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Copyediting JEES: Journal of Education and Educational Sciences

Exploring the Antecedents and Consequences of Challenging Behavior in Learners with Down syndrome: an Intervention for Teachers on Functional Behavior Assessment at Deborah Academy

Misahu Shumetu, Asmerom Tekle, Deborah Foundation

The purpose of this assessment was to evaluate functional behavior assessment (FBA) training for teachers on teaching children with Down syndrome who present challenging behaviors at Deborah Academy of Ethiopia. The intervention consisted of a two-week training program to diagnose this behavior and apply interventions. Results indicated considerable improvement in teachers’ levels of confidence and competence in handling difficult behaviors. Teachers reported having more access to information about why students acted out and could deliver better interventions in response. The other results were observed: disruptive issues were reduced and a positive classroom climate. FBA training can offer useful materials to educators with students who display challenging behaviors such as Down syndrome students. It allows teachers to learn systematically as a result of the method, which is good for both student and teacher.

Published JEES: Journal of Education and Educational Sciences • 2026

The Influence of Interest and Grit on Indonesian Primary Students’ English Language Performance

Detriana Abuk, Yumna Habibah Nurhasanah, Maria Cilia Nahak, Yeni Novelina Manek

This study investigated the relationship between learning interest, grit, and English language performance among Indonesian primary school students. A total of 240 students from three public elementary schools SDN Negeri 1 Tuk, SDN Negeri 1 Kedung Jaya, and SDN Negeri 1 Kedung Dawa participated in the study. Data were collected using structured questionnaires and analyzed through descriptive statistics, validity and reliability testing, and multiple linear regression analysis. The findings revealed that both interest and grit had significant positive correlations with English performance (r = 0.622, p < 0.001 for interest; r = 0.693, p < 0.001 for grit). Furthermore, regression analysis indicated that grit was the stronger predictor of English achievement (β = 0.503, p < 0.001), compared to learning interest (β = 0.278, p < 0.001), with the model accounting for 52.1% of the variance in performance (R² = 0.521). These results emphasize that while student interest enhances motivation, grit defined as perseverance and sustained effort-is a more influential factor in predicting academic success in English. The study highlights the importance of cultivating both interest and resilience in young learners. Teachers are encouraged to implement strategies that promote long-term motivation and persistence to support better outcomes in English language learning.

Published: 01 May 2026 View Details
Published JEES: Journal of Education and Educational Sciences • 2026

The Validity and Reliability of Social Responsibility Among Senior High School Students

Mar'atu Nafilah, Charmelia Nuraini, Nasya Dinda Afrillah

The purpose of this project is to create and verify a measurement instrument for evaluating high school students' social responsibility. Data were gathered quantitatively from 248 kids who were chosen from a variety of metropolitan schools using purposive sampling. Based on a theoretical framework of social responsibility, the instrument was validated both constructively using Exploratory Factor Analysis (EFA) and content by experts using the CVR and CVI methods. Cronbach's Alpha and McDonald's Omega were used to assess for reliability, and both showed strong internal consistency (α > 0.80). The findings point to a realistic and trustworthy factor structure with three primary dimensions: social justice, social culture, and contextual understanding. These results lend credence to the instrument's usage in educational settings, especially character education, for diagnostic and assessment purposes. This study offers educators and policymakers a useful tool for assessing teenagers' social responsibility that is context-specific. To assess the instrument's external validity in various institutional and cultural contexts, further study is advised.

Published: 01 May 2026 View Details
Published JEES: Journal of Education and Educational Sciences • 2026

Background and Scope of The Philosophy of Integrated Science Religion and Science and Their Goals and Benefits

Riskimilasari, Zulkifli Musthan

This study discusses the philosophy of science of integrating religion and science with an emphasis on its physiological and sociological background US well US its benefits and benefits. The study approach uses the library research method. The play data sources in this research are obtained from various references and research journals that are relevant and closely related to the issue of the integration of religion and science. All of the books and resources that have been successfully compiled are comprehensive guides that are relevant to the topics discussed. After the source collection process is completed, the next step is to analyze and synthesize the data to reach a valid conclusion from the results of this study. Physiologically, the relationship between modern science and religion has experienced dynamics from the 17th century to the 20th century from close encounters, views that reduce the role of God and the universe, to interactions that are dynamically re-formed. Sociologically, the integration of religion and science that was born in response to the dichotomy caused by the entry of secular western education into the Islamic world, resulted in two different educational systems, namely Islamic education and secular education. The philosophy of integrated science aims to create harmonization between religion and science, develop a holistic paradigm, strengthen Islamic epistemology and science, and develop an integrative educational curriculum. The benefits of this integration include moral and ethical foundations in the development of science and technology, motivating scientific research with religious nuances, bringing holistic and harmonious awareness in society, Reducing conflicts and dichotomies between religion and science.

Published: 01 May 2026 View Details
Published JEES: Journal of Education and Educational Sciences • 2026

The Effect of the Ethno-RME Learning Model on Improving HOTS and Self-Efficacy of Elementary School Students

Putik Rustika, Rifqi Hidayat

Mathematics learning in elementary schools is still largely abstract, as it focuses on memorizing formulas and procedures without involving cultural contexts that are close to students’ daily lives. This condition leads to low levels of higher-order thinking skills (HOTS) and self-efficacy. This study aims to examine the effect of applying the Ethno-Realistic Mathematics Education (Ethno-RME) model on improving HOTS and self-efficacy among elementary school students. This study highlights its novelty by simultaneously examining cognitive (HOTS) and affective (self-efficacy) outcomes within an Ethno-RME framework at the elementary school level, which remains underexplored in previous studies. The research employed a quantitative approach with a pre-experimental one group pretest-posttest design. The instruments consisted of a HOTS test and a self-efficacy questionnaire administered before and after the treatment. Data were analyzed concisely using multiple regression analysis to examine the contribution of Ethno-RME to both outcome variables. The subjects were 159 elementary school students in Kesambi District. The results showed a significant improvement in students’ HOTS and self-efficacy after the implementation of the Ethno-RME model based on traditional house miniatures. These findings indicate that integrating local culture into mathematics learning through a realistic approach not only enhances cognitive understanding but also strengthens students’ confidence. Therefore, the Ethno-RME model can serve as an alternative contextual learning strategy that supports the development of both HOTS and self-efficacy.

Published: 01 May 2026 View Details
Published JEES: Journal of Education and Educational Sciences • 2026

The Effect of the Snowball Drilling-Based Jigsaw Model on Learning Independence and Mathematical Spatial Ability of Elementary School Students

Ike Kurniawati, Herlin Kurniasari

This study aims to determine the influence of variables in the snowball drilling-based Jigsaw learning model. The research method employed a pre-experimental design using a one-group pretest–posttest design. The research subjects were school students with a saturated sampling technique and a sample size of 60 respondents. The research instruments consisted of a cognitive test of mathematical spatial ability and a questionnaire on students' mathematical learning independence as well as a questionnaire on responses to the Jigsaw learning model. Data analysis techniques used multiple linear regression tests to determine the effect of the snowball drilling-based Jigsaw model on students' learning independence and mathematical spatial ability. Path analysis was used to test the relationship between aspects of independence and mathematical spatial ability. The results showed that the application of the snowball drilling-based Jigsaw model had a significant effect (p < 0.05) on improving elementary school students' mathematical learning independence and mathematical spatial ability. This study contributes novelty by integrating the Jigsaw cooperative model with Snowball Drilling to simultaneously strengthen students’ learning independence and mathematical spatial ability at the elementary level, an area that has been rarely examined in previous studies. In addition, there is a positive relationship between aspects of the variables of learning independence and mathematical spatial ability, as can be seen from the p-value < 0.05. The Jigsaw model can encourage students to increase their learning independence through responsibility and develop mathematical spatial abilities through understanding relationships, perception, visualization, rotation, and spatial orientation. Thus, this study can be used as a reference in similar studies.

Published: 01 May 2026 View Details
Published JEES: Journal of Education and Educational Sciences • 2026

The Effect of the Project-Based Learning Model in Terms of Learning Styles on the Literacy and Numeracy Skills of Elementary School Students

Irma Sofiasyari, Rizky Arianty

This study aims to determine the effect of the project-based learning model in terms of learning styles on the literacy and numeracy skills of fourth-grade elementary school students in the Jamblang sub-district in 1 cluster, namely SDN 1 Wangunharja, SDN 2 Wangunharja, SDN 1 Sitiwinangun, SDN 2 Sitiwinangun, SDN 3 Sitiwinangun, SDN 1 Bojong Wetan, SDN 2 Bojong Wetan, and SDN 3 Bojong Wetan. This study used a quantitative method with a one-group pretest-posttest design. The sample in this study consisted of all 240 fourth-grade elementary school students. The research instruments consisted of a learning style questionnaire, literacy and numeracy tests with multiple choice questions for the pretest and posttest. Data collection was conducted before and after the implementation of the PjBL learning model. Data analysis included validity, reliability, normality, homogeneity, simple linear regression analysis, and paired sample t-test. The results show that each data point in the variables also meets the assumptions of normality and homogeneity. From the descriptive statistics calculation results, the hypothesis test of simple linear regression analysis and the paired sample t-test show a significant difference between the pretest and posttest scores for students' literacy and numeracy abilities. with the students' literacy ability level at the time of the pretest averaging 42.88 and the posttest score averaging 76.33, and the students' numeracy ability level at the time of the pretest averaging 43.46 and the posttest score averaging 71.21. Based on the hypothesis test, the significance value of each variable was 0.000 (

Published: 01 May 2026 View Details
Under Review MIREJ: Multidisciplinary Innovation Research Journal

A Comparative Evaluation of Large Language Models for Enterprise Deployment: Performance, Safety, Cost, and Scalability Using a Multi-Criteria Decision Framework

Jurgen Mecaj, Erarda Vuka

The proliferation of large language models (LLMs) across enterprise, research, and public-sector applications has created an urgent need for rigorous, multi-dimensional evaluation frameworks. This paper presents a comprehensive comparative analysis of seven state-of-the-art LLMs — GPT-4o, Claude 3.5 Sonnet, Gemini 1.5 Pro and Flash, LLaMA 3 70B, Mistral Large, and Claude 3 Haiku — across eight evaluation dimensions: benchmark accuracy, safety alignment, cost efficiency, inference latency, context handling, deployment flexibility, multilingual capability, and scalability. A weighted Multi-Criteria Decision Analysis (MCDA) framework is applied to produce transparent composite rankings from empirical benchmark data using five standardized benchmarks (MMLU, HumanEval, HellaSwag, GSM8K, MATH). Results indicate that Claude 3.5 Sonnet achieves the highest MCDA composite score (0.801), driven by accuracy (90.4% MMLU, 92.0% HumanEval) and safety alignment (4.9/5). Gemini 1.5 Flash emerges as optimal for cost-sensitive deployments ($0.075/1M tokens; 210 tok/s). The paper analyzes architectural trade-offs between dense transformers and Mixture-of-Experts designs, provides a deployment recommendation matrix, and contributes an extensible, evidence-based decision framework for enterprise AI practitioners.

Declined MIREJ: Multidisciplinary Innovation Research Journal

A Comparative Evaluation of Large Language Models for Enterprise Deployment: Performance, Safety, Cost, and Scalability Using a Multi-Criteria Decision Framework

Jurgen Mecaj

The proliferation of large language models (LLMs) across enterprise, research, and public-sector applications has created an urgent need for rigorous, multi-dimensional evaluation frameworks capable of guiding model selection beyond single-metric leaderboards. This paper presents a comprehensive comparative analysis of seven state-of-the-art LLMs — GPT-4o (OpenAI), Claude 3.5 Sonnet (Anthropic), Gemini 1.5 Pro and Flash (Google DeepMind), LLaMA 3 70B (Meta AI), Mistral Large (Mistral AI), and Claude 3 Haiku (Anthropic) — across eight evaluation dimensions: benchmark accuracy, safety alignment, cost efficiency, inference latency, context handling, deployment flexibility, multilingual capability, and scalability. The study applies a weighted Multi-Criteria Decision Analysis (MCDA) framework to produce transparent composite rankings from empirical benchmark data. Evaluation leverages five standardized benchmarks (MMLU, HumanEval, HellaSwag, GSM8K, MATH), official API pricing data, throughput metrics, and curated safety evaluation datasets. Results indicate that Claude 3.5 Sonnet achieves the highest MCDA composite score (0.801), driven by combined strengths in accuracy (90.4% MMLU, 92.0% HumanEval) and safety alignment (4.9/5). Gemini 1.5 Flash emerges as the optimal choice for cost-sensitive, high-throughput deployments ($0.075/1M tokens; 210 tok/s). The paper additionally analyzes architectural trade-offs between dense transformers and Mixture-of-Experts (MoE) designs, scaling law evidence, safety evaluation profiles, and provides a nine-row deployment recommendation matrix. This work contributes an extensible, evidence-based decision framework with practical guidance for practitioners, researchers, and enterprise decision-makers navigating the rapidly evolving LLM ecosystem.

Published DUTIES: Education and Humanities International Journal • 2026

Deciding When and How to Use AI in EFL Speaking Instruction: Evidence from Surveys and Teacher Interviews

Samikshya Bidari, Muhammad Aulia Taufiqi

The integration of Artificial Intelligence (AI) in English as a Foreign Language (EFL) instruction has expanded rapidly, yet little is known about how teachers make pedagogical decisions regarding AI use in speaking classrooms. This study investigates how EFL teachers explain and justify their decisions about when and how to use AI tools in speaking instruction, employing a convergent mixed-methods design. Quantitative data were collected through a survey of 24 teachers, analyzed using descriptive statistics, while qualitative insights were obtained from semi-structured interviews with 12 teachers, analyzed thematically. Findings reveal that teachers adopt a selective, context-sensitive approach, prioritizing AI for pronunciation practice and fluency exercises, where immediate feedback and structured practice are most effective. Teachers exercise professional judgment to balance AI affordances with pedagogical objectives, contextual constraints, and ethical considerations, ensuring that AI supplements rather than replaces human interaction. The study highlights the multidimensional nature of teacher agency in AI-supported speaking instruction and provides practical implications for professional development and curriculum design. Future research could examine AI integration across other language skills, diverse educational contexts, and longitudinal impacts on learners’ speaking proficiency and autonomy.

Published: 01 Mar 2026 View Details
Published DUTIES: Education and Humanities International Journal • 2026

When Feedback Must Be Human: Pedagogical Resistance to AI in EFL Speaking Classrooms

Ega Nur Fadillah, Uwaimir Ahad

The rapid advancement of artificial intelligence (AI) has intensified debates about its role in language education, particularly in providing automated feedback. While existing research has largely focused on teachers’ acceptance and use of AI tools, limited attention has been given to teachers’ deliberate decisions not to use AI in specific pedagogical contexts. This qualitative study investigates EFL teachers’ pedagogical resistance to AI-mediated oral feedback in speaking classrooms. Drawing on in-depth semi-structured interviews and reflective accounts from EFL teachers, the study employs thematic analysis to explore how teachers explain their resistance and the pedagogical values underlying their decisions. The findings reveal that resistance is grounded in teachers’ concerns about interactional immediacy, learner affect, dialogic engagement, and ethical responsibility. Oral feedback is viewed as a relational practice that requires human sensitivity to timing, tone, and emotional cues, which teachers perceive as inadequately addressed by current AI technologies. Rather than signaling technological reluctance, pedagogical resistance emerges as an enactment of teacher agency and professional judgment. The study contributes to critical discussions on AI integration in education by reframing non-use as a principled pedagogical choice and highlighting the need for context-sensitive, human-centered approaches to AI use in EFL speaking instruction.

Published: 01 Mar 2026 View Details
Published DUTIES: Education and Humanities International Journal • 2026

AI Game-Based Learning in Low-Resource Classrooms: Teachers’ Innovation Under Constraint

Mochamad Rizqi Adhi Pratama, Nur Karmila Maisara

Abstract: The integration of artificial intelligence into game-based learning has been widely promoted as a means of enhancing engagement and personalization in education. However, existing research largely assumes well-resourced classroom conditions, offering limited insight into how such approaches are enacted in constrained contexts. This qualitative multiple case study explores how teachers design and implement AI-supported game-based learning in low-resource classrooms and how contextual constraints shape their pedagogical reasoning and innovative practices. Drawing on interviews, classroom observations, teaching artifacts, and stimulated recall, the study foregrounds teachers’ agency in mediating AI use under conditions of limited infrastructure, device access, and institutional support. The findings reveal that teachers adopt selective and hybrid approaches to AI game-based learning, combining AI-generated content with offline activities and teacher-led scaffolding. Contextual constraints function not merely as barriers but as catalysts for reflection, improvisation, and ethical decision-making related to fairness and inclusivity. This study contributes to AI in education research by reframing innovation as a situated, teacher-driven process and by highlighting the importance of context-sensitive approaches to AI-supported pedagogies, particularly in underrepresented low-resource educational settings.

Published: 01 Mar 2026 View Details