available Twitter database (from March 2020 to March 2021), this study evaluated the impact of SARS-CoV-2 by using expressions of loneliness and anxiety to predict mental and physical symptoms. Bivariate correlations revealed expressions of loneliness were correlated to trouble breathing while expressions of anxiety were correlated to skin lesions, body aches, flu-like, seasonal cold, trouble breathing, nausea or diarrhea, fever, chills, and cough. Multiple multivariate linear regressions were completed, and a significant regression equation was found in predicting trouble breathing symptoms on expressions of loneliness and anxiety, however, the proportion of variance was 8% of the observed variation in the model. Further implications revealed the importance of understanding mental and physical well-being during a public health crisis as well as the use of social media platforms as primary and supplementary stimuli.

No abstract