Assessment Of Student Performance Research Articles

Evaluating Students' Academic Progress in the Role of Fuzzy Logic

This paper explores the role of fuzzy logic in the assessment of student performance in local high school, Badr, Libya, positing that it offers a more flexible and accurate alternative to traditional categorization methods of academic achievement. Conventional assessment tools, such as standardized test scores and GPAs, often yield a distorted and overly simplistic view of student performance. Utilizing a mixed-methods research design, this study compares the performance, attendance, and self-reported satisfaction of students assessed through fuzzy logic with those evaluated by traditional methods. The results demonstrate that students assessed using fuzzy logic achieved higher average scores and expressed greater satisfaction with the assessment process. Additionally, educators employing fuzzy logic provided more detailed and constructive feedback, enriching the learning experience. Thus, this research indicates that fuzzy logic can effectively mitigate the shortcomings of traditional assessment methods, enhancing the recognition of diverse student abilities. The findings advocate for the integration of fuzzy logic in educational assessment practices to promote inclusivity and improved learning outcomes.

Implementation of independent learning campus independent certified internship program for strengthening 21st century skills

Implementation of the Merdeka Belajar Campus Merdeka Certified Internship Program in Strengthening 21st Century Skills is a way to strengthen skills in using media information as well as career and life skills. The aim of this research is to; (1) Describe the implementation of the MBKM certified internship program in universities, (2) Describe the mastery of 21st century skills among students participating in certified internships. This research is qualitative research with an analytical study approach. The results of this research show that first, in the implementation of MBKM, the certified internship program was implemented in three areas of activity, namely marketing, finance and operations, both in banking and companies. In implementing a certified internship, there are several stages, namely conversion of 20 credits, internship activities for 18 weeks, experience in the world of work and the professional world, a series of skills, mentoring, and obtaining a certificate of recognition for the skills and experience gained. Apart from that, during the implementation of the certified internship program there is an evaluation. Evaluation is carried out by following up on reports, providing mentoring, checking recaps of internship activities, sharing lessons, and conducting a final assessment of student performance. Second, the mastery of 21st century skills by students participating in certified internships focuses on the skills of mastering the use of technology, including the use of marketplace applications, the use of Microsoft office applications, the use of e-learning systems, e-commerce, design and so on. Meanwhile, mastery of career abilities and life skills is carried out through strengthening adaptation and social abilities, productivity and accountability, and providing leadership abilities and responsibility

Predictive Analysis of Students’ Learning Performance Using Machine Learning

Several researchers and educational institutions got attracted to the domain of predicting the performance of the students to classify the educational level of student performance. Though the educational sector uses several techniques for extracting useful information about them and the measures to be undertaken in the learning process, it is necessary to develop a student performance assessment model to assist the students as well as faculty members to improve their performance to the next level. This research work majorly concentrates to examine and identify useful rules and patterns to motivate the students for handling their education as well as career in a better way and also to improve the functioning of academics to supervise the policies for students’ benefit. Here, EDM is employed to identify the effective data which helps in applying the active learning in technical applications. Initially, a review of different DM, machine learning (ML), and meta-heuristic models to assess the performance of the students. the proposed models can be employed as an appropriate tool for mining educational data to achieve effective performance assessment of the students.

Effects of Hands-on Laboratory Experiment on Students’ Skills Achievement in Physics in Day Secondary Schools in Rwanda: A Case of Gicumbi District

This research investigated the effect of a hands-on laboratory experiment on students’ skills achievement in physics in day secondary schools in Gicumbi district, Rwanda. Specifically, this research examined the hands-on laboratory practices that affect students’ skills and achievement in physics in day secondary schools in Rwanda, analyze the level of students’ skills achievement in physics that is due to the hands-on laboratory experiment in day secondary schools in Rwanda, and establish the relationship between the hands-on laboratory experiment and students’ skills achievement in physics in day secondary schools in Rwanda. The study adopted a descriptive survey design with a mixed approach. The targeted population of the study consisted of 72 headteachers, 5416 students, and 1750 teachers, making the total population of 7238, selected across Gicumbi district. The researcher used purposive sampling techniques to choose physics teachers and students and simple random sampling to choose schools and headteachers, a descriptive and correlational research design was used in combination with a mixed methodology. Quantitative data were collected using questionnaires, while qualitative data were acquired using interviews. The findings were analyzed through descriptive statistics such as frequency, percentage, mean, and standard deviation, as well as inferential statistics such as correlation and regression analysis. The findings revealed that 72.2% of students felt confident in applying theoretical knowledge to practical experiments, showcasing the effectiveness of structured hands-on practices. However, 67.6% expressed dissatisfaction with the clarity of laboratory activities, indicating a need for improvement. Additionally, 78.1% of students reported increased confidence in performing physics calculations after lab experiments, while 60% felt their understanding of complex concepts could be enhanced through hands-on activities. Furthermore, 75% of students believed practical experiments helped them retain physics concepts better than theory alone, and 87% of teachers agreed that regular exposure to laboratory activities boosts student performance in assessments. Collectively, these findings highlight the need to enhance hands-on laboratory practices to improve student engagement and achievement in physics. The research recommends curriculum developers to create structured hands-on activities aligned with theoretical concepts and incorporate diverse instructional strategies. NESA needs to integrate practical assessments into evaluations, while the Ministry of Education should allocate resources for improving laboratory facilities and provide professional development for teachers.

Redesigned Entrustable Professional Activity (EPA) Assessments Reduce Grade Inflation in the Experiential Setting

ObjectiveThis study aims to evaluate the impact of redesigning an entrustable professional activities (EPAs) assessment tool on the accuracy of student performance assessment within pharmacy education. MethodsThe study used retrospective programmatic data for students on clinical rotations over a 3-year period and compared entrustment levels assigned by preceptors with suggested entrustment levels. This tool was redesigned to separate formative EPA feedback from final grade determination. Data were analyzed using chi-squared tests to identify trends in students ABOVE, AT, or BELOW the suggested entrustment levels. Additionally, to account for intercohort variability, the relationship between students ABOVE the suggested level of entrustment and postgraduate metrics was examined. ResultsAfter the implementation of the revised tool, there was a significant decrease (−3%) in the percentage of students scoring ABOVE the suggested entrustment levels and an increase in the percentage of students scoring AT (+1%) or BELOW (+2%) the suggested entrustment levels. Changes were also observed in individual patient care settings, with a decrease in grade inflation and an increase in accurate assessments. North American Pharmacist Licensure Examination (NAPLEX) pass rates, residency match rates, and grade point average did not correlate with entrustment levels. ConclusionThe redesigned EPA assessment tool demonstrated a decrease in grade inflation resulting in more accurate assessments. The tool’s focus on holistic grading and narrative descriptors contributed to better alignment between preceptor assessment and school-suggested achievement levels. This study suggests that EPA assessments in pharmacy education could benefit from a stronger emphasis on formative feedback and the use of holistic assessment methods for final grade determinations. The findings underscore the potential advantages of considering a separation between EPA scoring and final grades, prompting the Academy to explore their assessment practices to better reflect student performance in clinical experiences.

Machine Learning, Software, Applications, and Websites For Language Instruction

This study aims to examine the latest developments in the application of machine learning, software, applications, and websites in language teaching. With the advancement of technology, language learning is increasingly facilitated by the use of digital tools that utilize artificial intelligence (AI) and machine learning to improve the learning experience in an adaptive and interactive manner. The study reviewed a variety of platforms that use this technology, including key features that support personalization, automated feedback, and student performance assessments. In addition, this study discusses the effectiveness of the technology in supporting independent and formal learning in the classroom, including implementation challenges in various educational settings. It was found that although this technology provides a great opportunity in accelerating language learning, there are some limitations, such as limited access in regions with low digital infrastructure, as well as lack of integration with relevant cultural and social contexts in language learning. This study concludes that machine learning-based technology in language teaching has great potential, but further research is needed to optimize its application in various educational contexts.

A smart system for student performance assessment (SPA)

The proposed smart system for Student Performance Assessment (SPA) is a system that evaluates students' knowledge and skill attainment in a specific course by measuring their achievements of the Course Learning Outcomes (CLOs). The instructor defines the aspects, weights, and rating scale used by SPA to analyze each course. The system calculates the average of students' marks in each learning outcome and compares them with the CLO targets and scores to determine the effectiveness of the teaching and learning methods used. The system uses facts and rules extracted from the course syllabus and Bloom's Taxonomy to build its knowledge base. This paper presents the development of the SPA inference engine, which is used to find CLO targets based on the course level. The inference engine uses efficient procedures and a prediction process to determine the correct target and score, providing a reliable and understandable methodology for reasoning about the information in the knowledge base and formulating conclusions. SPA is a highly responsive and intelligent system that can be a valuable tool for measuring students' achievements. Its characteristics include high performance, reliability, and intelligibility, and its combination of cognitive systems and cognitive theory has led to remarkable progress in measuring student performance. Limitations include dependency on accurate course content and initial setup time, potential bias in CLO weight assignments, challenges in integrating SPA with existing institutional databases, the need for continuous updates to the knowledge base to reflect curriculum changes, and potential resistance from educators to adopt new technologies. Future improvements could involve adaptive learning integrations, enhanced user interfaces, and broader applicability across diverse educational settings.

Teaching a New Obturation Technique in Preclinical Endodontic Training: Assessment of Student Learning Experience, Performance, and Self-Evaluation

IntroductionThis study investigated the impact of implementing hydraulic condensation (HC) as a second obturation technique in the Endodontic Preclinical course for dental students trained in warm vertical compaction (WVC). MethodsA total of 70 students performed root canal treatment of 2 extracted molars; they performed the HC technique for the first time after a demonstration. The combination of the obturation technique (WVC or HC) and the type of molar (maxillary or mandibular) was randomly assigned, resulting in 4 groups (n = 35). The students answered a questionnaire appraising their learning experience and completed a self-evaluation rubric. Masked instructors graded projects. Data were statistically analyzed (significance set at 5%). ResultsMost of the students (91%) considered learning 2 obturation techniques relevant and considered it difficult to perform the downpack in molars (P < .05). About half of the students (45.7%) responded that HC resulted in fewer errors and disagreed that WVC derives in a more homogeneous obturation; accordingly, 52.9% of the students selected the highest self-grading for HC obturations, while only 38.6% for WVC. No significant difference was found in the distribution of grades attributed by students and instructors (P > .05). Students reported significantly higher levels of confidence for HC and difficulty for WVC (P < .05). No difference was found between the techniques regarding the presence of voids. The presence of multiple errors was more frequent for WVC (P < .05). ConclusionThe findings indicate a positive learning experience and comparable performance among preclinical dental students in implementing HC as an alternative obturation technique.

Computer Allied Intelligence in the Education Resource-Sharing Based inContract Deep Learning

A resource-sharing platform is an online space where individuals or organizations can exchange or access various resources, such as knowledge, skills, tools, or assets. These platforms facilitate collaboration and cooperation among users by providing a centralized hub for sharing resources efficiently. In university higher education, a resource-sharing platform serves as a vital tool for students, faculty, and staff to optimize access to a wide array of educational resources. These platforms enable the sharing of academic materials, such as textbooks, lecture notes, and research papers, fostering collaborative learning environments. This paper proposed the proposed method of Distributed Consensus Blockchain Deep Learning (dCBDL) for a resource-sharing deep learning platform in higher education aims to revolutionize collaborative learning and resource utilization. Initially, the dCBDL model uses a blockchain network that serves as the underlying infrastructure for the platform. This blockchain will store transaction records, verify the authenticity of shared resources, and ensure data integrity and immutability. The proposed model uses smart contracts and decentralized storage with a consensus mechanism for data processing in higher education. Finally, the proposed dCBDL model uses the deep learning model for the classification and assessment of student performance in higher education. The proposed model achieves a classification accuracy of 98% which is significantly higher than the conventional techniques such as blockchain architecture and SVM and LSTM classifiers.

Integration of Project-Based STEM Learning in the Meliuk Menerjang Material within the Emancipated Curriculum

This study aims to develop a project-based STEM (Science, Technology, Engineering, and Mathematics) learning tool for the "Meliuk Menerjang" material in the Emancipated Curriculum for grade IV students in Indonesian elementary schools. The objective is to create a tool that is feasible, practical, and effective in improving student learning outcomes. The research employs a Research and Development (R&amp;D) approach, specifically following the ADDIE (Analysis, Design, Development, Implementation, Evaluation) model. Data was collected through validation from material and design experts, questionnaires, and student performance assessments. The study included 25 students and 20 teachers from various elementary schools in Malang City to identify the needs and effectiveness of the project-based STEM learning model. Data analysis was performed using SPSS for effectiveness analysis and qualitative analysis for feedback and validation results. Findings: The project-based STEM learning model demonstrated high feasibility with significant improvements in students' understanding and skills. Validation results showed that the content was relevant and supportive of STEM skill development. Both teachers and students positively accepted the learning model, indicating increased confidence and motivation. Conclusion: Integrating project-based STEM learning in the Emancipated Curriculum positively impacts student engagement, motivation, and learning outcomes. This approach fosters critical thinking, creativity, and teamwork among elementary students, preparing them for future technological challenges.

The impact of the COVID-19 pandemic on higher education: Assessment of student performance in computer science.

The COVID-19 pandemic had radically changed higher education. The sudden transition to online teaching and learning exposed, however, some benefits by enhancing educational flexibility and digitization. The long-term effects of these changes are currently unknown, but a key question concerns their effect on student learning outcomes. This study aims to analyze the impact of the emergence of new models and teaching approaches on the academic performance of Computer Science students in the years 2019-2023. The COVID-19 pandemic created a natural experiment for comparisons in performance during in-person versus synchronous online and hybrid learning mode. We tracked changes in student achievements across the first two years of their engineering studies, using both basic (descriptive statistics, t-Student tests, Mann-Whitney test) and advanced statistical methods (Analysis of variance). The inquiry was conducted on 787 students of the Lublin University of Technology (Poland). Our findings indicated that first semester student scores were significantly higher when taught through online (13.77±2.77) and hybrid (13.7±2.86) approaches than through traditional in-person means as practiced before the pandemic (11.37±3.9, p-value < 0.05). Conversely, third semester student scores were significantly lower when taught through online (12.01±3.14) and hybrid (12.04±3.19) approaches than through traditional in-person means, after the pandemic (13.23±3.01, p-value < 0.05). However, the difference did not exceed 10% of a total score of 20 points. With regard to the statistical data, most of the questions were assessed as being difficult or appropriate, with adequate discrimination index, regardless of the learning mode. Based on the results, we conclude that we did not find clear evidence that pandemic disruption and online learning caused knowledge deficiencies. This critical situation increased students' academic motivation. Moreover, we conclude that we have developed an effective digital platform for teaching and learning, as well as for a secure and fair student learning outcomes assessment.

Assessing Student Performance Through Pupil Dilation and Problem-Solving Time in Augmented Reality

Assessing Student Performance Through Pupil Dilation and Problem-Solving Time in Augmented Reality

PENILAIAN KINERJA (PERFORMANCE ASSESSMENT) PESERTA DIDIK DALAM PRAKTIKUM MATERI LARUTAN PENYANGGA (BUFFER)

This research aimed at knowing the students' performance ability in conducting chemistry practicum using performance assessment instruments. Questionnaires and student psychomotor observation sheets on buffer solution material were used for collecting the data, the observation sheet has indicators: 1) preparing preparations before doing the practicum, 2) skills in preparing tools and materials, 3) skills in conducting experiments in accordance with the practicum guide, 4) skills in using tools and taking materials, 5) drawing skills or recording the results of practical observations, 6) ability in creating, taking initiative. This research was conducted at Vocational High Schools of Ikasari Pharmacy and Abdurab Pekanbaru. This research used a qualitative descriptive. The population in this research were students at Vocational High Schools of Ikasari Pharmacy and Abdurab Pekanbaru with samples 61 students that were selected using a purposive sampling technique. The assessment results of the performance indicators in preparing preparations before conducting the practicum was 95.49%, skills in preparing tools and materials were 85.04%, skills in conducting experiments in accordance with the practicum guide was 88.66%, skills in using tools and taking materials were 93.03%, skills in drawing or recording the results of practical observations was 88.93% and the ability in creating, taking initiative were 88.17%, Overall the mean scores of the results students’ performance assessment in practicum the buffer solution material were 89.88%. Based on these results, it could be concluded that the student performance assessment observation sheet was in very good category in measuring students' psychomotor abilities on the main topic of buffer solutions. Keywords: Performance Assessment Instrument, Psychomotor Ability, Buffer Solution

Automated English Teaching System Through Deep Belief Network for Human-Computer Interaction Experience

This paper presented the integration of Human-Computer Interaction (HCI) with the Automated Teaching Belief Network (ATBN) to enhance automated English teaching experiences. The proposed ATBN model implemented the Deep Belief Network for the estimation of the factors related to the HCI to promote the experience of the users. The ATBN model uses the deep learning model for the classification in English Teaching. Through the capabilities of deep learning and HCI principles, the ATBN system offers personalized and adaptive learning experiences tailored to individual student needs. The proposed ATBN model estimates the features in English teaching to improve the performance of the Students through HCI model. Simulation analysis expressed that proposed ATBN model improves the pre-test and post-test score by +15 for the English Teaching. The classification values are achieved with accuracy value of 94.8% with minimal loss of 0.12. The assessment of student performance through pre-test and post-test score is improved by 15 for the beginner, intermediate and advanced level. The findings expressed that proposed ATBN model achieves the higher teaching test performance for the HCI language level through the belief network those significantly improves the user experience.

Assessment of Soccer Teaching Ability Based on Deep Learning Algorithm

Soccer teaching involves imparting fundamental skills, tactics, and strategies related to the sport of soccer. Coaches and instructors focus on teaching players proper techniques for dribbling, passing, shooting, and defending, while also emphasizing teamwork, sportsmanship, and game awareness. Soccer teaching sessions typically include a combination of drills, scrimmages, and tactical discussions tailored to the age and skill level of the players. This paper proposed an effective soccer assessment technique for teaching ability with the Automated Probabilistic Deep Learning (APDL) model. The proposed APDL model comprises an automated model for the assessment of student performance. The proposed APDL model processes the input soccer images with the pre-processing of the features. With APDL model uses the probabilistic computation features for the computation of the variables in the soccer data. With the extraction of the features, the maximum likelihood is computed for the classification with the deep learning model features. The APDL model implements the classification-based deep learning model features with the examination of soccer teaching, instruction, development of skill, and players. Simulation results demonstrated that prediction with the APDL model estimates the probability of prediction as 0.91 with an estimated uncertainty value of 0.08. In the case of teaching and coaching assessment, the uncertainty is stated as 0.08 for both with the prediction assessment score of 0.92. The classification accuracy of the proposed APDL model is achieved as 0.95 with the precision value of 0.97. The findings of this research contribute to the advancement of coaching methodologies in soccer, providing coaches and educators with valuable insights into their teaching effectiveness and areas for improvement. Additionally, the automated nature of the APDL model offers scalability and efficiency in assessing coaching performance, paving the way for enhanced coaching practices and player development in soccer.

Tanfiż Istirātījiyyah Majmū’ah al-Tahqīq litarqiyah al-Mahārāt al-Lugawiyyah liṭullāb al-Madrasah al-Ṡānawiyyah

This research aims to evaluate the effectiveness of Group Investigation strategies to teach language skills to Class 7 students at Nurul Mujtahidin School. The study employs Classroom Action Research (CAR) methodology, consisting of cyclical planning, acting, observing, and reflecting processes. The research design includes multiple cycles to ensure continuous improvement and adaptation of teaching strategies. Data were collected from classroom observations, student performance assessments, and interviews with students and teachers. The data collection techniques involved direct observation, structured interviews, and analysis of student work. Data analysis was performed using qualitative and quantitative methods to provide a comprehensive understanding of the impact of Group Investigation strategies. The results indicate that these strategies significantly enhance students' language skills, engagement, and collaborative learning abilities. The study concludes that Group Investigation is effective and innovative. The results of this study are: 1) The teaching of language skills using Group Investigation strategies can develop students' enthusiasm by seeing their enthusiasm for learning and coming to school on time. 2) The teaching of language skills using Group Investigation strategies can develop student grades by looking at the number of students 15, the highest score of 100, the standard value of 75, which is included in the standard score of 15, and the overall average score of 84. Based on the results of this study, the authors suggest that principals, curriculum sections, and teachers pay more attention to the factors that encourage students to improve their Arabic language skills. And to the eighth grade to further increase their enthusiasm for learning Arabic.

Assessment strategies and challenges of teachers in evaluating students during online learning

Education was forced to modify face-to-face classes into three pedagogical approaches: synchronous, asynchronous, and blended learning, requiring teachers to change the grading system, assessment, and evaluation of student performance. This study aimed to determine the assessment tools, strategies, and challenges that teachers encounter during online learning. The researchers conducted an online and face-to-face survey that consisted of 75 questions to 50 online teachers who were selected through convenience sampling from seven public and private elementary schools. Findings indicate that most teachers apply traditional assessment strategies to evaluate students in online learning. Some online assessment applications like Edpuzzle, Google Classroom, Kahoot, and Quizzes are rarely used to assess student learning. Teachers, however, frequently utilized Facebook and Messenger in delivering assessments. They applied multiple assessment strategies in online learning to accommodate the learning styles of their students. However, data revealed that most teachers have difficulty ensuring the quality of participation, integrating authentic assessment into online learning, and using online assessment applications. It is recommended for teachers to provide their students with balanced assessment, timely communication, constructive feedback, group multimedia projects, appropriate instructional materials, and alternative online tools to enable meaningful learning.

Investigating the Higher Education Students' Perception of an Interactive Virtual Processing Station Application

This study aims to evaluate the Virtual Processing Station as a simulation-based learning medium in the context of engineering education, based on student perceptions. Student perceptions of this medium were evaluated based on four main aspects: relevance, attention, interest, and usefulness. This study involved 30 students from the Department of Electrical Engineering Education at Yogyakarta State University who had used the Virtual Processing Station in laboratory practice sessions. Data were collected through a questionnaire with 17 statements using a Likert scale and supplemented with qualitative feedback from respondents. The results showed that this learning medium was very well received by students, with an average rating of 90.59%. The relevance aspect received the highest score (92.92%), followed by the interest aspect (90.83%) and usefulness (90.56%). Although the attention aspect received a slightly lower score (84.72%), the medium was still considered quite effective in capturing students' attention during the learning process. Positive comments from respondents emphasized the effectiveness of this medium in helping students understand both the practical and theoretical concepts of PLC-based industrial automation systems. The conclusion of this study indicates that the Virtual Processing Station has great potential in supporting more interactive and efficient engineering learning. However, there is still room for improvement in areas such as the user interface and visualization. Future research should focus on assessing the short-term and long-term impacts of this medium, particularly through larger sample sizes and objective assessments of student performance before and after using the Virtual Processing Station. This approach will provide deeper insights into how these medium influences learning outcomes and the development of practical skills in engineering education.

A digital pen-based writing state recognition algorithm for student performance assessment

A digital pen-based writing state recognition algorithm for student performance assessment

Penerapan Metode Kooperatif Tipe Learning Together Untuk Meningkatkan Hasil Belajar Seni Budaya di SMAN 8 Denpasar

After conducting initial observations at SMK Negeri 8 Denpasar, it was discovered that the students' learning outcomes in cultural arts subjects were relatively low. Therefore, the researcher decided to conduct further study using the PTK (Classroom Action Research) approach method. The aim of implementing the PTK method was to enhance students' understanding of the cultural arts subject through a cooperative learning model known as "learning together," with the goal of improving student learning outcomes. The PTK method involved 2 cycles, with each cycle consisting of 4 stages. The research subjects were the 35 students of class XII Mipa-4 at SMA Negeri 8 Denpasar. Data was collected using performance assessment and observation methods. The collected data was analyzed using a qualitative descriptive method, which aimed to examine the entire cultural arts learning process. Additionally, a qualitative method was applied to analyze the results of the assessment of student performance by comparing the average value of the completeness of learning outcomes. Following the analysis, it was observed that in cycle I, the highest and lowest scores for students of SMA Negeri 8 Denpasar class XII Mipa-4 were 85 and 60, respectively, with a class average score of 71. However, in cycle II, the highest and lowest scores increased to 95 and 80, and the class average score rose to 88. Furthermore, in cycle II, all students achieved scores above the minimum completeness level. This indicated a significant improvement in student scores from cycle I to cycle II.