INTERNATIONAL JOURNAL OF STEM EDUCATION 是一本学科内容教育的多学科期刊，专注于科学、技术、工程和数学 (STEM) 教学和学习的研究。它正在成为教育领域一个全新的、具有前瞻性的期刊。作为同行评审期刊，它的定位是促进全球快速发展的 STEM 教育领域的研究和教育发展。

The International Journal of STEM Education is a multidisciplinary journal focused on research in the teaching and learning of Science, Technology, Engineering, and Mathematics (STEM). As a peer-reviewed journal, it aims to promote research and educational advancements in the rapidly evolving field of STEM education, establishing itself as a new and forward-looking publication in the field of education.

《International Journal of STEM Education》是一本多学科的教育期刊，专注于科学、技术、工程和数学（STEM）领域的教学与学习研究。作为一本同行评审的期刊，它旨在促进全球快速发展的STEM教育领域的研究与教育进步，成为教育领域内一个全新的、具有前瞻性的期刊。

International Journal of STEM Education

Abstract Background In the realm of Science, Technology, Engineering, and Mathematic (STEM) education, computer programming stands as a vital discipline, amalgamating cross-disciplinary knowledge and fostering the capacity to solve real-world problems via fundamental concepts and logical methodologies inherent to computer science. Recognizing the important of computer programming, numerous countries have mandated it as a compulsory course to augment the competitiveness of K-12 learners. Nevertheless, the inherent complexity of computer programming for K-12 learners often goes unacknowledged. Constraints imposed by the course format, coupled with a low instructor–learner ratio, frequently inhibit learners’ ability to resolve course-related issues promptly, thereby creating difficulties in the affective domain. While precision education tools do exist to ascertain learners’ needs, they are largely research-oriented, thereby constraining their suitability for deployment in pragmatic educational settings. Addressing this issue, our study introduces the precision education-based timely intervention system (PETIS), an innovative tool conceived to enhance both programming skills and affective learning in K-12 learners. Our research investigates the influence of PETIS on learners’ performance and evaluate its efficacy in facilitating computer programming education in K-12 environments. Results Quantitative results demonstrate that the application of the precision education-based timely intervention system (PETIS) proposed by this research significantly improves programming skills and affective-domain learning objectives for K-12 learners. Similarly, qualitative results indicate that PETIS is beneficial for both teaching and learning in K-12 computer programming courses. Conclusions These results not only confirm that timely intervention and feedback improve K-12 learners’ programming skills and affective-domain learning objectives in computer programming courses, but also yield implications as to the feasibility of applying precision education in real-world STEM scenarios.

Hsin-Yu Lee

Chia-Ju Lin

Wei-Sheng Wang

Wei-Cyun Chang

Yueh-Min Huang

Precision education via timely intervention in K-12 computer programming course to enhance programming skill and affective-domain learning objectives

通过及时干预K-12计算机编程课程实现精准教育，提升编程技能与情感领域学习目标

The knowledge that is required for teaching includes subject matter content knowledge (CK) and pedagogical content knowledge (PCK). Although CK and PCK are distinct components of the teachers’ knowledge, the distinction between those two components and the relationships between them are still underexplored. In a previous study, we showed that biology teachers that participated in a long-term professional development program view CK as an important component of the knowledge required for teaching biology, yet they see it as distinct from PCK. We wondered what are the views of mathematics teachers, who participate in a similar program, on the knowledge that is required for teaching and on the relationships between CK and PCK. In addition, we compared the participating mathematics and biology teachers’ tacit views of the knowledge required for teaching and on the relationships between CK and PCK. We used the Repertory Grid Technique (RGT) as well as semi-structured interviews and a focus group, to elicit mathematics (n =13) and biology (n =16) teachers’ tacit views about the knowledge that is required for teaching. The results show that both mathematics and biology teachers view CK as a significant component of their teaching practice. However, whereas mathematics teachers tend to view CK and PCK as related entities, biology teachers tend to view them as separate. The main contribution of this study is in exposing that teachers from different disciplines may view differently the importance of high-level CK to their practice. The differences among the participating mathematics and biology teachers’ tacit views of the relationships between CK and PCK may aid in the design of professional development programs for mathematics and biology teachers. It is important to draw attention to the ability to recognize the tacit relationships between CK and PCK and to articulate these relationships in planning professional development programs.

Ronit Rozenszajn

Anat Yarden

Mathematics and biology teachers’ tacit views of the knowledge required for teaching: varying relationships between CK and PCK

数学和生物教师对教学所需知识的隐含观点：CK与PCK之间的不同关系

Women and students of color are widely underrepresented in most STEM fields. In order to investigate this underrepresentation, we interviewed 201 college seniors, primarily women and people of color, who either majored in STEM or started but dropped a STEM major. Here we discuss one section of the longer interview that focused on students' sense of belonging, which has been found to be related to retention. In our analysis, we examine the intersections of race and gender with students' sense of belonging, a topic largely absent from the current literature.We found that white men were most likely to report a sense of belonging whereas women of color were the least likely. Further, we found that representation within one's STEM sub-discipline, namely biology versus the physical sciences, impacts sense of belonging for women. Four key factors were found to contribute to sense of belonging for all students interviewed: interpersonal relationships, perceived competence, personal interest, and science identity.Our findings indicate that students who remain in STEM majors report a greater sense of belonging than those who leave STEM. Additionally, we found that students from underrepresented groups are less likely to feel they belong. These findings highlight structural and cultural features of universities, as well as STEM curricula and pedagogy, that continue to privilege white males.

Katherine Rainey

Melissa Dancy

Roslyn Mickelson

Elizabeth Stearns

Stephanie Moller

Race and gender differences in how sense of belonging influences decisions to major in STEM

种族和性别差异：归属感如何影响STEM专业选择决策

In the era defined by the fourth paradigm of science research, the burgeoning volume of science data poses a formidable challenge. The established data-related requisites within science literacy now fall short of addressing the evolving needs of researchers and STEM students. Consequently, the emergence of science data literacy becomes imperative. However, notwithstanding the escalating importance of science data literacy, a comprehensive definition and conceptual framework are still elusive, posing challenges to effective assessment.
This study analyzes the science literacy frameworks of six international organizations and countries, including the OECD, and reviews 16 data literacy-related literature sources identified using the PRISMA process. We also consider the characteristics of science data. Based on these sources, we clarify the connotation of science data literacy and construct a tailored conceptual framework for college students majoring in STEM. The framework undergoes two rounds of Delphi method refinement to enhance its applicability. Subsequently, we created and piloted a set of questions using physics, astronomy, geography, and other STEM subjects as examples to assess science data literacy. The revised assessment tool was then used in a formal test with 198 university students, employing Rasch modeling to evaluate its effectiveness. The tool’s validity in assessing science data literacy was confirmed.
This study offers a systematic and comprehensive conceptual framework for science data literacy tailored to STEM undergraduates. Endorsed by experts, the framework outlines essential literacies for STEM students in handling science data. The developed assessment tool enables educators to measure students’ science data literacy levels and serves as a scientific guide to enhance their competencies in this area.

Cuilan Qiao

Yuqing Chen

Qing Guo

Yunwei Yu

IJ STEM Ed

Understanding science data literacy: a conceptual framework and assessment tool for college students majoring in STEM

理解科学数据素养：面向STEM专业大学生的概念框架与评估工具

Abstract There has been substantial research undertaken on the integration of computational thinking (CT) in K-12 mathematics education in recent years, particularly since 2018 when relevant systematic reviews were conducted on the topic. Many empirical studies in this area have yet to elaborate clearly and explicitly on how CT may support mathematics learning, or otherwise, in CT-based mathematics activities. Addressing this research gap, we conducted a systematic review on the integration of CT in K-12 mathematics education with a focus on CT-based mathematics instruction and students learning under such instruction. The Web of Science database was searched for in terms of studies published from 2006 to 2021, from which 24 articles were selected to provide illustrations of CT-based mathematics instruction and related student learning, and they were further analyzed according to education levels and contexts, programming tools, learning outcomes in CT and mathematics, and the mutual relationship between CT and mathematics learning. Among the results, this review found that geometrized programming and student-centered instructional approaches were facilitators of productive learning in CT and mathematics. Moreover, CT-based mathematics learning entails an interactive and cyclical process of reasoning mathematically and reasoning computationally, which can occur when: (1) applying mathematics to construct CT artefacts; (2) applying mathematics to anticipate and interpret CT outputs; and (3) generating new mathematical knowledge in parallel with the development of CT. The findings contribute to an in-depth understanding of what, and how, CT-based mathematics instruction impacts student learning in K-12 contexts.

Huiyan Ye

Biyao Liang

Oi-Lam Ng

Ching Sing Chai

Integration of computational thinking in K-12 mathematics education: a systematic review on CT-based mathematics instruction and student learning

K-12数学教育中计算思维的整合：基于CT的数学教学与学生学习的系统综述

Abstract Background Despite demands to make higher education more relevant beyond academia, and a growing body of work testifying to the benefits of work-relevance programs (e.g., work-placements, or internships) for both students and the companies that host them, there is limited information available for those aiming to optimize these programs. For example, few have explored the challenges and needs of internship supervisors. Here, we focus on the experiences of supervisors in biology and geology programs across three Norwegian institutions. Specifically, through a series of focus groups, we asked internship supervisors about their motivations for serving as student mentors, any challenges they had faced, and what higher-education institutions could do to better prepare them for hosting students at their workplaces. Results Key challenges faced by supervisors include the need to tailor placements to individual student needs and capabilities, navigating the constraints imposed by academic structures, and addressing communication gaps between students, institutions, and workplace supervisors. Internship supervisors suggest enhancing communication strategies to better define roles and expectations, increasing support and training for supervisors, and establishing clearer, more collaborative frameworks for setting learning objectives with students. Conclusions The supervisors’ suggestions aim to ensure that internships are mutually beneficial, supporting both students' educational outcomes and the workplace needs. By focusing on the supervisor's perspective, we provide valuable insights into one aspect of implementing effective and rewarding internships (i.e., supervisor preparation), thereby suggesting pathways for future improvements in these high-impact educational practices.

Joel R. Schneider

Truls Aaby

Sanne Boessenkool

Emma Falkeid Eriksen

Kristin Holtermann

Iver Martens

Jonathan Soulé

Ariel Steele

Susanne Zazzera

Gro I. van der Meeren

Gaute Velle

Sehoya Cotner

A. Kelly Lane

Creating better internships by understanding mentor challenges: findings from a series of focus groups

通过了解导师挑战来创造更好的实习机会：一系列焦点小组的发现

From August 2014 to July 2024, the International Journal of STEM Education has completed ten full publication cycle years. In this editorial, I offer a brief reflection of the journal's successful growth over the past decade. I also celebrate the collective achievements of all those involved and highlight the journal's continued commitment to excellence, driven by the engagement of diverse researchers and readers from around the world.

Yeping Li

A decade of advancing development, diversity, engagement, and excellence in STEM education

STEM教育中推进发展、多样性、参与度和卓越的十年

Abstract The pervasive digitization of society underscores the crucial role of data and its significant impact on decision-making across various domains. As a result, it is essential for individuals to acquire competencies in handling data. This need is particularly pertinent in K-12 education, where early engagement with data and statistics can lay a foundational understanding for future academic and professional endeavors. Additionally, K-12 education should provide students with critical skills necessary for navigating the complexities of daily life and making informed decisions in a data-rich society. This systematic review examines the state of research on statistical and data literacy in K-12 STEM (Science, Technology, Engineering, and Mathematics) education. It focuses specifically on cognitive, affective, and behavioral metrics and pedagogical approaches empirically investigated in this context. Using a rigorous selection process, we identified and synthesized 83 original empirical papers. Additionally, we invited the authors of these studies to share their perspectives on future strategies for addressing statistical and data literacy. The results indicate that the included studies primarily focus on the construct of statistical literacy, which is operationalized through a diverse array of metrics, predominantly within the context of mathematics education. We identified effective pedagogical approaches, such as authentic problem-solving and the integration of real-world data. The researchers surveyed emphasized the importance of interdisciplinary teaching, adapted curricula, and improved professional development for pre- and in-service teachers. Our findings underscore the growing relevance of this field, but suggest that integrated perspectives on statistical and data literacy within STEM subjects are limited.

Anja Friedrich

Saskia Schreiter

Markus Vogel

Sebastian Becker-Genschow

Roland Brünken

Jochen Kuhn

Jessica Lehmann

Sarah Malone

What shapes statistical and data literacy research in K-12 STEM education? A systematic review of metrics and instructional strategies

K-12 STEM教育中统计与数据素养研究的形式是什么？基于指标和教学策略的系统综述

Abstract We discuss transforming STEM education using three aspects: learning progressions (LPs), constructed response performance assessments, and artificial intelligence (AI). Using LPs to inform instruction, curriculum, and assessment design helps foster students’ ability to apply content and practices to explain phenomena, which reflects deeper science understanding. To measure the progress along these LPs, performance assessments combining elements of disciplinary ideas, crosscutting concepts and practices are needed. However, these tasks are time-consuming and expensive to score and provide feedback for. Artificial intelligence (AI) allows to validate the LPs and evaluate performance assessments for many students quickly and efficiently. The evaluation provides a report describing student progress along LP and the supports needed to attain a higher LP level. We suggest using unsupervised, semi-supervised ML and generative AI (GAI) at early LP validation stages to identify relevant proficiency patterns and start building an LP. We further suggest employing supervised ML and GAI for developing targeted LP-aligned performance assessment for more accurate performance diagnosis at advanced LP validation stages. Finally, we discuss employing AI for designing automatic feedback systems for providing personalized feedback to students and helping teachers implement LP-based learning. We discuss the challenges of realizing these tasks and propose future research avenues.

Leonora Kaldaras

Kevin Haudek

Joseph Krajcik

Employing automatic analysis tools aligned to learning progressions to assess knowledge application and support learning in STEM

运用与学习进阶相匹配的自动分析工具评估知识应用并支持STEM学习

Abstract Background Integration of digital tools and resources in STEM instruction has garnered significant attention due to its high potential. Digital professional development is identified as a pivotal factor for equipping teachers with necessary digital skills to effectively orchestrate digital resources. Notably, the role of professional learning communities is considered critical. However, the intricate relationships among digital professional development, professional learning communities, and digital instructional integration among STEM teachers remain underexplored. Utilizing partial least-squares–structural equation models (PLS–SEM), the present study examined links in digital professional development, professional learning communities, and digital instructional integration among STEM teachers ( N = 16,072) who participated in the Programme for International Student Assessment (PISA) 2022. Results Findings from the PLS–SEM analysis indicate that digital professional development exhibits a direct positive relationship with professional learning communities and digital instructional integration. Relatedly, professional learning communities is positively correlated with digital instructional integration. In terms of indirect effect, findings show that professional learning communities play a significant positive mediating role in linking digital professional development and digital instructional integration. Conclusions This study reports new evidence on the influence of digital professional development on digital instructional integration through professional learning communities among 16,072 STEM teachers and concludes that, when STEM teachers regularly immerse themselves in professional learning communities, they are more likely to benefit from their digital professional development by integrating digital technologies in classroom instruction. Policymakers and educational leaders should consider promoting digital professional development and professional learning communities among STEM teachers, along with efforts to encourage digital instructional integration.

Ji Liu

Millicent Aziku

Faying Qiang

Bin Zhang

Leveraging professional learning communities in linking digital professional development and instructional integration: evidence from 16,072 STEM teachers

利用专业学习共同体连接数字专业发展和教学整合：来自16,072名STEM教师的证据

Abbreviation	IJ STEM Ed
Journal Impact	5.43
Quartiles(Global)	EDUCATION, SCIENTIFIC DISCIPLINES(Q1)

ISSN	2196-7822
h-index	50
Top Journals	Yes

Publication Information	Publisher: SpringerOpen，Publishing cycle: ，Journal Type: journal，Open Access Journals: Yes
Basic data	Year of publication: 2014，Proportion of original research papers: 86.15%，Self Citation Rate:8.90%， Gold OA Rate: 100.00%
Journal Fees	$1990Details
Average review cycle	网友分享经验：13 Weeks

International Journal of STEM Education

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