Academic engagement describes students’ involvement in academic learning and achievement. This paper reports the psychometric properties of the University Student Engagement Inventory (USEI) with a sample of 3992 university students from nine different countries and regions from Europe, North and South America, Africa, and Asia. The USEI operationalizes a trifactorial conceptualization of academic engagement (behavioral, emotional, and cognitive). Construct validity was assessed by means of confirmatory factor analysis and reliability was assessed using Cronbach’s alpha and McDonald’s omega coefficients. Weak measurement invariance was observed for country/region, while strong measurement invariance was observed for gender and area of graduation. The USEI scores showed predictive validity for dropout intention, self-rated academic performance, and course approval rate while divergent validity with student burnout scores was also evident. Overall, the results indicate that the USEI can produce reliable and valid data on academic engagement of university students across the world.

The COVID-19 pandemic caused unprecedented changes to educational institutions, forcing their closure and a subsequent shift to online education to cater to student learning requirements. However, successful online learning depends on several factors and may also vary between countries. As such, this cross-sectional study sought to investigate how engagement of university students, a major driver of online learning, was influenced by course content, online interaction, student acceptance, and satisfaction with online learning, as well as self-efficacy across nine countries (China, India, Iran, Italy, Malaysia, Portugal, Serbia, Turkey, and the United Arab Emirates) during the COVID-19 pandemic. Using a questionnaire-based approach, data collected from 6,489 university students showed that student engagement was strongly linked to perception of the quality of the course content and online interactions (p < .001). The current study also indicated that online interactions are a major determinant of academic efficacy but only if mediated by engagement within the online learning context. A negative correlation between student engagement and satisfaction with online learning was found, demonstrating the importance of students being engaged behaviorally, emotionally, and cognitively to feel satisfied with learning. Academic efficacy and student satisfaction were explained by course content, online interaction, and online learning acceptance, being mediated by student engagement. Student satisfaction and, to a lesser degree academic efficacy, were also associated with online learning acceptance. Overall, the structural equation model was a good fit for the data collected from all nine countries (CFI = .947, TLI = .943; RMSEA = .068; SRMR = .048), despite differences in the percentage variations explained by each factor (no invariance), likely due to differences in levels of technology use, learning management systems, and the preparedness of teachers to migrate to full online instruction. Despite limitations, the results of this study highlight the most important factors affecting online learning, providing insight into potential approaches for improving student experiences in online learning environments.

Despite the growing interest on the notion of academic engagement (AE) and its relevance for students’ success, a few valid and reliable instruments on AE have been developed. Moreover, most of the available measures consider AE as a student’s trait rather than a relational and situated dynamic process. This study presents the development and validation of a new instrument, the SInAPSi Academic Engagement Scale (SAES), which was developed within a project coordinated by the SInAPSi center of the Authors’ University and it aims to measure AE. The main sample was constituted by 680 students and a convenience sample of 312 biology and biotechnologies students was also involved to perform the confirmatory factor analysis of the initial factor structure of the SAES. Construct validity was assessed using the University Student Engagement Inventory (USEI), while criterion-related validity was established with the Academic Motivation Scale (AMS), the students’ confidence in one’s own preparation for academic studies and their academic performance. Results show that the SAES presents a robust factor structure, a good convergent and discriminant validity, and satisfactory psychometric properties. Furthermore, the SAES shows a positive correlation with the USEI and the AMS, the students’ confidence in their preparation for academic studies and their academic performance. The results indicate that the SAES can produce valid and reliable data on AE and it may have strong implications for assessing AE and implementing intervention programs for university students.

This study examined the relationships between first-year university students’ academic motivation, retrospective evaluation of school experiences, subjective well-being, engagement and intention to drop out. Self-determination theory, the SInAPSi model of academic engagement, the hedonic approach, and the retrospective judgment process were used to frame the study. A final sample of 565 first-year Italian students enrolled in Science-Technology-Engineering-Mathematics (STEM) courses (Biology, Biotechnologies, Chemistry, Computer Science, Physics, Mathematics) was included. Three mediation models based on structural equations were tested to analyse the relationships between the proposed variables: motivation as an antecedent of dropout intention with only commitment as a mediator (model 1); model 1 + subjective well-being as a second mediator (model 2); model 2 + retrospective judgement as an antecedent (model 3). The results showed that in all models the more autonomous motivational styles predicted students’ engagement, which in turn directly and indirectly influenced their intention to drop out. In model 2, subjective well-being acted as a mediator of the relationships between motivation, engagement and dropout intentions. In model 3, we found that subjective well-being also fully mediated the relationships between retrospective judgement and engagement. Overall, our findings provide new insights into the mechanisms underlying student engagement and dropout at university and may inform university policy.