International Journal of Science and Mathematics Education最新文献

This study analyzes the mathematical knowledge to teach early algebra exhibited by pre-service early childhood education teachers, from the perspective of the Mathematical Knowledge for Teaching (MKT) model. The research adopts a mixed exploratory-descriptive methodological approach, based on the application of the MKT-early algebra questionnaire (3–6), consisting of six open-ended items that place teachers in various teaching situations reflecting the knowledge that characterizes early algebra at this stage of schooling. The analysis of the answers given by the pre-service teachers of early childhood education revealed a level general of insufficient mathematical knowledge, with the common content knowledge exhibiting fewer limitations compared to the other subdomains that comprise the model, and the horizon content knowledge the weakest. We conclude that it is necessary to offer teacher training programs that deepen the didactics of early algebra and provide tools to further the effective teaching of this content block in early childhood education.

Scientific reasoning competencies (SRC) are an area of competence emphasized in science education and are considered essential in the world of 21^st Century skills. Developing these competencies is important for all levels of education, from primary school to university. However, to accurately measure them, measurement tools with validity and reliable evidence are needed. The current study was conducted with two different sample groups. In Study-1 (n = 155), the SRC test consisting of 21 items was adapted into Turkish, and evidence of its validity and reliability was presented. To this end, the Turkish adaptation of the SRC test, which was previously developed and tested for validity in different languages, was conducted in a sample of primary school teacher candidates. In Study-2 (n = 483), the relationship between SRC and epistemological beliefs and analytic thinking skills was examined. Regression analysis showed that epistemological beliefs and analytic thinking were significant predictors of SRC. The study and discussion offer implications for future research on the relationship between SRC and other thinking skills not examined in this research.

The importance of integrating effective teaching strategies in Professional Development (PD) programs for Educational Robotics (ER)-based Science Technology Engineering and Mathematics (STEM) education is increasingly recognized. However, we need to add to the growing body of studies on comprehensive instructional approaches for teaching robotics to educators within PD STEM environments. This study investigates the effects of the modified P3 task taxonomy enriched ER-based STEM PD course on science, mathematics, and computer science teachers’ STEM knowledge. The taxonomy denotes a strategy utilized to teach high school students ER. Twenty in-service teachers participated in the study, attended a 24-hour PD program in which they were taught how to use Arduino robotics kits, were assigned three tasks, and were engaged in creating lesson plans incorporating ER into their regular teaching practices. The one-group pre and post-test experimental design was adopted in the study. The instruments included a science, robotics, and mathematics content knowledge test administered before and after the PD program. Moreover, the variations in mean scores for both the pre-test and post-test, pertaining to knowledge in science, mathematics, and robotics, were demonstrated. Using a paired-sample t-test, we found that the P3 task taxonomy scaffolded PD program had statistically significant impacts with large effect sizes in robotics (2.08), science (1.49), and mathematics (0.92). These results hold important implications, suggesting that the P3 task taxonomy offers a new approach beyond learning by design, the 5E model, and project-based learning for scaffolding PD in ER settings.

To identify the research trends in studies related to STEM Clubs, 56 publications that met the inclusion and extraction criteria were identified from the online databases ERIC and WoS in this study. These studies were analysed by using the descriptive content analysis research method based on the Paper Classification Form (PCF), which includes publishing years, keywords, research methods, sample levels and sizes, data collection tools, data analysis methods, durations, purposes, and findings. The findings showed that, the keywords in the studies were used under six different categories: disciplines, technological concepts, academic community, learning experiences, core elements of education, and psychosocial factors (variables). Case studies were frequently employed, with middle school students serving as the main participants in sample groups ranging from 11–15, 16–20, and 201–250. Surveys, questionnaires, and observations were the primary methods of data collection, and descriptive analysis was commonly used for data analysis. STEM Clubs had sessions ranging from 2 to 16 weeks, with each session commonly lasting 60 to 120 min. The study purposes mainly focused on four themes: the impact of participation on various aspects such as attitudes towards STEM disciplines, career paths, STEM major selection, and academic achievement; the development and implementation of a sample STEM Club program, including challenges and limitations; the examination of students' experiences, perceptions, and factors influencing their involvement and choice of STEM majors; the identification of some aspects such as attitudinal effects and non-academic skills; and the comparison of STEM experiences between in-school and out-of-school settings. The study results mainly focused on three themes: the increase in various aspects such as academic achievement, STEM major choice, engagement in STEM clubs, identity, interest in STEM, collaboration-communication skills; the design of STEM Clubs, including sample implementations, design principles, challenges, and factors affecting their success and sustainability; and the identification of factors influencing participation, motivation, and barriers. Overall, this study provides a comprehensive understanding of STEM Clubs, leading the way for more targeted and informed future research endeavours.

In 2014, the NIH Diversity Program Consortium (DPC) launched an initiative to implement and evaluate novel interventions at a variety of academic institutions across the country to engage undergraduate students from diverse backgrounds in biomedically-related research. The local intervention examined in the current study provides Critical Race Theory (CRT)-informed mentoring, more broadly called critical mentoring, for its participants. We examined the relationship between critical mentoring and student outcomes. In this study, student outcomes consisted of three components: (a) mentor satisfaction, (b) science identity, and (c) science self-efficacy. To determine student outcomes, we used the 2020 Student Annual Follow-up Survey (SAFS). We found that participants in the intervention program reported higher levels of critical mentoring than non-intervention participants and critical mentoring was, in turn, predictive of higher. mentorship satisfaction, science identity, and science self-efficacy. This finding implies that the CRT-informed intervention was more effective by developing an environment in which high-quality, critical mentors influenced students’ sense of science identity and self-efficacy. Additionally, we also found that intervention participants reported higher science identity and science self-efficacy than non-intervention participants, which suggests that the intervention cultivated science identity and self-efficacy in other ways outside of critical mentorship as well. The current study highlights how participation in an intervention program can increase science identity and self-efficacy, two factors predictive of science career intentions. The connection between critical mentoring practices and increased science identity and self-efficacy underscores the significance of culturally and racially relevant social support in science education.

The modeling approach is used to prepare students to become responsible citizens and face the challenges and demands of modern times, mainly when they engage in modeling activities using digital tools. This study investigates the features of digital tools used in modeling processes among prospective teachers. Thirty-two prospective mathematics teachers participated in this study, and data were collected from video recordings of their participation in three modeling activities involving digital tools. The study’s findings indicate that in the first activity, most of the groups of participants used digital tools in the mathematical phases and actions of the modeling processes. However, in the final activity, participants used digital tools throughout most of the modeling processes. The findings also show that the level of digital tool utilization was neither dependent on time nor a specific activity. However, the average level of digital tool utilization illustrates that changes occurred between the first and the last activities in most of the modeling phases/actions. These changes in the utilization of digital tools rely on the sophistication of the digital functions being used. This means that the participants changed how they used digital tools, shifting from using them at a basic level to using the more sophisticated functions found in digital tools.

Teamwork and collaboration are twenty-first century skills valued by STEM employers for addressing the most urgent problems in society. To prepare undergraduate STEM students, they must graduate valuing teamwork and collaboration. The Integrated Concentration in STEM (iCons) program aims to meet this goal by utilizing interdisciplinary team-based learning to address complex real-world problems. In doing so, the program provides students with a learning experience that demonstrates the authentic value of teamwork and shows how collaboration can be useful for solving problems. The purpose of this study was to examine whether students who participated in iCons developed more positive values related to teamwork and collaboration than similar students who did not participate in the program. Framed by Expectancy Value Theory (EVT)—specifically the concept of utility value, which is how practically useful students find teams in helping them fulfill their objectives or to solve problems—we investigated the iCons program with a mixed methods design that analyzed survey and interview data from students. Overall, iCons had a positive effect on students’ perceptions of the utility value of teamwork and collaboration. Qualitative results helped to explain these findings in more depth, including students’ positive perceptions of the interdisciplinary design of the program. Findings suggest that more resources should be put into creating and expanding opportunities in STEM that utilize a combination of pedagogical strategies focused on team-based learning and an interdisciplinary design. Further research is needed to understand these effects in more detail.

This paper details an integrated inquiry-based mathematics and science method course for preservice teachers designed around STEM problem-based learning. It documents how problem-based learning (PBL) activities supported PSTs’ envisioning of equitable approaches for diverse children. The overarching research question was: How did preservice teacher learning and lesson design experiences within integrated STEM inquiry translate to their vision of equity-based STEM practice? The data included PSTs course reflections, STEM PBL 5E units, and reflections as they watched recordings of their teaching their units. This facilitated mapping the development of PSTs’ vision for equitable teaching across the field mediated experiences in teaching and learning STEM. Our findings revealed how visions of equitable STEM practices emerged from the PST's own experience as being a learner in an integrated STEM environment and from being a teacher who planned and enacted an equity focused STEM unit in a diverse classroom context. The dual teacher-learner experience of the mediated field experience was critically important to provide experiencing and witnessing the high level of motivation during the meaning-making process and provided evidence that rigorous math and science learning is possible in diverse contexts.

In the post-pandemic world, metaverse technology has become a popular approach to facilitating students’ online learning experiences. Drawing on Kolb’s experiential learning theory, we created immersive scenes using CoSpaces Edu, a ‘mirror-world’ metaverse platform that enables students to observe mathematical properties virtually. We applied a quasi-experimental design and evaluated the effect of integrating these virtual experiences into our learning resources. Students in the control group used conventional resources created using GeoGebra, which allowed them to manipulate mathematical objects and observe the locus of moving points. For the experimental group, in addition to the GeoGebra resources, we incorporated scenes (e.g., scenarios featuring running dogs) via CoSpaces Edu, which enabled the students to observe mathematical properties virtually online. The post-test results demonstrated that the students in the experimental group (N = 28) performed better than those in the control group (N = 35). The virtual world, which offered immersive walk-through experiences and different perspectives, enhanced the students’ understanding of locus concepts. However, some students encountered technical issues during their online learning, which may have hindered their mathematical exploration. This study contributes to the application of experiential learning theory using metaverse tools, thus offering educators valuable insights into creating immersive environments for online mathematics instruction.

Acquiring mathematical literacy requires students to apply mathematics in various real-world contexts. However, mathematics classes often provide brief, content-focused descriptions of reality-based tasks and tasks that describe the situation as more complex, closer to reality, are still lacking. Students with different sociodemographic characteristics and cognitive factors have difficulties in solving reality-based tasks in mathematics lessons. The relationship between sociodemographic characteristics and cognitive factors (language and mathematical competence) concerning complex situation descriptions has not yet been investigated. To identify disadvantaged students in integrating such complex-situation tasks in mathematics lessons, this study aims to investigate which sociodemographic characteristics predict the solving of complex-situation tasks and whether cognitive factors mediate the relationship. Experts created 30 complex situations with different mathematical questions. A total of 519 9th- and 10th-grade students participated in a paper–pencil test. Path analysis revealed that the competence to solve complex-situation tasks is directly linked to gender and social background, with mathematical content-related skills and language competence mediating this relationship.