Spatial ability is a fundamental component in geometry learning and a critical skill for prospective mathematics teachers. However, traditional instructional methods often fall short in fostering students’ spatial reasoning, especially in higher education contexts. This study aimed to investigate the effect of an instructional model integrating Project-Based Learning (PjBL) with ethnomathematics on the spatial ability of pre-service mathematics teachers. Employing a quasi-experimental one-group pretest–posttest design, the study involved 30 participants who received geometry instruction through PjBL with cultural integration. The findings revealed a substantial improvement in students’ spatial ability, indicating that the intervention was both effective and meaningful. The integration of culturally grounded projects enhanced students’ visualization, mental rotation, and engagement. These results support the use of ethnomathematics-based PjBL as an innovative and contextually relevant approach to improving spatial reasoning in mathematics teacher education. Future research is recommended to investigate the long-term effects and adaptability of this model in various educational settings.

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.