Journal of Education in Science, Environment and Health
type: channel
description: The Journal of Education in Science, Environment and Health (JESEH) is a peer-reviewed scholarly online journal. The JESEH is published quarterly in January, April, July and October. The language of the journal is English only. The JESEH welcomes any research papers on education in science, environment and health using techniques from and applications in any technical knowledge domain: original theoretical works, literature reviews, research reports, social issues, psychological issues, curricula, learning environments, and review articles. The articles should be original, unpublished, and not in consideration for publication elsewhere at the time of submission to the JESEH. JESEH accepted articles in three different fields related to each other. These areas are science education, environmental education and health education. The following content is given priority in the articles in these three areas.Science Education: Scholarly papers that focus on the teaching and learning of science in school settings ranging from early childhood to university education and the integration of science education with other disciplines, in particular, STEM (Science, Technology, Engineering, Mathematics), virtual laboratory, distance science and STEM education, research articles of the highest quality that address the intersection of science education and technology with implications for improving and enhancing science education at all levels across the world.Environmental Education: Papers and reports on all aspects of environmental education such as environmental issues such as air, water, soil pollution; acid rains, carbon footprints, climate change, greenhouse effect and global warming, and sustainable development. Manuscripts focus on enhancing understanding of outdoor and environmental education issues, environmental awareness, energy source and renewable energy, waste management, and consumption society through balanced and in-depth investigation of practices and theories rel…
publisher: ISRES Publishing - International Society for Research in Education and Science (ISRES)
language: en
publication name: Journal of Education in Science, Environment and Health
issn: 2149-214X
copyright: The articles may be used for research, teaching, and private study purposes. Any substantial or systematic reproduction, redistribution, reselling, loan, sub-licensing, systematic supply, or distribution in any form to anyone is expressly forbidden. Authors alone are responsible for the contents of their articles. The journal owns the copyright of the articles. The publisher shall not be liable for any loss, actions, claims, proceedings, demand, or costs or damages whatsoever or howsoever caused arising directly or indirectly in connection with or arising out of the use of the research material. All authors are requested to disclose any actual or potential conflict of interest including any financial, personal or other relationships with other people or organizations regarding the submitted work.
items: Examining Biology Teachers’ Cognitive Structures Regarding Artificial Intelligence Using a Word Association Test
items: The Relationship Between Science Teachers' Self-Efficacy and Anxiety Regarding Out-of-School Learning and Middle School Students' Informal Science Experiences
items: A Phenomenological Exploration of Pre-service Science Teachers’ Perspectives on Artificial Intelligence
items: A Comprehensive Bibliometric Analysis of Artificial Intelligence Research in the Field of Science Education
items: A Systematic Review Study on the Use of Artificial Intelligence in Environmental Education
items: Use of Artificial Intelligence in Biology Education: A Systematic Review of Literature
items: Development of Four Tier Misconception Test on Electrochemistry
items: Anxiety about Artificial Intelligence as an Emerging Field of Science: The Example of Preschool Teacher Candidates
items: Investigation of Pre-Service Teachers’ Artificial Intelligence Literacy and Views on the Use of Artificial Intelligence in Education
items: Primary School Students' Learning Achievement and Attitudes Towards Inquiry-Based Science Fieldwork with Socio-Demographic Information
items: The Impact of Generative AI Applications on Student Learning Outcomes in Science Education: A Systematic Review
items: Evaluation of Images Related to Climate Change with Deep Learning Models
items: Introducing Polar Animals with an AI-Based Educational Game: A Study for Middle School Students
items: Digitizing Early Childhood Environmental Education: A Bibliometric Study
items: The Effectiveness of Science Course Prepared According to Systematic Planning Model with ICT Integration: A Mixed Method Research
items: Technological Tools Used in Misconceptions Studies in Physics Education: A Systematic Review
items: The Heart and Art of Robotics: From AI to Artificial Emotional Intelligence in STEM Education
items: Exploring Elementary Preservice Teachers’ Nature Investigations
items: Bibliometric Analysis of Studies on Artificial Intelligence in Environmental and Health Education
items: Virtual Reality Technology in Science Education: Exploring Trends and Future Perspectives
items: Artificial Intelligence in Early Childhood STEM Education: A Review of Pedagogical Paradigms, Ethical Issues, and Socio-Political Implications
items: Use of Artificial Neural Network in Educational Laboratory Applications: Low-Velocity Impact Test
items: Gifted Students' Perceptions of Artificial Intelligence through Drawings: A Perspective from Science and Art Centers
items: Students’ Level of Awareness on the Environmental Implications of Generative AI
items: An Investigation of Coding Education Practices in terms of Primary School Students' Algorithmic Thinking Skills and Students' Opinions
items: Development of Science Process Skills and Learning Achievement Using Flipped Classroom Learning Management through Inquiry-Based Learning for Grade 8 Students
items: The Relationship between Gifted Students’ Scientific Epistemological Beliefs and Climate Change Awareness Levels
items: Bibliometric Analysis of Studies on the Artificial Intelligence in Science Education with VOSviewer
items: Use of Multi-Tier Concept Diagnostic Tests in Biology Education: A Systematic Review of the Literature
items: Decarbonizing K-12 Schools in the United States: Challenges, Opportunities and Future Directions

Examining Biology Teachers’ Cognitive Structures Regarding Artificial Intelligence Using a Word Association Test
type: item
description: In recent years, artificial intelligence has attracted great attention worldwide, particularly due to its impact on all areas of human life. The reasons for this interest include the rapid increase in the changes that artificial intelligence applications may bring to individuals’ lifestyles and the structure of society, and the potential problems that may accompany these changes. As in many other fields, artificial intelligence has quickly entered educational settings and has become a focal point for both students and teachers. In this respect, revealing teachers’ cognitive structures regarding artificial intelligence is of great importance, as their approaches to this development will directly influence their students. The aim of this study is to examine the conceptual frameworks of biology teachers regarding artificial intelligence. The data were collected from 126 participants using a free word association test. The analysis of the free word association test demonstrates various aspects of the participants’ conceptual frameworks concerning artificial intelligence. The participants emphasized the potential benefits of artificial intelligence in terms of advanced technologies, education, benefits to humanity, and contributions to the cultural and economic life of society. However, they also expressed the view that artificial intelligence may entail potential drawbacks, including ethical issues, security risks, and the risk of promoting laziness.
subject: Articles
  topic: section
subject: Artificial intelligence
  topic: keywords
subject: Biology teacher
  topic: keywords
subject: Cognitive structure
  topic: keywords
subject: Word association
  topic: keywords
creator: Sultan Cikrik
creator: Tugce Duran
creator: Musa Dikmenli
creator: Selda Kilic
rights: Copyright (c) 2026 Journal of Education in Science, Environment and Health https://creativecommons.org/licenses/by/4.0
date: 2026-01-01
publication date: 2026-01-01
starting page: 43
ending page: 59
doi: 10.55549/jeseh.889

The Relationship Between Science Teachers' Self-Efficacy and Anxiety Regarding Out-of-School Learning and Middle School Students' Informal Science Experiences
type: item
description: Pestalozzi emphasised that nature and life outside school are valuable teachers for children, stating, ‘When the birds are chirping beautifully and a worm is crawling on a leaf, stop your language studies immediately. Know that the bird and the worm teach the child better and more.’ All educational activities that take place outside of school throughout an individual's life are defined as ‘out-of-school education,’ and the learning occuring during this process is defined as ‘out-of-school learning.’ The scope of out-of-school learning environments is quite broad, and these environments are often considered as ‘learning laboratories.’ The aim of this study is to determine the relationship between science teachers' self-efficacy beliefs and anxiety levels regarding out-of-school learning and the levels of science experience acquired by the secondary school students taught by these teachers in informal settings. A correlational research design was utilized as a quantitative method in the study. The study sample consisted of 100 science teachers working in state schools in Eskişehir during the academic year of 2022-2023 and 2,767 secondary school students attending these teachers' classes. Convenience sampling was adopted to determine the study sample. The following data collection tools were used: Teacher Self-Efficacy Beliefs Scale for Out-of-School Learning Activities, Anxiety Level Assessment Scale for Out-of-School Learning Environments, a personal information form, and the Science Experience in Informal Settings Scale. The findings indicate a significant relationship between science teachers’ self-efficacy beliefs regarding out-of-school learning and their ability to design and organize out-of-school learning activities. However, no significant differences in self-efficacy beliefs were observed with respect to training related to out-of-school learning environments, years of professional experience, or graduation background. Furthermore, science teachers’ levels o…
subject: Articles
  topic: section
subject: Out of school learning environments, Informal learning, Science teacher, Self-efficacy belief, Anxiety
  topic: keywords
creator: Neslihan Er
creator: Bilge Gok
rights: Copyright (c) 2026 Journal of Education in Science, Environment and Health https://creativecommons.org/licenses/by/4.0
date: 2026-01-01
publication date: 2026-01-01
starting page: 83
ending page: 94
doi: 10.55549/jeseh.888

A Phenomenological Exploration of Pre-service Science Teachers’ Perspectives on Artificial Intelligence
type: item
description: Artificial intelligence (AI) in science education offers significant advantages to pre-service teachers in lesson planning, developing teaching resources, and implementing personalized learning. Simulations, visualizations, and intelligent assessment systems contribute to the concretization of abstract concepts and increased student participation. This phenomenological study aims to determine preservice science teachers' views on AI. To this end, semi-structured interviews were conducted with 13 preservice teachers from different grade levels who had prior experience with AI, including virtual laboratory applications. A semi-structured interview form was used for this purpose, and the data were evaluated using content analysis. Strategies such as in-depth data collection, expert review, and member check were employed to ensure internal validity. The findings indicate that preservice teachers view AI as a tool that supports lesson planning and teaching processes. However, they also believe that excessive reliance on AI may limit teachers' creativity. Participants' views were grouped into the following categories: AI use in educational processes, the effects of AI on students, reliability, and the role of the teacher. One emerging finding is that preservice teachers often do not verify the information they obtain from AI. The study highlights the potential of AI as a pedagogical tool in science education and the factors teachers should consider when using AI.
subject: Articles
  topic: section
subject: Preservice science teacher
  topic: keywords
subject: Artificial intelligence
  topic: keywords
subject: Integration
  topic: keywords
creator: Ibrahim Serdar Kiziltepe
creator: Tezcan Kartal
rights: Copyright (c) 2026 Journal of Education in Science, Environment and Health https://creativecommons.org/licenses/by/4.0
date: 2026-01-01
publication date: 2026-01-01
starting page: 30
ending page: 42
doi: 10.55549/jeseh.872

A Comprehensive Bibliometric Analysis of Artificial Intelligence Research in the Field of Science Education
type: item
description: Today, the importance of artificial intelligence in science learning and teaching is rapidly increasing. The growing interest in this field and the resulting increase in academic publications on the subject make it challenging to understand its progress and trends on a global scale. Furthermore, a literature review reveals a notable lack of studies that offer a comprehensive perspective, reflecting the current state and research trends in this field. Therefore, this study aims to analyze the current state, evolution, and important research trends in studies on artificial intelligence in science education from 1985 to 2024, utilizing bibliometric methods. To this end, a total of 169 articles were analyzed from the Web of Science database using specific keywords. Analytical tools such as VOSviewer and SciMAT software were used for data visualization. The results indicate that research on artificial intelligence in science education from 1985 to 2024 has developed irregularly, with significant growth occurring in recent years. The country with the highest citation and production levels in this research field is the United States. The most productive journals in the area are the Journal of Science Education and Technology, Frontiers in Education, and the Journal of Research in Science Teaching. The leading authors are Cooper, G., and Zhai, X. Keyword analysis showed that “science education,” “computer science education,” “machine learning,” “artificial intelligence assessment,” “ChatGPT,” and “learning analytics” are among the most frequently used terms and highlight emerging thematic clusters. Furthermore, this analysis showed that while artificial intelligence research in science education was initially more limited and focused on technology-related themes, it has recently shifted toward a research direction that includes learning analytics, interactive learning environments, computational thinking, and large language models. The results offer a guiding framework and …
subject: Articles
  topic: section
subject: Research trends
  topic: keywords
subject: Artificial intelligence
  topic: keywords
subject: Science education
  topic: keywords
subject: Bibliometric analysis
  topic: keywords
subject: Web of Science
  topic: keywords
creator: Seyma Ulukok-Yildirim
creator: Duygu Sonmez
rights: Copyright (c) 2025 Journal of Education in Science, Environment and Health https://creativecommons.org/licenses/by/4.0
date: 2025-10-01
publication date: 2025-10-01
starting page: 334
ending page: 353
doi: 10.55549/jeseh.870

A Systematic Review Study on the Use of Artificial Intelligence in Environmental Education
type: item
description: Environmental education is the solution to the environmental problems caused by technological advancements. Technological advancements make human life easier in many aspect. Today, artificial intelligence is one of the current technological advancements. The purpose of this research is to determine the general trend in studies on the use of artificial intelligence in environmental education, identify gaps in the relevant literature, and explain how current developments in educational technologies impact environmental education. This research is a systematic review. In this research, studies on the use of artificial intelligence in environmental education were systematically compiled to reveal how new developments in artificial intelligence affect the environmental education process. Seventeen studies were included in the review process. This research has two main conclusions. First, artificial intelligence in environmental education is a relatively new and current topic in literature. Second, the use of artificial intelligence tools causes water waste and carbon emissions. Therefore, the conscious use of artificial intelligence is essential for both teachers and students to be aware of it.
subject: Articles
  topic: section
subject: Environmental education
  topic: keywords
subject: Artificial intelligence
  topic: keywords
creator: Pelin Koseoglu
creator: Sinan Erten
rights: Copyright (c) 2026 Journal of Education in Science, Environment and Health https://creativecommons.org/licenses/by/4.0
date: 2026-01-01
publication date: 2026-01-01
starting page: 20
ending page: 29
doi: 10.55549/jeseh.869

Use of Artificial Intelligence in Biology Education: A Systematic Review of Literature
type: item
description: In recent years, the use of artificial intelligence (AI) has become increasingly widespread and has attracted significant attention worldwide. In this study, a systematic review was conducted to determine the use of AI in biology education and the prevailing trends in its application. The study aimed to conduct a comprehensive review of articles published between 2010 and 2024 that employed artificial intelligence in biology education. In line with this aim, a total of 49 keywords were searched from Web of Science, SCOPUS, ERIC and IEEE Xplore databases. The entire process was summarized in the PRISMA diagram. 39 articles were deemed eligible for inclusion in the systematic review. The selected articles were analyzed in terms of publication year, research method, country of conduct, study group, number of participants, subject area, artificial intelligence technologies used, artificial intelligence applications used, and their outcomes. An evaluation of the articles according to the main topics in biology revealed that there is a lack of sufficient research on the evolutionary history of biodiversity and the models and processes of evolution. It was also found that there is a lack of sufficient research in the literature on artificial intelligence-supported educational games and simulations in biology education. In this context, it is recommended that the use of artificial intelligence technologies in biology education be expanded to include educational games, which are frequently used to motivate students and encourage learning, and simulations, which are suitable for development in many areas of biology education.
subject: Articles
  topic: section
subject: Biology education
  topic: keywords
subject: Artificial intelligence
  topic: keywords
subject: Systematic review
  topic: keywords
creator: Tugce Duran
creator: Musa Dikmenli
rights: Copyright (c) 2025 Journal of Education in Science, Environment and Health https://creativecommons.org/licenses/by/4.0
date: 2025-10-01
publication date: 2025-10-01
starting page: 314
ending page: 333
doi: 10.55549/jeseh.864

Development of Four Tier Misconception Test on Electrochemistry
type: item
description: The purpose of this study was to develop a valid and reliable measurement tool that can be used to identify pre-service teachers' misconceptions about electrochemistry. The Electrochemistry Concept Test (ECT) developed for this purpose consists of a total of 12 questions, each containing four tiers. The Electrochemistry Concept Test (ECT) was applied to a total of 307 science teacher candidates from 10 different universities in seven regions of Türkiye. The data were analyzed using Excel, SPSS, and Factor programs. A four-factor structure with 12 questions was determined using EFA, and the KMO value of the test was calculated as 0,682, indicating that this four-factor structure explained 48% of the total variance. As a result of the reliability analyses, the KR-20 reliability coefficient for the scientific knowledge score obtained from correct answers was calculated as .819, and the KR-20 reliability coefficient for the misconception score obtained from wrong answers was calculated as 0,702. The item analyses revealed that the difficulty and discriminative indices of the test were at an intermediate level. Positive and negative wrong values were calculated for content validity. The validity and reliability analyses confirm that the developed test is a valid and reliable measurement tool. As a result of the analysis of the data collected in the study, it was determined that the pre-service teachers had misconceptions above 10% for each question related to electrochemistry - activity, reduction–oxidation, galvanic cell reactions, and cell potential - and that their scientific knowledge was not at a sufficient level. As a result of the study, a total of 37 misconceptions related to the topic of electrochemistry were identified, among which 9 misconceptions with a prevalence of over 10% were determined, thereby contributing new misconception statements to existing literature. In conclusion, a valid and reliable measurement tool has been developed that researchers can us…
subject: Articles
  topic: section
subject: Fen Eğitimi
  topic: keywords
subject: dört aşamalı test
  topic: keywords
subject: Kavram yanılgısı
  topic: keywords
subject: Elektrokimya
  topic: keywords
creator: Fatma Sener
creator: Cemil Aydogdu
rights: Copyright (c) 2026 Journal of Education in Science, Environment and Health https://creativecommons.org/licenses/by/4.0
date: 2026-01-01
publication date: 2026-01-01
starting page: 60
ending page: 82
doi: 10.55549/jeseh.858

Anxiety about Artificial Intelligence as an Emerging Field of Science: The Example of Preschool Teacher Candidates
type: item
description: The importance of artificial intelligence in daily life is increasing every day. This situation is inevitably reflected in educational environments. However, using artificial intelligence also causes anxiety. This study aims to determine the anxiety levels of preschool preservice teachers regarding artificial intelligence and examine them using various variables. The study was conducted using a survey, a quantitative research method. Data was collected from 208 volunteer participants using a convenience sampling method. The 16-item Artificial Intelligence Anxiety Scale was used as the data collection tool. t-test, ANOVA, percentage, and frequency were used in data analysis to obtain findings. In addition to the techniques used in interpreting the findings, the criterion for determining the level of artificial intelligence anxiety was used. The interpretation of the research findings revealed that preschool teachers had moderate levels of anxiety regarding artificial intelligence. This anxiety did not differ among preschool teachers' grade levels, daily internet use, knowledge about artificial intelligence, or number of siblings. However, it was found that there were differences in terms of gender.
subject: Articles
  topic: section
subject: Artificial Intelligence
  topic: keywords
subject: Artificial intelligence anxiety
  topic: keywords
subject: Educational technology
  topic: keywords
creator: Semih Ucar
creator: Salih Gulen
rights: Copyright (c) 2025 Journal of Education in Science, Environment and Health https://creativecommons.org/licenses/by/4.0
date: 2025-10-01
publication date: 2025-10-01
starting page: 305
ending page: 313
doi: 10.55549/jeseh.855

Investigation of Pre-Service Teachers’ Artificial Intelligence Literacy and Views on the Use of Artificial Intelligence in Education
type: item
description: This study aims to investigate the artificial intelligence (AI) literacy levels of pre-service teachers and their views on the use of AI in education. Adopting a mixed-methods approach, the study employed both quantitative and qualitative techniques to ensure comprehensive analysis. The quantitative data were collected using the “Artificial Intelligence Literacy Scale,” while qualitative data were gathered through open-ended questions developed by the researchers. The sample consisted of 323 pre-service teachers from different departments and grade levels at Nigde Omer Halisdemir University Faculty of Education. Statistical analyses, including independent samples t-tests and one-way ANOVA, were used to examine differences in AI literacy levels based on variables such as gender, age, grade level, field of study, parental education level, and use of AI technologies. Content analysis was applied to the qualitative data. The findings revealed that pre-service teachers generally possess high levels of AI literacy. Significant differences were observed based on personal factors such as having AI applications, receiving technology-related education, and using AI in academic tasks. However, no significant differences were found for gender, age, or parental education level. Qualitative findings indicated that pre-service teachers mostly use AI tools for academic purposes, recognize their benefits in terms of time-saving and knowledge access, but also express ethical concerns and the need for critical awareness. The study highlights the importance of embedding AI literacy into teacher education programs to prepare future educators for the digital age.
subject: Articles
  topic: section
subject: Artificial intelligence
  topic: keywords
subject: Education and AI
  topic: keywords
subject: Artificial intelligence literacy
  topic: keywords
creator: Oguz Cetin
creator: Gizem Celen
rights: Copyright (c) 2025 Journal of Education in Science, Environment and Health https://creativecommons.org/licenses/by/4.0
date: 2025-10-01
publication date: 2025-10-01
starting page: 285
ending page: 304
doi: 10.55549/jeseh.850

Primary School Students' Learning Achievement and Attitudes Towards Inquiry-Based Science Fieldwork with Socio-Demographic Information
type: item
description: This study investigated the impact of school setting, gender, and age on Namibian primary students’ learning achievement following an inquiry‑based science fieldwork (IBSF) intervention and examined how attitude towards IBSF varied by these factors. A mixed-methods approach was used with 100 seventh-grade students from two socio-demographically different schools. From this group, 20 students were purposively selected for semi-structured interviews. Thus, multiple linear regression, exploratory factor analysis, multivariate analysis of variance, and Pearson correlation coefficients were conducted. Our quantitative results showed that school setting—but not gender or age—significantly influenced post‑test learning achievement, underlining the critical role of the school environment in meeting learning outcomes. In contrast, school setting had no significant effect on students’ attitudes toward IBSF. Gender differences emerged in attitudes: boys reported more positive views of IBSF’s importance and greater eagerness to participate in future fieldwork, whereas girls expressed some reluctance despite strong performance. Content analysis of qualitative data confirmed that most students valued IBSF and were eager to engage again. These findings suggest that introducing IBSF at the primary level enhances students' understanding of science and its relevance to their futures. The study recommends that interventions also address gender stereotypes to promote equity and sustained interest in science education.
subject: Articles
  topic: section
subject: Inquiry-based science education
  topic: keywords
subject: Learning achievement
  topic: keywords
subject: Attitude
  topic: keywords
subject: Geoscience education
  topic: keywords
creator: Mirjam Ndaimehafo Asilevi
creator: Jingoo Kang
creator: Kari Sormunen
creator: Sirpa Karkkainen
creator: Sari Havu-Nuutinen
rights: Copyright (c) 2026 Journal of Education in Science, Environment and Health https://creativecommons.org/licenses/by/4.0
date: 2026-01-01
publication date: 2026-01-01
starting page: 1
ending page: 19
doi: 10.55549/jeseh.847

The Impact of Generative AI Applications on Student Learning Outcomes in Science Education: A Systematic Review
type: item
description: This systematic literature review examines the impact of generative artificial intelligence (AI) applications on student learning outcomes in middle school science education. Twelve studies that met the inclusion and exclusion criteria were included in the study. The studies were accessed from the WOS, SCOPUS, ERIC, and TrDizin indexes and databases. The PRISMA protocol was used in the selection of studies. The analysis reveals that generative AI tools significantly contribute to academic achievement, conceptual understanding, scientific and digital literacy, personalized learning opportunities, and students' motivational and emotional outcomes. The systematic review further emphasizes the importance of integrating AI tools into science education in a pedagogically and ethically sound manner. Recommendations include increasing AI literacy among teachers, incorporating ethical awareness into instruction, and developing culturally sensitive and interdisciplinary educational practices. Generative AI stands out as a transformative technology for improving the quality, accessibility, and inclusivity of science education.
subject: Articles
  topic: section
subject: Gen AI
  topic: keywords
subject: artificial intelligence
  topic: keywords
subject: science education
  topic: keywords
subject: student outcomes
  topic: keywords
subject: Systematic review
  topic: keywords
creator: Meryem Seda Gunsaldi
creator: Elif Gamze Guner
creator: Musa Uckan
creator: Kaan Bati
rights: Copyright (c) 2025 Journal of Education in Science, Environment and Health https://creativecommons.org/licenses/by/4.0
date: 2025-06-30
publication date: 2025-06-30
starting page: 196
ending page: 208
doi: 10.55549/jeseh.840

Evaluation of Images Related to Climate Change with Deep Learning Models
type: item
description: This study is developing a Deep Learning model automating the coding of drawings students provide about climate change phenomena in our world, as a learning contribution through formative assessment. We started first with ResNet50 architecture, but ultimately, we settled on MobileNetV2 reduced architecture for the sake of being able to integrate with mobile- and web-based applications. The challenge is the model has very few examples in the training set to work with, so we decided augmenting the data (i.e., rotate, zoom, flip horizontally,) will help the model generalize more reliably. The model achieved training accuracy of 92% and validation accuracy of 90%. Moreover, we were able to reduce the model size about 85% through optimization. Our model outputs not a simple classification, it also produces explanatory feedback for each class, and we have made possible for the feedback to be read by the student about their idea. Our findings are indicating, it is possible to use AI-based systems to teach how to investigate integrated fields like environmental education. Future studies will include multi-label classification, explainable AI (XAI) methodologies and dataset sizes will also increase.
subject: Articles
  topic: section
subject: Climate change
  topic: keywords
subject: Deep Learning
  topic: keywords
subject: Formative assessment
  topic: keywords
subject: Image Classification
  topic: keywords
creator: Orkun Kocak
creator: Sahin Idil
rights: Copyright (c) 2025 Journal of Education in Science, Environment and Health https://creativecommons.org/licenses/by/4.0
date: 2025-06-30
publication date: 2025-06-30
starting page: 170
ending page: 178
doi: 10.55549/jeseh.825

Introducing Polar Animals with an AI-Based Educational Game: A Study for Middle School Students
type: item
description: The poles are recognized as the northernmost and southernmost points on Earth. These extremes are defined differently in terms of cartography, magnetism, geography, and the polar star. In Turkey, numerous activities have been carried out concerning the polar regions, such as the establishment of a scientific research camp and meteorological station in Antarctica, seabed mapping, and similar initiatives. These activities have continued to expand rapidly. In this context, it is anticipated that the targeted educational content will be more easily accessed through studies conducted not only by public and private research and development institutions but also within the field of education. This study aims to increase middle school students' awareness of 20 animal species living in the polar regions, as part of the “World of Living Things” unit and the “Let’s Get to Know Living Things” section of the Science curriculum. The research was designed using a qualitative approach, specifically the phenomenological design, which aims to understand the essence of participants lived experiences with a particular phenomenon. The participants consisted of 105 volunteer 5th-grade students from a public middle school in Ankara. Data were collected through open-ended, self-assessment forms and analyzed using qualitative methods. As part of the study, 20 animals living in the polar regions were identified, and an Artificial Intelligence-Based Educational Game (AIEG) was developed. The game was created using the image recognition feature on the Teachable Machine (URL1) platform and deployed as an online, web-based educational tool. After engaging with the game, students completed a self-assessment form. Additionally, qualitative data were obtained through question–answer interviews with students, and the findings were evaluated using content analysis. The results revealed that students initially had limited knowledge of animals living in the polar regions, but their awareness significan…
subject: Articles
  topic: section
subject: Artificial intelligence
  topic: keywords
subject: Arctic animals
  topic: keywords
subject: Educational game
  topic: keywords
subject: Image recognition
  topic: keywords
creator: Resul Butuner
creator: Yusuf Uzun
rights: Copyright (c) 2025 Journal of Education in Science, Environment and Health https://creativecommons.org/licenses/by/4.0
date: 2025-06-30
publication date: 2025-06-30
starting page: 179
ending page: 195
doi: 10.55549/jeseh.823

Digitizing Early Childhood Environmental Education: A Bibliometric Study
type: item
description: The integration of digital tools in education has gained attention for enhancing engagement and interactivity, particularly in fostering environmental awareness in early childhood. Early exposure to ecological concepts can nurture environmentally conscious individuals equipped to address climate challenges. This study analyzes research trends on digitizing environmental education in early childhood from 1968 to 2023. Using the Dimensions database, 443 relevant publications were identified from 9214 documents, and a bibliometric analysis was conducted via VOSviewer 1.6.20. Findings indicate that research in this field remains nascent. Although digital technology was first mentioned in 1968, significant scholarly interest only surged in 2023, with a record 1,503 publications. Vietnam, Thailand, and South Africa lead in publications, while top institutions include the University of Johannesburg, Mahidol University, and Ho Chi Minh University of Social Sciences and Humanities. The study also identifies key journals, prolific researchers, and highly cited works. Keyword co-occurrence analysis provides deeper research insights. These findings emphasize the rising role of digital tools in early childhood environmental education. Integrating technology enhances ecological understanding and fosters environmental responsibility. Additionally, this study offers a comprehensive literature overview, guiding future research on digitizing environmental education.
subject: Articles
  topic: section
subject: Digitizing environmental education
  topic: keywords
subject: Early childhood curriculum
  topic: keywords
subject: Bibliometric analysis
  topic: keywords
subject: Research trends
  topic: keywords
subject: VOSviewer
  topic: keywords
creator: Reuben Sungwa
rights: Copyright (c) 2025 Journal of Education in Science, Environment and Health https://creativecommons.org/licenses/by/4.0
date: 2025-10-01
publication date: 2025-10-01
starting page: 266
ending page: 284
doi: 10.55549/jeseh.818

The Effectiveness of Science Course Prepared According to Systematic Planning Model with ICT Integration: A Mixed Method Research
type: item
description: This study examined the impact of the 'Systematic Planning Model', an ICT integration model, on student achievement and perceptions in a 4th-grade primary school science course. The research aimed to determine whether there were significant differences in the achievement and retention scores between an experimental group, where a curriculum based on this model was implemented, and a control group, where it was not. Additionally, students’ views on the model were explored. Using an explanatory mixed-method design, the study involved 45 students from a private school in Konya during the 2022–2023 academic year. Data were collected through an achievement test (reliability: 0.896) focused on the unit “Lighting and Sound Technologies from Past to Present” and semi-structured interviews. The findings revealed statistically significant improvements in the achievement and retention scores of the experimental group, while no significant changes were found in the control group’s scores. Qualitative results showed that students responded positively to the model, particularly appreciating the use of technology and interactive activities. They described the lessons as enjoyable and educational. Furthermore, many students suggested that similar technology-supported activities be implemented in other subjects, underlining the effectiveness of engaging, tech-integrated learning environments.
subject: Articles
  topic: section
subject: Information and communication technologies
  topic: keywords
subject: Augmented reality
  topic: keywords
subject: Integration
  topic: keywords
subject: Science
  topic: keywords
subject: Primary School
  topic: keywords
creator: Mustafa Ok
creator: Fusun Gulderen Alacapinar
rights: Copyright (c) 2025 Journal of Education in Science, Environment and Health https://creativecommons.org/licenses/by/4.0
date: 2025-06-30
publication date: 2025-06-30
starting page: 235
ending page: 250
doi: 10.55549/jeseh.816

Technological Tools Used in Misconceptions Studies in Physics Education: A Systematic Review
type: item
description: Today, knowledge and technology are produced rapidly. In this case, the aim of educators is to develop appropriate environments instead of presenting information directly to students and to develop students' ability to access and use information by blending it with other information. This situation reveals the importance of concept education in education with technological tools. In this study, it is aimed to understand what and how technological tools have been used to identify or eliminate misconceptions in physics education in the last 10 years. For this reason, 83 studies, including 22 theses and 63 articles, were analyzed in this field between 2010 and 2020. The studies were examined according to the themes of publication year, publication type, purpose, method/pattern, sample, data collection tools, technological tool method/technique used, data analysis method, and the subject studied. As a result of the examinations; it was seen that the studies in this field increased as the year 2020 approached, that they were aimed at eliminating rather than detecting, that the majority of the studies consisted of articles, that they focused on the abstract concepts of physics, which are difficult, that animations and simulations were mostly used, and that quantitative research methods were preferred.
subject: Articles
  topic: section
subject: Science Education
  topic: keywords
subject: Misconceptions
  topic: keywords
subject: Educational technology
  topic: keywords
creator: Atilla Ayaz Unsal
creator: Cemil Aydogdu
rights: Copyright (c) 2025 Journal of Education in Science, Environment and Health https://creativecommons.org/licenses/by/4.0
date: 2025-06-30
publication date: 2025-06-30
starting page: 209
ending page: 219
doi: 10.55549/jeseh.814

The Heart and Art of Robotics: From AI to Artificial Emotional Intelligence in STEM Education
type: item
description: The evolution of artificial intelligence (AI) and robotics in education has transitioned from automation toward emotionally responsive learning systems through artificial emotional intelligence (AEI). While AI-driven robotics has enhanced instructional automation, AEI introduces an affective dimension by recognizing and responding to human emotions. This study examines the role of AEI-powered robotics in fostering student engagement, cognitive development, and social-emotional learning (SEL) across early childhood, K-12, and higher education. Constructivist and experiential learning theories provide a foundation for integrating emotionally intelligent robotics into interdisciplinary and transdisciplinary STEAM education. Findings indicate that AEI enhances motivation, problem-solving, and collaboration by creating adaptive learning environments that respond to student affective states. However, challenges such as data privacy, inaccuracies in emotion recognition, and access to robotics must be addressed to ensure ethical implementation. The study advocates for further interdisciplinary research, professional growth, and infrastructure investment to optimize AEI-powered robotics in education. The study also emphasizes prioritizing emotionally intelligent interactions for AEI-driven robotics that represents a shift toward human-centered, AI applications for supporting personalized learning and holistic student development. Future directions include refining affective computing models and fostering ethical AI and AEI frameworks to ensure responsible and effective implementation in early childhood through higher educational settings.
subject: Articles
  topic: section
subject: Artificial Emotional Intelligence
  topic: keywords
subject: Robotics
  topic: keywords
subject: STEM
  topic: keywords
subject: STEAM
  topic: keywords
subject: Artificial Intelligence
  topic: keywords
creator: Christopher Dignam
creator: Candace M. Smith
creator: Amy L. Kelly
rights: Copyright (c) 2025 Journal of Education in Science, Environment and Health https://creativecommons.org/licenses/by/4.0
date: 2025-03-26
publication date: 2025-03-26
starting page: 151
ending page: 169
doi: 10.55549/jeseh.813

Exploring Elementary Preservice Teachers’ Nature Investigations
type: item
description: The shift to online instruction during the COVID-19 pandemic posed significant challenges for engaging preservice teachers in authentic, inquiry-based science learning. To address these challenges, place-based and inquiry-driven investigations emerged as promising strategies for supporting meaningful scientific engagement in remote settings.This study aims to explore elementary preservice teachers’ (PTs) inquiry-based nature investigations and their reflections on their perceptions of the experience. The participants of the study included 38 PTs in the context of a science laboratory course in an elementary education program at a public university in Turkey. Data sources included PTs’ inquiry reports and reflections and were analyzed for inquiry coherence and their perceptions of the nature experience. Findings showed varying levels of inquiry engagements, from fully coherent investigations with clear research questions and explanations to minimal engagement with purely descriptive observations lacking inquiry focus. In addition, PTs reflected on the advantages of nature investigation, including increased biodiversity knowledge, awareness, and a deeper connection to the environment, as well as the affordances of mobile applications. Based on the findings, implications for teacher education are discussed.
subject: Articles
  topic: section
subject: Science inquiry investigations
  topic: keywords
subject: Biodiversity
  topic: keywords
subject: Mobile applications
  topic: keywords
subject: Nature observation
  topic: keywords
subject: Qualitative research
  topic: keywords
creator: Arzu Tanis-Ozcelik
rights: Copyright (c) 2025 Journal of Education in Science, Environment and Health https://creativecommons.org/licenses/by/4.0
date: 2025-10-01
publication date: 2025-10-01
starting page: 251
ending page: 265
doi: 10.55549/jeseh.808

Bibliometric Analysis of Studies on Artificial Intelligence in Environmental and Health Education
type: item
description: While the use of artificial intelligence in education is a prominent area of research, it has also become a collaborative application for educational institutions. These institutions are working to develop AI-based systems to enhance existing educational frameworks. Accordingly, this study conducts a bibliometric analysis of research on artificial intelligence in environmental and health education published between 2020 and 2024 (the past five years), using the Web of Science database. VOSviewer software was employed for the analysis. A search of the Web of Science database using these criteria yielded 640 studies. An examination of the publication distribution by year reveals a notable concentration of publications in 2024. In terms of country-specific contributions, the leading contributors were China, the United States, and England. The most prolific authors in the field were identified as Ai Koyanagi, Brendon Stubbs, and Joseph Firth. In terms of document and citation numbers within journals, the "Journal of Medical Internet Research" emerged as the most prominent. The most frequently cited keywords included "Artificial Intelligence," "Health Education," followed by "Machine Learning," "COVID-19," and "ChatGPT." These findings offer valuable insights into recent advancements in artificial intelligence research within the fields of environmental and health education. This study is anticipated to help researchers identify key trends and offer guidance for future investigations in the field.
subject: Articles
  topic: section
subject: Artificial intelligence
  topic: keywords
subject: Bibliometric analysis
  topic: keywords
subject: Environmental education
  topic: keywords
subject: Health education
  topic: keywords
creator: Hayriye Nevin Genc
creator: Nuriye Kocak
rights: Copyright (c) 2025 Journal of Education in Science, Environment and Health https://creativecommons.org/licenses/by/4.0
date: 2025-03-26
publication date: 2025-03-26
starting page: 140
ending page: 150
doi: 10.55549/jeseh.806

Virtual Reality Technology in Science Education: Exploring Trends and Future Perspectives
type: item
description: The importance of virtual reality in science education is constantly increasing. For this reason, this study aims to identify current trends in science education through virtual reality (VR) themes using a bibliometric analysis of the Web of Science (WoS) database. Data analysis was conducted with VOSviewer software. Findings reveal that VR studies are primarily categorized under “Education Educational Research” and “Education Scientific Disciplines.” VR technology first appeared in science education research in 2002, with publications steadily increasing over time. The most prolific and influential researchers were Lamb, Richard, and Etopio, Elisabeth, while the United States, Australia, and Türkiye had the highest academic impact. The most frequently used keywords were “virtual reality,” “science education,” “augmented reality,” and “higher education,” while recurring abstract terms included “technology,” “knowledge,” and “research.” These results underscore the rising importance of VR technologies in science education and map the evolving research landscape, offering valuable insights for future studies and educational practices.
subject: Articles
  topic: section
subject: Virtual reality
  topic: keywords
subject: Bibliometric analysis
  topic: keywords
subject: VOSviewer
  topic: keywords
creator: Aysun Tekindur
creator: Serpil Kara
rights: Copyright (c) 2025 Journal of Education in Science, Environment and Health https://creativecommons.org/licenses/by/4.0
date: 2025-06-30
publication date: 2025-06-30
starting page: 220
ending page: 234
doi: 10.55549/jeseh.802

Artificial Intelligence in Early Childhood STEM Education: A Review of Pedagogical Paradigms, Ethical Issues, and Socio-Political Implications
type: item
description: This study examines the pedagogical, ethical, and political dimensions of artificial intelligence (AI) in early childhood STEM education from a theoretical perspective. As digital technologies become increasingly prevalent in education, AI applications offer significant opportunities in areas such as personalized learning experiences, game-based education, and data analytics. However, they also pose critical ethical concerns, including data security, algorithmic bias, and privacy, while influencing children's cognitive, linguistic, and social development. Drawing on Piaget’s theory of active discovery and learning, Vygotsky’s emphasis on social interaction and teacher guidance, and Bronfenbrenner’s ecological systems theory, this study explores how AI-supported learning environments can enrich children's natural developmental processes. A qualitative literature review and theoretical analysis reveal the necessity of achieving a balanced integration between the individualized educational opportunities offered by AI and the potential risks it entails. The findings highlight the critical importance of developing human-centered, ethically sound, and inclusive educational models for educators, policymakers, and researchers in the face of technological transformation. In this context, teacher training, parental collaboration, and interdisciplinary strategies are identified as fundamental prerequisites for the sustainable and effective integration of AI in early childhood education.
subject: Articles
  topic: section
subject: Artificial intelligence
  topic: keywords
subject: Early Childhood Education
  topic: keywords
subject: pedagogical paradigms
  topic: keywords
subject: Ethical issues
  topic: keywords
subject: Educational policies
  topic: keywords
creator: Elif Ozturk
rights: Copyright (c) 2025 Journal of Education in Science, Environment and Health https://creativecommons.org/licenses/by/4.0
date: 2025-03-26
publication date: 2025-03-26
starting page: 108
ending page: 125
doi: 10.55549/jeseh.800

Use of Artificial Neural Network in Educational Laboratory Applications: Low-Velocity Impact Test
type: item
description: In this study, which focuses on selecting the material and predicting its mechanical behaviors in materials science, an Artificial Neural Network (ANN) was used to predict and simulate the low-speed impact effects of hybrid nano-doped aramid composites. There are not enough studies about open education practices in this field. Since error values below 1% were obtained with the proposed method, it has been shown that ANN results contribute to the prediction and derivation of force-time, force-displacement, and energy-time curves. It was concluded that the proposed ANN model could be useful in finding solutions to the impact responses of nanohybrid-doped aramid composites. ANN successfully predicted the prediction process for Part I and Part II, with accuracy rates of 99.4% and 99.3% for the displacement feature, 99.2% and 99.1% for the energy feature, and 97.1% and 98.3% for the force feature, respectively. This study is an applied training step that will simulate the impact strength of composite materials reinforced with nano additives and make serious contributions to important and easy-to-access technical training with a library feature that can be used as a basis for use as training material.
subject: Articles
  topic: section
subject: Educational applications
  topic: keywords
subject: Open education
  topic: keywords
subject: Artificial neural network
  topic: keywords
subject: Aramid composite plates
  topic: keywords
subject: Low-velocity impact
  topic: keywords
creator: Yusuf Uzun
creator: Mehmet Kayrici
rights: Copyright (c) 2025 Journal of Education in Science, Environment and Health https://creativecommons.org/licenses/by/4.0
date: 2025-03-26
publication date: 2025-03-26
starting page: 82
ending page: 92
doi: 10.55549/jeseh.796

Gifted Students' Perceptions of Artificial Intelligence through Drawings: A Perspective from Science and Art Centers
type: item
description: Artificial Intelligence (AI) emerges as the development of computer systems and software that imitate human abilities and perform human-like tasks. Understanding what gifted students think about this system that includes deep cognitive abilities is considered important. Based on this premise, this study examines the perceptions of gifted students towards the concept of AI. The research was conducted using phenomenological design, a qualitative research method. The data of the research were collected from 50 gifted students enrolled at a Science and Art Center and selected through a convenience sampling method. The “Draw-Write” form was used as the data collection tool. The data obtained were analyzed using content analysis, consistent with the nature of qualitative research methods. The study shows that participants may have three types of positive, neutral and negative roles related to AI. The research findings suggest that gifted students perceive AI as both a supportive tool and a potential competitor to human capabilities. The research showed the need for ethical considerations and awareness of the societal impacts of AI. Their futuristic vision shows that they are ready to explore the potential applications of AI in various fields. By recognising and addressing these perspectives, educators and policy makers can foster an environment that balances innovation with ethical responsibility and enables AI to serve as a tool for collective progress.
subject: Articles
  topic: section
creator: Galip Bedir
creator: Ibrahim Benek
creator: Eda Yuca
creator: Ismail Donmez
rights: Copyright (c) 2025 Journal of Education in Science, Environment and Health https://creativecommons.org/licenses/by/4.0
date: 2025-03-26
publication date: 2025-03-26
starting page: 126
ending page: 139
doi: 10.55549/jeseh.785

Students’ Level of Awareness on the Environmental Implications of Generative AI
type: item
description: In recent years, the number of studies on artificial intelligence or AI has increased tremendously, and their place in daily life is beginning to be felt more and more each day. Current rise of generative AI tools has brought forth dangers regarding its potential misuse, leading to impacts on the environment. College students were surveyed using an infographic and a 5-point Likert scale to assess their awareness regarding these environmental implications. The students exhibited a lack of awareness on most of the implications, only recognizing generative AI’s impact on the environment to a certain extent. In particular, the awareness of students on the environmental implications of generative AI such as its carbon footprint resulted in an unclear consensus. Additionally, students only showed an understanding of the electricity that generative AI demands and not also the fresh water and rare metals it consumes. The data suggests that this lack of awareness may stem from insufficient knowledge regarding generative AI. To address these concerns, further promotion in raising awareness was recommended, and an infographic was proposed.
subject: Articles
  topic: section
subject: Students
  topic: keywords
subject: Generative AI
  topic: keywords
subject: Artificial intelligence
  topic: keywords
subject: Environment
  topic: keywords
subject: Awareness
  topic: keywords
creator: Charles Aaron B. Dungo
creator: Zak Laurence E. Beltran
creator: Bryan C. Declaro
creator: Jan Jacek C. Dela-Cruz
creator: Rosan U. Viray
rights: Copyright (c) 2025 Journal of Education in Science, Environment and Health https://creativecommons.org/licenses/by/4.0
date: 2025-03-26
publication date: 2025-03-26
starting page: 93
ending page: 107
doi: 10.55549/jeseh.777

An Investigation of Coding Education Practices in terms of Primary School Students' Algorithmic Thinking Skills and Students' Opinions
type: item
description: This study aims to examine the views of fourth-grade primary school students on coding education given through the Scratch program by determining the students' skills in using the program and algorithmic thinking skills. The study was conducted as a one-group study with an embedded mixed design. The study group consisted of 32 students attending the 4th grade in a primary school. The data were collected using the Algorithmic Thinking Skills Scale developed by the researcher, Semi-structured Interview Form, Student Diaries, Scratch Programming Skills Checklists and Researcher Diary. According to the quantitative results of the study, a significant difference was found between the Algorithmic Thinking Skill Scale pre-test and post-test results of the students in the experimental group. According to the results obtained from the Scratch checklists among the qualitative results of the study, it was observed that the students in the experimental group generally added the decor, characters and codes in the projects correctly. According to the student diaries among the qualitative results of the study, it was determined that students generally found the coding course and the projects done in the course enjoyable. The data obtained from the researcher's diaries also supported the student diaries. Finally, according to the student opinions among the qualitative results of the study, it was concluded that the students liked the Scratch program enjoyed making projects and did not get bored. In this context, it is recommended to provide coding education to primary school students and to teach the Scratch program to primary school students.
subject: Articles
  topic: section
subject: Coding education
  topic: keywords
subject: Scratch program
  topic: keywords
subject: Algorithmic thinking skills
  topic: keywords
subject: STEM education
  topic: keywords
creator: Anil Erkan
creator: Sumeyra Akkaya
rights: Copyright (c) 2025 Journal of Education in Science, Environment and Health https://creativecommons.org/licenses/by/4.0
date: 2025-01-01
publication date: 2025-01-01
starting page: 47
ending page: 73
doi: 10.55549/jeseh.769

Development of Science Process Skills and Learning Achievement Using Flipped Classroom Learning Management through Inquiry-Based Learning for Grade 8 Students
type: item
description: The objectives of this research are: (1) to develop a flipped classroom learning plan using inquiry-based learning on the topic of substance separation for Grade 8 students, to achieve effectiveness according to the 75/75 criteria; (2) to compare science process skills and learning achievement before and after implementing the developed learning plan. The study included 45 Grade 8 students from a high school in Khon Kaen Province, Thailand, during the second semester of the 2022 academic year. The students were chosen using cluster random sampling. The research tools included: (1) six flipped classroom learning management through inquiry-based learning on the topic of mixture separation, totaling 11 hours; (2) a multiple-choice test with 30 questions on the topic of mixture separation to measure learning achievement; and (3) a multiple-choice test with 30 questions to assess science process skills. The statistical analysis includes mean, percentage, standard deviation, and hypothesis testing with Hotelling’s T-Square. The research findings were: (1) the flipped classroom learning plan using inquiry-based learning had an effectiveness of 89.2/77.5; (2) the learning achievement and science process skills of students after implementing the developed learning plans were significantly higher than before, with statistical significance at the .05 level.
subject: Articles
  topic: section
subject: Learning achievement
  topic: keywords
subject: Science process skills
  topic: keywords
subject: Flipped classroom
  topic: keywords
subject: Inquiry-based learning
  topic: keywords
creator: Yolradee Supornpanitkul
creator: Apantee Poonputta
creator: Orrasa Prasitnok
rights: Copyright (c) 2025 Journal of Education in Science, Environment and Health https://creativecommons.org/licenses/by/4.0
date: 2025-01-01
publication date: 2025-01-01
starting page: 74
ending page: 81
doi: 10.55549/jeseh.761

The Relationship between Gifted Students’ Scientific Epistemological Beliefs and Climate Change Awareness Levels
type: item
description: One of the most talked about and discussed topics in our current time is climate change. Therefore, it is important to draw attention to this issue in educational environments. The purpose of this study is to examine the relationship between scientific epistemological beliefs and climate change awareness of gifted students and whether these variables differ according to gender. The study was conducted using a relational screening model. The Scientific Epistemological Belief Scale and the Global Warming/Climate Change Awareness Scale were used as data collection tools. The sample of the study consists of 106 gifted students at the secondary school level in a city in the western region of Turkey. The research findings showed that there was a relationship between the epistemological beliefs of gifted students and their awareness levels of the causes and effects of climate change, their awareness of personal initiatives, and their tendency to change behaviour. In addition, the awareness level of personal initiatives to prevent climate change and the scientific epistemological belief levels differed significantly in favor of gifted female students.
subject: Articles
  topic: section
subject: Climate change
  topic: keywords
subject: Epistemological belief
  topic: keywords
subject: Environmental Education
  topic: keywords
subject: Gifted students
  topic: keywords
creator: Yesim Ozdeniz
creator: Hilal Aktamis
rights: Copyright (c) 2025 Journal of Education in Science, Environment and Health https://creativecommons.org/licenses/by/4.0
date: 2025-01-01
publication date: 2025-01-01
starting page: 13
ending page: 23
doi: 10.55549/jeseh.758

Bibliometric Analysis of Studies on the Artificial Intelligence in Science Education with VOSviewer
type: item
description: Understanding the trends and developments in artificial intelligence research in science education, which has rapidly advanced in recent years, is crucial for technological innovations and applications in education. Therefore, this study examines research on artificial intelligence in science education conducted between 2019 and 2023 (the last five years) through bibliometric analysis, utilizing the Web of Science database. VOSviewer was used for the analysis. As a result of scanning the Web of Science database under these criteria, 867 studies were identified. Analyzing the distribution of these 867 publications by year reveals a concentration in 2023 and 2022. In terms of publication distribution by country, the leading contributors were the USA, China and Australia. The most prolific authors were identified as D. Gasevic, Z. Xiaoming and S. S. Oyelere. Regarding the number of documents and citations in journals, "Computers & Education" ranked first. The most cited used keywords were "Machine Learning" and "Artificial Intelligence", followed by "Learning Analytics", "Data Science" and "Higher Education". The findings illuminate recent research on artificial intelligence in science education. This study is expected to assist researchers in identifying trends within the field and to provide guidance for future studies.
subject: Articles
  topic: section
subject: Artificial intelligence
  topic: keywords
subject: Bibliometric analysis
  topic: keywords
subject: Science education
  topic: keywords
subject: VOSviewer
  topic: keywords
creator: Hayriye Nevin Genc
creator: Nuriye Kocak
rights: Copyright (c) 2024 Journal of Education in Science, Environment and Health https://creativecommons.org/licenses/by/4.0
date: 2024-10-01
publication date: 2024-10-01
starting page: 183
ending page: 195
doi: 10.55549/jeseh.756

Use of Multi-Tier Concept Diagnostic Tests in Biology Education: A Systematic Review of the Literature
type: item
description: This study aimed to comprehensively examine the articles in which multi-tier concept diagnostic tests, which are among the alternative assessment methods frequently used in recent years to identify misconceptions, were used in biology education between 2000 and 2022. For this purpose, systematic review steps were followed and summarized in the PRISMA diagram. In this process, four databases (Web of Science, SCOPUS, ERIC, and TR Index) were searched, articles were downloaded, elimination/inclusion criteria were applied, and the full texts of the remaining 71 articles were examined in detail. These articles were analyzed in terms of test type, year of publication, country of application, study group and number of participants, validity and reliability analysis, number of questions in the test and question types according to the test type, and it was revealed which subjects of biology they focused on. As a result of the analysis, it was seen that two-tier tests are mostly used in biology education (62%), followed by three-tier (30%) and four-tier tests (8%). It was seen that the reviewed articles were administered in a total of 21 countries. The subjects of the articles were grouped under 11 themes and 53 codes. Although they are new to the literature and have high validity and reliability, it was seen that especially four-tier concept diagnostic tests were rarely used in biology education. In this context, it was recommended to expand the use of four- and five-tier concept diagnostic tests in biology education.
subject: Articles
  topic: section
subject: Biology education
  topic: keywords
subject: Multi-tier concept diagnostic test
  topic: keywords
subject: Systematic review
  topic: keywords
creator: Tugce Duran
creator: Musa Dikmenli
rights: Copyright (c) 2024 Journal of Education in Science, Environment and Health https://creativecommons.org/licenses/by/4.0
date: 2024-10-01
publication date: 2024-10-01
starting page: 224
ending page: 244
doi: 10.55549/jeseh.755

Decarbonizing K-12 Schools in the United States: Challenges, Opportunities and Future Directions
type: item
description: K-12 schools in the United States significantly contribute to greenhouse gas emissions due to aging infrastructure, inefficient energy practices, and a heavy reliance on fossil fuels. Addressing these issues through decarbonization is not just important—it is becoming a critical initiative aimed at reducing environmental impact while simultaneously improving the educational environments we offer our students. This paper examines the current landscape of decarbonization efforts in K-12 schools, focusing on our challenges, opportunities, and emerging best practices. By analyzing existing strategies and policies at the federal, state, and local levels, this paper highlights how these efforts are supported—or, in some cases, hindered—by the frameworks in place. The benefits of decarbonization are clear: improved indoor air quality, enhanced learning conditions, and reduced operational costs, all of which contribute to a healthier and more effective educational environment. This research also delves into successful case studies, showcasing innovative approaches and replicable models in other schools nationwide
subject: Articles
  topic: section
subject: Decarbonization
  topic: keywords
subject: Emissions Reduction
  topic: keywords
subject: K-12 Schools
  topic: keywords
creator: Ryan Kmetz
creator: Gus Norrbom
rights: Copyright (c) 2025 Journal of Education in Science, Environment and Health https://creativecommons.org/licenses/by/4.0
date: 2025-01-01
publication date: 2025-01-01
starting page: 24
ending page: 33
doi: 10.55549/jeseh.754