Digital technologies used by middle school students and mathematics teachers in the statistical inquiry process: From data to probability

Purpose: The technological transformation brought about by the 21st century has reshaped learning and teaching processes by transcending the traditional boundaries of mathematics education. Artificial intelligence tools, which have gained prominence in recent years, support higher-order thinking processes by helping students analyze data, discover patterns, and make probabilistic inferences. The purpose of this study is to comprehensively evaluate the digital technologies utilized by middle school mathematics teachers and students in the statistical research process from data to probability. Materials and Methods: This study is a qualitative, case study. Data were collected using Interview Forms (IF) developed by the researchers and analyzed using content analysis. The study was conducted with mathematics teachers and students in the Battalgazi district of Malatya province, selected using simple random sampling. In this study, the views of middle school students and mathematics teachers were analyzed in a comparative and holistic manner. The research data were analyzed using the MAXQDA qualitative data analysis software and visualized using code maps. During the analysis of the findings, categories were formed using codes, and themes were developed using these categories. Findings: This study examined the digital technologies teachers use in the classroom when teaching probability and statistics in middle school mathematics classes. In this context, the study identified which specific physical technological tools were used most frequently. It was found that the digital technologies used had an impact on students' motivation, academic achievement, and the prevention of conceptual misunderstandings. The role of artificial intelligence (AI) applications—offered by the current technological age—in probability instruction was also evaluated in the study. The potential of artificial intelligence-supported learning environments to foster statistical thinking processes was highlighted. Furthermore, within the scope of the statistical research process—from data to probability—the digital technologies that both teachers and students could use when designing a project assignment were identified, along with potential tools in this regard. Conclusion: It is evident that teachers and students exhibit different approaches to the use of technology. In terms of digital technologies, while students make intensive use of platforms such as EBA, search engines, and e-books, teachers tend to focus more on specialized instructional systems and simulations. Regarding physical technological tools, the smart board is the most prominent tool for both teachers and students in classroom use, whereas outside the classroom, students prefer tablets, computers, and mobile phones more actively. When examining software, it is observed that teachers prioritize data analysis programs such as SPSS and Excel, while students intensively use Excel, which is more accessible. In the data visualization process, it is notable that both groups turn to GeoGebra. It appears that students are adopting multi-purpose systems such as ChatGPT, Gemini, and Copilot more extensively in their use of AI tools, whereas teachers utilize them to a more limited extent. Canva, used for instructional purposes, stands out particularly among students. In terms of project resources, students heavily prefer mobile devices, computers, and AI-based tools, while teachers tend to turn more toward organizational and analytical software. Overall, the findings reveal that teachers use technology primarily for pedagogical organization, assessment, and evaluation; whereas students are more open to personalizing the learning process, extending it beyond the classroom, and integrating artificial intelligence.