International large-scale assessments, particularly PISA, have a significant influence on educational policy and curriculum development. Previous research highlights that sustained underperformance of Slovak pupils is often associated with an insufficient emphasis on real-life and application-oriented tasks in mathematics education. In response, an ongoing curriculum reform in Slovakia aims to align national education more closely with international assessment frameworks. The present study investigates the process of modifying the national mathematics assessment system to better reflect PISA standards, with a focus on the integration of criterionreferenced testing alongside traditional normative testing. The underlying hypothesis assumes that newly designed assessment tools can more accurately capture pupils achieved levels in key educational areas. A pilot study was conducted using newly developed mathematics tests administered to a representative sample of pupils (N = 1047), and the data were analysed using statistical evaluation methods appropriate for educational measurement. The results reveal both strengths and limitations of the proposed testing tool, including specific shortcomings identified during the first experimental administration. These findings provide evidence-based guidance for further refinement of national assessments and contribute to improving the validity of large-scale testing in mathematics education, thereby supporting more effective curriculum reform and instructional practice.

The study aimed to determine the level of effectiveness of the Rapid Mathematics Assessment Program for primary grade pupils in public elementary schools in the Baras District Office during the School Year 2024-2025. A descriptive survey research design was applied, utilizing a researcher-made questionnaire checklist as a tool in gathering the needed data. The respondents of the study included the total population of primary grade teachers in the said schools, consisting of 146 teachers. The study revealed that teacher-respondents perceived Rapid Mathematics Assessment Program (RMAP) as much effective in terms of its objectives, intervention process, and monitoring and evaluation, with the obtained composite mean of 3.53. The level of effectiveness of the Rapid Mathematics Assessment Program for primary grade pupils does not differ significantly with respect to the cited variables. In addition, the level of performance of the primary grade pupils differs significantly in the RMA as revealed in the pretest and posttest results, with a p-value of .007, which is less than the standard significance level of 0.05. It was concluded that the performance of the primary grade pupils in Mathematics significantly improved after undergoing intervention activities in the Rapid Mathematics Assessment program. It was recommended that school administrators conduct continuous professional development on effective assessment practices, data analysis, and instructional planning based on RMAP results.

This study assessed the level of performance in Mathematics of Grade 3 learners at Francisco Balagtas Elementary School, District III, Division of Manila, during the School Year 2024–2025 using a quantitative-descriptive research design. The study aimed to determine the learners’ level of performance in Mathematics, identify their specific areas of weakness, develop support learning materials to address these weaknesses, and evaluate the acceptability of the proposed materials as assessed by the school head and Mathematics teachers. The respondents of the study consisted of 328 Grade 3 learners and three Mathematics teachers. Data were gathered through Mathematics assessment results and evaluation instruments for the support learning materials. Findings revealed that 38.11% of the learners demonstrated a high level of performance, 48.48% showed an average level of performance, and 13.41% exhibited a low level of performance in Mathematics. The major weaknesses identified among the learners included two-step word problems involving addition, addition of dissimilar fractions and whole numbers, equal fractions, and other fundamental mathematical skills. Based on these findings, support learning materials were developed focusing on targeted lessons and exercises to improve learners’ mathematical understanding and skills. The acceptability of the support learning materials was evaluated in terms of content, quality of presentation, and physical make-up. Results showed that the materials were rated “very acceptable” by both the school head and Mathematics teachers, indicating their suitability for classroom use. The study concludes that the developed support learning materials can effectively address the identified weaknesses of Grade 3 learners and contribute to improving their overall performance in Mathematics.

This article, based on an analysis of the results of the All-Russian Mathematics Assessment, presents identified student deficiencies. It also provides methodological recommendations for improving the quality of mathematics education in primary schools, helping to prevent difficulties in mastering a number of mathematical topics presented in the assessments, which less than 40% of students completed correctly. Particular attention is paid to the problem of low skills in solving word problems and logical problems. These methodological recommendations are intended for various categories of educators: primary school teachers, specialists from institutions of continuing professional education, heads of methodological associations, and teachers from educational institutions with low learning outcomes.

East Asian students consistently outperform their global peers in international mathematics assessments such as PISA, yet the key contributing factors remain under debate. This study investigates the determinants of East Asian students’ superior mathematics achievement using a machine learning approach applied to PISA 2018 data across 77 countries and economies. Our analysis incorporates a wide range of student-, school-, and country-level variables and employs gradient boosting to model complex, nonlinear relationships between predictors and mathematics test scores. The results reveal that variables such as mathematics learning time, repetition rates, ICT use outside of school, early childhood education, class size, and school size significantly contribute to the performance advantage of East Asian students. In addition, cultural factors—including a greater emphasis on independence, responsibility, thrift, and long-term orientation—are also strongly associated with higher performance. The machine learning framework allows us to assess the relative importance and marginal effects of each variable without imposing functional form assumptions. This study contributes to the literature by identifying predictive features of mathematical achievement using a flexible, data-driven method and by highlighting the role of educational and cultural systems in shaping learning outcomes.

This study aimed to develop an authentic mathematics assessment for elementary schools in the form of a testlet-based instrument integrated with deep learning principles and the Adiwiyata context within the framework of transformative Islamic education in the Special Region of Yogyakarta. Employing basic research with an embedded mixed-methods design, the development process adapted the Plomp model and the instrument development framework of Oreondo and Antonio. Data were collected through teacher needs surveys, expert validation, readability testing, and field trials involving 462 fifth-grade students from elementary schools and Islamic elementary schools. Quantitative analyses included Content Validity Index (CVI), Aiken’s V, Cronbach’s Alpha, Classical Test Theory (CTT), and Item Response Theory (IRT) using the 2-PL Graded Response Model. The results indicate that the developed instruments meet acceptable psychometric standards, with Aiken’s V values ranging from 0.75 to 1.00 and high internal consistency for both the testlet instrument (Cronbach’s Alpha = 0.845) and the environmental awareness questionnaire (Cronbach’s Alpha = 0.850). Item analysis shows adequate discrimination and a structured progression of difficulty, although one item exhibited low discrimination in the 2-PL GRM, highlighting the importance of IRT-based diagnostics for testlet refinement. Descriptive findings reveal that students demonstrate high levels of environmental awareness, particularly in the knowledge and attitude dimensions, while mathematical achievement remains low on non-routine items. Correlation analysis shows no significant relationship between environmental awareness and mathematical ability. Methodologically, this study contributes a validated and contextually grounded assessment framework that integrates expert judgment, reliability analysis, and complementary CTT–IRT procedures. Theoretically, the findings reconceptualize authentic assessment as a diagnostic bridge rather than a direct causal link between affective values and cognitive performance, demonstrating that environmental concern functions as a potential cognitive resource only when explicitly activated within mathematical tasks.

We illustrate the use of exploratory latent class analysis (LCA) in item development or item adaptation. In particular, we focus on the use of LCA as a method for justifying the assumption that the target construct reflects a latent continuum, a key assumption in both classical test theory (CTT) and item response theory (IRT) analyses. We show how LCA statistics, in particular contrasts of predicted probabilities for each item based on the logic of Kelley's discrimination index, are informative about whether items behave in a manner consistent with the assumption of a latent continuum. LCA is particularly valuable because it makes relatively minimal assumptions and can cope with important design issues, such as planned missingness or mixed item types, that confound CTT. Moreover, LCA output is understood more readily by nontechnical stakeholders such as content experts, teachers, or clinicians than the results of most IRT analyses. For simplicity, we focus on binary scored test items, although extensions to polytomous data are not difficult. To illustrate, we use simulated data that mimic two pilot studies of a prototype mathematics assessment. Our code is available for readers who want to run their own examples. (PsycInfo Database Record (c) 2026 APA, all rights reserved).

Abstract Cognitive Diagnostic Models (CDMs) provide fine‐grained diagnostic feedback, but their central component—the Q‐matrix—remains costly and labor‐intensive to construct. This study explores the automated generation of Q‐matrices using general‐purpose AI, including ChatGPT‐4o, Gemini‐2.5‐pro, and Claude‐sonnet‐4. We evaluated two prompting strategies (all‐at‐once and one‐by‐one) across TIMSS 2007, TIMSS 2011, and PISA 2012 mathematics assessments. Results show that AI‐generated Q‐matrices approximate human baselines with competitive model fitting performance (AIC, BIC, log‐likelihood, and SRMSR) and acceptable classification discrepancies. While AI predictions for larger and more complicated assessments (TIMSS 07 and 11) were generally sparser than human‐generated Q‐matrices, they still achieved equal or better fit statistics under most CDMs. In contrast, for the smaller and less complicated PISA 2012 assessment, AI‐generated Q‐matrices matched human density and fitting quality. Importantly, chatbot‐human matching accuracy remained high across models, with Gemini benefiting from all‐at‐once prompting, ChatGPT‐4o maintaining stable performance under both strategies, and Claude showing sensitivity to prompt structure. These findings highlight both the promise and current limitations of automated Q‐matrix generation, underscoring opportunities for integrating LLMs into scalable diagnostic assessment practices.

This study investigated the influence of administrative and professional support on the teaching attitudes of junior high school mathematics teachers. The inquiry was undertaken in response to persistent challenges in mathematics performance and the varied implementation of assessment initiatives, particularly the Rapid Mathematics Assessment (RMA). Employing a descriptive-correlational research design, quantitative data were collected from junior high school mathematics teachers through a researcher-made questionnaire. Descriptive statistical tools, including frequency, percentage, weighted mean, and standard deviation, were used to determine the level of administrative support, professional support, and teaching attitudes. The Pearson Product-Moment Correlation Coefficient was utilized to examine relationships among the key variables. Results revealed that the level of administrative support and professional support was generally high, while teaching attitudes toward mathematics instruction were positive. Further analysis showed a significant relationship between administrative support and teaching attitudes, as well as between professional support and teaching attitudes. Teachers who reported receiving regular guidance, constructive feedback, and sufficient instructional resources demonstrated more favorable attitudes toward mathematics teaching. In addition, professional development activities that were relevant, sustained, and aligned with classroom realities were associated with increased confidence and openness to assessment innovations such as RMA. The study concludes that both administrative and professional support significantly influence the teaching attitudes of junior high school mathematics teachers. Strengthening leadership practices and professional learning systems is recommended to enhance instructional effectiveness and improve mathematics learning outcomes.

Abstract Despite the widespread integration of ICT into education, research linking students’ everyday ICT use to mathematics performance has yielded inconsistent results. A key gap in the existing literature is the limited attention to factors such as actual digital literacy and the specific purposes for which ICT is used. This study addresses this gap by examining the relationship between students’ performance in the International Computer and Information Literacy Study (ICILS) and their results in the national mathematics assessment. The analysis is based on data from 2309 students who participated in the national mathematics assessment in fifth grade and again took both the ICILS and the national mathematics assessment in eighth grade. A structural equation model incorporating the study variables explained 43% of the variance in students’ mathematics scores. After controlling for socioeconomic status (SES) and prior mathematics achievement, the findings indicate that digital literacy significantly contributes to mathematics performance. Specifically, students with higher ICILS scores at the beginning of the school year achieved better mathematics outcomes by the end. In contrast, the frequency of ICT use for study or social communication was not linked to digital literacy or improved mathematics performance. These findings suggest that enhancing students’ ICT skills is a promising strategy for improving mathematics performance. The study highlights that growing up with digital devices does not automatically equate to sophisticated digital skills. It supports the argument that the focus of the “digital divide” should shift toward differences in the development of digital skills, rather than merely access to technology.

Psychological flexibility and inflexibility (PF/PI) are increasingly targeted in clinical and preventive interventions as processes relevant to both flourishing and distress. However, brief multidimensional measures that assess both constructs and are developmentally appropriate for children and younger adolescents remain scarce. This study investigated the dimensionality of PF/PI in early and mid-adolescence, and conducted a preliminary structural validation of a brief questionnaire for potential use in school settings. Data were drawn from a cross-sectional sample of 1,289 Finnish lower secondary school students in grades six, eight, and nine. Eighteen items adapted from the Children's Psychological Flexibility Questionnaire (CPFQ) were administered before a digital mathematics assessment. Both exploratory (EFA) and confirmatory factor analysis (CFA) with tests of measurement invariance were conducted using a split sample approach. Internal consistency was evaluated using alpha and omega coefficients, and average inter-item correlations. The iterative item retention process resulted in a three-factor nine-item solution (CPFQ-9) that met predefined psychometric criteria and was replicated with CFA. The model included two modestly correlated PF factors (1) committed action with awareness, 2) acceptance and defusion) and one largely independent PI factor (3) self-judgment and fusion). Configural, metric and partial scalar invariance were supported across grade and gender. Subscale internal consistency were questionable to borderline acceptable but average inter-item correlations were within recommended ranged for shorter scales. Findings suggest that a brief, multidimensional measure can capture developmentally relevant flexibility- and inflexibility-related processes in early and mid-adolescence. Further work is needed to establish convergent, divergent, and predictive validity, test-retest reliability, and applicability in younger age groups and contexts, before the CPFQ-9 can be considered a robustly validated, developmentally sensitive measure.

Abstract We reflect on over ten years’ experience of using the STACK computer-algebra-aided online assessment system to support the learning of large numbers of distance learning students at the UK Open University. The motivation for the use of, in particular, computer-algebra-aided assessment is discussed together with the use of formative practice quizzes to enhance learning and summative tests for assessment. We consider the challenges faced in the adoption and use of the system, as well as the successes achieved.

In this study, we present evidence for the validity of a shortened form of the Quantitative Reasoning for College Science (QuaRCS) Assessment, a validated instrument assessing the numeracy and math-related affect of undergraduate students in general education/introductory science courses. Previously published analyses of QuaRCS data revealed that 1) roughly 30% of students found the assessment boring, leading to lower self-reported effort and 2) affective factors (e.g. numerical self-efficacy) were significant predictors of QuaRCS score. As a result, we reduced the length of the assessment from 25 to 15 quantitative items, and expanded the affective variable selection from three to eight to include math related anxiety, situational math affect, sense of belonging, growth mindset and metacognition. We administered the abbreviated assessment ("QuaRCS light") to roughly 15,000 students across 18 institutions and validated it with classical test theory and item response theory based methods. We found, despite a modest decrease in reliability, students' effort scores were significantly higher on QuaRCS light, justifying this tradeoff. In addition, we validated the new affective factors using exploratory and confirmatory factor analysis. When included in a linear regression model as predictors of QuaRCS score, these 8 factors explain 31% of the observed score variance, increasing to 49% when student confidence, effort, and calculator usage are included. Our findings emphasize the importance of affective factors in understanding and fostering numeracy, and this work informs the design of more holistic and effective assessments that are appropriate for assessing numeracy in diverse student populations.

This study evaluated teachers’ instructional practices and their effect on the mathematics performance of Grade 6 learners in Mauro Diaz Elementary School, Tubajon District, Division of Dinagat Islands, during School Year 2025–2026, as basis for a proposed intervention program aligned with DepEd’s learning recovery thrust. A descriptive–correlational design was employed with 131 Grade 6 learner-respondents, while teachers joined the instrument tryout for reliability. Data were gathered using validated survey questionnaires covering gamification, use of manipulatives, visual representations, and peer-assisted learning, including learners’ appreciation, plus Rapid Mathematics Assessment (RMA) pretest and posttest results. Frequency, percentage, weighted mean, paired-samples t-test, and Spearman rho were used for analysis. Results showed that in the RMA pretest, 46.56% of learners were at Low Proficiency and 45.80% were Not Proficient. Learners rated teachers’ practices as Very Strong across domains and expressed Very Satisfied appreciation overall. Posttest performance improved, with 45.04% reaching Nearly Proficient and no learner remaining Not Proficient; the pretest–posttest difference was significant (t=29.913, p=.000). Correlation analysis, however, indicated very weak and non-significant relationships between each instructional practice and posttest performance (ρ=−.074 to .093). This shows that learning improvements of a learner was basing on what they already know, how ready they are to learn, and the support they received at home and school. The ENHANCE -MATH 6 program is highly recommended to use to strengthened targeted remediation, intensify the concrete-representational-abstract transition, standardize peer tutoring with coaching and feedback and to deepen home-school support through parents-teacher orientation based on these study findings.

The use of varied teaching strategies in mathematics has been recognized as a promising approach to enhance the teaching and learning process, providing students with meaningful and engaging learning experiences. In line with this, the present study investigated the effectiveness of Contextualized Learning Activity Sheets (cLAS) compared to DepEd-provided Self-Learning Modules (SLMs) in improving the mathematical performance of Grade 9 students at Carrascal National High School. The study was motivated by the recent Rapid Mathematics Assessment (RMA) results, which indicated that over 50% of Grade 9 learners were classified as low proficient, highlighting the need for targeted instructional interventions.

This study aims to investigate the relationship between internal and external assessment in Mathematics and English subjects based on grades for students appearing in the Secondary Education Examination (SEE) in Diktel Rupakot Majhuwagadhi Municipality (DRMM), Khotang District, Koshi Province, Nepal. The study employed a quantitative research design. Using Cluster random sampling technique among seven schools out of 24 secondary schools of DRMM.The data have been processed and analyzed using SPSS 16 software. The study found that A larger number of A+ and A grades is noticed in internal/practical assessment, but other grades, B+, B, C+, C, D and NG, are more visible in external assessment of Mathematics and English subjects for SEE. It shows of grade inflation in internal and external assessment. The average GPA of internal assessment is higher than the external assessment in Mathematics and English subjects. Two hypotheses were formulated and tested at p < 0.05, using Pearson-Product product-moment correlation Coefficient. It is found that there is a low degree of positive correlation between internal assessments and external assessments of class 10 Compulsory Mathematics and English subjects for SEE in Khotang district, Nepal. Represented samples were selected so the results cab be generalized through out the municipality. Regular workshops should be organized for the teacher of secondary level school to conduct internal assessment supervision mechanisms, to form to maintain predictive validity of the assessment.

Teacher Competencies (TC), as a pivotal dimension of teacher effectiveness influencing teachers' professional growth, has gained prominence in recent teacher education research. This article aims to define TC through literature review, examine the current status and future directions of TC research. Analyzing 1117 SSCI-indexed articles from the Web of Science database (2000-2023), a bibliometric analysis was conducted, exploring research areas, journals, countries, affiliations, authors, citations and keywords. The results, corroborated by the Mann-Kendall trend test, highlight a robust and influential Teacher Competencies literature indicating growing interest, with a notable increase in publications, especially in 2021-2022. While the United States of America leads the way, contributions from Germany, Spain, China, and Turkey show global participation. The findings affirm sustained growth, emphasizing the field's dynamism, global collaboration and a solid foundation. Among the influential authors, Pantic, Krueger, Pekrun, Blömeke and Kaiser stand out; “Sustainability”, “Zeitschrift für Erziehungswissenschaft” and “Teaching and Teacher Education” stand out as the most prolific journals, and the most citations are mainly concentrated in “Teaching and Teacher Education”. Leading institutions include ‘Nanyang Technological University’, ‘Humboldt University’ and ‘Hong Kong University’. Diverse keywords signify comprehensive expertise, reflecting the field's multidimensionality. As a result of the thematic clustering analysis conducted with VOSviewer, six keyword clusters were identified: ‘higher education and teacher training in the context of COVID-19’, ‘teacher education and professional development for sustainable STEM Teaching and creativity’, ‘assessment of competencies in preservice teachers’, ‘formative assessment in mathematics teacher professional development’, ‘teacher competence in science education and preparation’ and ‘motivation and self-efficacy in technology’. In summary, this study confirms the dynamic and globally collaborative nature of TA research and offers insights for future research. Therefore, it is recommended that future studies focus on prominent themes such as digital competence, self-assessment, sustainable teacher education, and cross-cultural comparisons. Furthermore, fostering greater interdisciplinary and international collaboration in teacher education will increase the scope and impact of the field.

Background. In the era of digitalization, maintaining resilient security systems in agro-industrial enterprises is crucial. This paper examines approaches to developing intelligent models aimed at assessing and predicting the resilience of organizational and technical systems based on the analysis of interrelated risk factors. Cognitive and fuzzy modeling approaches are applied as methodological tools to formalize expert knowledge and support managerial decision-making. A methodology for constructing an integrated resilience indicator that takes into account both external and internal dynamics is proposed. Scenario analysis demonstrates the potential of intelligent algorithms to model critical situations and to select optimal response measures. The developed models can be applied to strengthen infrastructure protection strategies, enhance information and physical security, and ensure the sustainable operation of enterprises in uncertain environments. The aim of the study is to develop and verify a model based on fuzzy cognitive maps (FCMs) for the mathematical assessment of the resilience of agricultural enterprise security systems. The work aims to integrate expert knowledge, scenario modeling, and dynamic visualization of system behavior under changing external and internal factors. Materials and methods. The methodological framework of the study is based on cognitive and fuzzy modeling, simulation, and machine learning. FCMs are used as tools, accounting for uncertainty, the subjectivity of expert assessments, and nonlinear relationships between factors. Logistic Regression, Random Forest, and XGBoost algorithms, implemented in Python, were used for computational experiments. The analysis was conducted using the IGLA package for constructing cognitive models and assessing impact scenarios. Results. An intelligent security system resilience model was developed, incorporating five key concepts: financial resilience, human resources, technological reliability, information security, and organizational processes. Scenario modeling was conducted to identify the impact of various management strategies on the integrated resilience indicator. Scenario simulations revealed that an integrated approach can increase overall system resilience by 15–20% compared to isolated security improvements. Machine learning experiments achieved a high classification accuracy (up to 0.98) across all models, with logistic regression providing the best balance between precision and recall. Conclusion. Intelligent models based on fuzzy cognitive maps and machine learning methods provide effective assessments of the resilience of security systems in agricultural enterprises. The proposed approach allows for the consideration of uncertainty, modeling threat scenarios, and improving the adaptability of security systems. The practical significance of this work lies in the potential application of the developed models to improve infrastructure protection strategies, enhance information and physical security, and ensure the stable operation of enterprises in uncertain environments. EDN: LNXZMQ

Assessments for the General Certificate of Secondary Education (GCSE) are typically taken at the end of compulsory secondary education. They are considered high-stakes examinations because access to further education and employment is often dependent on performance at GCSE. Despite this significance, GCSE students have historically not been given opportunity to share their views on assessments. This UK-based research reports findings from part of a survey that explored the changes students would wish to make to the assessment of GCSE English, Mathematics, and Science. Areas of focus were informed by the researcher’s preliminary research involving a focus group with GCSE students. Three-hundred-and-fifty-one Year 11 students completed an online survey. Open-ended questions were analysed using content analysis. Descriptive statistical analyses were completed on Likert-scale item data. Participants indicated different changes for GCSE English, Mathematics, and Science. The most prevalent desired change was for GCSE English examinations to be open book. The largest proportion of respondents indicated for Mathematics to stay as it is. For GCSE Science, the most prevalent responses were for several ‘smaller’ exams throughout the year and a combination of assessment types (e.g. exams with coursework and ‘controlled assessments’). Frequency and length of survey responses demonstrates students’ motivation to contribute to this area. Grounded in the student experience, this study offers valuable insights that contribute to broader discussions across schools, examination boards, and educational policy.

This study examined the implementation strategies, challenges, and effectiveness of the Rapid Mathematics Assessment (RMA) as a formative assessment tool intended to enhance learners’ mathematical competence, as facilitated by teachers in the Panganiban District, Schools Division of Catanduanes. Guided by Black and Wiliam’s (2023) Formative Assessment Theory and Vygotsky’s Constructivist Learning Theory (Kaur & Natarajan, (2022), the study utilized a descriptive-correlational quantitative design to determine how RMA strategies, covering assessment design, frequency, feedback, and instructional integration, relate to perceived effectiveness and encountered challenges. Data were gathered from 71 mathematics teachers across twelve public schools using a validated researcher-made questionnaire. Statistical analyses included weighted mean and Pearson correlation. Results revealed that teachers “highly implemented” the RMA (GWM = 3.62), with assessment design and feedback rated as highest. Despite frequent challenges (GWM = 3.51), such as learner readiness, workload, and time constraints, teachers perceived the RMA as “very effective” (GWM = 3.51) in enhancing mathematical proficiency, conceptual understanding, problem solving, and real-life application. Significant positive correlations were found between implementation strategies and both challenges (r = 0.721) and effectiveness (r = 0.648), but challenges showed no significant correlation with effectiveness (r = 0.053). These findings highlight teachers’ resilience and adaptive capacity in sustaining RMA effectiveness despite contextual limitations. The study concludes that effective and consistent implementation of formative assessment strategies directly strengthens mathematical learning outcomes. A strategic intervention plan was developed to improve RMA application through targeted professional development, resource provision, and feedback driven instructional integration.