Student Assessment Research Articles

COMPARATIVE ASSESSMENT OF VISUAL COLOR MATCHING FOR ARTIFICIAL AND NATURAL TEETH BY STUDENT OF DENTAL FACULTY AT KHARKIV NATIONAL MEDICAL UNIVERSITY

The purpose of this study was to conduct a comparative assessment of dental students’ ability to match the color of patients’ teeth with aesthetic restorations. Materials and Methods. The study was conducted from 2021 to 2024 with participation of 2nd- and 3rd-year students at the Faculty of Dentistry, Kharkiv National Medical University, Kharkiv, Ukraine. Results. Accurate determination and reproduction of natural tooth color is a challenging task in aesthetic dentistry, as color plays a crucial aesthetic role. This process depends heavily on the experience and perception of dentists and can be approached subjectively (visual analysis) or objectively (special devices). Although shade determination is a routine task for dentists, errors are still common. The study revealed that 2nd-year students struggled significantly with color matching, especially for natural teeth, with error rates of 66.6% for artificial teeth and 80.8% for natural teeth, indicating a need for more training. Students performed better using the VITA Classic shade guide, which is simplified, but matching the color of natural teeth requires additional practice. The results confirm that clinical training improves students’ color-matching skills. After training, 3rd-year students showed a marked decrease in error rates: 35.8% for artificial teeth and 53.3% for natural teeth. The Vita 3D Master scale proved more accurate due to its broader color-matching capabilities. Overall, the accuracy levels improved significantly, highlighting the effectiveness of the training program. Conclusion. The results of the study demonstrate that training significantly improves students' ability to accurately determine tooth color. The 3rd year students who underwent clinical training showed better results in matching the color of both artificial and natural teeth, reducing the number of errors by 35.8% and 53.3%, respectively. The Vita 3D Master scale proved to be more accurate due to a wider selection of colors and more evaluation parameters. The 81.5% increase in the overall score confirms the effectiveness of the training in improving the accuracy of tooth color determination in the educational process.

Responding to Generative AI

There are few technologies which have such great a potential impact on the design and delivery of tertiary education, as found with Generative Artificial Intelligence (Gen-AI). Student’s deep learning and the integrity of student assessment in particular is impacted by this emerging technology. This presentation will report on a three-cycle action research project to redesign assessments for effective learning in an Australian university Health Science (HS) faculty. Cycle 1 reviewed assessments using an innovative appraisal tool for assessments which was designed by the presenting HS academics that aligned recent Gen-AI and academic integrity guidelines from Australian institutions (Lodge et al., 2023a; Monash University, 2023; Flinders University, 2023; TEQSA, 2022; Torrens University n.d.). The tool was reviewed and improved for use in Cycle 2, which involved reviewing the remaining 16 HS subjects and designing a team-based strategy for implementing assessment reform. Cycle 3 involves implementing identified strategies for redesigning assessments across all HS subjects. We will report on the action-research methods used, including the development and use of the assessment appraisal tool, as well as the Cycle 3 early findings from the HS subjects assessment review. Results from the subsequent strategic assessment design will be presented using example assessment improvements based on the study findings. The findings highlight the need for a unified approach to assessment reform, and the potential benefits of systematic, team-based approaches to address emerging technologies. Action-research methodologies such as this one, employed with subject coordinators' involvement and training in evaluation, encourages pro-active subject quality improvement as well as scholarly thinking among university academics. This approach may be relevant to all academics interested in actively creating assessment reform amid the transformative education environment precipitated by the use of Gen-AI.

The national student survey of GenerativeAI use among Australian university students

Entrusting GenerativeAI (GenAI) to complete tasks that require critical engagement with content can have wide-spread implications to the integrity of student learning outcomes. This paper presents the preliminary findings of a mixed-methods survey of Australian university students (n=399) on their use of GenAI in their studies. Preliminary findings suggest student GenAI use in universities is common, with approximately one third of students using GenAI and 53% engaging with ChatGPT alone. In open-ended responses, stigma and judgement towards students utilising GenAI to complete their assignments is evident. Stigma may entrench a culture of secrecy around integrating GenAI into the student workflow, which may work against any initiatives to increase citation or transparency in the sanctioned use of GenAI. Students also discussed implications for employability, skill development, and the originality of their work, with 80% of students concerned that GenAI is devaluing their degrees. These findings require universities to critically engage with either: building a culture of engagement with, or increasing surveillance against the use of GenAI in student assessments (reflecting the GenAI stance of each university).

Exploring Online Teaching's Impact on Instructors in Core Engineering Courses: Insights, Challenges, and Future Directions

ABSTRACTThis study examines the impact of online teaching on instructors of fundamental engineering courses, focusing on insights, challenges, and future pathways. By analyzing the instructors' perspectives, the research examines various aspects of online teaching, including mode of delivery, student engagement strategies, assessment preferences, and future directions. Insights are drawn from a comprehensive survey of instructors, shedding light on their experiences, challenges, and preferences in the online teaching landscape. The findings highlight a preference for synchronous sessions, the utilization of diverse engagement techniques, and the significance of maintaining academic integrity in assessments. Instructors' preference for face‐to‐face interaction for improved academic performance and openness to hybrid teaching modes are evident. This study not only provides valuable insights into the dynamics of online teaching but also paves the way for future advancements in pedagogical strategies and educational technology integration. The research identifies potential areas for future work, ranging from refining hybrid teaching models to exploring emerging technologies and fostering instructor training.

Research on physical health assessment and intervention strategies for college students based on biomarkers

Effective physical health assessments and intervention strategies are crucial for college students, who often face unique stressors that can impact their physiological health. In this analysis, we explore how biomarkers can be utilized to assess physical health and the efficacy of targeted interventions for this demographic. Hypotheses were developed based on the three intervention groups: (1) a face-to-face intervention group receiving a tailored wellness program, (2) an Internet of Things (IoT) gadgets intervention group using a health management assessment, and (3) a control group with only baseline and follow-up measurements. College students (n = 204) were randomized into these groups. Biomarkers related to stress and inflammation (e.g., cortisol levels, high-sensitivity C-reactive protein (hs-CRP)) were measured at baseline, post-intervention (10 weeks), and follow-up (36 weeks). Psychological and physical health outcomes were also assessed using standardized questionnaires. The Mixed-Effects Models, ANOVA, and Structural Equation Modeling (SEM) were used to analyze the differences between groups, changes in biomarkers over time, and the relationships between psychological, physiological, and lifestyle variables. Results indicated that the face-to-face wellness group demonstrated significantly better physical health outcomes compared to both the IoT gadgets group and control group, with diet modification showing the highest effectiveness, followed by physical activity and stress management interventions.

Assessing Learning in Mathematical Sensemaking Electromagnetism Instructions among Rwanda Polytechnic Students at Huye College

In the realm of electromagnetic (EM) courses in engineering, many studies have reported students’ learning difficulties related to mathematical frameworks representing physical phenomena. Students’ learning engagement and learning gains are not satisfying. The present study assessed first-year engineering students’ behavioural engagement and perceived learning gains in mathematical sensemaking electromagnetism instructions at RP-Huye College. Within a single-case research design, a six-weeks intervention incorporating mathematical sensemaking instructions, supported by physical experimentation and computer simulations, was implemented to 61 first-year engineering students who were enrolled in the department of electrical and electronics engineering. All enrolled students were purposively recruited to participate because this target population was less than 100. Data were collected through classroom observations, which used the behavioural engagement related to instruction (BERI) and a post-topic evaluation, which used a semi-structured questionnaire. Data analysis involved the use of graphs, descriptive statistics and inductive thematic analysis. Findings revealed that students were mostly engaged during mathematical sensemaking by hands-on and simulation-based activities, particularly in topics related to electromagnets, where engagement levels peaked at 7.5 in average. Conversely, lecture-based tasks, especially on magnetic forces and electromagnetic induction, recorded the lowest engagement at 6.2 in average. The post-topic assessment on perceived learning gains showed that students had highly positive perceptions on their learning experiences (M=4.82, SD=0.48) and recognized the significance of EM in engineering (M=4.85, SD=0.38). These numerical results were complemented by students’ narrations, which indicated that they gained particular attention about specific EM formulas and how they can apply them in engineering. However, the present study also noted that further refinement in instructional design, particularly by incorporating specific dimensions of mathematical sensemaking, could optimize learning outcomes for EM courses in engineering. Additionally, formal assessments of students’ mastery and experimental studies can benefit future work.

Enhancing science achievement through inquiry activities: the critical role of perceived teacher support

ABSTRACT In science education, scientific inquiry is crucial for developing inquiry skills and constructing scientific knowledge. However, the impact of scientific inquiry activities on student achievement continues to be debated. A number of counterintuitive findings highlight the need to explore the underlying factors influencing the effectiveness of inquiry-based learning. This study employed hierarchical linear models (HLM) to investigate the role of students’ perceived school teacher support in moderating the relationship between inquiry-based science activities and science achievement. The sample used in this study was drawn from Beijing, Shanghai, Jiangsu, and Guangdong in mainland China (B-S-J-G-China). These four provinces participated in the 2015 Programme for International Student Assessment (PISA) as a collective group. The dataset comprised 9,592 students (4,543 females and 5,049 males) from 261 schools. Results revealed a negative correlation between inquiry-based activities and science achievement, indicating that a higher frequency of inquiry-based activities was associated with lower science achievement. However, this association was positively and significantly moderated by the extent of school teacher support. These findings highlight the pivotal role of students’ perceived school teacher support in enhancing the effectiveness of inquiry-based practices and shed light on optimising inquiry-based educational strategies. This suggests that the effective implementation of inquiry-based activities requires the backing of supportive teachers, with broader implications for curriculum design and teacher development in science education.

Формирование профессионально-важных качеств сотрудников ОВД посредством проектной методики изучения дисциплины «Профессиональная этика и служебный этикет»

The article is devoted to the study of the formation of professionally important qualities (hereinafter referred to as PIC) of students at the Barnaul Law Institute of the Ministry of Internal Affairs of Russia, ensuring their moral and psychological stability (honesty, discipline, responsibility, justice, etc.). An analysis of expert assessments of the formation of professionally important qualities grouped into four clusters "Moral stability", "Sustainability of working capacity", "Self-organization in professional activity", "Extroversion, social activity" was conducted on a representative sample (over 600 respondents). A comparative analysis by forms of study (full-time, part-time, faculty of professional retraining - short-term full-time programs) showed that students of the correspondence form of study included in practical professional activity, assess the formation of "professionally important qualities of students" significantly higher than students of other forms, with the exception of the cluster "Self-organization in professional activity". A comparative analysis of expert assessments of full-time students of the 2nd and 4th years demonstrated positive dynamics in three clusters, proving the overall effectiveness of the educational work of the university. Stagnation of indicators is observed for the factor "sustainability of working capacity". The results of the study formed the basis for developing the content of the course "Professional Ethics and Service Etiquette". The experience of implementing the project method as a technology for developing "professionally important qualities of students" is substantiated and described

Redefining student assessment in Nigerian tertiary institutions: The impact of AI technologies on academic performance and developing countermeasures

Integrating artificial AI technologies in education has revolutionised teaching, learning, and assessment worldwide. In Nigerian tertiary institutions, students increasingly rely on AI tools for assignments, research, and exam preparation, raising concerns about the integrity of traditional assessment methods. This paper explores the impact of AI technologies on academic performance and the challenges they pose to accurately evaluating student capabilities. It argues for the urgent need to redefine assessment strategies in Nigerian higher education to preserve academic standards while harnessing the benefits of AI. The study highlights ethical concerns such as data privacy, access inequality, and over-reliance on AI tools, which can undermine critical thinking skills. It provides countermeasures and policy recommendations, including establishing AI usage guidelines, promoting equitable access to technology, and integrating assessments that prioritise critical thinking and problem-solving skills. By adopting these innovative policies, Nigerian tertiary institutions can enhance the quality of education and ensure that students develop genuine skills and academic excellence. This paper calls for immediate action to align education with the realities of the AI age, ensuring sustainable and authentic student outcomes.

Developing the KATAKU Mobile Application to Enhance Vocabulary Acquisition for Deaf Students

This study presents the development of the KATAKU (Kata untuk Tunarungu Interaktif dan Unik) application as an educational tool designed to support vocabulary learning for deaf students. Deaf students, who have the same educational rights as their hearing peers, often attend Special Schools (SLB). The integration of visual aids and technology in learning has proven effective in increasing their engagement and interest. This study employed a mixed-methods approach, including vocabulary assessments for deaf students, classroom observations, and teacher interviews for a needs analysis to identify the specific requirements of schools and students. Results from the vocabulary assessments revealed that deaf students face significant challenges, particularly with academic terms and word categorization. Classroom observations at three SLB schools in Jombang highlighted engaging but challenging learning dynamics, reinforcing the need for accessible and efficient teaching tools for educators. Teacher interviews indicated that using the paper dictionary provided by the Ministry of Education can be time-consuming and lacks efficiency. This study concludes that deaf students in Jombang face substantial obstacles in vocabulary comprehension, especially with academic vocabulary. The findings underscore the need for targeted vocabulary interventions using modern technological tools to better prepare students for advanced educational demands.

Assessing and Improving Medical-Spanish Language Proficiency Among Nursing Students.

Introduction: Language discordance among health care providers and patients has been shown to result in poor patient outcomes. Health care providers who identify as being proficient in the native language of their patients may decline the use of professional interpreters due to their self assessment of language proficiency. More information is needed about whether providers who speak Spanish are proficient in medical Spanish. This study measured medical-Spanish language proficiency among nursing students. Methods: A quantitative pretest posttest evaluation (N = 30) at a large private university in the northeastern U.S. compared student and faculty assessment of student language proficiency after taking a medical-Spanish course using the Interagency Language Roundtable (ILR). T-tests compared student's final, self-assessed ILR scores with faculty's final ILR scores. Results: A significant difference was noted between students' self assessments and faculty assessments of student language proficiency (Rater 1: t(29) = -2.660, p = 0.013; Rater 2: t(29) = -2.693, p = 0.012) with high interrater reliability (kappa = 0.875). There was a significant difference between students' self-assessment of language abilities before and after the course (t(29) = -3.694; p < 0.001). Conclusion: Objective assessment of medical-Spanish language proficiency following a medical Spanish course may more accurately measure proficiency than self-assessment alone.

Decompositions of Information Criteria in Joint Model Under Probit Link for Response

ABSTRACTThe item response and response time are naturally encountered in variety of computerized testing, which are jointly analysed to achieve efficient model fitting. Several novel Bayesian assessment criteria, which quantify the enhancement in the fit of one dataset given the other, are proposed by utilizing decompositions of the deviance information criterion (DIC) and the logarithm of the pseudo‐marginal likelihood (LPML) under a logistic link. However, the calculation of these criteria under a probit link, a commonly employed alternative, remains unexplored. Moreover, decomposing DIC and LPML under probit link presents greater challenges than in the logistic model due to the intricate additional dimension integral. This paper addresses this gap by demonstrating the application of Bayesian model assessment criteria with a normal ogive model in the context of item response data within a joint modelling framework. Additionally, we also illustrate how to implement Bayesian sampling via a powerful R package ‘nimble’. Extensive simulation studies are conducted to evaluate the empirical performance of those criteria. Further, a detailed analysis of the Programme for International Student Assessment (PISA) data is carried out to illustrate the methodology.

Commentary on the Applications of Blended Learning in the Teaching and Learning Process – A Review

Blended learning, an innovative approach that combines traditional face-to-face (FTF) instruction with online elements, has gained prominence in education. This article provides a comprehensive overview of blended learning, including its definition, advantages, disadvantages, and various factors that affect the effectiveness of this teaching and learning approach. It also explores students’ and teachers’ perceptions of blended learning and the challenges and issues that may arise in its implementation. Blended learning has been found to provide several benefits such as personalized learning, flexibility, improved engagement, cost-effectiveness, accessibility, and real-world skill development. However, it also presents challenges related to technological dependence, digital inequality, reduced face-to-face interaction, and assessment difficulties. Instructors may face challenges in terms of preparation, time management, and scheduling. Factors affecting learning in a blended environment include pedagogical approaches, technology infrastructure, teacher skills and training, student engagement, assessment methods, cultural and social context, and time management. Students and teachers generally perceive blended learning positively, citing improvements in learning outcomes and teaching practices. While blended learning offers a sound pedagogical approach, successful implementation requires addressing technical barriers, ensuring engagement, effective assessment and evaluation methods, effective time management, and providing instructor training and support. Data privacy and security, social isolation, and course redesign are also important considerations in implementing blended learning. In conclusion, blended learning is a versatile and effective educational approach with many advantages and challenges. To ensure its success, careful planning, continuous evaluation, and support for educators and learners are essential to create rich learning environments in a rapidly evolving educational environment.

Enhancing Real-Time Emotion Recognition in Classroom Environments Using Convolutional Neural Networks: A Step Towards Optical Neural Networks for Advanced Data Processing

In contemporary academic settings, end-of-semester student feedback on a lecturer’s teaching abilities often fails to provide a comprehensive, real-time evaluation of their proficiency, and becomes less relevant with each new cohort of students. To address these limitations, an innovative feedback method has been proposed, utilizing image processing algorithms to dynamically assess the emotional states of students during lectures by analyzing their facial expressions. This real-time approach enables lecturers to promptly adapt and enhance their teaching techniques. Recognizing and engaging with emotionally positive students has been shown to foster better learning outcomes, as their enthusiasm actively stimulates cognitive engagement and information analysis. The purpose of this work is to identify emotions based on facial expressions using a deep learning model based on a convolutional neural network (CNN), where facial recognition is performed using the Viola–Jones algorithm on a group of students in a learning environment. The algorithm encompasses four key steps: image acquisition, preprocessing, emotion detection, and emotion recognition. The technological advancement of this research lies in the proposal to implement photonic hardware and create an optical neural network which offers unparalleled speed and efficiency in data processing. This approach demonstrates significant advancements over traditional electronic systems in handling computational tasks. An experimental validation was conducted in a classroom with 45 students, demonstrating that the level of understanding in the class as predicted was 43–62.94%, and the proposed CNN algorithm (facial expressions detection) achieved an impressive 83% accuracy in understanding students’ emotional states. The correlation between the CNN deep learning model and the students’ feedback was 91.7%. This novel approach opens avenues for the real-time assessment of students’ engagement levels and the effectiveness of the learning environment, providing valuable insights for ongoing improvements in teaching practices.

Learning Opportunities for Solving Context-Based Calculus Tasks in Nepal’s High School Mathematics Textbooks

ABSTRACT A vital skill for students to acquire in school mathematics involves solving problems embedded within real-world contexts. The extent to which students achieve intended learning outcomes largely depends on whether textbooks offer opportunity-to-learn (OTL) the assessed concepts and skills. The National Assessment of Students’ Achievements (NASA) reveals a significant deficiency in the performance of Nepali students in solving context-related problems. We conducted a content analysis of the most commonly adopted Nepali mathematics textbooks for grades XI and XII to assess the OTL they afford for tackling context-related problems in calculus. Results show that almost all mathematical concepts were introduced without providing related contexts, and around 95% of worked examples and exercise problems did not have any context and offered little or no opportunities for modeling and mathematization. Although most of the contexts presented in the problems were categorized as real and essential, the cognitive demands of many tasks were lower. The investigated textbooks were not necessarily aligned with Nepal’s updated National Mathematics Curriculum (2018), which underscores the integration of mathematics with real-world applications. Results of this study indicate that the limited access to quality mathematics textbooks might be a significant barrier hindering students’ ability to solve context-related problems.

Assessment of Dental Students' Knowledge and Attitudes About the Epidemiologic and Clinical Characteristics of Oral Cancer: Implications for Other Middle-income Countries.

The stage of detection of head and neck cancer and the time between detection and treatment are critical to prognosis. The importance of the dentist in primary diagnosis and treatment planning has been emphasized. The purpose of this study was to evaluate the knowledge of dental students in the prevention and early diagnosis of oral cancer. A descriptive cross-sectional study was conducted on 199 students from different institutions. A self-administered questionnaire with 34 multiple-choice questions on clinical and epidemiologic knowledge and opinions about oral cancer was used. Descriptive analysis to show means and frequencies and the binomial logistic regression test were used to perform the statistical analysis. The confidence level used was 95%. The results showed that all students in the study had heard of the existence of oral cancer, but only 24.6% knew someone with the disease. The majority reported a lack of information in the population about prevention and self-examination, as well as a lack of information campaigns in institutions. Although the majority perform clinical examinations of the oral mucosa (73.4%) and refer patients with suspicious lesions to specialists, there is low confidence in performing biopsies (73.4%) and gaps in training during graduation (84.4%). The majority have never attended continuing education courses on oral cancer but show interest (97.5%). The study identifies deficiencies in the knowledge and practices of dental students and highlights the need for improved teaching and training to promote oral cancer prevention and early detection. Further research in this area and ongoing assessment of students' skills are suggested.

Leveraging professional learning communities in linking digital professional development and instructional integration: evidence from 16,072 STEM teachers

BackgroundIntegration of digital tools and resources in STEM instruction has garnered significant attention due to its high potential. Digital professional development is identified as a pivotal factor for equipping teachers with necessary digital skills to effectively orchestrate digital resources. Notably, the role of professional learning communities is considered critical. However, the intricate relationships among digital professional development, professional learning communities, and digital instructional integration among STEM teachers remain underexplored. Utilizing partial least-squares–structural equation models (PLS–SEM), the present study examined links in digital professional development, professional learning communities, and digital instructional integration among STEM teachers (N = 16,072) who participated in the Programme for International Student Assessment (PISA) 2022.ResultsFindings from the PLS–SEM analysis indicate that digital professional development exhibits a direct positive relationship with professional learning communities and digital instructional integration. Relatedly, professional learning communities is positively correlated with digital instructional integration. In terms of indirect effect, findings show that professional learning communities play a significant positive mediating role in linking digital professional development and digital instructional integration.ConclusionsThis study reports new evidence on the influence of digital professional development on digital instructional integration through professional learning communities among 16,072 STEM teachers and concludes that, when STEM teachers regularly immerse themselves in professional learning communities, they are more likely to benefit from their digital professional development by integrating digital technologies in classroom instruction. Policymakers and educational leaders should consider promoting digital professional development and professional learning communities among STEM teachers, along with efforts to encourage digital instructional integration.

Curriculum Assessment Reform for Convention and Exhibition English

Convention and Exhibition English is a typical course in English for Specific Purposes (ESP). With Chinese business activities increasing, there is a growing demand for convention and exhibition-related talents, since most businesses are in connection with these events. To cultivate competent graduates, Guangdong Technology College has tried replacing traditional written test with a video in the assessment of students’ performance after their learning of this course to stimulate practice and self-exploring. Role play in the videos can inspire students’ interest in this field and build up their confidence in English. This article will introduce the background information on the development of the course, the necessity of its reform, and how it has been implemented. This paper aims to attract attention to the creative reform of teachers and hopes to contribute to more studies on ESP teaching for the better cultivation of English talents that the growing Chinese economy requires.

The environment is somewhat alike for different adaptive motivations: Machine learning reveals optimal motivational contexts involve collective support of parents, teachers, and peers

Achievement motivation is fundamental for human flourishing. While numerous adaptive motivational constructs have been proposed, they are often examined in isolation without considering their shared contextual roots. To identify the contextual factors underlying different forms of adaptive achievement motivation, we conducted comprehensive analyses by integrating a global student assessment dataset (n = 77,068 middle-school students across 19 countries, Mage = 15.79). We conducted a literature review and identified 27 potential predictors theoretically and empirically related to achievement motivation, including immediate contextual factors available in the dataset and distal contextual factors available from varying sources. Results from machine learning analyses showed convergent patterns of the contextual predictors for adaptive motivation (self-efficacy, learning goals, and task mastery orientation). Specifically, the optimal environment for adaptive motivation is characterized by the collective positive influence from parents, teachers, and peers, rather than depending on one exclusively. In comparison, the pattern of other less adaptive motivation constructs (fixed mindsets, performance goals, and fear of failure) is idiosyncratic. These findings provide synthesized evidence consolidating achievement motivation research, highlighting the shared contextual foundations for various adaptive motivations. This integrative approach clarifies that the optimal motivational contexts involve the collective social support of parents, teachers, and peers.

Realistic mathematics education and mathematical literacy: a meta-analysis conducted on studies in Indonesia

A considerable body of literature exists pertaining to realistic mathematics education (RME) and its correlation with mathematical literacy, with numerous studies demonstrating incongruent results. The principal objective of this meta-analysis is to systematically investigate the overarching influence of RME on mathematical literacy within the context of Indonesia. The collection of documents comprises a total of seventeen publications that were released between the years 2014 and 2023. The estimation methodologies utilized in this study were grounded on a random-effects model, and statistical computations were conducted utilizing the comprehensive meta-analysis (CMA) software in academic writing. The equation proffered by Hedges was employed for the quantification of effect magnitude. The outcomes of the investigation reveal that the implementation of RME learning yielded a noteworthy and advantageous impact (effect size = 1.031; p 0.05) on the adeptness of students in the domain of mathematical literacy. Moreover, many moderating factors, including class capacity, educational level, geographical location, content of the Programme for International Student Assessment (PISA), and the combination of learning, did not significantly impact students' diverse mathematical literacy proficiency. This study proposes that mathematics educators should consider utilizing the RME as a means of improving students' proficiency in mathematical literacy.