Predictive Modeling of Academic Performance of Online Learners Based on Data Mining

Background Our study aimed to examine the effects of COVID-19 on the physical fitness and academic performance of Chinese college students. Participants The sample included physical fitness test data from 9,712 undergraduate students and academic performance data from 12,000 undergraduate students at a top university in China. Methods Physical fitness was measured and evaluated according to the Chinese National Student Physical Fitness Standard. Data were analyzed using two-sample t-tests and Pearson product-moment correlations. Results Total physical fitness test scores of college students decreased after the outbreak, but their mean body mass index (BMI) remained at normal levels. The mean academic performance of college students unexpectedly improved during the online learning period. The positive correlation between physical test scores and academic performance was significantly higher during COVID-19 than that before the outbreak. Conclusions Chinese college students with high physical fitness during COVID-19 were more likely to achieve good academic performance.

Introduction. The article examines the influence of various factors on the academic performance of university students. The purpose of the article is to identify the degree of influence of various factors on first-year university students’ academic performance taking into account their gender. The study is based on students’ self-assessment. Materials and Methods. The methodological basis of the research was the articles of Russian and foreign scholars devoted to the factors affecting the academic performance of university students (A. Alhadabi, H. W. Brink, Y. García, H. G. Hidajat, E. V. Krekhovets, F. Moradi, N. S. Nurieva, A. O. Ryazhkin, V. N. Shlyapnikov, D. R. Valeeva, S. D. Vaulin, S. V. Yaroshevskaya, I. Živčić-Bećirević and etc.). The empirical study was carried out at Tyumen State University. The sample consisted of 232 first-year students of various fields of study, including 101 males and 131 females. Results. The analysis of the scholarly literature on the research problem enabled the authors to identify the factors that influence the academic performance of university students and propose a classification of these factors. Based on students’ self-assessment, the degree of influence of each of the selected factors on their academic performance was determined. Significant differences in the assessment of the influence of a few factors on academic performance related to the students’ gender were revealed. According to the self-assessment of students, the competence of academic staff has the strongest influence on their academic performance. Within the framework of the proposed classification of factors, the most important for students was a group of factors related to their personal characteristics. Factors related to randomness and academic fraud were ranked among the least important. Intrinsic motivation as a factor influencing academic performance turned out to be more important than extrinsic positive and extrinsic negative motivation. Conclusions. The experimental data show that women, to a greater extent than men, associate their academic performance with external factors (teachers’ competence, learning environment, study facilities), or with their innate personality traits (intellectual abilities, memory characteristics and attention, emotional balance). For men, a more significant factor in academic performance is relying on their own strengths and expectations of success from their efforts. At the same time, their academic performance is more determined by the social environment at the university.

Education can be utilized as a tool to face many problems, overcome many hurdles in life. The knowledge obtained from education helps to enhance opportunities in one's employment development. To extract useful information from the knowledge obtained, Educational Data Mining is widely used. Educational data mining provides the process of applying different data mining tools and techniques to analyze and visualize the data of an institution (school) and can be used to discover a unique pattern of students' academic performance and behavior. The present work intends to enhance students' academic performance in secondary school using data mining techniques. Real data was collected using school reports and questionnaire method by the Portugal school which has been used in this paper. Naive Bayesian algorithm can be easily implemented to predict the students' academic performance and behavior. Classification of students into two classes, pass and fail, involves training phase and testing phase. In training phase, Naive Bayes classifier is built and in the testing phase, Naive Bayes classifier is used to make the prediction. The accuracy of the classifier is calculated using WEKA tool in which confusion matrix is generated. The accuracy of the classifier obtained is 87% which can be further improved by the selection of appropriate attributes. Developing the classification algorithms in this way helps to obtain a more efficient student performance predictor tool using other data mining algorithms and it also helps to improve the quality of education in an educational institution.

The current study intended to examine the association between emotion regulation (i.e., cognitive reappraisal and expressive suppression) and academic performance in university students. In this correlational study, a sample of 300 (men=119; women=181) university students (BS and MS programs) in the age range of 18-29 years (M=21.45; SD=2.14) was selected randomly from a public sector university in Faisalabad city, Pakistan. The Emotion Regulation Questionnaire (Gross & John, 2003) was used to assess emotion regulation whereas the percentages of obtained marks in the last semester/degree program served as the measure of the academic performance of the participants. The results depicted a significant correlation between emotion regulation and academic performance indicating a significant positive association between cognitive reappraisal and academic performance while, a significant negative association between expressive suppression and academic performance in university students. Moreover, cognitive reappraisal and expressive suppression were found to be significant predictors of academic performance. Besides the significant implications of this study highlighting the role of relevant policymakers, university authorities, students’ counselors, and mental health professionals, suggestions for future studies are discussed based on the current findings.

PurposeCreating suitable learning conditions in university classrooms continues to be a topical issue in higher education. The above means that a continued search for innovative teaching and learning strategies in universities remains a priority issue. The study therefore investigated conditions that facilitate the effective implementation of cooperative learning (CL) as well as how CL influences the academic performance of students in universities in Zimbabwe.Design/methodology/approachThe research adopted a quantitative research approach located in the descriptive research design. A sample of 341 undergraduate students selected using a simple random sampling strategy from a sample frame of 701 undergraduate students participated in the study. The study first used a pre-test and later, a post-test to determine the initial and end of semester (EOS) academic performance levels of students, respectively, on a Calculus 1 course. A self-constructed structured questionnaire was also used for data collection on the views of students towards the use of CL with particular reference to the 5 dimensions of positive interdependence (PDI), promotive interaction (PI), individual and group accountability (IGA), social and interpersonal skills (SS) and group processing (GP). The questionnaire was validated using confirmatory factor analysis. Structural equation modelling was used to test proposed relationships. A total of 341 questionnaires were administered through an email survey. Of the total, 149 completed questionnaires were received from the students, giving a return rate of 43.7%.FindingsThe results showed that positive interdependence, promotive interaction, social and interpersonal skills, individual and group accountability as well as group processing were important antecedents to the effective implementation of CL in universities. The results further showed that CL plays a significant role in improving the academic performance of university students; hence, academic performance was viewed as a significant consequence of CL.Research limitations/implicationsThis is the first study on the application of CL to enhance the academic performance of university students in the context of Zimbabwe. As a result, caution should be exercised when generalising the results as more studies to either confirm or disconfirm these results in the context of Zimbabwe may still be required.Practical implicationsThese results have implications on policy and practice with regards to active teaching strategies in universities. With regards to practice, the results demonstrated that the use of group activities that allow students to share knowledge and support each other while the teacher plays a facilitating role is important for enhancing students' academic performance. With regards to policy, the results showed that universities can enhance the academic performance of students if policies that promote student-centered teaching and learning approaches to ensure that teaching in universities is more student-led than lecturer-led are developed.Originality/valueWhile many studies have been conducted in other contexts, to establish the influence of CL on the academic performance of university students, there is no known study on the influence of CL that has been conducted in the context of Zimbabwean universities. The results of this study therefore are an eye opener on the role of CL in enhancing the academic performance of students in Zimbabwean universities.

Over the last decade data warehousing and data mining tools have evolved from research into a unique and popular applications, ranging from data warehousing and data mining for decision support to business intelligence and other kind of applications. The chapter presents and discusses data warehousing methodologies along with the main components of data mining tools and technologies and how they all could be integrated together for knowledge management in a broader sense. Knowledge management refers to the set of processes developed in an organization to create, extract, transfer, store and apply knowledge. The chapter also focuses on how data mining tools and technologies could be used in extracting knowledge from large databases or data warehouses. Knowledge management increases the ability of an organization to learn from its environment and to incorporate knowledge into the business processes by adapting to new tools and technologies. Knowledge management is also about the reusability of the knowledge that is being extracted and stored in the knowledge base. One way to improve the reusability is to use this knowledge base as front-ends to case-based reasoning (CBR) applications. The chapter further focuses on the reusability issues of knowledge management and presents an integrated framework for knowledge management by combining data mining (DM) tools and technologies with CBR methodologies. The purpose of the integrated framework is to discover, validate, retain, reuse and share knowledge in an organization with its internal users as well as its external users. The framework is independent of application domain and would be suitable for uses in areas, such as data mining and knowledge management in e-government.

Recent advances in computing, communications, digital storage technologies, and high-throughput data-acquisition technologies, make it possible to gather and store incredible volumes of data. It creates unprecedented opportunities for large-scale knowledge discovery from huge database. Data mining (DM) technology has emerged as a means of performing this discovery. There are countless researchers working on designing efficient data mining techniques, methods, and algorithms. Many data mining methods and algorithms have been developed and applied in a lot of application fields [1]. Unfortunately, most data mining researchers pay much attention to technique problems for developing data mining models and methods, while little to basic issues of data mining [2]. In this talk, some basic issues of data mining are addressed. What is data mining? What is the product of a data mining process? What are we doing in a data mining process? What is the rule we should obey in a data mining process? Through analyzing existing data mining methods, and domain-driven (or user-driven) data mining models [3-5], we find that we should take a data mining process as a process of knowledge transformation. Based on this understanding of data mining, a conceptual data mining model of domain-oriented data-driven data mining (3DM) is proposed [2]. The relationship between traditional domain-driven (or user-driven) data mining models and our proposed 3DM model is also analyzed. Some domain-oriented data-driven data mining algorithms for mining such knowledge as default rule [6], decision tree [7], and concept lattice [8] from database are proposed. The experiment results for these algorithms are also shown to illustrate the efficiency and performance of the knowledge acquired by our 3DM data mining algorithms.

Online distance learning (ODL) has spread worldwide in all levels of education, and academic performance is a frequently mentioned topic in the research of ODL. This research focuses on the impact of students’ prior academic performance in different subjects on their academic performance in the context of transition from a traditional class to online distance learning. The participants are students from a key public high school in China. They took a traditional in-person class in their twelfth grade first semester and took ODL in twelfth grade second semester. Positive and strong Spearman and Pearson Correlation (~0.8) is found between student’s academic performance during traditional class and student’s academic performance during ODL; positive and weak Spearman and Pearson Correlation (~0.4) is found between student’s academic performance during traditional class and the change of student’s academic performance through the transition from the traditional class to ODL, indicating a positive correlation between prior academic achievement and later performance. Linear regression fitting is applied to the student’s academic performance during traditional class and the student’s academic performance during ODL, the results have shown that the prior academic performance represents by cumulative exam have a good prediction of the later academic performance in both traditional class and ODL context.

Self-efficacy, self-discipline and academic performance: Testing a context-specific mediation model

The problem and the aim of the study. The COVID-19 pandemic has caused a worldwide emergency, with consequences for more than just physical health, including mental health and educational outcomes. University students are particularly vulnerable since they are dealing with a number of challenges at once, such as the health effects of the pandemic both directly and indirectly, the sudden shift to online schooling, and doubts about their future employment opportunities. Critical to understanding the far-reaching effects of the pandemic on student lives, learning processes, and mental health is research into COVID-19-related psychological anxiety and its impact on academic performance in higher education. This research subject seeks to investigate the extent to which college students are anxious about the COVID-19 pandemic and how this unusual stressor affects their participation in class, grades, and general satisfaction with their education. By looking at it from this perspective, we may identify the many ways in which the epidemic has affected the future generation of researchers and professionals, and then develop strategies to help them cope with the difficulties they will face. Research methods. The study employed a correlational descriptive approach to investigate the psychological distress caused by the COVID-19 epidemic and its influence on the academic performance of university students in Jordan. The sample consisted of 300 undergraduates (male and female) from the College of Educational and Psychological Sciences at Amman Arab University in the 2021–2022 school year, with the entire student body serving as the population. The survey tool was distributed online via social media, leading to 379 respondents, and a chance sample was used because it was feasible to reach a large number of participants—especially during the pandemic. Results. The study results show a detailed range of stress and worry, with average scores varying from 2.8 to 4.1 among 25 items. Major concerns involve social isolation, indicated by an average score of 4.1 for feeling alienated because of social distancing measures, and academic disruptions, with an average score of 4.0 for experiencing a lack of control over academic life owing to the pandemic. There is a significant gender gap between the reported levels of anxiety and its effect on academic performance; 40% of female students and 30% of male students express high levels of anxiety, and the average academic impact score for female students is 3.0 while the average score for male students is 2.5. The data also shows that anxiety levels and the detrimental effect they have on academic performance are getting worse over the years, with fourth-year students having the worst levels of anxiety (45%) and the greatest academic impact score (3.5). The findings highlight the importance of providing students with personalized support to help them cope with the psychological effects of the pandemic. Scientific novelty: Novelty resides in the study's exhaustive examination of COVID-19's psychological effects on Jordanian university students, with a particular emphasis on anxiety levels and how they relate to academic achievement. By looking at the effects of the pandemic across genders and academic years, it shows how anxiety levels rise over time and how there are clear differences between the sexes. The study offers important insights into the many ways in which the pandemic affected students' academic performance and mental health by using a large sample size, a correlational descriptive approach, and social media to reach a wide audience during the epidemic.

The present study investigates the multifaceted impact of part-time employment on the academic performance, well-being, and career readiness of college students. Drawing upon responses from 120 students, the research explores how variables such as job type, gender, working hours, and income levels influence students’ experiences. Findings reveal that while part-time jobs provide crucial financial support, foster independence, and enhance transferable skills such as communication, teamwork, and time management, excessive working hours negatively affect academic focus, health, and overall well-being. Temporary jobs are associated with greater skill acquisition and financial benefits compared to permanent roles, though they also impose heavier time and health burdens. Gender-based differences emerged, with female students reporting both higher benefits and greater challenges than their male peers. Similarly, higher-income students enjoyed greater financial and skill-related rewards but faced increased time pressure and health concerns. The study concludes that part-time employment is neither wholly advantageous nor detrimental; its effects depend on balance, job nature, and institutional support.

Student dropout and academic failure are serious problems faced by universities around the world. The academic development of university students is the joint result of external (teacher support) and internal factors (resilience). The goal of this study is an in-depth understanding of the association between university Students' academic resilience and academic performance. All respondents were from a local Chinese public university. Two self-report scales with adequate reliability and validity were completed by 440 undergraduate students: the Connor-Davidson Resilience Scale (CD-RISC) and the Perceived Teacher Support Scale (PTSS). The results of this study demonstrated that academic resilience and teacher support were positively and closely correlated with the academic performance of university students. Teacher support plays a mediating role in the nexus between academic resilience and academic performance. The findings of this study shed light on the improvement of university students' academic performance and reducing the dropout rate from theoretically and practically. The study helps identify the key factors that contribute to students' academic success and improve their well-being. The results also provide evidence for university directors to design effective programs and take initiatives to increase retention rates and improve university students' success.

Video games have remained popular ever since the video game industry boom in the 1980s. It has remained popular, especially for children, teenagers, and adults. However, video games have also sparked controversies among the population. Concerns have been raised regarding the harmful effects of video games, particularly regarding addictions. Video games have been accused by many of being the cause of lowering academic performance. Therefore, this study aims to explore the relationship between video games and the overall academic performance of university students in depth. We applied several statistical methods using a questionnaire, which 100 university students filled out. The insights uncovered from this study may help determine if and how much video games affect the academic performance of university students.

Parental bonding is a crucial component for the acquisition of a positive attitude and better academic performance among students.In this study, the correlational research design was to investigate the relationship among parental bonding, self-regulation, proactive attitude, and academic performance in university students.Data consisted of 200 university students with ages ranging from 18 to 24, selected through non-probability purposive sampling technique.Due to the COVID-19 pandemic situation data collection was undertaken through an online Google form.Parental Bonding Instrument, Self-Regulation Scale (SRS), Proactive Attitude Scale (PA), demographic sheet, and recently obtained GPA of each participant were used for data collection.Correlation analysis showed that there is a significant positive correlation between self-regulation and proactive attitude, control mother, and control father.Proactive attitude was found to be positively correlated with control mother.Multiple regression analysis showed that the control mother was a significant positive predictor of self-regulation whereas the care father was a negative predictor of selfregulation and the care mother was a negative predictor of proactive attitude.Independent sample t-test results showed that there were significant gender differences between males and females based on GPA and care father.Findings of the study would help broaden the understanding and knowledge of the role of parental bonding as a predictor of self-regulation, proactive attitude, and academic performance in university students.

This article presents a systematic review on the relationships between mental well-being and academic performance in university students. The primary aim is to elucidate how different mental health states can influence academic achievement and vice versa. Through the review of existing literature, it was identified that an optimal mental health state fosters skill such as concentration, stress management, and adaptability, all essential for good academic performance. Conversely, stressful academic environments can contribute to mental health issues, highlighting the responsibility of educational institutions in providing an environment conducive to the holistic well-being of their students. The importance of training and raising awareness among academic and administrative staff for early detection and appropriate response to mental health issues was emphasized. Multifaceted interventions that address both mental well-being and academic performance were found to be particularly effective. In conclusion, this study underscores the need to adopt a holistic approach in higher education.