This study investigates the effectiveness of Guided Inquiry-Based Instruction (GIBI) integrated with Variation Theory in improving grade ten students’ solid geometry achievement in Debre Tabor City, Ethiopia. A quasi-experimental design involving 99 students found in three classes from three government schools assigned them randomly to three groups: Experimental Group 1 (EG1, n=30) received GIBI with Variation Theory, Experimental Group 2 (EG2, n=37) received only GIBI and the Control Group (CG, n=32) followed traditional methods. Pre- and post-tests analyzed using ANCOVA and paired t-tests revealed significant improvements, with EG1 achieving the highest scores (p = .000). Effect sizes were substantial for EG1 (Cohen's d = 1.50) and EG2 (d = 1.39) compared to CG (d = .73). The results highlight that GIBI combined with Variation Theory significantly enhances students’ solid geometry achievement, emphasizing the value of such kind of innovative teaching strategy to foster students’ achievement in similar educational contexts. 

We aimed to explore how Early Childhood (EC) preservice teachers (PSTs) choose and apply content-specific mathematics and science standards by analyzing two sets of lesson plans and two transcripts from whole class discussions from an EC mathematics and science methods course. From our analyses, we identified major themes and explanatory categories that indicated issues related to PSTs’ standards selection process. Students’ reasoning about their choices illustrated the resiliency of their beliefs about teaching and learning EC mathematics and science, and how their own observation experiences prevailed over our explicit instruction and assignment expectations. Drawing from literature related to Lortie’s (1975) Apprenticeship of Observation, we use our findings to consider ways to better appreciate and mitigate the strength of PSTs’ incoming beliefs on their readiness to plan for and implement lessons. 

This study delved into the factors affecting secondary school students’ interest to learn Mathematics. The aim was to gather insights that can inform strategies aimed at enhancing students' engagement, enthusiasm, and achievement in Mathematics education. Literature information was downloaded using databases such as Google Scholar, ERIC, Search 4 Life, Scopus, Web of Science, and Academia. Of the 129 studies obtained, 117 articles were retained after removing duplicates and studies that did not meet the themes of the study. Further filtering of studies by removing primary and higher learning school-related studies allowed the retention of 25 relevant pieces of research published between 2000 and 2024. The results from the systematic reviews analysis showed that instructional strategy, instructional materials, the importance of Mathematics, a future career in Mathematics, students’ attitudes towards Mathematics, students’ enjoyment of Mathematics lessons, teachers and parental support, and students’ perception towards Mathematics, are amongst the key factors affecting positively secondary school students’ interest to learn Mathematics.  

This study investigated the integration of artificial intelligence (AI) tools into secondary school chemistry education in Zimbabwe, assessing their impact on student engagement and academic performance. Grounded in Vygotsky’s Sociocultural Theory and Cognitive Load Theory, the research employed a mixed-methods approach within a pragmatic framework. Quantitative data were collected through pre-test and post-test assessments and structured surveys, comparing an experimental group using AI tools with a control group employing traditional methods. Qualitative data from student and teacher interviews and classroom observations were analysed thematically. ANCOVA analysis revealed a statistically significant difference in post-test scores between the experimental and control groups, F (1, 117) = 188.86, p < .005, η² = 0.617, demonstrating a large effect size of AI integration on academic performance. Students in the experimental group exhibited a mean improvement of 20%, controlling for pre-test differences. Additionally, interaction effects between AI use and gender (F (1,115) = 0.17, p = .684) as well as prior chemistry knowledge (F (1,115) = 0.05, p = .829) were not statistically significant. Furthermore, 85% of the experimental group reported higher engagement levels, confirming AI’s role in fostering motivation and conceptual understanding. AI tools facilitated personalized learning paths, interactive simulations, and real-time feedback, optimizing cognitive efficiency and deep learning. Despite these advantages, significant challenges emerged, including limited internet access, insufficient technological resources, lack of teacher training, and curriculum integration difficulties. These barriers highlight the need for strategic investments in digital infrastructure, professional development for educators, and curriculum revisions to fully integrate AI into chemistry education. The findings underscore AI’s transformative potential in STEM education within developing nations. Addressing infrastructural and pedagogical challenges is critical to maximizing AI's impact, ensuring equitable access, and fostering long-term sustainability in educational innovation.

The article investigates the impact of assessment data analysis on promoting deeper learning in Canadian high schools, specifically focusing on teachers’ flexibility in data-driven evaluation. The research contributes to the discourse on assessment practices by emphasizing the importance of authentic assessments, competency-based learning, and grading methodologies. Selected high school teachers drawn into this further study formed a fraction of the initial set of participants. Classroom practices of assessments concentrate on: (a) Freedom to facilitate deeper learning in instructing, assessing, and sustaining interest. The others are: (b) Teacher’s emphasis on competency-based (standard-based) learning to make learning appealing to students in educational spaces, and (c) Testing, collecting test score data, analyzing, and reporting students grades to present parents and school districts/boards with accurate progressive data reflective of diversity in learning. In this qualitative focus group case-study discussion, participants indicated time expended in performing critical analysis of data to grade students is burdensome, but the joy of such practice far outweighs the inherent difficulties, knowing that student success is founded on flexibility, freedom in decision-making, and being reflective as educators.

Global concern surrounds students' mathematics learning, development, and achievement. Scholarly discussions have explored various factors influencing students' mathematics performance. However, more information is needed to understand the impact of mathematics teaching styles on student outcomes in developing contexts like Nepal. This study examines the moderators of mathematics teaching styles and their influence on students' performance. To achieve this, the Teachers' Teaching Style Questionnaire (TTSQ) collected quantitative data from 469 grade nine students across 14 high schools in Kathmandu, Lalitpur, and Bhaktapur districts of Nepal. Confirmatory factor analysis, path analysis, and moderation analysis were performed to examine the effects of teaching styles on student achievement in mathematics. Key findings indicate that teaching styles, such as consideration and openness, are not significant predictors of student achievement, but rigid teaching styles can predict student achievement in mathematics. However, impact of the rigid teaching style was negative on student achievement. School type influenced the relationship between performance and considerate teaching, favoring private schools. School location influenced the relationship between considerate teaching and student performance in mathematics, favoring rural schools. Likewise, urban schools had a negative effect on the relationship between teacher openness and student performance, but rural schools had a positive effect on their relationship. Furthermore, low and high-ability students moderated the relationship between considerate teaching and student achievement, with the negative effect of low ability on considerate teaching and student performance and the positive influence of high ability on considerate teaching and student achievement. Student ability influenced the relationship between teacher openness and student performance, with a negative moderations of low and moderate ability students. The study concludes by emphasizing the importance of teacher training in teaching styles for high schools in Nepal and similar contexts.

This study investigates an integrative instructional model combining Concrete-Pictorial-Abstract (CPA), Task Analysis (TA), and the 3R strategies (relaxation, repetition, and routine) in teaching mathematics to students with learning disabilities (LD). LD is a neurological disorder that affects the capacity to acquire skills in reading, writing, and mathematics, presenting persistent challenges that traditional teaching approaches may not fully address. Through an ethnographic approach involving participatory observation of a teacher and three LD students over a semester, this study examines how the CPA model—progressing from concrete objects to pictorial aids and then to abstract concepts—can be customised to individual needs. Findings highlight that CPA is most effective when adapted to the diverse learning styles of LD students. While one student thrives with tactile tools to reinforce understanding, another becomes distracted, viewing the concrete aids as play items, and a third displays a preference for abstract reasoning without needing pictorial or tangible support. The TA framework, used to deconstruct complex tasks, enables students to engage in incremental learning steps, while the 3R approach helps foster a supportive learning environment by incorporating relaxation, routine, and reinforcement of concepts. By accommodating individual learning preferences, teachers can support diverse cognitive processes and promote meaningful progress in mathematical understanding. The study calls for educators to move beyond conventional one-size-fits-all strategies, advocating for personalised and adaptive approaches that can better meet the unique needs of LD students in mathematics education.

Comparison of mathematics textbooks between Indonesia and Singapore is one way to assess the educational process. This article provides insight into how mathematical concepts are taught and applied in problem-solving in each country. The study provides knowledge about how mathematical concepts are constructed by teachers and students and implemented in problem-solving between countries. This study aims to compare task designs in high school mathematics textbooks between Indonesia and Singapore based on the type of task, technique, technology, and theory used, with a focus on cubes and cuboids. The comparative analysis of the two books uses praxeological theory, the main construction of Didactic Anthropology Theory, with reference to epistemological model (REM) model analysis. The research results show that there are differences in the approaches, methods, and habits used in task design in the two countries. The techniques, technology and theories found in the two task designs show that Indonesian mathematics textbooks use more verification and drawing up conclusions which are influenced by perceptual techniques. Meanwhile, the task of designing Singapore's mathematics textbooks involves more direct investigations into forming students' knowledge through physical and operational techniques. The techniques, technology, and theories used in both designs influence the number of learning obstacles. Epistemological constraints occur in Indonesian textbooks and only a few in Singapore textbooks. These findings provide insight into how to build mathematical knowledge for students through good assignment design based on a country's educational character.

The infusion of indigenous knowledge in academic subjects is often problematic due to personal perceptions or little experience with indigenous knowledge in a teaching and learning environment. The aim of the research was to indicate the experiences of pre-service teachers when infusing indigenous knowledge via storytelling in Physical Science. This article reports on the personal experience(s) of pre-service teachers in training at a higher education institution where indigenous knowledge was infused into the teaching and learning of Physical Sciences. The implementation of Ethnophysics as a teaching strategy, storytelling as a teaching technique, contextualised - and project-based learning as teaching methods and approaches and reflection on experiences when implementing participatory action learning and action research indicated a transformative way to embrace indigenous knowledge in the teaching and learning of Physical Science. Stories, related to the concept of heat in physical science were collected by the pre-service teachers from trusted adult members in their local communities. The pre-service teachers analysed the stories and reported their interpretation of scientific and indigenous knowledge in the stories. Inductive, thematic analysis was used to interpret pre-service teacher reflection on the experience and the Cultural Historical Activity Theory was used to indicate an overview and the connection between different elements of the research. The participating pre-service teachers indicated that storytelling, as a teaching technique, adds value to how they interpret concepts in Physical Science related to their unique culture. The pre-service teachers gained research skills regarding qualitative research and showed the ability to identify the contribution of both scientific and indigenous knowledge.

This study explores how mentor teachers in specialized teaching areas, particularly chemistry, interact in an Online Professional Development (OPD) program. The Mentor Teacher Professional Development (MeT-PD) program was designed to improve mentoring practices by creating opportunities for collaborative learning through various online activities, such as Individual Response (IR), Interactive Individual Response (IIR), Small Group Discussions (SGD), and Large Group Discussions (LGD). Using a qualitative case study approach, the research analyzed data collected from Zoom recordings and Nearpod activity logs. The findings indicate that while LGDs were useful for interactions between facilitators and learners, they were not as effective in fostering interaction among learners themselves, mainly due to the cognitive demands and how these discussions were structured. On the other hand, SGDs seemed to foster stronger participant interaction, probably because the smaller group settings led to more valuable exchanges. These findings highlight the need of thoughtful planning of OPD activities, with particular focus on group size management and selection of suitable discussion formats to improve both interaction and learning outcomes.

Data from over 1,500 middle-grade mathematics students were used to investigate their mathematical affect and identity. Early secondary students were asked if they considered themselves mathematicians and a prompt was employed to substantiate their mathematical identity. Separating by gender and grade affiliation (6, 7, and 8), Chi-square and Z-score analyses were used to compare subgroups. Data show that the gap in male and female mathematics identity and affect is shrinking. Though progress has occurred in encouraging young women to consider themselves mathematicians, work remains. Consistent with previous research concerning the sustained and relatively permanent nature of mathematical affect/identity at grade six, in this study it appeared to become stable near grade 7 (approximately age 13). Perhaps not ironically, grade seven appears to be the age at which adolescents enter a period of successful abstract reasoning, and the age (13) aligns with the beginning of pre-algebra for many grades seven students.

This study assessed the benefits and challenges of leveraging artificial intelligence in transforming science education in public universities in Kogi State, Nigeria. The population of this study comprises 52 science educators from the four public universities in Kogi State, Nigeria. There was no sampling since the population was manageable. The study adopted a descriptive survey research design. The instrument used for data collection was an online Google Form survey questionnaire titled Benefit and Challenges of Leveraging Artificial Intelligence Questionnaire (BCLAIQ). BCLAIQ contained 36 items and underwent trial testing. Cronbach’s alpha was used to analyze the reliability value, which yielded a value of .87. Three research questions and three null hypotheses guided the study. Mean and standard deviation scores were used to answer the research questions, while inferential statistics, specifically the t-test, were used to test the null hypotheses. The study revealed that there is no significant difference between the mean ratings of male and female respondents’ opinions on the benefits and challenges of leveraging artificial intelligence in transforming science education, respectively {t = 1.98, df =50, p > .05} {t = 1.83, df = 50, p > .05}. Thus, it was recommended, among other things, that government university administrators and relevant stakeholders should subsidize, partner with tech companies, and invest in AI-powered technologies. University administrators and relevant stakeholders should prioritize AI literacy and ethics by providing diverse professional staff training on AI fundamentals.