Preservice mathematics teachers' beliefs about actions related to the use of the technological tools in teaching mathematics may affect how they are going to use them in their classroom activities. However, there is a limited evidence of what beliefs they hold on their intended actions of using technological tools in teaching mathematics. This study presents two preservice high school mathematics teachers' actional beliefs related to their intended actions in teaching geometric transformations (GTs) using Geometer's Sketchpad (GSP). The study comprised of a series of five task-based qualitative interviews with each of two senior undergraduate preservice teachers at a medium-sized public university in the Rocky Mountain Region of the United States. This study used a radical constructivist grounded theory (RCGT) with five assumptions—symbiosis, voice, cognition, adaptation, and praxis as a theoretical framework to guide the study process. The thematic findings of the study included four in vivo categories of their beliefs associated with actions of teaching GTs with GSP – assessment of student learning, engaging students in a group activity in exploring GTs with GSP, engaging students in individual activity in exploring GTs with GSP, and exploring GTs with GSP as 'suck it up and do it.' Pedagogical implications of these categories have been discussed.

Learning in STEM subjects is to a high degree based upon understanding logic, especially in subjects like mathematics. It has always been challenging to preserve the benefits of on-campus teaching and learning while digitalizing the teaching of mathematics. In this article an approach to design for a suitable online pre-calculus course is discussed, that aims to address the challenges. The main focus will be on student active learning in synchronous online environments, technical teaching methods in lectures, and pre-planning of the course. The final exam in the course was held as a closed-book proctored exam on-campus with pen and paper, providing data on comparisons of the final exam scores with the exam from the previous year, in which the entire course was held on-campus. The results indicate a positive effect from the presented design. Also, student surveys indicated high student satisfaction.

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.

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 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.