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This study examined the effects of QUEST+AI, an AI-supported inquiry model, on AI literacy and authentic performance among preservice teachers in Central China. The study used a nonequivalent-groups, quasi-experimental pretest–posttest design with two intact sections of an undergraduate Educational Research Methods course at a public university. Ninety-five preservice teachers participated, including 52 students in the experimental group and 43 students in the comparison group. Both groups received the same face-to-face course instruction over a 10-week period. The experimental group completed two QUEST+AI inquiry cycles with coached use of generative artificial intelligence, while the comparison group completed conventional homework assignments.

The data include participant demographic variables, pretest and posttest responses to a multidimensional AI literacy questionnaire, AI literacy total and subscale scores, final research proposal scores, and group assignment indicators. AI literacy measures cover use and application of AI, knowledge and understanding of AI, AI detection, AI ethics, AI creation, AI-supported problem solving, AI persuasion literacy, and AI emotion regulation. Authentic performance is represented by scores on a final educational research proposal, evaluated with a common rubric by two independent raters. The dataset also includes variables used in the study’s comparative analyses, including group condition, pretest scores, gender, grade level, age, and major.

MT21 is a cross-national study of the preparation of middle school mathematics teachers. Countries participating included Chinese Taipei (Taiwan), South Korea (Korea), Bulgaria, Germany, Mexico, and the United States. Data were collected from teachers in their first and last year of preparation by sampling institutions in each country. Future teachers were asked about their backgrounds, course-taking and program activities, knowledge relevant to their teaching (mathematical and pedagogical), and beliefs and perspectives on content and pedagogy.

The 1995 Third International Mathematics and Science Study (TIMSS) data revealed that countries with higher achievement have teachers who teach substantially different content than that of their less accomplished counterparts (see Schmidt et al., 1996; Schmidt et al., 2001). The 1996 Report of the National Commission on Teaching and America's Future argued that what teachers know and do in the classroom matters for pupil learning. It also argued that teacher education might be a viable policy tool to improve the quality of education (National Commission on Teaching and America's Future, 1996). United States reform efforts are consistent with this line of thought. They have introduced standards to measure teacher quality as it relates to student achievement. This, in turn, led to accountability concerns regarding teacher preparation programs (INTASC, 1995; Murray, 2000; Leithwood, Edge and Jantzi, 1999; NCATE, 2000).

The MT21 Project was designed to answer the following question: how shall we prepare our future teachers to teach a more rigorous curriculum to all students? Several assumptions were made going into this work: the concepts and models defining teacher preparation are not fixed across the world. Recognizing and understanding this diversity to develop a cross-national study of teacher preparation poses a complex and challenging problem. It is hoped that the resulting international data would not only serve to provide policy insights but would also bring about change by making visible contrasts with other countries in terms of teacher preparation in the United States.