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The research paper examines the complex relationship between gamification, student engagement and academic performance in educational environments. The study employed a structural equation model that highlights important connections among key constructs within the educational setting.

This research aims to explore the connection between gamification, student engagement and academic performance in educational settings. The study employs various statistical techniques such as factor analysis, Kaiser–Meyer–Olkin (KMO), Bartlett’s test, component transformation matrix, correlation and regression analysis, descriptive statistics, ANOVA, coefficients and coefficient correlations, residual statistics and confirmatory factor analysis (CFA) to analyze the data.

It was found that active participation by the instructor and good time management skills have a positive impact on student engagement levels (β = 0.380, p < 0.001; β = 0.433 and p < 0.001). However, peer interaction does not significantly predict student engagement (β = −0.068 and p = 0.352). Additionally, there is a positive correlation between student engagement and performance (β = 0.280 and p < 0.001).

The study highlights the importance of innovative design to fully utilize gamification. Future research should consider design, user characteristics and educational context. The findings can guide informed decisions about gamification in education, fostering motivation and learning objectives.

The study presents a reliable tool for assessing student engagement and performance in educational settings, demonstrating high Cronbach’s alpha and robust reliability. It identifies student engagement and time management as significant predictors of Global Learning Outcome. The findings can inform decisions on implementing gamification in educational settings, promoting intrinsic motivation and aligning with learning objectives.

The research highlights the transformative impact of gamification on educational practices, highlighting its potential to enhance student experiences, motivate, promote diversity and improve long-term academic performance, highlighting the trend of integrating technology into education.

In today’s ever-changing education landscape, it is essential to incorporate innovative techniques to keep students engaged and enthusiastic about learning. Gamification is one such approach that has become increasingly popular. It is a concept that takes inspiration from the immersive world of games to enhance the overall learning experience.

The topic of student engagement (SE) has received considerable attention in the literature for its robust correlation with many positive educational outcomes in higher education (HE). However, among these desirable outcomes, student competencies have rarely been examined despite their importance in employability. While universities are expected to improve graduates' competencies and prepare them to adapt in an uncertain and complex workplace, the results are still limited. Therefore, this study attempts to examine the impacts of SE on student competencies in HE in Vietnam, focusing on the out-of-class environment. It also aims at developing a measurement instrument for out-of-class SE.

Based on student self-reports, this study collected two different datasets of 492 and 490 undergraduate business students in Hanoi to implement separate exploratory and confirmatory factor analyses. The measurement instrument of out-of-class engagement was adapted from the literature review and developed based on qualitative research, which combined the four subconstructs of participatory, emotional, cognitive and agentic engagement.

Findings confirms four subconstructs of SE in the out-of-class context where agentic engagement is a valid and distinct aspect. Findings further show that, among these four subconstructs, cognitive and agentic engagement have significant impacts on all four important student competencies for business students, while participatory and emotional engagement do not.

This study confirmed out-of-class SE has significant positive impacts on student competencies in HE, especially with out-of-class cognitive and agentic engagement. The findings show evidence of different impacts between participatory and agentic engagement, in which while participatory has no impacts on student competencies, agentic engagement significantly contributes to competencies of managing self, communicating and managing people and tasks. This implies different outcomes can be expected from different levels of engagement.

From a managerial point of view, the findings of this study strongly suggest that higher education institutions (HEIs) should view the out-of-class environment as an important extended learning context for students' complete development. Besides, as student out-of-class participatory engagement is not sufficient to the formation of student competencies, HEIs should strengthen out-of-class cognitive and agentic engagement among students. From the leadership perspective, building a good campus environment with various opportunities to involve students in diversified extra-curricular activities is beneficial to university students.

This paper contributes to the body of knowledge in SE by establishing a theoretical linkage between out-of-class engagement and student competencies and provides sufficient statistical significance. In addition, it validated out-of-class agentic engagement as a separate and distinct subcomponent of out-of-class SE and confirmed the positive impact of out-of-class engagement on student competencies for business students.

The purpose of this study is to examine effects of classroom-level and student-level factors on student engagement in the context of a higher education system vertically differentiated into research, applied and comprehensive university types.

The study used a cross-sectional multilevel design to explain student engagement based on class and student variables. Specifically, the study collects data from 656 students and 61 randomly selected teachers at both levels and uses multilevel modeling to explain relationship patterns.

The results show that institutions vary significantly in student engagement scores. In addition, while a significant variation is found at the student and classroom level, the effects of academic achievement, instructional quality, teaching experience and teacher qualifications on student engagement vary across classrooms in institutions. However, the interaction effect of classroom and student-level variables on student engagement remains non-significant.

The main contribution of this lies in the explanation of student engagement using classroom and student level factors in a vertically differentiated higher education system using multilevel modeling. Student engagement varied in classrooms research universities applied and comprehensive universities.

The integration of digital technologies into education has brought about a profound transformation, fundamentally reshaping the learning landscape. The purpose of this study is to underscore the importance of investigating the factors influencing students’ engagement (SE) in this evolving digital era, particularly within formal digital learning environments. To address this need, the study is grounded in self-determination theory (SDT) and presents a comprehensive model comprising interconnected elements: digital competence (DC), smartphone use (SPU), perceived autonomy (PA), digital formal learning (DFL) and SE.

The research conducted an investigation within Saudi Arabian universities, collecting a robust data set of 392 cases. This data set underwent rigorous analysis to validate the proposed model. To untangle the intricate relationships within the framework, the study used partial least squares structural equation modelling. Given the distinct dimensions of the two constructs under study, the researcher used a disjoint two-stage approach to establish reflective-formative higher-order constructs (HOC).

The findings revealed that digital literacy and digital skills (DS) constitute the foundational constituents of DC. Simultaneously, the study identified facilitation, distraction and connectedness as integral components of SPU. Importantly, the study established that DC, SPU, PA and DFL significantly influence SE. Furthermore, the research illuminated the mediating roles played by SPU, PA and DFL in the complex relationship between DC and SE.

This study advances the literature by delineating the dynamic interplay between DC, SPU and SE in digital learning. It extends SDT within educational contexts, emphasizing the role of internal motivations and DS. Methodologically, it innovates through reflective-formative HOCs, deepening the analysis of complex educational constructs. Managerially, it guides institutions in enhancing DC and integrating smartphones effectively into learning, advocating for tailored strategies to foster engaging and autonomous digital learning environments, thereby enriching both theoretical understanding and practical application in education.

We aimed to identify factors that influence student engagement in distance learning.

The research involved a group of 671 students from economic and technical higher education institutions in Poland. We collected the data with the CAWI technique and an original survey. Next, we processed the data using principal component analysis and then used the extracted components as predictors in the induced smoothing LASSO regression model.

The components of the students’ attitude toward remote classes learning conditions are: satisfaction with teachers’ approach, attitude to distance learning, the system of students’ values and motivation, IT infrastructure of the university, building a network of contacts and communication skills. The final model consisted of seven statistically significant variables, encompassing the student’s sex, level of studies and the first five extracted PCs. Student’s system of values and motivation as well as attitude toward distance learning, were those variables that had the biggest influence on student engagement.

The research result suggests that in addition to students’ system of values and motivation and their attitude toward distance learning, the satisfaction level of teachers’ attitude is one of the three most important factors that influence student engagement during the distance learning process.

The main value of this article is the statistical model of student engagement during distance learning. The article fills the research gap in identifying and evaluating the impact of various factors determining student engagement in the distance learning process.

The study aims to examine the mediating effect of psychological well-being (PWB) on the relationship between teamwork skills and student engagement (SE) in higher education institutional setups.

The study used a triangulation mixed-methods approach. Data were collected from final-year students pursuing post-graduation and graduation in private colleges in India. In the main study, quantitative data was gathered from 276 students through a survey. The relationship among the variables-teamwork skills, SE and PWB was empirically validated through path analysis; mediation was also conducted. In the auxiliary study, qualitative data was gathered through focus group sessions and was analyzed using thematic analysis.

Results depicted that teamwork skills positively predict students' engagement with their academic program. Additionally, PWB partially mediates the relationship between teamwork skills and SE.

The study was conducted to expand understanding of aspects related to promoting students' engagement in HEIs in Delhi and Haryana through being attentive toward teamwork skills development and through taking care of students' PWB.

The lack of physical contact and the absence of nonverbal clues could make some learners uncomfortable interacting with others via online learning platforms. Hence, understanding the determinants of students' motivation and engagement in online learning platforms is crucial in harnessing digital technology as an enabler of unrestricted and quality learning experiences.

Drawing on the self-determination theory (SDT), this study investigates the factors associated with student’s motivation to learn (MOL) and their influence on online learning engagement (OLE). Data were collected from 228 university students from the Klang Valley region of Malaysia using the online survey method.

The results of data analysis using the partial least squares structural equation modeling indicate that self-directed learning, computer and Internet self-efficacy and online communication self-efficacy significantly influence MOL. Besides, these factors indirectly influence OLE through MOL.

This study adds to the SDT framework by demonstrating how students' perceptions of autonomy, competence and relatedness through online interaction relate to MOL and OLE.

The aim of this paper is to explore the importance of individual learner differences and the effect differentiated instruction (DI) has on learners' levels of engagement.

The author carried out this research using a small-scale action research (AR) study.

The findings suggest that in acknowledging and responding to individual learner differences, especially interests, levels of learner engagement are positively affected.

This study’s key limitations were sample size, short-term study and potential teacher as researcher bias.

Recommendations were made for a further longitudinal study into the relationship between DI and language learner levels of engagement at University. An additional study into DI that looksbeyond language learning at HE, could add value to pedagogic approaches, which could make courses of greater intrinsic value to its students.

This research study aims to help fill a gap in the literature on the application of DI, as well as a unique perspective into its effect on learner engagement within a university context.

Large class sizes are becoming the norm in higher education against concerns of dropping learning qualities. To maintain the standard of learning and add value, one of the common strategies is for the course convenor to proactively monitor student engagement with learning activities against their assessment outcomes and intervene timely. Learning analytics has been increasingly adopted to provide these insights into student engagement and their performance. This case study explores how learning analytics can be used to meet the convenor’s requirements and help reduce administrative workload in a large health science class at the University of New South Wales.

This case-based study adopts an “action learning research approach” in assessing ways of using learning analytics for reducing workload in the educator’s own context and critically reflecting on experiences for improvements. This approach emphasises reflexive methodology, where the educator constantly assesses the context, implements an intervention and reflects on the process for in-time adjustments, improvements and future development.

The results highlighted ease for the teacher towards the early “flagging” of students who may not be active within the learning management system or who have performed poorly on assessment tasks. Coupled with the ability to send emails to the “flagged” students, this has led to a more personal approach while reducing the number of steps normally required. An unanticipated outcome was the potential for additional time saving through improving the scaffolding mechanisms if the learning analytics were customisable for individual courses.

The results provide further benefits for learning analytics to assist the educator in a growing blended learning environment. They also reveal the potential for learning analytics to be an effective adjunct towards promoting personal learning design.

In an effort to position higher education institutions to survive in this fiercely competitive environment, the paper aims to identify the direct and indirect relationships between higher education institutional positioning and exogenous factors (student engagement, employability, technology adaptation, teaching quality, and moral values).

A cross-sectional data was collected from 1,015 students studying in the pre-final year of graduation or post-graduate course/program from various educational institutions that were shortlisted based on the Indian NAAC and NIRF rankings. Thereafter, robust assessment criteria of PLS-SEM were used for model assessment and computation of results.

The findings revealed that to develop the greatest platform for upcoming young talent, higher educational institutional positioning ought to be addressed as a priority, which in turn will result in better living standards for upcoming generations.

Framing strategies for urban students can never match those living in rural areas, as they are deprived of money due to their level of upbringing from childhood, which creates a high difference in the psychological mindset of students while choosing a career path.

The higher positioning of educational institutions clearly reflects the authentic learning environment, with professionalism leading to better student engagement with best industry practice.

Research novelty is highlighted as a more focused and streamlined approach to students’ career development and institution branding by reanalyzing and grouping various concepts of institutional positioning into a single model.