Academic Performance Of Students Research Articles

Academic Tutoring and Academic Performance: An Analysis at UNSM

This study explores the relationship between the comprehensive tutoring system and the academic performance of students at the National University of San Martín (UNSM). The study addresses the issues faced by the institution, whose tutoring programme lacks a coordinated approach between faculties, a strong clinical psychology team, and teachers with adequate tutoring skills, resulting in a loss of student interest. The aim was to determine whether there is a significant relationship between the comprehensive tutoring system and academic performance. A quantitative methodology with a non-experimental, cross-sectional design was used. A questionnaire was applied to 342 students selected through stratified probabilistic sampling, and their academic performance was analysed. The results indicated that, although most students perceived the tutoring system as acceptable, no significant correlation with their academic performance was found. In conclusion, the current tutoring system does not appear to directly influence academic performance, suggesting a need to review its structure and integration. This study addresses a gap in the literature by examining the relationship between tutoring and academic performance in Peruvian universities, aligning with SDG 4 (Quality Education). Future studies should investigate contextual and personal factors that may influence academic performance.

Developing Canva-Based Sitekol on Collage Topic for First-Grade Public Elementary School Students

The study aims to create a learning media product using Canva for elementary school students to alleviate the lack of learning materials, which has been negatively impacting student academic performance. The research also seeks to evaluate the practicality and effectiveness of the learning media product. This study uses research and development with ADDIE design. The results of the analysis revealed that some students do not meet the minimum standards and require learning tools to improve their skills in cutting and sticking when studying collage topics. This research developed Sitekol media on collage topics in the design stage using Canva and Wordwall applications. The validity test results showed that Sitekol media received a 90% score from media experts for color appearance, image combinations, fonts, media layout, videos, and practical use. Material experts rated it at 95.3% for material aspects, levels of thinking, and supporting learning content. Students also found Canva-based Sitekol learning media to be beneficial as a teaching tool due to its accessibility, portability, convenience, interactive features, and detailed learning media instructions. The statistical tests conducted resulted in significant findings with high average values. Students responded very positively to the practicality of the media, giving an average score of 4.9 out of 5, indicating 98% of the ideal score. It can be concluded that using Canva-based Sitecol learning on grade 1 collage material exhibits practicality and validity as a learning medium.

Predictive Model for Identification and Analysis of Factors Impacting Students Academic Performance Using Machine Learning Algorithms

Background: Education is a vital component of both societal and individual growth. To create effective learning environments, it is essential to understand the factors that influence student achievement. However, the application of machine learning algorithms can drive positive change, providing higher education institutions with effective solutions to their challenges. Aim: This research develops a predictive model to identify and analyze the factors affecting student academic performance, aiming to provide institutional administrators and lecturers with a better understanding of the key factors impacting student success. Method: A comprehensive dataset was collected from undergraduate students at Modibbo Adama University (MAU), Yola, comprising student-related, home-related, lecturer-related, and institution-related factors. Model development was carried out using Python in Google Colab, a cloud-based Jupyter notebook environment. Classification algorithms such as K-Nearest Neighbors (KNN), Decision Tree (DT), Gradient Boosting Method (GBM), and Random Forest (RF) were applied to predict student academic performance. Four evaluation metrics namely; accuracy, precision, recall, and f1-score were used to analyze the models. Results: The Random Forest model outperformed the other machine learning models, achieving an overall accuracy of 95%. For predicting low-performing students, the model achieved a precision of 0.9677, recall of 0.9474, and f1-score of 0.9574. For high-performing students, the precision was 0.9324, recall was 0.9583, and f1-score was 0.9452. These strong performance metrics across both low and high performing student groups demonstrate the effectiveness of the Random Forest model in accurately predicting student academic performance based on the factors considered in the study. Feature importance analysis identified lecture attendance, sponsor support, quality of facilities, and lecturer clarification as the most influential factors on student performance. Other features, such as accommodation, employment status, and program preference, were found to have a low impact. These findings emphasize the importance of considering a comprehensive set of student, lecturer, institution, and home-related factors to sustain a conducive learning environment and enhance educational practices.

The Impact of Exemplars On The Academic Outcomes For Master’s In Education Online Graduate Students

Annotated exemplars have recently been scrutinized as an academic support strategy in the context of Higher Education Institutes (HEIs). The idea is that using exemplars may front-load the system regarding student academic performance through the provision of meaningful feedback and task-specific comments before formal student submissions. More specifically, The Scholarship of Teaching and Learning (SoTL) research regarding exemplar use has called for the investigation of these exemplars on academic performance for the online graduate student. The purpose of this quantitative, quasi-experimental study was to determine if and to what extent the integration of annotated exemplars impacted the academic outcomes for Masters in Education online graduate students. Academic outcomes were designated as assessment grades and overall course grades. The study methodology and design were quantitative quasi-experimental using traditional pre-/post- techniques regarding this exemplar implementation with a convenience sample. The sample size of the experimental group is n = 17. The control group ranges from n = 25 to n = 27. The objective stated explicitly is to investigate if and to what extent the use of annotated exemplars impacts overarching student outcomes for graduate students at a university in the southwestern United States. The results showed no statistically significant difference between the control group and the experimental group for assignment grades, resulting in a retention of the null hypothesis. The results also indicated that there was a statistically significant difference between the control group and the experimental group for overall course grades, resulting in a rejection of the null hypothesis. Potential areas of future research might include brick-and-mortar settings, larger sample sizes, other student populations, or a qualitative examination of student perceptions about exemplars.

Using Supervised and Unsupervised Machine Learning Models to Analyze Students Academic Performance

Examination result repositories generated by most universities can serve as machine learning datasets for training various models to gain insights from the data. These datasets can train multiple linear regression models to determine a student's cumulative grade point average (CGPA), or the score that a student will get in specific courses. Additionally, classification-based supervised machine learning models can use these datasets to provide insights into the class result that a student will obtain. These insights can be invaluable for academic advising and early intervention. Moreover, these datasets can train clustering-based unsupervised machine learning models, such as the K-means clustering model, to understand how student results are grouped into various clusters. This information can be crucial for planning and evaluating the quality of the university. This paper uses the dataset of undergraduate students' examination results from the Department of Computer Science at the University of Nigeria, Nsukka, to train three supervised machine learning models and one unsupervised machine learning model, utilizing Jupyter Notebook as the Python IDE. The training results showed acceptable accuracies of 91.5% for the Naïve Bayes model and 95.1% for the Decision Tree model. The linear regression model demonstrated a negligible root mean square error of 8.23×10−18, while the K-means clustering model exhibited an acceptable Silhouette metric of 0.12.

GENDER BASED FACTORS AND FEMALE STUDENTS ACADEMIC PERFORMANCE IN HIGHER LEARNING INSTITUTIONS IN RWANDA: A CASE STUDY OF KIBOGORA POLYTECHNIC IN NYAMASHEKE DISTRICT

This paper examined gender related factors influencing female students academic performance in higher learning institutions in Rwanda with reference to Kibogora Polytechnic. The specific objectives were to determine the level of female students academic performance, structural cultural factors, socioeconomic conditions, and cultural factors and their effect on female students academic performance. The research surveyed female students and staff from higher learning institutions, involving 486 participants. A representative group of 220 was calculated using Yamane formula. Data was collected through semi-structured questionnaires, interviews, desk reviews, and pre-tests. Statistical Package for Social Sciences was used to generate descriptive and inferential statistics. To the first objective, results revealed that 86.4% accepted female attendance rate was increased, 77.0% contended that female student has active participation in class within higher learning institutions, 76.4% accepted that there is a rate of graduation. To the second objective, the research revealed that 74.5% accepted that the existing policies influence female academic performance, 86.4 accepted that the higher learning procedures have influenced female academic performance, 87.2% show an agreement and strongly agreement respectively. The correlation coefficient r=0.522 was produced with p-value of 0.000 of a two-tailed. To the third objective, 74.5% provided positive responses concerned with the number of girls and boys in the family has influenced female academic performance, 86.4% agreed domestic work performed at home influence negatively academic performance in higher learning institutions, Findings demonstrated the association between socio-economic and the success of performance of female students was 0.820 the p-value was 0.000 for 2-tailed. To the fourth objective, the research felt that 88.0% that domestic responsibilities reduce female willingness to school and educational activities. Correlation coefficient and the p-value demonstrate the existence of significant effect of cultural factors on female student academic performance. The study recommends that the Ministry of education should establish effective female sensitive policies. The society should leave unfavorable cultural norms and hand habits that affect female students in higher learning institutions owing to their effect in lowering self-confidence and academic target. Further studies should investigate effect creating awareness on female education at all level and to establish the forums to debate on societal factors hindering girls education.

Perceived Level of Family Relationships and Predictors of Students’ Motivation from a Higher Education Institution

Family relationships and student motivation are two crucial factors that can significantly impact student academic performance. Studies have shown that students from supportive family environments tend to have higher motivation levels and better academic performance compared to those from less supportive homes. The objective of this study is to determine the perceived level of family relationships and student motivation for a higher education institution in Olongapo City, Philippines. At the same time, the study also intends to discover the underlying predictors of student motivation. The proponents then used a descriptive correlational research design to attain the objectives. Four hundred (400) students participated voluntarily in the online survey using purposive sampling. The online poll adopted two (2) validated research instruments to analyze the perceived level of family relationships and student motivation. The garnered data underwent statistical analysis using descriptive and inferential statistics. Results reveal that the students had a high level of cohesion and a moderate degree of expressiveness and conflict in their family. There was also a high student motivation level. The study also observed significant differences in the perceived level of family relationships and students’ motivation when grouped according to their demographic characteristics. There was a weak positive association between family relationships and students’ motivation. Cohesion, expressiveness, and conflict were predictors that influenced students’ motivation to confirm relationships. This study contributes in the aspect exploring family relationship variables and how they influence a student’s learning motivation.

Uncovering Reflective Practices of Educators In Teaching and Learning Process: a Phenomenological Study from Elementary School in The Philippines

Recent PISA results consistently show that 15-year-old students in the Philippines are five (5) to six (6) years behind in critical competencies, including mathematics, science, and reading—issues that predate the pandemic. Given teachers' enormous influence on students' academic success, the efficacy of their teaching tactics is becoming increasingly important. The advent of the epidemic and adjusting to a new normal posed significant hurdles to established information transfer techniques. This study investigates the reflective practices of educators at Los Baños Central Elementary School, Philippines, analyzing the evolution of these practices across three key periods: pre-pandemic, during the pandemic, and in the post-pandemic "new normal." It further examines the integration of three distinct learning modalities employed during the 2020-2021 and 2021-2022 academic years. Additionally, the study emphasizes the importance of ongoing reflection by educators on their instructional methods to more effectively meet the needs of their students. Using a transcendental phenomenological methodology, the researchers conducted in-depth interviews with seven (7) educators, resulting in the identification and analysis of major themes in their responses. Through the data collection process, this study revealed that, despite numerous challenges encountered during the pandemic, educators effectively managed the crisis by engaging in reflective practices to enhance their teaching methods. The findings underscore the pivotal role of reflective practices in advancing the teaching-learning process and improving student academic performance.

The The Effect of STEM Activities on the Academic Performance of Students with Reading Problems

The The Effect of STEM Activities on the Academic Performance of Students with Reading Problems

Influence of Cultural Norms on Student Academic Performance in Marsabit Central Sub-County

Influence of Cultural Norms on Student Academic Performance in Marsabit Central Sub-County

Impact of Parental Involvement on Children’s Academic Performance of Secondary School Students in Katsina local Government, Katsina State

This study explores the impact of parental involvement on the academic achievement of secondary school students in Katsina Local Government and to determine whether the demographic variable of parents has an effect on their involvement in their children’s education. In addition, the study sought to examine what existing literature review found on the relation between parental involvement and children’s academic achievement. The present study is going to be carried out in Katsina. The responses of 40 parents, whose children are enrolled in secondary schools, were taken as samples for the current study. The Intensity Sampling Technique was used in this research. A questionnaire about the demographics of parents will be distributed and interviews will also be conducted to assess the level of parents’ involvement. To find out student achievement levels, the student’s results will be used. The qualitative method will be used to gauge the impact of parental involvement on students’ academic achievement. The results revealed that parental income level has no impact on the level of involvement in their children’s education. However, the educational level, age, employment and marital status of the parents had a greater impact on parental involvement. The main findings of this research indicated that students with highly involved parents had better academic performance and higher test scores in all the subjects compared to students whose parents were not involved in their education. The findings, suggested that parents should grow more awareness on the importance of visiting and supporting their children in school. It was also recommended that parents should take an active role in assisting their children’s education at school and at home since they are the first teachers of their children.

Analysis of the Impact of the Qaliwarma Program on the Academic Performance of Students in Primary Schools in San Roman Province, Puno, Peru

The research work had the general objective of analyzing the impact of the Qali Warma Program on the quality of life of students in primary educational institutions in the province of San Roman, the quantitative approach of non-experimental design was used, the study population and sample consisted of 80 parents of primary educational institutions in the province of San Roman, the results revealed that the satisfaction of students with the food provided by the program is neutral, with 56. 25% of parents perceiving it this way, 33.75% not very satisfied and only 10% very satisfied, likewise there is an increase in the number of approved students making a difference of 1336 students between the periods 2016 - 2023, and a reduction of disapproved students of 84, as a final conclusion it was determined that the Qali Warma Program has a moderate impact on the quality of life and academic performance of primary students in San Roman, with a majority of parents who perceive the program in a neutral way. However, the program has demonstrated success in improving academic performance and increasing the number of beneficiaries, contributing to the development of skills and progress in reading comprehension and mathematics.Feeding

Utilizing Data Mining Techniques to Predict Student Academic Performance

During this epidemic, a problem in fundamental education affecting all globe is occurring, and we note that education and learning were online and conducted in students. Academic performance of students must be forecast, so that the instructor may better identify the missing pupils and offer teachers a proactive opportunity to develop additional resources for the student to maximize their chances of graduation. Students' academic achievement in higher learning (EH) has been extensively studied in addressing academic inadequacies, rising drop-out rates, graduation delays, and other difficult questions. Simply said, the performance of students refers to the amount to which short and long-term educational objectives are met. Academics nonetheless judge student achievement from different viewpoints, from grades, average grade points (GPAs) to prospective jobs. The literature encompasses numerous computing attempts to improve student performance in schools and colleges, primarily through data mining and analysis learning. However, the efficiency of current smart techniques and models is still unanimous.

Mathematical Modelling of the Impacts of Morning Fatigue on Academic Performance: A Case Study of Federal University Wukari, Taraba State

Several authors have researched the phenomenon of sleep deprivation among students. In their studies, we discovered that they did not consider morning fatigue. So, we decided to fill the gap in the literature by using mathematical models to study the impact of morning fatigue. The aim is to develop mathematical modelling for the impact of morning fatigues on the academic performances of the students, a case study of the Federal University Wukari in Taraba State. In this project work, we formulated a mathematical model based on a system of ordinary differential equations to study the impact of morning fatigue on academic performance. We tested the model for existence and uniqueness and discovered that the model exists and that it is unique. The basic reproduction number was computed using the next-generation matrix approach. Questionnaires were distributed to 400 students and the data for this research were collected from the responses of the students. The result of the basic reproduction number shows that morning fatigue can be controlled. Using the Routh-Hurwitz criterion for local stability, the fatigue-free equilibrium (FFE) states of the model were established and proved to be locally asymptotically stable. Sensitivity analysis was then carried out to determine which parameters should be targeted by control intervention strategies of which the result shows that an increase in the acceptance of the control measure rate leads to a reduction in the prevalence of fatigue. Finally, a numerical simulation of the model was carried out and the result shows that Morning fatigue has a great impact on the academic performance of students. This means that there is a need for students to avoid reading till daybreak which in turn brings morning fatigue.

Meta-Analysis of Collaborative Learning Approaches in Educational Management and Their Impact on Student Performance

This meta-analysis investigates the effects of collaborative learning approaches within the framework of educational management and their impact on student performance. Collaborative learning, as a student-centered instructional method, has been widely adopted across various educational levels and settings. However, its effectiveness in enhancing academic achievement remains a topic of debate. This study synthesizes findings from 12 empirical studies conducted between 2022-2024, covering primary, secondary, and higher education contexts globally. Using a random-effects model, the meta-analysis quantifies the overall effect size of collaborative learning approaches on student performance, while accounting for variations in geographical region, subject matter, and educational level. The results reveal a high to strong positive effect of collaborative learning on student academic performance (mean effect size = 0.819). Additionally, subgroup analyses show that the impact is more pronounced in subjects requiring higher-order thinking skills, such as science and mathematics, and in educational settings where collaborative learning is systematically supported by institutional management. The analysis also highlights key factors that influence the success of collaborative learning, including group dynamics, teacher facilitation, and the integration of technology.

The Traditional System of Qur’anic Education in Northern Nigeria (Tsangaya): Recipe For A Feasible and Sustainable Reform

Succumbing to absolute neglect, the Tsangaya system faces many avoidable problems. Most of the attempts made by some administrations to address these problems appeared to have been narrowed down to either abolishing the system or blending it with alien elements. The beautiful aspects of the system appeared to have been ignored. This paper, generating data from interviews and document analyses, attempts to bring out some of the ignored features of the Tsangaya system, the problems it faces and suggestions for a sustainable reform. The aim is to bring into light some aspects of the system which risks being lost amidst the blind attacks against Tsangaya and the way for a feasible and sustainable reform. The reason for selecting this topic is the present attempts being made to reform the Tsangaya system in Nigeria. The paper reveals that aspects such as student/teacher relationship, class management and control, assessment of student's academic performance, etc. are beautiful features of the system which the conventional education system could borrow and integrate. A holistic approach, including recognising the noble status of the system as the custodian of the Qur’an, its teachers and students, is suggested in order to realise a sustainable and feasible reform.

Impact of Yoga Nidra on the Academic Performance of Students: A Narrative Review

Impact of Yoga Nidra on the Academic Performance of Students: A Narrative Review

Relationship between Self-Esteem and Academic Performance of Hearing-Impaired Students at Kuja School for the Deaf, Rongo Sub-County, Migori County, Kenya

Conducted in Kuja School for the Deaf, Rongo Sub-County, Migori County, the research investigated if there existed a relationship in academic performance between students with different levels of self-esteem. Study objectives sought to assess the levels of self-esteem, the academic performance of students with high or low self-esteem and how hearing-impaired students cope as they protect and enhance their self-esteem. Hierarchy of Needs theory propounded by Abraham Maslow guided the study. The theory states that individuals will strive to satisfy higher-level needs when lower needs in the hierarchy are fulfilled. The study also used Person-centred theory by Carl Rogers; this theory posits that a child will attain self-understanding when they accept the self and reality. This study was descriptive in nature and utilized a quantitative approach to collecting data with the use of a mixed questionnaire. The study used Rosenberg's self–esteem assessment tool for the measurement of self-esteem levels, academic performance was measured using examination scores, and coping mechanisms were measured using a Likert scale. Students and administrators of Kuja School for the Deaf made the target population for this study. In total, 290 participants were targeted, and 98 participants were sampled to participate in the study using purposive and simple random sampling. Quantitative data was organized and then analyzed using SPSS version 23; the data was displayed through tables, charts and frequency distributions. From the study, it was deciphered that a majority (77.08%) of the students exhibited high self-esteem, while a few (22.92%) portrayed low self-esteem. The findings also showed that the mean difference between hearing-impaired students showing low self-esteem and students who showed high self-esteem was not statistically significant. The findings further revealed that the students sometimes or often employ various coping strategies, including withdrawal and bicultural skills. This study, therefore, concluded that students with hearing impairment mostly exhibit high self-esteem, and their academic performance is not necessarily determined by self-esteem levels. Further, the study concluded that there are coping strategies that enable students with hearing impairment to protect their personal self-esteem. On the basis of these findings, this study suggests that teachers and administrators of schools for the hearing impaired should seek to understand the needs and challenges of their students, which could be affecting their academic performance and adopt strategies to address them.

The Impact of Teacher Training in Social Justice Education on Classroom Practices and Student Outcomes in Nigeria

This study investigated the impact of teacher training in social justice education (SJE) on classroom practices and student results in Nigerian schools, including cultural, economic, and sociological aspects. The research emphasized the crucial importance of teacher training in incorporating social justice ideas into education, as it acknowledges the significant impact of SJE in fostering critical thinking, empathy, and social equity. The study utilized a combination of quantitative and qualitative analyses to evaluate the level of SJE integration in teacher training programs. It also examined how this integration affects instructional tactics and therefore influences student academic performance and social awareness. The results emphasized the strong positive relationship between extensive SJE training and enhanced classroom inclusivity, increased student involvement in social matters, and overall academic success. Although educators trained in SJE face obstacles related to institutions and resources, they are able to create a learning environment that is more inclusive and encourages critical engagement. This research adds to the discussion on educational equity by promoting the implementation of SJE training in teacher education programs. The goal is to provide educators with the skills they need to address social inequalities and create a fair and inclusive learning environment. Keywords: Teacher Training, Social Justice, Education, Classroom Practices, Student Outcomes

Breaking Down the Wall: The Effect of Immigration Enforcement and Nonprofit Services on Undocumented Student Academic Performance

Abstract Much of public administration and nonprofit research centers on issues of race and gender, but citizenship remains underdeveloped for a variety of reasons, especially due to a lack of data on the undocumented community. The first research aim of this study is to identify how immigration enforcement affects undocumented student performance. The second contribution is to understand the effect of how legal service provision by immigrant-serving nonprofits comes into play. Theoretically, these services work toward helping buffer the negative implications of community arrests and deportations on student performance. We test our theoretical arguments using a unique dataset comprised of student-level performance metrics of 2 million Latino students – including nearly 225,000 undocumented students – in Texas public schools. These data are merged with county and district-level data that reflect the level of immigrant deportations and the presence of immigrant-serving nonprofits (ISOs) in their communities. This research finds that immigration enforcement negatively impacts undocumented student performance. Furthermore, ISOs can help limit these effects and improve educational performance.