Evaluation Of Student Performance Research Articles

Student's Performance Evaluation Using Ensemble Machine Learning Algorithms

Student's Performance Evaluation Using Ensemble Machine Learning Algorithms

A Bibliometric Analysis of Online Assessment Platforms in English as a Foreign Language (EFL) Classrooms

This study presents a bibliometric analysis of research on online assessment platforms in English as a Foreign Language (EFL) classrooms, with a focus on Indonesian educational contexts from 2018 to 2022. The analysis highlights the growing recognition of digital tools in enhancing student assessment and learning outcomes. The findings reveal a significant increase in the number of publications on online assessment tools, reflecting the shift toward technology-driven education, especially during the COVID-19 pandemic. Quantitative research methods are predominantly used, emphasizing the objective evaluation of student performance through standardized tests, such as the Cornell Critical Thinking Test (CCTT). However, a noticeable gap exists in qualitative research, which could provide deeper insights into the contextual factors affecting the effectiveness of these tools. Additionally, the study identifies concerns regarding the transparency of data collection instruments, particularly their validity and reliability. The study concludes that while quantitative approaches dominate the field, there is a need for more balanced research methodologies and rigorous validation of assessment tools to ensure credible and comprehensive insights into the role of online assessments in EFL education.

Developing valid assessments in the era of generative artificial intelligence

Generative Artificial Intelligence (GAI) holds tremendous potential to transform the field of education because GAI models can consider context and therefore can be trained to deliver quick and meaningful evaluation of student learning outcomes. However, current versions of GAI tools have considerable limitations, such as social biases often inherent in the data sets used to train the models. Moreover, the GAI revolution comes during a period of moving away from memorization-based education systems toward supporting learners in developing the ability to apply knowledge and skills to solve real-world problems and explain real-world phenomena. A challenge in using GAI tools for scoring assessments aimed at fostering knowledge application is ensuring that these algorithms are scoring the same construct attributes (e.g., knowledge and skills) as a trained human scorer would score when evaluating student performance. Similarly, if using GAI tools to develop assessments, one needs to ensure that the goals of GAI-generated assessments are aligned with the vision and performance expectations of the learning environments for which these assessments are developed. Currently, no guidelines have been identified for assessing the validity of AI-based assessments and assessment results. This paper represents a conceptual analysis of issues related to developing and validating GAI-based assessments and assessment results to guide the learning process. Our primary focus is to investigate how to meaningfully leverage capabilities of GAI for developing assessments. We propose ways to evaluate the validity evidence of GAI-produced assessments and assessment scores based on existing validation approaches. We discuss future research avenues aimed at establishing guidelines and methodologies for assessing the validity of AI-based assessments and assessment results. We ground our discussion in the theory of validity outlined in the Standards for Educational and Psychological Testing by the American Educational Research Association and discuss how we envision building on the standards for establishing the validity of inferences made from the test scores in the context of GAI-based assessments.

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.

Adjectives in the Summary Paragraph of the MSPE: Are They Telling Us Something?

Rationale and ObjectivesMany US medical schools do not provide a summative, comparative assessment of students (class rank), instead utilizing descriptive adjectives in the summary paragraph of the Medical Student Performance Evaluation (MSPE). The objective of this study was to determine whether those adjectives correlate with student performance. Materials and MethodsApplications from all US allopathic medical schools received by a single diagnostic radiology program in the 2023-24 cycle were reviewed. The final adjectives from schools that rank students were coded as positive, negative, or neutral. For students from non-ranking schools, descriptive adjectives from the MSPE summary paragraphs were extracted and categorized based on the final adjective coding schema along with a library of commonly used positive adjectives. The frequency of adjectives was correlated with applicant academic and demographic factors using multivariable logistic regression. ResultsApplications from 97% (147/151) of US allopathic medical schools were received. 60.5% (89/147) of schools rank their students with 27.9% (41/147) using a final adjective coded to performance tier. Of the 58 non-ranking schools, 56.9% (33/58) used descriptive adjectives in the MSPE’s summary paragraph. There was no association with academic performance metrics and either generally positive adjectives or coded descriptive adjectives. There was a greater association with positive descriptive adjectives for non-white applicants (p=0.011) and generally positive adjectives for higher ranked schools (p=0.004). ConclusionUndefined descriptive adjectives in the MSPE’s summary paragraph, when benchmarked to final adjectives, do not correlate with academic performance, and may instead be used for student advocacy by medical school deans.

Artificial intelligence: Reducing inconsistency in the surgical residency application review process

The incorporation of artificial intelligence (AI) into the general surgery residency recruitment process holds great promise for overcoming limitations inherent to traditional application review methods. This study assesses the consistency of AI, particularly ChatGPT, in evaluating medical student performance evaluation (MSPE) letters in comparison to experienced human reviewers. While the results suggest that ChatGPT demonstrates greater consistency in grading than human reviewers, AI still has its limitations. This underscores the necessity for careful refinement and consideration in its implementation. While AI presents opportunities to enhance residency selection procedures, further research is imperative to fully grasp its capabilities and implications.

Manajemen Peserta Didik Sekolah Dasar (Studi Multi Situs pada SDN Paringin Selatan 1 dan SD IT Darul Fikri Kabupaten Balangan)

The aim of this research is to describe student management including student admission planning, student development and student evaluation at SDN Paringin Selatan 1 and SD IT Darul Fikri, Balangan Regency. This research is qualitative research in the form of case studies at 2 sites, namely SDN Paringin Selatan 1 and SD IT Darul Fikri. The research data sources are school principals and teachers. Data collection was carried out through interviews, observation and documentation and then analyzed using within-site data analysis, individual site analysis and cross-case data analysis. Checking the validity of the data was carried out by source triangulation. The research results from 2 research sites illustrate that student admission planning includes stages starting from analyzing student needs, such as planning the number of students who will be accepted, forming a new student admissions committee and holding promotions and outreach, implementing the School Environment Introduction Period (MPLS). Developing students by creating a comfortable and conducive learning atmosphere, integrating the general curriculum with character and religious education values. Organizing extracurricular activities as a means of channeling students' talents and potential. Student evaluations, attitude competency evaluations, knowledge competency and skill competency evaluations are all contained in evaluation reports in the form of student report cards, remedial implementation and teacher performance evaluations. The conclusion of this research is that student recruitment planning includes: analysis of student needs, student recruitment planning, student selection, student orientation and reporting of new student data. Student development includes coaching in the learning process, coaching in extracurricular activities and coaching students in discipline. Student evaluation includes the development of children's knowledge, reports on children's learning outcomes, remedial activities and evaluation of teacher performance. Keywords: Elementary School Students, Management olah Dasar

Exploring the Relationship of Cognitive and Motivational Factors to Sonography Student Performance

Objectives: The purpose of this mixed-methods study was to explore the cognitive and motivational challenges sonography students encounter by examining the relationships between sonography students’ levels of self-regulation and self-efficacy and their performance in a 16-week introductory vascular sonography skills laboratory course. Materials and Methods: Measures for the study were designed to yield qualitative and quantitative data related to student goals, strategies, and course performance and were generated by both students and faculty. Qualitative data from the study included student self-reports of self-regulatory strategies and instructor evaluations of student performance, while quantitative data were provided by instructor and student ratings of performance, student self-efficacy ratings, and student reports on their use of deliberate practice. Results: The data showed that many students learning how to perform sonographic examinations encountered motivational challenges that appeared to be tied both to their self-efficacy and their ability to effectively use self-regulatory activities. Conclusion: The findings of this study suggest possibilities for improving sonography’s curricular models and teaching strategies toward the goal of making sonography instruction more efficient and effective.

Analyzing Test Performance of BSIT Students and Question Quality: A Study on Item Difficulty Index and Item Discrimination Index for Test Question Improvement

This study presents a comprehensive assessment of the test performance of Bachelor of Science in Information Technology (BSIT) students in the System Integration and Architecture (SIA) course, coupled with a meticulous examination of the quality of test questions, aiming to lay the groundwork for enhancing the assessment tool. Employing a cross-sectional research design, the study involved 200 fourth-year students enrolled in the course. The results illuminated a significant discrepancy in scores between upper and lower student cohorts, highlighting the necessity for targeted interventions, curriculum enhancements, and assessment refinements, particularly for those in the lower-performing group. Further examination of the item difficulty index of the assessment tool unveiled the need to fine-tune certain items to better suit a broader spectrum of students. Nevertheless, the majority of items were deemed adequately aligned with their respective difficulty levels. Additionally, an analysis of the item discrimination index identified 25 items suitable for retention, while 27 items warranted revision, and 3 items were suitable for removal, as per the analysis outcomes. These insights provide a valuable foundation for improving the assessment tool, thereby optimizing its capacity to evaluate students' acquired knowledge effectively. The study's novel contribution lies in its integration of both student performance assessment and evaluation of assessment tool quality within the BSIT program, offering actionable insights for improving educational outcomes. By identifying challenges faced by BSIT students and proposing targeted interventions, curriculum enhancements, and assessment refinements, the research advances our understanding of effective assessment practices. Furthermore, the detailed analysis of item difficulty and discrimination indices offers practical guidance for enhancing the reliability and validity of assessment tools in the BSIT program. Overall, this research contributes to the existing body of knowledge by providing empirical evidence and actionable recommendations tailored to the needs of BSIT students, promoting educational quality and student success in Information Technology.

Impact of activity-based learning on understanding linear and quadratic functions: An evaluation of student performance and satisfaction in a Thai high school

Linear and quadratic functions are crucial topics in math education, and there is a significant focus on using activity-based learning (ABL) to teach these subjects. However, previous research has shown gaps, especially in how this approach affects high school students' learning outcomes. Most studies focus only on test scores and do not consider students' satisfaction or apply these methods to other math topics. This study aimed to assess the impact of ABL on the academic performance and satisfaction of 11th-grade students with linear and quadratic functions. The research was conducted in a Thai public school with 38 participants, using various tools like an ABL curriculum, skills assessments, achievement tests, and a satisfaction survey. The findings clearly showed that ABL improves students' understanding and problem-solving skills in complex math topics like linear and quadratic functions. This study provides solid evidence that ABL is effective in high school math, suggesting it could improve students' overall learning experiences and outcomes.

The Urgent Need for Reporting Accurate and Fair Student Comparisons in the Medical Student Performance Evaluation.

The Urgent Need for Reporting Accurate and Fair Student Comparisons in the Medical Student Performance Evaluation.

Improved Decision Support System for College Sports Training Based on Id3 Algorithm

A Decision Support System (DSS) is a computer-based tool designed to assist individuals and organizations in making informed decisions. It utilizes data analysis, modeling techniques, and interactive interfaces to provide users with relevant information and insights. DSSs help streamline decision-making processes by synthesizing large amounts of data from various sources, generating forecasts, and evaluating alternative courses of action. They are particularly valuable in complex and uncertain situations where decisions have significant implications. DSSs can be used in a wide range of domains, including business, healthcare, finance, and logistics, to support strategic, tactical, and operational decision-making processes. This paper introduces an Integrated Hybrid Feature Subset Decision Support System (HFS-DSS) designed to optimize decision-making processes in student performance evaluation within educational institutions. The HFS-DSS combines feature subset selection techniques with decision support algorithms to identify key attributes and make accurate predictions regarding student performance. Through experimental evaluation, the system demonstrates its effectiveness in accurately assessing student performance based on selected features, with predictions closely aligning with actual observations. The results underscore the system's reliability and effectiveness in supporting informed decision-making processes, offering valuable insights for educators and administrators to enhance academic outcomes. The adaptability and versatility of the HFS-DSS make it well-suited for various educational contexts, providing potential applications in curriculum planning, student support services, and performance monitoring. The present paper highlights the significant contributions of the Integrated HFS-DSS towards enhancing decision-making processes and improving academic outcomes in educational institutions.

Optimization and Application of English Word Memory Algorithm Based on Reinforcement Learning

The optimization and application of an English word memory algorithm based on reinforcement learning involve refining a system that utilizes reinforcement learning techniques to enhance vocabulary retention. By leveraging reinforcement learning, the algorithm can adapt its strategies for presenting and reviewing English words based on users' responses and performance. This adaptive approach enables personalized and effective learning experiences, wherein the algorithm adjusts the frequency and timing of word repetitions to maximize memorization efficiency. Applications of this optimized algorithm span language learning platforms, educational apps, and personalized tutoring systems, offering learners tailored support to strengthen their English vocabulary acquisition and retention skills. This paper introduces the Spider Swarm Optimized English Word Memory Algorithm (SSOEWMA) algorithm, a novel approach aimed at optimizing language processing and learning tasks. Leveraging principles of reinforcement learning and swarm intelligence, SSOEWMA demonstrates its effectiveness in enhancing various aspects of language processing, including word difficulty assessment, sentence estimation, memory retention, and student performance evaluation. Through a series of experiments and evaluations, we showcase SSOEWMA ability to optimize dataset attributes, accurately estimate sentence characteristics, and improve memory retention performance. Simulation results achieved an average word recall accuracy of 85% across multiple evaluations. Through its utilization of reinforcement learning principles and swarm intelligence, SSOEWMA significantly improved memory retention performance, reducing recall latency by an average of 20% compared to baseline measures. Additionally, the algorithm demonstrated strong learning efficiency, converging to optimal solutions with a speed increase of 30% compared to traditional methods.

The Role of Artificial Intelligence in Medical Education: A Systematic Review.

To examine the artificial intelligence (AI) tools currently being studied in modern medical education, and critically evaluate the level of validation and the quality of evidence presented in each individual study. This review (PROSPERO ID: CRD42023410752) was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement. A database search was conducted using PubMed, Embase, and Cochrane Library. Articles written in the English language between 2000 and March 2023 were reviewed retrospectively using the MeSH Terms "AI" and "medical education" A total of 4642 potentially relevant studies were found. After a thorough screening process, 36 studies were included in the final analysis. These studies consisted of 26 quantitative studies and 10 studies investigated the development and validation of AI tools. When examining the results of studies in which Support vector machines (SVMs) were employed, it has demonstrated high accuracy in assessing students' experiences, diagnosing acute abdominal pain, classifying skilled and novice participants, and evaluating surgical training levels. Particularly in the comparison of surgical skill levels, it has achieved an accuracy rate of over 92%. AI tools demonstrated effectiveness in improving practical skills, diagnosing diseases, and evaluating student performance. However, further research with rigorous validation is required to identify the most effective AI tools for medical education.

Development and psychometric evaluation of a 360-degree evaluation instrument to assess medical students’ performance in clinical settings at the emergency medicine department in Iran: a methodological study

In the Iranian context, no 360-degree evaluation tool has been developed to assess the performance of prehospital medical emergency students in clinical settings. This article describes the development of a 360-degree evaluation tool and presents its first psychometric evaluation. There were 2 steps in this study: step 1 involved developing the instrument (i.e., generating the items) and step 2 constituted the psychometric evaluation of the instrument. We performed exploratory and confirmatory factor analyses and also evaluated the instrument’s face, content, and convergent validity and reliability. The instrument contains 55 items across 6 domains, including leadership, management, and teamwork (19 items), consciousness and responsiveness (14 items), clinical and interpersonal communication skills (8 items), integrity (7 items), knowledge and accountability (4 items), and loyalty and transparency (3 items). The instrument was confirmed to be a valid measure, as the 6 domains had eigenvalues over Kaiser’s criterion of 1 and in combination explained 60.1% of the variance (Bartlett’s test of sphericity [1,485]=19,867.99, P<0.01). Furthermore, this study provided evidence for the instrument’s convergent validity and internal consistency (α=0.98), suggesting its suitability for assessing student performance. We found good evidence for the validity and reliability of the instrument. Our instrument can be used to make future evaluations of student performance in the clinical setting more structured, transparent, informative, and comparable.

Emotional Intelligence, Perceived Stress and Life Quality Assessment Among Dental Students.

The capacity to grasp and recognize one's own and human feelings, use cognitive awareness to control actions and behavior, and modify moods in response to difficult situations is known as emotional intelligence (EI). Perceived stress has been linked to higher levels of depression among healthcare students. This study set out to assess EI, perceived stress (PS), and life quality assessment (LQA) among dental undergraduates and to ascertain how these factors are linked to one another. The self-reported cross-sectional research was organized among preclinical and clinical years of dental students to examine their emotional intelligence and stress-coping capacity. About 146 students participated in the study, with ages ranging from 19 to 25, irrespective of gender. The students were given the Schutte Emotional Intelligence and Perceived Stress Scale tools (PSS10) by Cohen, and with World Health Organization Quality of Life (WHOQOL-BREF) tool examined the characteristics that contribute to life quality among students. The study included 146 individuals, 38 males (26.02%) and 108 females (73.97%), with an unresponsiveness rate of 2.66%. The correlation revealed statistically high significance among emotional intelligence and perceived stress (P = 0.000), perceived stress and life quality (P = 0.02), and emotional intelligence and life quality (P = 0.008). The statistical analysis of the influence of EI, PS, and LQA on academic year-wise analysis determined non-significant (P > 0.05). Due to the time constraints of their job, dentistry training may be highly stressful, yet regular evaluations of student performance and the accompanying factors would help us to understand how students behave in challenging circumstances.

Analysis of variability and trends in medical school clerkship grades

BackgroundMedical school clerkship grades are used to evaluate orthopedic surgery residency applicants, however, high interinstitutional variability in grade distribution calls into question the utility of clerkship grades when evaluating applicants from different medical schools. This study aims to evaluate the variability in grade distribution among medical schools and look for trends in grade distribution over recent years. MethodsApplications submitted to Rush University's orthopedic surgery residency program from 2015, 2019, and 2022 were collected from the Electronic Residency Application Service. Applications from the top 100 schools according to the 2023–2024 U.S. News and World Report Research Rankings were reviewed. The percentage of “honors” grades awarded by medical schools for the surgery and internal medicine clerkships were extracted from applicants' Medical Student Performance Evaluation letters. ResultsThe median percentage of honors given in 2022 was 36.0 % (range 10.0–82.0) for the surgery clerkship and 33.0 % (range 6.7–80.0) for the internal medicine clerkship. Honors were given 6.6 % more in the surgery clerkship in 2022 compared to 2015. There was a negative correlation between a higher (worse) U.S. News and World Report research ranking and the percentage of honors awarded in 2022 for the surgery and internal medicine clerkships. ConclusionThere is substantial interinstitutional variability in the rate that medical schools award an “honors” grade with evidence of grade inflation in the surgery clerkship. Residency programs using clerkship grades to compare applicants should do so cautiously provided the variability demonstrated in this study.

Implementation of an early alert system in quizzes of a high complexity subject in higher education: Improvement of student performance and teacher perception

AbstractEarly Alert Systems (EAS) play a fundamental role in education by supporting the learning process and evaluating student performance. In this study, an innovative EAS designed to specifically identify weaknesses in Cognitive Skills (CS) in first-year higher education students is presented, focusing on a challenging course at a South American university. Through big data technology, approval rates linked to various cognitive skills were evaluated using quizzes. Subsequently, teachers, after analysis and dialogue, applied adapted strategies to strengthen these skills in their classes, which were evaluated in subsequent exams. The sample under study included 1,691 students from various health majors enrolled in a complex subject. The experimental group (994 students) that participated in the EAS was compared with a control group (697 students). Evaluations validated by the academic team were used, applying three quizzes throughout the 2022-20 academic period, and the results were analysed with the Power BI computer tool, generating online reports that highlighted CS by section. The EAS, based on teacher surveys, is innovative and it also positively impacts student achievement, evidenced in overall approval rates, by teacher and section. In addition to promoting collaboration among professors, it also improves the teaching quality and suggests a positive impact on the learning of complex subjects in Higher Education Institutions (HEIs). This comprehensive approach to early monitoring of student performance shows promise for the ongoing improvement of educational quality.

Attitudes of Greek Foreign Language Teachers Regarding the Role of Authentic Assessment in Foreign Language Teaching

The evaluation of student performance, which is closely tied to all school functions and is a fundamental responsibility of teachers in their role as educators, has been a challenging and contentious issue in educational policy and practice in recent years. It plays a crucial role in the educational process, as it is essential for fostering creativity and human development within the school environment. Between traditional assessment based mainly on written and oral measurable tests and authentic assessment that highlights the role of the pupil through the self-evaluation or other techniques such as the materials folder, teachers are called upon to undertake a difficult task. In this article the results of a qualitative research in relation to the role of authentic assessment in foreign language teaching that took place in the Attica Region in Greece from March 10 to April 10, 2022 were presented. A total of 20 foreign language teachers (English, French, German) participated in semi-structured interviews and expressed their views on the relevant questions. The research problem posed in this study was to investigate the views and attitudes of foreign language teachers (English, French, German) regarding the framework of authentic assessment in foreign language teaching. The survey asked teachers to share their opinions on the role of authentic assessment in foreign language teaching, their preferred assessment criteria, the use of alternative forms of assessment, and their satisfaction with their training in authentic assessment. In general, it emerged that permanent secondary school teachers with many years of service prefer traditional forms of assessment and choose techniques that result in measurable criteria. In contrast, younger contractual teachers are more receptive to alternative forms of evaluation. However, no significant difference was observed on the issue of training. This survey aimed to gather language teachers' perspectives on authentic assessment in order to enhance textbooks and training programs.

Education planning analysis using augmented reality, virtual reality, and blockchain

The development of information technology has changed the educational landscape by providing new opportunities to enhance the learning experience. This article aims to analyze educational planning using advanced technologies such as Augmented Reality (AR), Virtual Reality (VR), and Blockchain. Through this approach, we explore the potential of integrating these technologies in optimizing educational planning, including curriculum management, student performance evaluation, and increased student participation in the learning process. The research method used is a literature study to review literature related to AR, VR, and Blockchain technology in an educational context. The results of the analysis present ideas on how the application of this technology can improve efficiency, effectiveness, and transparency in educational planning. The conclusion of this study highlights the importance of integrating advanced technologies in educational planning to support the achievement of better learning objectives.