The study investigated the impact of YouTube video assisted instructions (YVAI) on pre-service teachers’(PSTs) attitudes and academic performance in chemistry classroom. A quasi-experimental design was adopted for the study. One hundred and twenty (120) Pre-Service Teachers (PSTs) pursuing primary education programme constituted the participants of the study. Sixty (60) PSTs each were non-randomly assigned to the Experimental Group (EG) and Control Group (CG). Data on PSTs’ attitude and performance were collected with PSTAS and GCPT respectively. The SPSS software version 20 was used to analyse the data to generate descriptive and inferential statistics. A non-parametric analysis was used in the inferential statistics. The attitude means rank (MR=78.62) of EG (U = 713.000, Z=-6.924, p <.001) was statistically higher than CG (MR=42.38) (U = 713.000, Z=-6.924, p <.001) after treatment. The EG after treatment recorded a mean rank (80.86) statistically higher than CG (40.14), U = 578.500, Z = -6.441, p <.001 after treatment. YVAI was proven as an effective instructional strategy that enhances learners’ altitudinal changes and performance. The study recommended the use of YouTube technological-driven instructions to support classroom instructions.

Scaffolding dialogue is a concept in learning that refers to the support or assistance given to individuals during the dialogue process. The main objective of this research is to create a basic structure of dialogue to help and support students during the learning process in improving their algebraic reasoning skills. Algebraic reasoning is a process in which students generalize mathematical ideas from a certain set of examples, establish these generalizations through argumentative discourse, and express them in a formal and age-appropriate way. The study was designed using the grounded theory qualitative model method, which used three sequential steps: open coding, selective coding, and theoretical coding. The research was conducted on students of the mathematics education department at Universitas Islam Sultan Agung. Data collection methods include algebraic reasoning ability tests, questionnaires, and interviews. Data analysis in grounded theory is an iterative and non-linear process that requires researchers to constantly move back and forth between data collection and analysis. This process aims to produce a theory that is valid and can explain phenomena well based on empirical data obtained during research. The dialogue scaffolding strategy framework in improving students' algebraic reasoning abilities includes instructing, locating, identifying, modeling, advocating, exploring, reformulating, challenging, and evaluating.

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.

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.

This study examines the validity of the Force Concept Inventory (FCI) in Ugandan secondary schools using Item Response Curves (IRCs) and provides a comparative evaluation of its effectiveness across different educational contexts. The survey focused on Senior Four students preparing for the Uganda Certificate of Education (UCE) examinations, with a representative sample of 941 students (aged 15–17) selected through a multi-stage sampling technique. The initial analysis employed Classical Test Theory (CTT) metrics before the detailed analysis of IRCs for the FCI items. The CTT evaluates item-level and whole test statistics like item difficulty level, discrimination index, and reliability. The CTT indices revealed that the FCI was highly challenging, with an average score of 5.76 out of 30 and a low-reliability coefficient (α = 0.15). Additionally, 73.3% of the items showed poor discrimination, and some distractors were ineffective. The detailed analysis of IRCs showed that several FCI items are inefficient in the context of the Ugandan education system. The IRCs also demonstrated a widespread choice of distractors for many items, with overall scores falling below the threshold indicative of a generally agreed-upon understanding of Newtonian physics. Comparative analysis from other global contexts studies suggests that language barriers, curriculum differences, and instructional methods influence student performance. These findings underscore the necessity of adapting the FCI tool to better fit local educational contexts and implementing additional instructional strategies to enhance conceptual understanding. A more culturally and contextually adapted diagnostic tool may improve physics education and better assess students’ conceptual comprehension of force and motion within the region.

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.