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.

Learning to teach mathematics has become crucial since its application in real life cannot go unmentioned. The desire of mathematics education researchers to make mathematics concepts easier for pre-service teachers to easily understand has attracted attention. This has become indispensable since after college, pre-service teachers are deployed from K-12 to assist learners in understanding mathematics concepts. The study aimed to ascertain how improvement in the learning of mathematics concepts using the Problem-based learning (PBL) approach could be understood and/or explained among pre-service teachers. This was viewed in two folds: how improvement in learning outcomes using the PBL approach could be explained; and how pre-service teachers’ disposition about the PBL could be explained/understood. Exploratory case study design involving qualitative and quantitative data was concurrently gathered and used. This involved the use of data collection instruments such as focus group discussion, pre-post-test scores, PBL observation protocol, and PBL disposition questionnaire. The study showed that the PBL method improved the learning of mathematics concepts among pre-service teachers. Pre-service teachers also showed a positive disposition (interest, belief, and attitude) toward the PBL intervention. The authors advocated for the conduct of a longitudinal study to understand the direction of change over time.

In the domain of engineering education, the crucial role of mathematics, especially Calculus, cannot be overstated, as it lays the foundational groundwork for numerous sciences, technology, engineering and mathematics (STEM) courses. The integration of mathematics into STEM disciplines is achieved through the practical application of mathematical concepts in real-world scenarios or in conjunction with other STEM subjects, thereby enhancing the coherence of engineering studies and acting as a significant motivational catalyst for students. This paper presents an analytical narrative of a practical mathematics assignment, woven into the Calculus curriculum and other STEM courses from 2013 to 2018. It delves into the potential impacts of these practical assignments on student performance and attitudes by evaluating data sourced from final exam scores and anonymous course surveys, both before and after the intervention period. Through the analysis of an extensive dataset comprising 1526 final exam scores, this study endeavors to make a substantive contribution to Future Technology Studies (FTS), focusing on the strategic harmonization of mathematics and STEM courses to enrich the educational experience and foster a more cohesive and applied learning framework in these disciplines.

Science, magic, and education have always been linked, from science-based magic shows to teachers presenting demonstrations as magic tricks to capture their students’ interest and provide a mnemonic reference for the topics under discussion. Magic as an art form is also often used to convey information or act as an analogy for invisible phenomena. This study examined how the use of a magic effect designed as an analogy for active and passive transport in cells affected student scores and perception of the activity when compared to a standard story analogy in a high school integrated science course. To determine this, students participated in either a magic-based analogy activity (MBAA) or a concrete story-based analogy activity (SBAA), and then data was collected and analysed using a pre-test/post-test for the content and a Likert-scale anonymous survey for the student perception of the activity. The MBAA was shown to be similar to the SBAA in helping students learn but had the added benefit of increasing students’ reported engagement with the activity. This study shows how bringing magic into the science classroom can have a positive impact on student engagement and provides teachers with another option to support student learning.

Research shows that learning enjoyment in specific socio-scientific issues (SSI) plays an important role in predicting grade 10 students’ learning interest and learning enjoyment (i.e., genuine interest) in SSI subjects generally. However, it remains unexplored whether learning enjoyment also mediates a predictive effect of learning interest in a Big Science SSI of pressing contemporary global concern—COVID-19—on grade 12 high school students’ learning interest in SSI generally. The purpose of this study is to investigate how learning enjoyment may mediate the predictive effect of learning interest in the specific Big Science SSI of COVID-19 specifically on students’ learning interest in SSI subjects generally. Latent variable modeling using data collected from grade 12 students (N = 691) showed personal perceptions of learning enjoyment in SSI partially mediated the predictive effect of learning interest in the SSI of COVID-19 on learning interest in other Big Science SSI subjects. Implications for promoting among science educators and policy specialists the active development of students’ individual interests and involvement in other 21st century Big Science SSI challenges are forwarded. 

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 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.