Millions of students follow online classes which are delivered in video format. Several studies examine the impact of these video formats on engagement and learning using explicit measures and outline the need to also investigate the implicit cognitive and emotional states of online learners. Our study compared two video formats in terms of engagement (over time) and learning in a between-subject experiment. Engagement was operationalized using explicit and implicit neurophysiological measures. Twenty-six (26) subjects participated in the study and were randomly assigned to one of two conditions based on the video shown: infographic video or lecture capture. The infographic video showed animated graphics, images, and text. The lecture capture showed a professor, providing a lecture, filmed in a classroom setting. Results suggest that lecture capture triggers greater emotional engagement over a shorter period, whereas the infographic video maintains higher emotional and cognitive engagement over longer periods of time. Regarding student learning, the infographic video contributes to significantly improved performance in matters of difficult questions. Additionally, our results suggest a significant relationship between engagement and student performance. In general, the higher the engagement, the better the student performance, although, in the case of cognitive engagement, the link is quadratic (inverted U shaped).

Computer-based learning has gained popularity in recent years, providing learners greater flexibility and freedom. However, these learning environments do not consider the learner’s mental state in real-time, resulting in less optimized learning experiences. This research aimed to explore the effect on the learning experience of a novel EEG-based Brain-Computer Interface (BCI) that adjusts the speed of information presentation in real-time during a learning task according to the learner’s cognitive load. We also explored how motivation moderated these effects. In accordance with three experimental groups (non-adaptive, adaptive, and adaptive with motivation), participants performed a calibration task (n-back), followed by a memory-based learning task concerning astrological constellations. Learning gains were assessed based on performance on the learning task. Self-perceived mental workload, cognitive absorption and satisfaction were assessed using a post-test questionnaire. Between-group analyses using Mann–Whitney tests suggested that combining BCI and motivational factors led to more significant learning gains and an improved learning experience. No significant difference existed between the BCI without motivational factor and regular non-adaptive interface for overall learning gains, self-perceived mental workload, and cognitive absorption. However, participants who undertook the experiment with an imposed learning pace reported higher overall satisfaction with their learning experience and a higher level of temporal stress. Our findings suggest BCI’s potential applicability and feasibility in improving memorization-based learning experiences. Further work should seek to optimize the BCI adaptive index and explore generalizability to other learning contexts.

As the world adapts to COVID-19, the transport behaviour of commuters has been greatly modified. Governments and transit authorities will need strong, well-received mitigation measures and education campaigns to maintain the historically upward trend of sustainable mass transit usage following this pandemic. This study, from a survey of 1968 Canadians in early May 2020, reveals that, following the end of stay-at-home orders, commuters intend to use their cars more and mass transit less. Driving these behavioural changes are commuters’ perceptions that mass transit use will negatively impact their health safety, peace of mind, and travel experience. The results also show that certain mitigation measures, such as more frequent cleaning and mandatory hand washing, are likely to reduce this decline, whereas e-monitoring and the use of health certificates will be detrimental to mass transit ridership through user perception. These results can help lessen the environmental impact of the public returning to work by encouraging their continued use of more environmentally friendly modes of transportation.

Background: Psychological distress increases across adolescence and has been associated with several important health outcomes with consequences that can extend into adulthood. One type of technological innovation that may serve as a unique intervention for youth experiencing psychological distress is the conversational agent, otherwise known as a chatbot. Further research is needed on the factors that may make mental health chatbots destined for adolescents more appealing and increase the likelihood that adolescents will use them. Objective: The aim of this study was to assess adolescents’ emotional reactions and likelihood of responding to questions that could be posed by a mental health chatbot. Understanding adolescent preferences and factors that could increase adolescents’ likelihood of responding to chatbot questions could assist in future mental health chatbot design destined for youth. Methods: We recruited 19 adolescents aged 14 to 17 years to participate in a study with a 2×2×3 within-subjects factorial design. Each participant was sequentially presented with 96 chatbot questions for a duration of 8 seconds per question. Following each presentation, participants were asked to indicate how likely they were to respond to the question, as well as their perceived affective reaction to the question. Demographic data were collected, and an informal debriefing was conducted with each participant. Results: Participants were an average of 15.3 years old (SD 1.00) and mostly female (11/19, 58%). Logistic regressions showed that the presence of GIFs predicted perceived emotional valence (β=–.40, P<.001), such that questions without GIFs were associated with a negative perceived emotional valence. Question type predicted emotional valence, such that yes/no questions (β=–.23, P=.03) and open-ended questions (β=–.26, P=.01) were associated with a negative perceived emotional valence compared to multiple response choice questions. Question type also predicted the likelihood of response, such that yes/no questions were associated with a lower likelihood of response compared to multiple response choice questions (β=–.24, P=.03) and a higher likelihood of response compared to open-ended questions (β=.54, P<.001). Conclusions: The findings of this study add to the rapidly growing field of teen-computer interaction and contribute to our understanding of adolescent user experience in their interactions with a mental health chatbot. The insights gained from this study may be of assistance to developers and designers of mental health chatbots.