STEM Education Research Articles

Does training improve the action research skills of STEM teachers? Examining the mediating roles of attitude and knowledge

Professional development programs are essential for supporting STEM teachers in improving their teaching practices by creating engaging and effective learning experiences for students. One of the professional development programs referred to is their participation in action research training. However, while there is a growing number professional development program relating to it, there is no substantial amount of reports regarding its impact toward developing teachers' action research attitude, knowledge, and skills. In this regard, this study aims to empirically investigate the influence or impact of training programs on the development of STEM teachers' action research skills, knowledge, and attitude. Driven by Evans' (2014) concept of professionalism and professional development as a guiding framework, a structural model was proposed and validated using a quantitative cross-sectional survey design. There were 214 STEM teachers who participated in an online survey. Results revealed that from five hypotheses proposed in the structural model, four are supported except the causal path between training and action research skills. The paths between training to action research knowledge and attitude are supported as well as the paths between action research knowledge and attitude to skills. This indicates that teachers’ action research knowledge and attitude fully mediate the causal path between training and action research skills. The findings of this study imply that the focus of the training programs should go beyond the mechanical aspects or skills development of teachers but on developing their knowledge and shaping a positive attitude toward action research. Over time, both provide an enabling environment to practice and develop action research skills. The finding also offers a new perspective or guiding framework as to how teacher training programs particularly action research can be evaluated.

Exploring Interest in Informatics with a Focus on K-12 Students’ Preferences in the Context of a Robotics Workshop

Digital literacy is considered to be crucial for social and professional participation. Hence, several projects have been launched in school, as well as extracurricular activities to promote digital literacy in middle school. They aim, among other things, to increase interest in the so-called STEM subjects (science, technology, engineering, and mathematics), which include computer science. Interest in a topic is described in the literature as a crucial factor for learning success and career choice. Still, there is a potential for current research on the expression and distribution of interest in computer science. Therefore, this study aims to address this research gap by examining interest in computer science. The exploration of interest is expanded to include gender aspects and pupils’ dispositions. Given the significantly lower number of women studying in STEM fields, there is a particular focus on an improved understanding of the interests of female pupils as early as middle school. Moreover, the literature suggests that pupils’ dispositions should also be considered in instructional design to achieve stable interest. In this context, the following two dispositions shine out in literature and are therefore focused on in this article: first, interest in contextual, people-related topics (mainly found among women), and second, interest in factual, object-related topics (mainly found among men). In summary, this study investigates how pupils’ interest in computer science is expressed before and after a programming intervention and how it is distributed across gender and dispositions. Therefore, the study surveyed 8th-grade pupils (N \(=\) 114) about their preferences and assessed their interest in computer science before and after an intervention with unplugged materials and playful robots. Results show that all groups of pupils find computer science interesting, and the intervention slightly increased interest. Girls show a marginally lower interest in computer science. Furthermore, the results indicate that interest in computer science did not correlate with interest in contextual or factual dispositions.

Investigating Determinants of STEM Major Choice Among Malaysian Undergraduates

STEM education plays a significant role in a country’s economy growth. Consequently, innovative and advanced careers in STEM domains are fast emerging because more people are employed in STEM related professions. Literature has identified various determinants of STEM career and STEM major choices including gender, self-efficacy, parental influence, outcome expectancy and aptitude towards science and mathematics. While extensive literature exists on STEM major choices, it is predominantly concentrated on Western countries. This study aims to fill the gap by providing empirical evidence of gender, ethnicity, and high school grades as determinants of STEM major choice among undergraduates in a developing country. The results expand the understanding of how demographic factors influence academic choices in non-Western settings. Practically, the findings can inform policy makers on strategies to encourage STEM enrolment among diverse student populations in Malaysia.

The World Smarts STEM Challenge: A promising approach to fostering STEM and global competence skills for adolescents in the US and Ghana.

Given the increasingly global nature of work, the global workforce needs STEM (science, technology, engineering and math) workers who have both STEM content knowledge and intercultural competence. This study reports on findings from a 10-week bi-national virtual STEM challenge, the World Smarts STEM Challenge, that brought adolescents in the United States and Ghana together to complete a STEM learning program. There were 114 participants from Ghana (female = 56%) and 95 from the US (female = 48%); Mage = 16.21 years, SD = 1.65. In Ghana 100% of participants identified as ethnically Ghanaian and in the US participants identified as Black/African-American (50%), Latino/a/x or Hispanic (23.9%), Asian/Asian-American (7.6%), White/European-American (7.6%), bi-racial or multi-racial (7.6%), and "other" (3.3%). After the Challenge, participants increased in awareness of global issues, and engagement with others, but also showed a small but significant decrease in respect for people from other cultural backgrounds. Girls demonstrated an increase in global-mindedness in both countries and Ghanaian participants reported an increase in self-efficacy for global issues and demonstrated significant growth in both STEM ability self-concept and STEM activism orientation. Findings suggest the value of virtual STEM Challenges for building both STEM and global competence skills.

Bibliometric Analysis of Artificial Intelligence in STEM Education

This study conducts a bibliometric analysis of artificial intelligence (AI) in STEM education research from 2020 to 2024. The study uses citation analysis to examine publication trends, country contributions, top authors, cited journals, and influential articles in this field. Data was collected from the Dimensions database using the keywords "artificial intelligence" AND "stem education." The analysis reveals a significant increase in publications and citations in 2024 compared to previous years. The United States emerges as the leading country in the number of documents (9) and citations (103). China follows with five documents but no citations. The most cited authors include Nesra Yannier, Kenneth R. Koedinger, and Scott E. Hudson, each with 55 citations. The International Journal of Artificial Intelligence in Education is the most cited journal, with 55 citations. The most influential article, "Active Learning is About More Than Hands-On: A Mixed-Reality AI System to Support STEM Education," received 55 citations. Carnegie Mellon University stands out as the most cited institution, with 55 citations. The findings highlight the growing importance of AI in STEM education research, focusing on personalized learning, advanced analytics, and instructional automation, inspiring us all with the potential of AI to transform the future of education. This bibliometric analysis provides valuable insights for researchers, educators, and policymakers interested in the intersection of AI and STEM.

Expanding Teacher's technological, pedagogical, and content knowledge with funds of knowledge: An exploratory STEM professional development model using video creation workshops

AbstractRecent initiatives in the Philippines have underscored the significance of 21st‐century approaches to preparing K‐12 STEM public teachers to embrace technology‐enhanced pedagogies. This case study, part of a larger investigation, employed portraiture methodology to examine one science teacher's growth in technological, pedagogical, and content knowledge (TPACK) while integrating students' funds of knowledge (FoK) in a 4‐week science video creation workshop. The workshop trained the teacher as a learning doctor to diagnose teaching and learning impediments during pre‐ to post‐video production. Data included the teacher's pre‐ to post‐production video creation experience, reflections, and individual interviews. Findings indicated: (a) a gradual growth from a self‐assessed detached TPACK to an expanded TPACK, (b) concrete FoK integration, which served as a bridge to widen the teacher's TPACK, and (c) effective science video creation workshop, viewed through the lens of a science teacher as a learning doctor, offered explicit scaffolding to address teaching and learning impediments during video creation. The findings suggest that science video creation workshops represent an exploratory and innovative model for deliberate professional development (PD) in STEM education, particularly for teachers in rural areas. This model highlights the relevance of research integrating FoK and TPACK and offers a new approach to enhancing teachers' TPACK. The findings have potential implications for advancing PD for rural science teachers in the Philippines and STEM educators in rural areas globally, emphasizing the value of rural schools as centers for relevant pedagogical innovation in STEM education.

Influential Factors in the Decision to Pursue a Bachelor’s Degree in Computer Engineering and Artificial Intelligence at the School of Engineering and Technology, Walailak University

Background and Objectives: University education is essential for empowering individuals and fostering economic, social, and intellectual growth. In Thailand, fair and competitive university admissions are ensured across 75 institutions by the Thai University Center Admission System (TCAS). At the same time, each individual’s decision to pursue higher education is influenced by the quality of program’s curriculum and academic reputation, along with geographical considerations and parental guidance. This study investigates factors influencing the decision to pursue a bachelor's degree in Computer Engineering and Artificial Intelligence (CEAI) at Walailak University, focusing in particular on their revised curriculum. Insights gained aim to enhance curriculum alignment, boost recruitment, and meet the diverse needs of students. Methodology: This study employed an exploratory approach, using descriptive statistics and multiple regression analysis. The population consisted of 126 students enrolled in the CEAI program at Walailak University in 2022. A sample of 96 participants were randomly selected and voluntarily completed an online questionnaire. The questionnaire, distributed via academic platforms and social media, elicited demographic information and explored factors influencing participants’ decision to pursue this degree. Main Results: The results showed that curriculum factors had the greatest impact on the decision to pursue the program, followed by financial factors, educational institution factors, and personal reasons. The t-test results indicated that gender impacted decision regarding course enrollment and the total monthly income of the family affected the decision as to whether or not to enroll at a particular institution. Discussions: This study revealed key factors influencing enrollment decisions for CEAI students at Walailak University. Curriculum relevance, faculty expertise, and financial considerations emerged as their primary concerns. Notably, female students valued curriculum aspects more highly than their male counterparts, yet they remain underrepresented, highlighting persistent gender stereotypes in engineering. Income-related differences significantly impacted perceptions of financial factors. To address these findings, we recommend: (1) curriculum-focused marketing emphasizing industry relevance, (2) targeted outreach to female students, (3) expanded financial support and transparency, and (4) enhanced public relations leveraging social media and outreach programs. These strategies aim to create a more diverse and inclusive program, aligning with global trends in STEM education and workforce development. Conclusions: The study reveals that curriculum factors, particularly job market relevance and faculty expertise, are most important to students in Walailak University's CEAI program. Gender and income related differences significantly influence student perspectives. These insights can help improve program quality, develop targeted admission strategies, and better serve diverse student needs.

Investigating gender stereotypes in nursing/midwifery and engineering students in Ireland

Stereotypical behaviour in higher education has been linked with inequality with relevant negative output. This project's aim is to replicate the design of a previous study by expanding further into exploring the gender stereotypes’ relationships for two traditionally gendered polarised areas of study: Engineering and Nursing/Midwifery and assessing participants’ earlier experiences in their secondary education. Survey participants were Engineering and Nursing/Midwifery students (N = 161) of a university in Ireland. Results came positive for stereotypical biases in favour to men in Science, Technology, Engineering and Mathematics (STEM), and specifically for Mathematics. Stereotypes emerged stronger among the female participants. While comparing the two genders within each of the two study areas, significant differences emerge among the female Nursing/Midwifery and female Engineering participants. Female Engineering participants appear with stronger preference, attitude and importance towards STEM than their Nursing/Midwifery counterparts. Nevertheless, Mathematics is an indicator subject for success in higher education and the need to strengthen critical thinking, evidenced based practice and quality of quantitative research in female dominated areas such as Nursing/Midwifery has been recognised. In addition to identified stereotypes, differences in respondents’ views/elements of their interaction with STEM were associated with the type of secondary school they attended. Further research is recommended on traits that could contribute to the formation of gender biased stereotypes in single and mixed gender education systems with an aim to reverse them.

Examining How Student Identities Interact with an Immersive Field Ecology Course and its Implications for Graduate School Education.

One of the central issues in ecology is the underrepresentation of individuals from diverse backgrounds. This underrepresentation starts at the undergraduate level and continues into graduate programs, contributing to a need for more diversity in the discipline. We hypothesize that the interplay of students' identities and contextual factors influence how students perceive their sense of belonging in a field-based discipline. We present findings from a 2-yr evaluation of a pregraduate school field program, FIRED UP (Field-Intensive Research Emphasizing Diversity UP in the alpine), where students interacted with a curriculum focused on building field skills and cohort bonding. Students provided feedback through surveys and interviews conducted at various phases throughout the program. Using the Phenomenological Variant Ecological Systems Theory, we present our interview results in three cases describing differing student outcomes regarding belonging which allows us to give voice and weight to students with more critical and constructive perspectives. Thus, the results of this study can be used to critically examine field-based educational program design to maximize the ability of programs to respond to diverse student needs. The broader implications of this work address how to approach pregraduate school training and cohort building that supports students marginalized in science, technology, engineering and mathematics (STEM) disciplines as they enter graduate school.

A systematic review of afterschool STEM literature in education

In this study, the literature on Afterschool STEM education was reviewed from the Proquest database. Within the scope of the research, 25 theses and dissertations that met the criteria were examined. The year, type, a method used, data collection tools, study group and number, and keywords of the theses were systematically analyzed. The systematic review method, one of the qualitative research methods, was used to examine the graduate theses on Afterschool STEM. As a result of the findings obtained by examining the theses related to Afterschool STEM; it was found that the first thesis study was a doctoral dissertation in 2003, there was a great increase in the number of theses published in 2015, and no thesis was published between 2004-2013, and most of the published theses were in the doctoral thesis type. In addition, in the distribution of theses according to the fields selected in the Proquest database, it was determined that most theses were published in the field of Science Education, qualitative and mixed research methods were used equally and mostly as research methods, and survey, interviews, and observation were mostly used as data collection tools. In the analyzed theses, data were collected mostly from Middle school students. When the number of participants in the theses was examined, the participants between 31-100 were mostly preferred in the studies. According to the keywords used in the theses, the words "education", "out of school time", "afterschool", "STEM" and "STEM education" were preferred.

AI in STEM Education: The Relationship between Teacher Perceptions and ChatGPT Use

The rapid development of AI in the recent years has triggered numerous discussions in the education sector since it offers numerous opportunities, but also challenges. This study addresses one context in which AI might become a relevant tool for different purposes: German secondary education. This study therefore examines the extent to which STEM teachers in German secondary education assess the benefits but also the risks of ChatGPT and how this influences the future use of AI in an educational context. As part of a questionnaire study, 102 STEM teachers were investigated. The current and future use of ChatGPT and various teacher variables were recorded with questionnaires based on classifications of researchers as well as political institutions. Relationships between the variables were explored using a path model investigating hypotheses regarding the affect heuristic, perceived risks and benefits as well as effects on teaching quality. In general, AI is still used relatively rarely, but future usage expectations are high compared to current usage. Results further revealed that perceived competence and benefits of ChatGPT have a positive influence on the use and intention to use it. Perceived risks and concerns have no significant influence on the usefulness of ChatGPT in the classroom, indicating that STEM teachers use AI in the classroom despite potential concerns and perceived risks. Additionally, perceived benefits and risks are negatively associated with each other, indicating that teachers rely on an affect heuristic when judging the usefulness of AI technology in the classroom.

Low-stakes Scientist Spotlight Assignment Demonstrates High Value and Multiple Effects for Introductory Biology Students.

Scientist Spotlights are homework assignments that highlight the personal and scientific stories of counterstereotypical scientists. Previous research has focused on whether these assignments promote possible selves in STEM (science, technology, engineering, mathematics). We sought to understand the value students themselves placed on the assignment using expectancy-value theory complemented by further analysis of the assignment's self-reported impacts on students. Therefore, at the end of an introductory biology course with several Scientist Spotlights, we asked students to reflect on how the course would influence them for years to come. We found that although the assignments had low instrumental value, 49% of students mentioned Scientist Spotlights or a highlighted scientist. Thematic analysis on the Scientist Spotlight-related parts of the reflections found novel emergent themes including diversity in science, humanizing scientists, and self-efficacy. Most students mentioned multiple themes, with few differences between students from minoritized and nonminoritized groups. We interpreted our results through the lens of the "mirrors, windows, and sliding glass doors" framework, as Scientist Spotlights appeared to function as "windows" into the diverse scientific world, "mirrors" for seeing human traits in scientists, and "sliding glass doors" inviting students further into science. Our study expands our understanding of the broad, multiple, and intersecting impacts of Scientist Spotlights.

Impact of Digital Game-Based Learning on STEM education in primary schools: a meta-analysis of learning approaches

Enhancing learning outcomes in Science, Technology, Engineering, and Mathematics (STEM) subjects for primary school students remains a challenge. This meta-analysis, guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), explores Digital Game-Based Learning (DGBL) interventions as a potential solution. Eighteen empirical studies published from 2010 to 2020 were analyzed to identify effective DGBL approaches. Key factors examined include subject disciplines, control treatment, game type, platforms, and intervention duration. Findings reveal significant positive effects of DGBL interventions on learning outcomes, particularly in mathematics, language, and science. The study underscores the importance of optimizing gameplay design and platform choices for DGBL effectiveness and highlights the potential benefits of incorporating DGBL into primary STEM education. Future research should further investigate contributing factors like game genres, technologies, implementation strategies, and specific game components to promote optimal learning processes in diverse educational settings.

Exploring the Journey of STEM Faculty into Justice-centered Pedagogy.

In higher education and science, technology, engineering, and mathematics (STEM), interlocking oppressions can lead to inequitable environments for those who hold marginalized identities. Instructors can play key roles in either exacerbating or mitigating these inequities through their pedagogical approaches and choice of curricular material. However, it remains unclear how instructors who self-identify as committed to justice achieve higher levels of consciousness around areas of injustice and develop the self-efficacy to dismantle barriers for students over time. Here, we draw upon critical race theory and critical white studies to investigate what events or life experiences influence STEM instructors to understand the importance of social justice and examine how STEM instructors use this understanding to drive pedagogical shifts. We find variations in the ways that instructors' experiences and identities shape their understanding of justice. In addition, we uncover factors that influence the switch moment; curriculum and pedagogical shifts; their relationship to justice work broadly; and barriers and supports for justice work. These stories hold powerful lessons for STEM education, but also for education more broadly, both in terms of pedagogical practice and the questions that shape research agendas on equity in education.

All In: Understanding and Motivating Stakeholders to Create an Equitable Culture of Student Success.

Discourse around Science, Technology, Engineering, and Mathematics (STEM) education in the United States has long focused on improving the persistence and academic achievement of students. On the surface, such goals are reasonable and well-intentioned. However, the near-exclusive focus on those two outcomes as shorthand for "success" serves hegemonic norms which preclude the equitable success of all students. Although STEM education research has begun to address the inequitable systems within which students and faculty operate, the language of success has largely not changed. While previous work has aimed to recognize and characterize how normative definitions of success harm students and faculty, they fall short of providing readers with strategies for how to sustainably change these systems of injustice. Utilizing the four frames model for systemic change, this Essay 1) deconstructs the operational definitions of student success among key stakeholders involved in STEM higher education: students, faculty, departments, and institutions; 2) determines how extant policies and practices drive misalignments among these definitions and thwart equity; and 3) highlights three key opportunities for change agents to transform how success is measured and defined within STEM higher education.

Calling for Equity-focused Quantitative Methodology in Discipline-based Education Research: An Introduction to Latent Class Analysis.

Mixture modeling is a latent variable (i.e., a variable that cannot be measured directly) approach to quantitatively represent unobserved subpopulations within an overall population. It includes a range of cross-sectional (such as latent class [LCA] or latent profile analysis) and longitudinal (such as latent transition analysis) analyses and is often referred to as a "person-centered" approach to quantitative data. This research methods paper describes one type of mixture modeling, LCA, and provides examples of how this method can be applied to discipline-based education research in biology and other science, technology, engineering, and math (STEM) disciplines. This paper briefly introduces LCA, explores the affordances LCA provides for equity-focused STEM education research, highlights some of its limitations, and provides suggestions for researchers interested in exploring LCA as a method of analysis. We encourage discipline-based education researchers to consider how statistical analyses may conflict with their equity-minded research agendas while also introducing LCA as a method of leveraging the affordances of quantitative data to pursue research goals aligned with equity, inclusion, access, and justice agendas.

RELATIONSHIP BETWEEN ATTITUDE TOWARD STEM AND COMPUTATIONAL THINKING ABILITY IN MATHEMATICS LEARNING OF ELEMENTARY SCHOOL STUDENTS

Computational Thinking (CT) plays an important role in Science, Technology, Engineering, Mathematics (STEM) fields. However, whether Attitude toward STEM is related to CT skills is still unknown. The purpose of the study was to determine whether there is a relationship between Attitude Toward STEM and Computational Thinking skills in mathematics learning of elementary school students. This research is a correlational quantitative research that measures the relationship between two variables. The research was conducted at SDN Gandaria Utara 03 in class IVA and IVB. Simple random sampling technique was used to determine the research sample. The instruments in this study used a questionnaire to measure Attitude Toward STEM and a test instrument to measure Computational Thinking ability. The instruments in this study were measured for validity and reliability before use. Data analysis techniques using linear regression statistical tests. The results showed that Attitude toward STEM is related to Computational Thinking ability. From the results of data analysis, the regression model equation is Y = 19.635 + 0.387x. The coefficient of determination or R2 of 0.805 means that the Attitude Toward STEM variable simultaneously has an influence of 80.5% on the Computational Thinking ability variable

Principal Competency, Teacher Readiness, and Teacher Commitment in STEM Education Implementation: A Qualitative Study

The growing emphasis on Science, Technology, Engineering, and Mathematics (STEM) education in schools demands strong leadership and teacher commitment for effective implementation. However, challenges related to principal competency, teacher readiness, and their commitment have been identified as major obstacles to achieving desired outcomes through STEM initiatives. This qualitative study explores the competencies of school principals, teacher readiness, and the commitment required for successful STEM education. It aims to identify the principal competencies that influence teacher readiness and commitment, as well as the elements of teacher readiness that affect their commitment, and the specific aspects of teacher commitment crucial for STEM implementation. The study employs semi-structured interviews with teachers from selected schools, analyzed using thematic analysis to identify themes related to leadership competency, teacher preparedness, and commitment. Findings reveal that principals with competencies in STEM knowledge, management skills, and professional attributes are more likely to boost teacher readiness and commitment. Teacher readiness, particularly in terms of knowledge, skills, and attitude, plays a vital role in strengthening their commitment. Teacher commitment is driven by affective, continuance, and normative commitment, which are critical for STEM success. In conclusion, the study highlights the need to develop leadership competencies and teacher readiness as key strategies to enhance teacher commitment in STEM education. These findings have significant implications for education policy and professional development, calling for targeted interventions to support school leaders and teachers in effectively implementing STEM education.

Empowering Futures: STEM Aspirations among Bangladeshi Girls in Secondary Education

This research examines the desire of the class nine and ten girls towards STEM education in Khulna and Rajshahi, Bangladesh. Despite growing awareness of gender parity, girls’ STEM participation is little. This study surveys various socio-cultural, economic, and educational aspects to determine whether female students choose STEM streams in secondary school. This study has explored the unexplored aspirations of high school girls in these two areas of Bangladesh. A mixed-methods approach was used to meet the objectives of this study. For this, researchers used a wide range of quantitative and qualitative data. Eight girls’ high schools in Khulna and Rajshahi, Bangladesh, were studied using questionnaires in which 410 girls participated. The students were selected from ninth and tenth grades. In addition, 44 respondents shared their ideas, experiences, and observations in four focus group discussions (FGD) conducted at various schools. The data was collected from July 2021 to June 2023. STEM female students have been studied using descriptive statistics and qualitative methods. Some critical issues have been explored through this study. These include motivations for studying STEM, completion, desired degree, and chosen STEM higher education institutions. The present global STEM education scenario and STEM occupations largely influence female STEM students. The results reveal that every respondent has well-defined STEM aspirations; nonetheless, the majority target the biological sciences. It also found that they have less interest in engineering, technology, and applied sciences. The earth, space, and physical science occupy a smaller subset in their chosen row. The girls also know local and global STEM education trends and actively seek knowledge to guide their academic and career paths. It is important to note that the students are ambitious and aware of STEM career opportunities despite their knowledge deficits. The research suggested the need to provide additional assistance in a few areas, like providing high-quality teaching methods and materials for STEM girls, mentorship, organizing workshops for guardians, and offering scholarships and financial aid. If these suggestions are implemented, the girls' desires may be fulfilled.

Status of Scheduled Tribe Students in Science, Technology, Engineering and Mathematics (STEM) at the Level of Higher Education in India

Status of Scheduled Tribe Students in Science, Technology, Engineering and Mathematics (STEM) at the Level of Higher Education in India