Do diligent students perform better? Complex relations between student and course characteristics, study time, and academic performance in higher education

Socio-economic status and academic performance in higher education: A systematic review

Artificial neural networks in academic performance prediction: Systematic implementation and predictor evaluation

Smartphones may be particularly prone to distracting students, allowing them to spend more time engaging with their devices rather than focusing on academic tasks. The purpose of this study was to explore the impact of the use of smartphones on student academic performance in higher education. We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines to guarantee the inclusion of relevant academic materials. We examined 8 out of 299 documents gathered from the Education Resources Information Centre (ERIC), Scopus, and Web of Science (WoS) databases that were published since 2018. During the screening phase, excel files with details about the paper, including title, author and abstract, were exported from the database. Specifically, these papers focused on parameters such as primary, middle and high school students, smartphone addiction. Our bibliometric assessment shows that research on the use of smartphones for specific academic purposes has remained scarce in recent years, and most of the studies are located in Asian countries. The research supports that the academic use of smartphones has a significant positive impact on student academic performance in higher education. It shows that using smartphones for learning purposes has various positive effects on students' learning in and out of the classroom, such as motivating students, increasing their collaboration and interaction, and improving their engagement in learning. Also, the study found positive student attitudes toward the use of smartphone-assisted learning apps. We concluded that smartphone use has a significant positive impact on academic performance.

Aim/Purpose: The main objective of this study is to explore students’ beliefs with regard to social media use (SMU) in higher education and the consequences of such use on the perception of their academic performance. Additionally, the study aims to determine the major influential factors with regard to SMU in student learning settings as a means of enhancing their performance. To achieve these objectives, drawing on the literature related to SMU in higher education settings, a research model has been developed. Background: Social media platforms have led to a significant transformation with regard to the communication landscape in higher education in terms of offering enhanced learning and improved teaching experience. Nevertheless, little is known, particularly in developing countries such as Jordan, as to whether or not the use of such platforms by students in higher education increases the perceptions of their academic performance. Therefore, this study has developed a model to examine the perceptions of higher education students with regard to social media use and its effect on their performance. Methodology: The Structural Equation Modelling approach is used to analyze data collected via an online survey in the form of a questionnaire to examine the use of such a model. The study sample is drawn from undergraduate and postgraduate students from three universities (one public and two private) in Jordan. Convenience sampling is used to collect data. Out of 730 sent questionnaire, 513 responses were received, of which 403 were deemed qualified to be part of the data analysis process. Contribution: This study contributes to the literature on social media in higher education by enhancing our understanding of the perceptions of higher education students on the use of social media in their learning. The tested model can be used as a benchmark for other studies that target the impact of social media on student performance in higher education. Findings: The results reveal that perceptions of (1) usefulness, collaborative learning, enhanced communication, enjoyment, and ease of use of social media have a positive effect on the use of such media in student learning; (2) resource sharing has an insignificant effect on social media use in student learning, and (3) social media use has a positive influence on students’ perceptions of their academic performance. Recommendations for Practitioners: Senior management and policy makers in higher education institutions will have to train faculty members on effective strategies and methods in order to effectively integrate social media into education. This would equip faculty members with the necessary digital skills needed to help them to be fully informed regarding the benefits of social media and its tools in learning and teaching activities and would also allow them to avoid any possible drawbacks. Furthermore, faculty members should reconsider their current techniques and strategies, and adopt new methods in their teaching that encourage students to use social media platforms as part of their learning. For example, they can regularly post discussions and assignments on social media platforms to inculcate the habit of using such platforms among students for educational purposes. Students, on the other hand, should be aware of the implications and potential advantageous aspects of SMU in their learning. This could be done by conducting regular workshops and seminars in the various faculties and schools at universities. Recommendation for Researchers: Researchers are encouraged to investigate additional factors that might influence the use of social media by students as well as faculty members. Specially, an emphasis should be given to identify any potential obstacles that might hinder the use of social media in higher education. Impact on Society: Social media is not only useful for socializing, but also it can be an effective educational tool that enhance students’ performance in higher education. Future Research: Although the collected data support the research model, this study is subjected to various limitations that need to be tackled by further studies. This study is based on the principles of quantitative research design. Data for this study was collected via survey questionnaires. Accordingly, future studies may consider a qualitative research design in order to uncover additional factors that may impact the use of social media on the part of higher education students. This would allow researchers to generate in-depth insights and a holistic understanding of SMU by higher education students. A convenience sampling method was employed to select respondents for this study. The respondents who participated in this study were from three universities (one public and two private) in Jordan. Accordingly, future research is deemed to be necessary to achieve a degree of generalizability regarding the findings of this study.

Current research investigates the impact of students' E-Learning Attitudes (ELA), Digital Readiness (DR), and Academic Engagement (AE) on their academic performance in higher education. A survey in the form of an online questionnaire was administered to students through the networks established by the research teams. These networks encompassed academic staff from diverse Malaysian private as well as public universities. These academic staff were directed to share the survey link with their undergraduate students through WhatsApp or email. Two hundred eighty-six (286) valid surveys were collected from students at six public and private university campuses in Malaysia that offer courses and have used E-learning for at least one semester as part of COVID-19. In contrast to previous debates and studies, the outcomes of employing structural equation modeling through PLS 4.0 revealed a positive and noteworthy influence of E-learning platforms on students' academic performance. These findings hold broader implications for policymakers in higher education, researchers as well as educators, particularly in terms of considering the potential incorporation of social media tools within higher education, especially in developing nations. This research suggests that educational institutions that embrace change by aligning the goals of both students and instructors to establish a constructive and encouraging online learning atmosphere. This will foster active academic participation and enhance students' academic achievements.

This research investigates the impact of online learning on student engagement and academic performance in the higher education landscape. In a sample of 300 students from public sector universities in Punjab, Pakistan, the researcher examined online learning experiences, demographic factors, and academic performance. The descriptive statistics revealed moderately positive online learning experiences and moderately favorable academic performance on average, accompanied by significant variability within the sample. Correlation analysis, however, unveiled very weak and often statistically insignificant relationships between these variables, suggesting complex and non-linear dynamics at play. Consequently, we advocate for personalized support, adaptable pedagogical approaches, inclusivity, accessibility, and interdisciplinary collaboration as essential components to enhance online learning. Moreover, this study calls for continued research to unearth the intricate dynamics of online education's influence on student outcomes, driving the evolution of evidence-based practices in higher education. The study underlines the necessity for continued research into online education's complex dynamics and student outcomes. This includes studying new technology, learning analytics, and pedagogical methods to inform evidence-based practices in higher education.

The assessment of students’ academic performance in higher education is generally still dominated by conventional numerical approaches, which are less capable of representing qualitative and subjective variables such as classroom activeness and student participation. These approaches often result in evaluations that are not holistic and do not fully reflect students’ overall academic achievements. Therefore, this study aims to analyze the concept of fuzzy logic as a support tool for assessing students’ academic performance in higher education, with a case study of students at Universitas Asahan. The research method employs a descriptive qualitative and quantitative approach by applying Mamdani fuzzy logic. The input variables consist of exam scores, assignment scores, and classroom activeness, while the system output is the category of academic performance, namely sufficient, good, and very good. The sample data consist of ten active undergraduate students from Universitas Asahan. The data processing stages include fuzzification, the construction of fuzzy rules (rule base), fuzzy inference, and defuzzification using the centroid method. The results indicate that fuzzy logic is able to integrate quantitative and qualitative variables and accommodate uncertainty in academic assessment. The resulting evaluation is more proportional and realistic compared to conventional assessment methods based solely on average scores. Therefore, fuzzy logic can be considered an effective and flexible alternative approach to support student academic performance assessment systems in higher education.

This research assesses the student engagement mediating effect on the interaction between feedback offered through generative AI and academic performance in higher education. Understanding the impact of AI-generated feedback on student performance is increasingly important as technology is integrated into educational systems. Information was gathered using a structured questionnaire administered to 432 students, of which 311 provided usable responses. Hypothesized relationships were tested using regression analysis. Findings indicate that the use of AI-fed-back especially increases academic performance and student engagement has a mediating effect. Increased engagement due to prompt and tailored AI responses leads to improved motivation, enhanced learning, and academic performance. The active involvement of students during the application of AI systems into education is crucial as per the findings of this research. The study offers additional evidence paving the way for policy guidelines about the application of AI technology in education to support students’ performance. The study discusses the need to design AI feedback systems for active users emphasizing the role of generative AI on the higher education landscape.

(1) Background: The current study aimed to examine the mediating role of psychosocial factors in academic performance in higher education based on the adaptation of teaching due to COVID-19. (2) Methods: The methodological design is descriptive–exploratory, cross-sectional, and ex post-facto, using a structural equation model in a sample of 824 university students from Granada. For data collection, the AF-5 questionnaire was used for self-concept; EME-E for motivation, REIS for emotional intelligence, and CD-RISC for resilience, in addition to a specific questionnaire for sociodemographic and academic data. (3) Results: The findings show that (a) academic performance was positively related to personal competence and inversely related to self-confidence, with a higher regression weight in students who did not experience adaptations; that (b) there is a positive relationship between intrinsic motivation and academic performance; that (c) personal competence helped to decrease demotivation in students; and that (d) a positive self-concept acts as a protective factor against demotivation. (4) Conclusions: Therefore, the relevance of educational institutions in the holistic development of young adults is highlighted, ensuring not only academic success but also the emotional and personal well-being of students in a constantly changing world.

The integration of Information and Communication Technology (ICT) in higher education has emerged as a critical factor in enhancing academic performance and student engagement. ICT tools such as e-learning platforms, virtual classrooms, learning management systems, and educational software offer innovative ways to facilitate teaching and learning processes (Almazroi et al., 2020). These technologies enable students to access vast learning resources, collaborate in real-time, and receive timely feedback, which collectively contribute to improved academic outcomes (Nguyen et al., 2015). Moreover, ICT empowers instructors to adopt student-centered pedagogies, streamline administrative tasks, and personalize learning experiences (Bates, 2019). Despite its advantages, challenges such as digital inequality, lack of ICT skills, and inadequate infrastructure persist in some contexts, limiting its full potential (Buabeng-Andoh, 2012). This paper explores the impact of ICT on academic performance in higher education, highlighting both the transformative potential and the barriers to effective implementation. The study recommends institutional investment in ICT infrastructure and capacity-building programs to maximize the benefits of technology-enhanced learning

PurposeThe purpose of this study is to determine whether students' self-assessment (SSA) could be used as a significant attribute to predict students' future academic achievement.Design/methodology/approachThe authors address how well students can assess their abilities and study the relationship between this ability and demographic properties and previous study performance. The authors present the study results by measuring the relationship between the SSA across five different topics and comparing them with the students' performance in these topics using short tests. The test has been voluntarily taken by more than 300 students planning to enroll in the School of Business Informatics and Mathematics master's programs at the University of Mannheim.FindingsThe study results reveal which attributes are mostly associated with the accuracy level of SSA in higher education. The authors conclude that SSA, it can be valuable in predicting master's students' academic achievement when taking specific measures when designing the predictive module.Research limitations/implicationsDue to time constraints, the study was restricted only to students applying to master's programs at the Faculty of Business Informatics and Mathematics at the University of Mannheim. This resulted in collecting a limited data set. Also, the scope of this study was restricted to testing the accuracy of SSA and did not test using it as an attribute for predicting students' academic achievement.Originality/valuePredicting students' academic performance in higher education is beneficial from different perspectives. The literature reveals that a considerable amount of work is published to analyze and predict academic performance in higher education. However, most of the published work relies on attributes such as demographics, teachers' assessment, and examination scores for performing their prediction while neglecting the use of other forms of evaluation such as SSA or self-evaluation.

This paper has been designed to analyze theoretical insights into gender-based academic performance in higher education through the lens of Bourdieu's cultural capital theory. A systematic approach to review the published and available documents in online databases. The researcher reaches the point of saturation by browsing 68 published documents. These documents have been selected using the inclusion criteria on gender differentials in academic performance in higher education. The study findings outline that biological differences are less likely to affect the performance of female and male students rather than shaped by cultural differences. Females’ deprivation of education was due to the traditional and cultural practices in male hegemonic society. The study concludes that the difference in educational performance among female and male students in higher education is not linked with biological characteristics. It has roots in the difference of psycho-social, socio-economic, and cultural factors of socialization among female and male students.

ABSTRACTThis paper examines whether one of the determinants of academic performance in higher education is the geographical distance separating the place of study and the place of family residence. Twelve years of data on students from a public university are utilized to estimate a model of relative academic performance, with an instrumental variables two-stage least squares estimator to account for possible endogeneity bias. The results indicate that distance is a negative determinant of academic performance and provide a new factor to take into account in reflexions over the impact of the spatial organization of higher education institutions.

This study investigates the impact of inclusive and accessible learning technologies on student engagement and academic performance in higher education. Grounded in Universal Design for Learning (UDL) and Technology-Enhanced Learning (TEL) frameworks, the research explores how assistive technologies, AI-driven systems, and intelligent tutoring platforms contribute to equitable and effective learning environments. Employing a mixed-methods design integrating bibliometric and content analyses, the study systematically examines 56 peer-reviewed articles from the Web of Science database. Quantitative indicators, including co-authorship networks, keyword co-occurrences, and citation patterns, were combined with qualitative thematic analysis to identify research trends and trajectories. Results reveal a steady global increase in inclusive educational technology research, with notable emphasis on AI-based personalization, assistive tools, and intelligent tutoring systems. Findings indicate significant regional variations: institutions in technologically advanced contexts demonstrate higher adoption rates, while socio-economic disparities and limited faculty training impede equitable access elsewhere. The study concludes that inclusive learning technologies significantly enhance engagement and performance when supported by robust institutional strategies, professional development, and equity-focused policies. These findings advance the discourse on inclusive education by providing an integrated empirical overview and identifying pathways for future research and policy development.

This study explores the interrelationship between Knowledge Management (KM), Digital Literacy, and Academic Performance in higher education, with a qualitative approach focusing on the experiences of students and lecturers. KM plays a vital role in reducing information redundancy, ensuring quick access to relevant knowledge, and fostering a culture of knowledge sharing within academic environments. Meanwhile, Digital Literacy equips students with the skills to efficiently process, analyze, and utilize data through appropriate digital tools, expanding opportunities for collaboration via online platforms, academic forums, and professional networks. The integration of KM and Digital Literacy not only enhances academic efficiency and productivity but also strengthens innovation and collaborative capabilities, preparing students to adapt to technological advancements and curriculum changes. Furthermore, this synergy equips graduates with the competencies required to thrive in a knowledge-based economy and face the demands of the digital era. Findings reveal that institutions embracing both KM practices and Digital Literacy development achieve higher levels of academic engagement, collaborative innovation, and adaptive learning. The study underscores the need for higher education to integrate KM frameworks and digital competency programs to optimize academic performance and graduate employability in an increasingly competitive and technology-driven landscape.