International Journal of Science and Mathematics Education最新文献

This meta-analysis explores the impact of informal science education experiences (such as after-school programs, enrichment activities, etc.) on students' attitudes towards, and interest in, STEM disciplines (Science, Technology, Engineering, and Mathematics). The research addresses two primary questions: (1) What is the overall effect size of informal science learning experiences on students' attitudes towards and interest in STEM? (2) How do various moderating factors (e.g., types of informal learning experience, student grade level, academic subjects, etc.) impact student attitudes and interests in STEM? The studies included in this analysis were conducted within the United States in K-12 educational settings, over a span of thirty years (1992–2022). The findings indicate a positive association between informal science education programs and student interest in STEM. Moreover, the variability in these effects is contingent upon several moderating factors, including the nature of the informal science program, student grade level, STEM subjects, publication type, and publication year. Summarized effects of informal science education on STEM interest are delineated, and the implications for research, pedagogy, and practice are discussed.

Engaging in argument from evidence is a fundamental science practice. However, preservice elementary teachers have difficulty constructing arguments. They need effective experience with argument construction in science. Written argumentation is crucial in the process of science learning. One of the approaches for learning science through argumentative writing is the science writing heuristic. However, only a few studies have investigated preservice science teachers’ argument construction experiences with science writing heuristics. None of them involved preservice elementary teachers. Therefore, this study aimed to investigate preservice elementary teachers’ understanding of argument components and the effect of the science writing heuristic on their quality of written arguments. A mixed-methods design was used in this study. The research was carried out for 10 weeks during the Science Laboratory Practices course. A total of 57 preservice teachers participated in nine laboratory experiments. They completed 409 laboratory reports structured based on the science writing heuristic. The scores were analyzed through a mixed effect model. Additionally, a questionnaire was used to investigate the participants’ understanding of the argument components. The data were analyzed through content analysis. The analysis indicated that the science writing heuristic improved participants’ written argument quality over time. It can be concluded that this approach is effective at improving the quality of written arguments. In addition, although most of their understanding of argument components is aligned with expectations, there are several shortcomings as well. This study contributes to the literature by facilitating the effective engagement of preservice elementary teachers in argumentation through science writing heuristics.

The COVID-19 pandemic has prompted pre-service teachers to assume various teacher roles in distance education, necessitating a diverse range of competencies. However, pre-service mathematics teachers have expressed the need for professional support to enhance their preparation for future teaching responsibilities. This study explores the impact of a designed training program on pre-service mathematics teachers' self-assessment of their knowledge regarding teacher roles in distance education. The training course comprised seven sessions dedicated to instructional design, technology integration, pedagogical strategies, classroom management, facilitation, social interaction, and evaluation. Additionally, three sessions provided support for participants in designing their micro-teaching activities, followed by four sessions of micro-teaching with peer assessment. Data collected through questionnaires, interviews, micro-teaching materials, and rubrics were analysed using t-tests and content analysis. The results demonstrate that the implemented training program, incorporating micro-teaching and peer assessment, significantly enhanced pre-service mathematics teachers' perceived competence in various teacher roles. Consequently, we recommend the integration of these methods into teacher training programs as valuable pedagogical approaches.

Artificial intelligence (AI) shows increasing potential to improve mathematics instruction, yet integrative quantitative evidence currently is lacking on its overall effectiveness and factors influencing success. This systematic review and meta-analysis investigate the effectiveness of AI on improving mathematics performance in K-12 classrooms compared to traditional classroom instruction. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, we searched five databases from 2000 through December 2023, synthesizing findings from 21 relevant studies (40 samples) which met screening criteria. Results indicate a small overall effect size of 0.343 favoring AI under a random-effects model, showing a generally positive impact. Only one variable, AI type, was identified as having moderate effects, with AI demonstrating a greater impact when served as an intelligent tutoring system and adaptive learning system. Our findings establish an initial knowledge base for implementation and future research on the effective integration of AI into K–12 mathematics classrooms. This study also focuses on the appropriateness across age, mathematical contents, and AI design factors is aimed at further advancing the judicious adoption and success of classroom AI integration.

This study investigates Contemporary Mathematical Instruction Competence (CMIC) using the PISA 2022 dataset. The research aims to identify the underlying dimensions of CMIC and assess their consistency across different cultural contexts. Variables were selected from teacher surveys in PISA 2022, focusing on mathematical reasoning, cognitive competencies, ICT use, and teaching goals. Data manipulation, cleaning, and factor analysis were performed in R. Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) were conducted to validate the construct. EFA results indicated a well-defined two-factor structure: Technological and Collaborative Competence (TCC) and Cognitive and Pedagogical Competence (CPC). CFA confirmed this structure, with fit indices showing an excellent model fit (CFI = 0.984, TLI = 0.976, RMSEA = 0.046). Cross-cultural validation demonstrated the robustness of the CMIC model across nine countries: Australia, Brazil, Colombia, Kosovo, Korea, Malaysia, Panama, United Arab Emirates, and the United States. Partial scalar invariance was achieved, indicating acceptable model fit. These findings highlight the importance of integrating technological and cognitive competencies in mathematics instruction and suggest that CMIC is a relevant construct across diverse educational settings. Future research should explore further cross-cultural validations and the impact of educational policies on CMIC development.

While national curricula in science education highlight the importance of inquiry-based learning, assessing students’ capabilities in scientific inquiry remains a subject of debate. Our study explored the construction, developmental trends and validation techniques in relation to assessing scientific inquiry using a systematic literature review from 2000 to 2024. We used PRISMA guidelines in combination with bibliometric and Epistemic Network Analyses. Sixty-three studies were selected, across all education sectors and with a majority of studies in secondary education. Results showed that assessing scientific inquiry has been considered around the world, with a growing number (37.0%) involving global researcher networks focusing on novel modelling approaches and simulation performance in digital-based environments. Although there was modest variation between the frameworks, studies were mainly concerned with cognitive processes and psychological characteristics and were reified from wider ethical, affective, intersectional and socio-cultural considerations. Four core categories (formulating questions/hypotheses, designing experiments, analysing data, and drawing conclusions) were most often used with nine specific components (formulate questions formulate prediction/hypotheses, set experiment, vary independent variable, measure dependent variable, control confounding variables, describe data, interpret data, reach reasonable conclusion). There was evidence of transitioning from traditional to online modes, facilitated by interactive simulations, but the independent tests and performance assessments, in both multiple-choice and open-ended formats remained the most frequently used approach with a greater emphasis on context than heretofore. The findings will be especially useful for science teachers, researchers and policy decision makers with an active interest in assessing capabilities in scientific inquiry.

The aim of this study was to determine how 5-year-old children identified the functional relationship of correspondence, and whether or not they generalized when working on a task that involved programmable robots. We conducted this study with 15 children (9 girls and 6 boys) in their last year of preschool education. The study was designed around a generalization task that involved the function f(n)=n+2. Our findings indicate that nine of the children identified the correspondence relationship and five children generalized, three of them correctly.

Considering the interdisciplinary nature of the sustainable development concept, this study aims to investigate the effect of a cross-curricular mathematical modeling course on pre-service teachers’ sustainable development attitudes and mathematical modeling self-efficacies and to investigate their opinions about the course. The sample for this mixed-method study with concurrent triangulation design was 44 pre-service mathematics teachers who were enrolled in a university from the western region of Türkiye. The data for the study is gathered through the sustainable development attitude scale, the mathematical modeling self-efficacy scale, and open-ended questions administered before and after the cross-curricular mathematical modeling course. Findings and analysis of the quantitative and qualitative data revealed that pre-service teachers showed a statistically significant improvement in both sustainable development attitude and mathematical modeling self-efficacy scores. Their statements from open-ended questions also supported the quantitative findings.

Although culturally responsive mathematics teaching is important, post-secondary education for preservice teachers (PTs) does not typically lead to learning opportunities for them to use mathematics to recognize the roles of social agents. To address this issue, we created a culturally responsive mathematical modeling task in which we invited PTs to use diverse approaches to create an action plan for the handling of local pothole data and maintenance. This study explores the approaches that PTs take when generating solutions to solve a culturally responsive mathematical modeling task and to investigate the perceptions of preservice teachers towards the task. The study involved 41 PTs, most of whom had no prior experience with mathematical modeling before participating in the task. PTs compared and inspected the documented data and noticed problems, such as a large economic disparity in the city. The PTs drafted solutions and shared their findings and suggestions in a proposal to the City’s Public Works Department. The proposals reflected different approaches, which helped the PTs understand the large income disparity and inequities certain neighborhoods in the city experience and provided recommendations for the city to address these issues. The creation of a culturally responsive mathematical modeling task provided an opportunity for PTs to engage in critical thinking and problem-solving while using diverse approaches to address a local social justice issue. This study provides insights into effective strategies for promoting socially responsible mathematics education in teacher preparation programs.

This study aimed to develop a comprehensive diagnostic tool for assessing upper-secondary school students’ understanding of isomers, expanding upon existing two- and three-tier conceptual diagnostic methods. By incorporating ‘Confidence Rating Factor’ tiers within the answer and reason sections, a four-tier test was designed and developed. This test was utilized to evaluate students’ comprehension of the isomeric conceptual framework and to identify prevalent misconceptions in terms of quantity, complexity, and typicality. The initial phase involved evaluating the reliability and content validity of the developed test before its distribution, resulting in a total of 385 effective test returned for analysis. Data analysis focused on descriptive statistics of students’ scores across each tier and dimension, supplemented by unstructured interviews to gain deeper insights. Results indicated a general suboptimal mastery of isomer conceptual understanding among upper secondary school students. Notably, students exhibited higher scores and confidence ratings in the answer tier compared to the reason tier. At both tiers, there was a significant positive correlation between scores and their confidence ratings. Further examination revealed varying levels of proficiency across different content dimensions, with students demonstrating the strongest grasp on the concept of isomers but facing challenges, particularly in ‘number judgment and writing’. The study identified eight misconceptions, classified as moderate, serious, and typical across four dimensions, offering valuable insights for teachers. These insights enable teacher to address students’ specific learning challenges related to isomers promptly and effectively, ultimately enhancing their understanding and mastery of the subject.