What Is STEM Education

2021 ◽  
Vol 9 (3) ◽  
pp. 19-29
Author(s):  
Daniela Kozhuharova ◽  
Mariya Zhelyazkova
Keyword(s):  
Stem Education ◽  
Stem Learning

The article discusses the essence of STEM learning – its occurrence, definitions and skills that it develops in students. Based on a survey among Bulgarian teachers, an analysis of their knowledge and understanding of the occurrence and applicability of STEM training in the Bulgarian school was made.

scholarly journals Understanding intrinsic challenges to STEM instructional practices for Chinese teachers based on their beliefs and knowledge base

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Yan Dong ◽  
Jing Wang ◽  
Yunying Yang ◽  
Premnadh M. Kurup
Keyword(s):  
Knowledge Base ◽  
Stem Education ◽  
Structural Equation ◽  
Mathematical Problem ◽  
Equation Model ◽  
Chinese Society ◽  
Stem Learning ◽  
Chinese Teachers ◽  
Teachers Beliefs ◽  
K 12

Abstract Background China has great student participation in STEM education. Chinese society has a progressive and positive attitude towards STEM as it is considered to provide more opportunities in life. Teachers play a vital role in the success of any STEM program in K-12 schools. However, teachers are facing instructional challenges because of the interdisciplinary nature of the STEM curriculum and the current typical school structure. The success of the STEM programs depends on teachers’ beliefs and their knowledge in adapting to instructional implementation of STEM concepts. Results The data (n = 216) was collected from STEM primary and secondary teachers from 25 provinces in mainland China. Exploratory factor analysis (EFA) was applied, and Pearson’s correlation analysis was used to examine the correlation between Chinese STEM teachers’ beliefs, knowledge, implementation, and the intrinsic challenges of STEM education; t tests and analysis of variance (ANOVA) were performed to ascertain whether there were differences. The structural equation model (SEM) was applied to identify interrelationships. The results indicated that Chinese STEM teachers encounter higher-level intrinsic challenges to instructional implementations based on their beliefs and knowledge. Teachers who utilize their experience of teaching science as their main discipline and then attempt to integrate STEM using mathematics and engineering are likely to encounter higher-level intrinsic challenges in implementation. Conclusion The intrinsic challenges perceived by Chinese teachers in the practice of STEM education can be predicted by their beliefs and knowledge base. Teachers who understand the nature and pedagogy of STEM education are more likely to encounter lower-level intrinsic challenges of STEM teaching, while teachers who utilize their main discipline when conducting integrated STEM learning activities through modeling based on science, technology, engineering, and mathematical problem situations are more likely to encounter higher-level intrinsic challenges. This study also reveals that there are some significant differences in the level of STEM teachers’ beliefs, knowledge base, instructional practice, and their intrinsic challenges based on their teaching grade, seniority, and experience of STEM training and teaching.

An analysis of Australian STEM education strategies

2018 ◽  
Vol 17 (2) ◽  
pp. 122-139 ◽  
Author(s):  
Steve Murphy ◽  
Amy MacDonald ◽  
Lena Danaia ◽  
Cen Wang
Keyword(s):  
Early Childhood ◽  
Stem Education ◽  
Career Pathways ◽  
Learning Trajectories ◽  
Stem Learning ◽  
Equity Issues ◽  
Australian State ◽  
Education Strategy ◽  
The Individual ◽  
Stem Dispositions

In December 2015 the Australian state and territory governments endorsed the ‘National STEM School Education Strategy 2016–2026’. Since then, the individual jurisdictions have released their own STEM education strategies that aim to improve student STEM capabilities and aspirations. This paper analyses the various Australian STEM education strategies in relation to six themes informed by research into effective STEM education: STEM capabilities; STEM dispositions; STEM educational practices; Equity; Trajectories; and Educator capacities. The analysis shows that Australia’s STEM education strategies focus on actions aimed at building student STEM capabilities, particularly through inquiry and problem-based learning, and enhancing educator capacity. The strategies recognise student STEM learning trajectories and pay particular attention to the importance of early childhood STEM education, as well as the ways in which students’ potential career pathways might be influenced. However, less emphasis is placed on supporting key transitions in STEM education, developing student STEM dispositions, and addressing equity issues in STEM.

scholarly journals Studies of impact of specialized STEM training on choice further education

2020 ◽  
Vol 75 ◽  
pp. 04014 ◽  
Author(s):  
Viacheslav Osadchyi ◽  
Nataliia Valko ◽  
Liudmyla Kuzmich ◽  
Nataliya Abdullaeva
Keyword(s):  
Stem Education ◽  
Teaching Methods ◽  
Essential Element ◽  
Education Institution ◽  
Further Education ◽  
Self Determination ◽  
Stem Learning ◽  
Motivation For Learning ◽  
Conscious Choice ◽  
Professional Self

The specialized training influence to the choice of further direction of study is considered in the work. The assumption that early involvement of students in the study of natural and mathematical disciplines, in particular mathematics is given. It will stimulate young people to get STEM education in future. The essential element in future professional choice, development and formation is the issue of motivation for learning. It is important that modern students are gradually losing their incentive to study. Almost a third of those who choose the appropriate study profile have contradictions between professional self-determination and the availability of the necessary knowledge for the profession, between choosing a higher education institution and being able to enter in it. The contradiction requires purposeful formation of a conscious choice of future activities. The conducted research has shown that the basis of the motivational component of the choice of STEM-learning is studying of natural and mathematical disciplines by modern teaching technologies and organizing of additional lessons system based on the projected teaching methods. It satisfies the growing needs for intelligence, knowledge, motivational beliefs to understand the specifics of the future profession.

scholarly journals Best IASL Conference 2017 Paper: Preparing Teacher Librarians to Support STEM Education

2017 ◽  
pp. 1-11
Author(s):  
Melissa P. Johnston
Keyword(s):  
Stem Education ◽  
Teaching And Learning ◽  
The United States ◽  
Stem Learning ◽  
Post Secondary ◽  
Integration Of Technology ◽  
And Mathematics ◽  
Teacher Librarians ◽  
New Generation ◽  
Pre Service Teacher

A current focus in schools in the United States is STEM education, which prepares students for successful employment and post-secondary studies that require unique and more-technically advanced skills through teaching and learning in the areas of science, technology, engineering, and mathematics (STEM). This approach is grounded in problem solving, discovery, and exploratory learning, which requires students to actively engage in a situation in order to find its solution. Students engage in STEM learning in many different ways, with technology and digital resources playing an important role. The prominence of technology in STEM education provides leadership opportunities for teacher librarians. Yet, teacher librarians must be prepared to lead in the integration of technology to support STEM education. This report presents identified needs of teacher librarians in regards to supporting STEM education and discusses implications for better preparing pre-service teacher librarians to lead in order to address the needs of a new generation of learners.

scholarly journals STEM Education in Indonesia: Science Teachers’ and Students’ Perspectives

2021 ◽  
Vol 2 (1) ◽  
pp. 7-16
Author(s):  
Anna Permanasari ◽  
Bibin Rubini ◽  
Oktian Fajar Nugroho
Keyword(s):  
Science Teachers ◽  
Stem Education ◽  
Training And Development ◽  
Stem Learning ◽  
Lesson Analysis ◽  
Teachers And Students ◽  
Points Of View ◽  
Level Of Understanding ◽  
Teachers Training ◽  
Survey Approach

STEM education in indonesia has become a commitment for all of stakeholders in the field of science education in the last several years. All education participants agree to increase the popularity of STEM education in various parties, especially teachers and students. The research has been conducted to see to what extent science teachers in the secondary school interpret and understand STEM education and how Students pertain toward STEM learning. The research was conducted with a descriptive method using a survey approach. A set of questionnaire which comprises open-ended and closed-ended questions about teachers’ and students’ perceptions and understanding regarding STEM education were developed and applied. Responses from science teachers as well as students were then analysed through interpretative methods in which the participants’ own meanings and points of view were sought. The result indicated that STEM education is quite well understood by science teachers. Most of teachers show the same level of understanding toward STEM Education. Unfortunately, not many teachers have applied the STEM approach for science learning in the classroom. This is led to the weak understanding of STEM learning in students’side. Most of students did not familiar with “STEM learning” term. Based on the research, it is reccomended that the science teachers’ training and development should be reorientated and implemented through lesson analysis with various best practices on STEM learning systematically and continually.

scholarly journals Fabric-Based Computing: (Re)examining the Materiality of Computer Science Learning Through Fiber Crafts

2021 ◽  
Author(s):  
Anna Keune
Keyword(s):  
Computer Science ◽  
Stem Education ◽  
Science Learning ◽  
Cultural Practices ◽  
Educational Practice ◽  
Computational Learning ◽  
Stem Learning ◽  
Domestic Practices ◽  
Materials Used ◽  
Fabric Manipulation

AbstractFiber crafts, such as weaving and sewing, occupy a tension-filled space within computing. While associated with domestic practices, fiber crafts have been recognized as a precursor of the earliest computers and continue to present sources of computational inspiration. The connections between fiber crafts and computing have the potential to uncover possibilities for computing to become more diversified in terms of materials, cultural practices, and ultimately people. To explore the promises of fiber crafts for STEM education, this qualitative dissertation built on constructionist and posthumanist perspectives to examine two fiber crafts (i.e., weaving and fabric manipulation) as contexts for computer science learning. Collectively, the dissertation effectively aligned fiber crafts with computational concepts and showed their potential as a promising context for computer science learning. The work further showed that materials used for STEM learning are non-neutral. Materials matter in what can be learned computationally. Lastly, guided by posthumanist perspectives, the dissertation uncovered computational learning as the process of producing physical expansions and highlighted learning as the process of how computational concepts physically change. The work has implications for theorizing learning, designing for learning, and educational practice. For example, the dissertation presents the utility of posthumanist perspectives as an additional theoretical approach to the study of learning that can surface and help address ongoing relational deficit orientations.

scholarly journals Which Cognitive Abilities Make the Difference? Predicting Academic Achievements in Advanced STEM Studies

2018 ◽  
Vol 6 (4) ◽  
pp. 48 ◽  
Author(s):  
Michal Berkowitz ◽  
Elsbeth Stern
Keyword(s):  
Spatial Ability ◽  
Stem Education ◽  
Undergraduate Students ◽  
Cognitive Abilities ◽  
Structural Equation ◽  
Equation Model ◽  
Stem Learning ◽  
Ability Test ◽  
Reasoning Abilities ◽  
The Difference

Previous research has shown that psychometrically assessed cognitive abilities are predictive of achievements in science, technology, engineering and mathematics (STEM) even in highly selected samples. Spatial ability, in particular, has been found to be crucial for success in STEM, though its role relative to other abilities has been shown mostly when assessed years before entering higher STEM education. Furthermore, the role of spatial ability for mathematics in higher STEM education has been markedly understudied, although math is central across STEM domains. We investigated whether ability differences among students who entered higher STEM education were predictive of achievements during the first undergraduate year. We assessed 317 undergraduate students in Switzerland (150 from mechanical engineering and 167 from math-physics) on multiple measures of spatial, verbal and numerical abilities. In a structural equation model, we estimated the effects of latent ability factors on students’ achievements on a range of first year courses. Although ability-test scores were mostly at the upper scale range, differential effects on achievements were found: spatial ability accounted for achievements in an engineering design course beyond numerical, verbal and general reasoning abilities, but not for math and physics achievements. Math and physics achievements were best predicted by numerical, verbal and general reasoning abilities. Broadly, the results provide evidence for the predictive power of individual differences in cognitive abilities even within highly competent groups. More specifically, the results suggest that spatial ability’s role in advanced STEM learning, at least in math-intensive subjects, is less critical than numerical and verbal reasoning abilities.

scholarly journals Direction of collaborative problem solving-based STEM learning by learning analytics approach

2019 ◽  
Vol 14 (1) ◽  
Author(s):  
Li Chen ◽  
Nobuyuki Yoshimatsu ◽  
Yoshiko Goda ◽  
Fumiya Okubo ◽  
Yuta Taniguchi ◽  
...  
Keyword(s):  
Problem Solving ◽  
Learning Strategies ◽  
Stem Education ◽  
Learning Analytics ◽  
Learning Strategy ◽  
Collaborative Problem Solving ◽  
Learning Performance ◽  
Stem Learning ◽  
Learning Behaviors ◽  
Collaborative Problem

AbstractThe purpose of this study was to explore the factors that might affect learning performance and collaborative problem solving (CPS) awareness in science, technology, engineering, and mathematics (STEM) education. We collected and analyzed data on important factors in STEM education, including learning strategy and learning behaviors, and examined their interrelationships with learning performance and CPS awareness, respectively. Multiple data sources, including learning tests, questionnaire feedback, and learning logs, were collected and examined following a learning analytics approach. Significant positive correlations were found for the learning behavior of using markers with learning performance and CPS awareness in group discussion, while significant negative correlations were found for some factors of STEM learning strategy and learning behaviors in pre-learning with some factors of CPS awareness. The results imply the importance of an efficient approach to using learning strategies and functional tools in STEM education.

A Novel Strategy to Improve STEM Education

2015 ◽  
pp. 1215-1226
Author(s):  
Samar I. Swaid
Keyword(s):  
Stem Education ◽  
Information Acquisition ◽  
Computational Thinking ◽  
Instructional Delivery ◽  
Stem Learning ◽  
Computing Services ◽  
Information And Communication ◽  
Low Performance ◽  
And Mathematics ◽  
Novel Strategy

Undergraduate traditional instructional delivery that does not utilize computation is linked significantly to students' low performance and thereby attrition. Over the last two decades, new computational technologies, information, and communication have emerged, creating comprehensive cyberinfrastructure-based service systems, or what is termed here e-science. E-science environments are virtual systems that support data management, data mining, information acquisition, visualization, computing services, and people collaboration over the Web. Although a number of attempts have been successful in utilizing e-science environments to change how research is conducted, using e-science environments for education has been rarely realized. This chapter describes a project that aims to transform Science, Technology, Engineering, and Mathematics (STEM) education through using e-science systems at the undergraduate level. The strategy is built on three arms: (1) injecting Computational Thinking (CT) in STEM education; (2) using e-science for STEM learning; and (3) building a community-of-practice around e-science. By using e-science resources and services, an inquiry-based approach to learning can be the key to students' motivations, achievements, and enthusiasm for science.

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