Enhancing Student Performance Insights ThroughMulti Parametric STBO Based Analysis inEngineering Education

Enhancing student's performance is a significant part of developing quality education in any educational institute. It is very difficult to get promising student performance without student categorization according to their academic performance as there are different standardized students. In this paper, our aim is to determine the performance of the students. For this purpose, a survey has been conducted on students in our university in order to collect data and to analyze and predict the student category based on their performance. Apart from this, another purpose of this study is to examine the effect of the reduced features on the classification model using state-of-art machine learning algorithms. Here, we propose a workflow of web-based four-tier architecture for the student performance prediction that will define the student's category in order to help them exactly pinpoint their learning capabilities. Hence, we used multiple supervised learning-based machine learning techniques for the prediction of student performance. Each of the student category categorized by considering on the top features. The analysis results indicate that we got the highest performance that is 88.00% by using the Artificial Neural Network (ANN) among the classifiers by showing its superiority to the existing model.

Adaptive learning dynamically adjusts the level or types of instruction based on individual student abilities or preferences and helps personalize instruction to improve or accelerate a student’s performance. It is done by helping to address common learning challenges, including student’s inspiration, diversify the student backgrounds, and limiting the different resources. Targeting instruction to the abilities and content needs of the individual student can scale down the course drop-out rates; improve student results and/or speed of achieving those resulting outcomes, and enable faculty to focus their dedication where it is most needed. The design and formation of the test depend on the questions. The test should generate the quiz such that all different levels of questions are inserted to make the test more competitive. This research work aims at assigning weightage to questions in the quiz based on the difficulty level. Assigning the weightage to question is a tedious task. This paper aims to discuss two methods for assigning weightage to the questions in the test and decide the difficulty level of the question.

To consider rapid development of advanced technology in the fashion industry this study focuses on analyzing how D CAD patternmaking and D garment simulation programs have been used as tools for enhancing student performance in student centered fashion design education A case study is used to capture students rsquo perceptions while they are using D and D software for design development and measure student performance with respect to enhancement of understanding of D visualization in student centered education This study discovered that both D patternmaking and D simulation program usage increased and enhanced student learning and helped them be more efficient in their pattern development process It was also found that both programs encouraged students to think critically about their design process This study provides insight with respect to how fashion design classes can properly equip future professionals with new technology developments in the fashion industry nbsp

This study examines the effectiveness of the Concrete-Representational-Abstract (CRA) approach, grounded in Jerome Bruner’s cognitive development theory, in enhancing students’ performance among Grade 7 students at St. Christine National High School, Lianga, Surigao del Sur, Philippines. Using a quasi-experimental design, two groups—experimental (CRA) and control (conventional approach)—were assessed via pre- and post-tests on operations of integers, simplifying numerical expressions, and identifying the absolute value of an integer and its meaning. The CRA group progressed through three stages: hands-on manipulatives (concrete), visual representations (representational), and symbolic problem-solving (abstract), while the control group received traditional/conventional approach. Initial pre-test scores were comparable (Control: M = 15.22, SD = 3.97; Experimental: M = 15.75, SD = 5.02), but post-tests revealed a marked divergence: the experimental group achieved a mean score of 24.22 (SD = 6.62), reflecting an 8.47-point improvement, whereas the control group scored 21.28 (SD = 8.73), with a 6.06-point gain. This 39.8% greater improvement in the CRA group underscores its efficacy in fostering deeper conceptual mastery and reducing performance variability, attributed to structured scaffolding that bridges tangible experiences to abstract reasoning. The results demonstrate the effectiveness of the CRA approach in improving Grade 7 learners' mathematics performance, underscoring its value in enhancing mathematics education and addressing educational challenges faced by Filipino learners.

Malaysian second language learners are often passive in English language classrooms. Today, not only English is largely used for communication purposes in the physical world, it is extended to the virtual world too. Thus, it is pivotal for educators to enhance students’ tendency and confidence to speak in English. This paper discusses the importance of being able to converse in English, factors which hinder secondary students’ participation during English speaking lessons, and proposes the use of gamification to promote active participation among upper secondary students A pilot study was conducted using qualitative (classroom observation and interview) method, using convenience sampling. Ten upper Malaysian secondary students were selected at random to partake in the one group pre-post test experiment, and random sampling was used to sort them into pairs. Five students were randomly selected for the interview session. Based on the findings of the pilot study, it was observed that the students were more active and engaged in the speaking lesson when gamification was applied. In addition, students responded positively on how gamification has helped them become more engaged during the speaking lesson. By implementing gamification in English speaking lessons, it is seen as effective in enhancing students’ overall engagement during their speaking sessions. The study recommends English language teachers to incorporate gamification in all four language skills (speaking, reading, listening and writing), Grammar and vocabulary during the lessons.

The flipped classroom, a form of blended learning, has gained popularity in higher education due to its potential to improve student engagement and performance. This approach addresses limitations in traditional teaching methods, such as didactic lectures and passive learning methods, by moving content delivery outside class and utilizing in-person sessions for active learning activities. This study aimed to assess the effectiveness of the flipped classroom as a teaching-learning strategy and to gather students’ opinions of the idea. A second-year undergraduate nursing class (n = 96) was split into two groups, one of which used the flipped classroom technique and the other the conventional approach in a quasi-experimental design. Questionnaires on a Likert scale were utilized to assess students’ opinions of the flipped classroom, and pre-and post-test results were evaluated. A variety of statistical analyses were used to compare mean scores and evaluate the efficacy of the flipped classroom, including paired and independent t-tests. A quasi-experimental study involving a second-year undergraduate nursing class showed a statistically significant improvement in student performance and a positive perception of the flipped classroom approach with P<0.001. The flipped classroom in nursing education allows students to learn at their own pace through pre-class work, with an instructor as a facilitator. This personalized approach uses technology like online platforms and collaborative tools to deliver lectures and facilitate in-class activities, potentially improving student engagement, critical thinking, and clinical reasoning abilities.

Over the years, there have been many factors that have influenced the landscape of higher education within the UK. These factors include the rise in tuition fees, the introduction of the Teaching Excellence Framework (TEF) and the formation of Office for Students. Although student performance plays a vital part, another significantly influential key performance indicator that impacts these factors is student experience, which is influenced by positive or negative feedback and engagement. Despite student engagement forming a key part of the learning environment, it is still perceived as one of the weakest aspects when it comes to enhancing the student experience. In this paper, we present the implementation of an innovative, holistic teaching & learning framework for the final year project module trialed within the Department of Engineering and Computing at the University of East London. This project module had been running in different forms since the inception of the undergraduate programmes within the department, however it generally yielded poor and inconsistent evaluation, student experience and engagement. The framework was introduced during the academic year 2015/16, where its evaluation has shown a positive impact on student engagement, performance and experience, compared to the previous year.

This action research investigated the low mastery of competency in the measuring tools, specifically in measuring ingredients using measuring tools, among Grade 9 students at Raniag High School. The goal of the study was to find out why the students weren’t very good at understanding and using heat transfer principles in cooking and to create and put into action an intervention program to help them. The study revealed that the experimental group significantly improved from a mean pre-test score of 4.10 (Beginning) to 7.95 (Proficient), while the control group remained at the Beginning level with a post-test mean of 5.65. With a large effect size (d ≈ 1.5) and higher survey ratings in engagement and instructional support, the intervention proved effective in enhancing students’ mastery and learning experience in food processing. The intervention program, which included better teaching materials and cooking activities that students could do themselves, helped them understand heat transfer principles much better.

The purpose of this study was to investigate the role of homework in enhancing students’ academic performance in Arusha city. The specific objectives were to investigate the extent of homework given to students and its contribution to their academic performance in private primary schools. The study adopted a cross-sectional design and a quantitative approach, collecting data from 48 respondents, including 30 students and 18 teachers, using questionnaires. The tools were validated by experts and pilot tested to ensure reliability. Data were analyzed using descriptive statistics with SPSS, and results were presented in tables and figures. Ethical considerations were observed, and all sources were cited in the Harvard style. The findings indicate that most teachers assign homework daily and students agreed that homework improves their time management and understanding of topics. However, opinions vary on the difficulty of homework tasks. The study concluded that homework is a crucial tool for reinforcing learning and developing essential skills. It was recommended that the government ensure homework aligns with curriculum goals, teachers regularly assess homework tasks and parents provide a supportive environment for homework completion.

ABSTRACTIn contemporary music education, innovative technologies, particularly artificial intelligence (AI)‐based tools, play a crucial role. The objective of this study was to assess the effectiveness of AI‐based tools in enhancing students' success and creativity. The study involved 158 students from a leading music institution, who were divided into control and experimental groups. Methods employed included surveys and testing, along with AI‐based tools: Vocal AI Analyzer and Smart Vocal Coach. The results indicated a significant improvement in vocal skills (from 3.5 to 4.5 in the experimental group) and creativity (from 2.9 to 4.1 in the experimental group) compared with the control group. The AI‐based tools demonstrated high effectiveness, providing individualised instruction and immediate feedback. The practical significance of the research lies in the potential implementation of such technologies in music educational institutions to enhance teaching effectiveness and the development of students' creative abilities.

Global integration of adaptive quizzing in nursing education: Enhancing Student performance and bridging educational gaps: A narrative review.

— Student performance is a crucial factor in higher education institutions, as admission to a high-quality institution often relies on a good academic record. The primary objective of this paper is to predict student performance by considering their personal and academic achievements. By identifying poorly performing students, teachers can offer timely guidance and support to improve their academic outcomes. However, predicting student performance becomes challenging due to the processing of a large amount of data, including both numerical and non-numerical values. This work aims to determine the most effective prediction algorithm and identify the key variables in student data to enhance student performance and success rates through classification techniques using educational databases from both universities and schools. The proposed system leverages this data to predict a student's next year's result (GPA). The dataset used for this experiment is locally obtained from third-year students, encompassing their core subject results (6 subjects, 2 laboratories), and personal details. The methods employed in this work include the Multiple Linear Regression, Naive Bayes and Decision Tree. The extracted factors impacting the results will help students prepare better in advance. The highest accuracy achieved in this prediction is 88.44%, bringing significant benefits to students, teachers, and educational institutions. Keywords— Prediction; Multiple Linear Regression; GPA; Decision Tree; Naive Bayes;

Physical Education (PE) is essential to students’ holistic development, yet it often receives limited attention in school curricula, resulting in reduced engagement and inconsistent performance outcomes. This systematic review examines recent empirical strategies proven to enhance student motivation, participation, and achievement in PE. Guided by PRISMA procedures, a comprehensive search of major academic databases yielded 45 studies published between 2020 and 2023, representing varied educational settings, methodologies, and instructional models. The findings reveal five widely supported approaches that positively influence student outcomes: technology integration and gamification, autonomy-supportive teaching, sport education and peer-teaching models, goal-setting combined with self-monitoring, and culturally responsive instructional practices. Among these, autonomy-supportive pedagogy demonstrated the most consistent effectiveness, contributing to sustained improvements in engagement and perceived competence across grade levels. Technology-based interventions showed particular promise in motivating learners, especially in middle school contexts, though their impact on motor skill development was less robust. The review also identifies methodological limitations in existing research, including small sample sizes, limited longitudinal evidence, and inconsistent measures of performance. Overall, the synthesis underscores the importance of adopting evidence-based and developmentally appropriate PE practices that prioritize meaningful learning experiences. Strengthening teacher professional development, integrating technology thoughtfully, and implementing inclusive instructional models are recommended to further enhance student engagement and performance in PE.

The integration of Artificial Intelligence in education has significantly transformed lesson delivery by fostering increased student engagement, customised learning experiences, and improved performance assessments. This research aims to evaluate the effectiveness of AI-driven teaching methods in enhancing student learning experiences, addressing engagement disparities, facilitating adaptive instruction, and refining performance evaluation. A quasi-experimental research design that incorporated a correlational methodology was employed. A sample size of 1,200 students and teachers was used. These participants were chosen through a stratified random sampling technique, ensuring a representative cross-section of the population to enrich the findings. Data collection methods included structured surveys, standardized academic assessments, and classroom observations. Descriptive and inferential statistical analyses were performed using SPSS, employing t-tests, ANOVA, regression analysis, and Pearson correlation to explore the relationships between AI integration and student outcomes. The findings revealed that the incorporation of AI significantly boosts student engagement, personalised learning, performance assessment, and holistic development. These results align with existing literature on AI-enhanced education while emphasising the necessity for context-specific implementation strategies in Ghana. Furthermore, the study emphasises the importance of policy-driven AI adoption, teacher training initiatives, and infrastructure improvements to fully harness AI's potential in Senior High Schools in Ghana.

The traditional face to face teaching is still a common feature at universities in Sri Lanka. However, several pilot studies conducted previously on web-based learning and interactive computer aided language learning gave ample evidence to the enhancement of student performance. It is popularly believed that the local graduates do not meet the industry expectations as they have had none or less exposure to and interaction with the experts from the industry. Thus the present study was conducted to ascertain whether the student performance as well as the quality of the course modules could be enhanced by integrating web-based learning and online teaching by providing opportunities for industry experts to address and interact with the students online to broaden their horizons and prepare them for future employment.