This study compares experts' and teachers' conceptualization of pedagogical content knowledge (PCK). The study participants included teachers (n=20) enrolled in a graduate mathematics education course on PCK. Participants responded to two open-ended questions: a) describe in your own words what PCK is; b) provide an example of PCK. The responses were collected, qualitatively and quantitatively analyzed, and then compared to those suggested by experts to identify and describe the similarities and differences between teachers’ and experts’ conceptualizations using the Pareto analysis. Experts’ and teachers’ PCK components ranking was analyzed using the nonparametric Mann-Whitney U test. Even though the results of the quantitative analysis were not significant (e.g., the observed U-value is 32 whereas the critical value of U at p < .05 is 13), the qualitative discussion on the differences between expert and teachers’ ranking suggests insightful interpretation of priorities among PCK components across the two groups.

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.

Research consistently highlights the importance of promoting creativity in curricula worldwide and within school settings. However, teachers often fail to recognize mathematical creativity (mainly described and evaluated through fluency, flexibility, originality, and elaboration) and are usually ill-prepared to enhance it in their students. Few studies have incorporated educational programs focused on mathematical creativity, showing positive results in enriching participants' knowledge and perception of creativity. Nevertheless, participants' teaching practices were not observed, leading to uncertainty about whether these participants could integrate opportunities for students’ development of mathematical creativity in their lessons. In this qualitative study, we attempt to bridge this gap by observing teachers' practices before and after an intervention focused on mathematical creativity. Seven in-service primary school Greek teachers participated in the study. Their teaching practices were examined through classroom observation, using an observation protocol, before and after their voluntary participation in an educational program aimed at enriching their knowledge of mathematical creativity and their ability to cultivate it in the classroom. Observational data were coded and analyzed using thematic analysis. Results showed that prior to the intervention, participants sparsely employed creativity-fostering approaches in their teaching. However, after the intervention, they significantly increased the time spent on creativity-provoking tasks, utilizing various creativity-promoting approaches and primarily focusing on developing fluency, flexibility, and generating new knowledge. Nevertheless, they did not significantly develop their skills in originality and elaboration, indicating the need for further support in cultivating these aspects of creativity. Future implications for professional teacher training and mathematics textbook writing are discussed.