Science Education Research Articles

Teaching and Learning to Support Climate-Neutral Transitions: Exploring Opportunities and Challenges for Interdisciplinary Design Courses

Students’ individual and collective learning processes in interdisciplinary teaching and learning activities that integrate prototype-oriented courses present an opportunity for further exploration. This is particularly relevant given the broader need for capacity-building to support climate-neutral transitions. This contribution draws on an exploratory workshop-in-workshop (WiW) approach to understand and evaluate students learning experiences in an experimental and interdisciplinary design course setting. This experience was embedded in the ENHANCE Alliance, a European network cooperation to innovate research and education in science and technology. The inductive analysis and results from the WiW approach draw upon surveys, group discussions, mapping exercises, and reflections with students. These indicate strong appreciation for problem-based and prototype-oriented teaching along with learning experiences as a part of their individually differentiated but collectively shared learning trajectories. The final insights acknowledge the method as an effective way to enhance instructor-student relationship dynamics and interdisciplinary opportunities. Future improvements to the interdisciplinary design format are discussed and highlight students desires for open and safe learning environments that are more transdisciplinary in nature.

Solar cell based power-bank prototype as a media to increase students' scientific literacy

This research aims to i) implement the solar cell based power-bank prototype for learning media; ii) describe the feasibility of the solar cell-based power-bank prototype for learning; and iii) describe students' scientific literacy. This research method uses the analysis, design, development, implementation, and evaluation (ADDIE) research and development model. The subjects of this research are class IX students and science teachers at SMPN 4 Central Bengkulu. Data collection techniques include questionnaires, tests, and interviews. The data analysis technique uses N-gain analysis, percentages, and the Aiken's V formula. The research results show that the media developed is valid with an Aiken index value of 0.98 > the minimum standard Aiken' V of 0.92 and can increase students' scientific literacy based on an N-gain of 0.92. 0.71, this can be seen in the dimensions of context and content based on N-gain of 0.73 and 0.69, while the dimensions of attitude, curiosity, respect, and willingness, reflect the respective percentages of 79.62%, 78.86%, 78.89%, 75.60%. Based on the results of the hypothesis test, the sig value is obtained. (2 tailed) 0.000 < 0.05 which means Ha is accepted and Ho is rejected, which means the solar cell-based renewable energy media used in science learning influences the increase in students' scientific literacy.

Three applications of semantic network analysis to individual student think-aloud data

Student during-learning data such as think-alouds or writing are often coded for use of strategies or moves, but less often for what knowledge the student is using. However, analyzing the content of such products could yield much valuable information. A promising technique for analyzing the content of student products is semantic network analysis, more widely used in political science, communication, information science, and some other social science disciplines. We reviewed the small literature on semantic network analysis (SemNA) of individuals with relevant outcomes to identify which network analysis metrics might be suitable. The Knowledge Integration (KI) framework from science education is discussed as focusing on amount and structure of student knowledge, and therefore especially relevant for testing with SemNA metrics. We then re-analyze three published think-aloud data sets from undergraduate students learning introductory biology with the metrics found in the literature review. Significant relations with posttest comprehension score are found for number of nodes and edges; degree and betweenness centrality; diameter, and mean distance. Inconsistent results possibly due to text-specific features were found for number of clusters, LCC, and density, and null results were found for PageRank centrality and centralization degree. Basic principles from the KI framework are supported—amount of information (nodes), connections (edges, average degree), key ideas (degree and betweenness centrality) and length of causal chains (mean distance and diameter) are related to posttest comprehension, but not density or LCC. Possible explanations for slight variations across data sets are discussed, and alternative theories and metrics are offered.

DVRT: Design and Evaluation of a Virtual Reality Drone Programming Teaching System

Virtual Reality (VR) is an immersive virtual environment generated through computer technology. VR teaching, by utilizing an immersive learning model, offers innovative learning methods for Science, Technology, Engineering and Mathematics (STEM) education as well as programming education. This study developed a Drone Virtual Reality Teaching (DVRT) system aimed at beginners in drone operation and programming, with the goal of addressing the challenges in traditional drone and programming education, such as difficulty in engaging students and lack of practicality. Through the system's curriculum, students learn basic drone operation skills and advanced programming techniques. We conducted a course experiment primarily targeting undergraduate students who are beginners in drone operation. The test results showed that most students achieved scores above 4 out of 5, indicating that DVRT can effectively promote the development of users' comprehensive STEM literacy and computational thinking, thereby demonstrating the great potential of VR technology in STEM education. Through this innovative teaching method, students not only gain knowledge but also enjoy the fun of immersive learning.

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

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

Implementing an online course in the MOOC environment with a focus on science and mathematics education

Implementing an online course in the MOOC environment with a focus on science and mathematics education

Action competence for sustainability instrument base on spirituality for prospective science teacher

Action competence for sustainability instrument base on spirituality for prospective science teacher

Comparing two online learning activities addressing interprofessional approach on health science students’ attitudes towards teamwork

BackgroundPhysical distancing restrictions during the COVID-19 pandemic led to the transition from in-person to online learning for many health sciences educators. This study was conducted to compare the effects of two online learning activities addressing interprofessional teamwork on health science students’ attitudes towards teamwork. MethodsThis study was designed as a randomized quasi-experimental study. The nursing (n = 30), physiotherapy and rehabilitation (n = 30), and nutrition-dietetics (n = 30) students were assigned to either online standardized patient simulation (n = 45) or online case analysis (n = 45) groups. Students’ attitudes towards interprofessional teamwork were collected pre- and post-test evaluation using the TeamSTEPPS Teamwork Attitudes Questionnaire (T-TAQ). ResultsNo significant differences were found between T-TAQ mean scores prior the intervention (p > .05). However, following the intervention, whilst the T-TAQ mean scores were not found to be statistically significant between the two groups (p > .05), the students’ pretest and posttest T-TAQ mean scores did show a statistically significant difference (p < .05). ConclusionWe found online learning activities to be a successful alternative to physical interprofesional education activities and a worthwhile opportunity to develop health science students to interprofesional teamwork.

Medical imaging and radiation science students' use of artificial intelligence for learning and assessment

IntroductionArtificial intelligence has permeated all aspects of our existence, and medical imaging has shown the burgeoning use of artificial intelligence in clinical environments. However, there are limited empirical studies on radiography students' use of artificial intelligence for learning and assessment. Therefore, this study aimed to gain an understanding of this phenomenon. MethodsThe study used a qualitative explorative and descriptive research design. Data was obtained through five focus group interviews with purposively sampled undergraduate medical imaging and radiation science students at a single higher education institution in South Africa. Verbatim transcripts of the audio-recorded interviews were analysed thematically. ResultsThree themes and related subthemes were developed: 1) understanding artificial intelligence, 2) experiences with the use of artificial intelligence with the subthemes of the use of artificial intelligence in theoretical and clinical learning and challenges of using artificial intelligence, and 3) incorporation of artificial intelligence in undergraduate medical imaging and radiation sciences education with the subthemes of student education, ethical considerations and responsible use and curriculum integration of artificial intelligence in relation to learning and assessment. ConclusionParticipants used artificial intelligence for learning and assessment by generating ideas to enhance academic writing, as a learning tool, finding literature, language translation and for enhanced efficiency. Simulation-based artificial intelligence supports students' clinical learning, and artificial intelligence within the clinical departments assists with improved patient outcomes. However, participants expressed concerns about the reliability and ethical implications of artificial intelligence-generated information. To address these concerns, participants suggested integrating artificial intelligence into medical imaging and radiation sciences education, where educators need to educate students on the responsible use of artificial intelligence in learning and consider artificial intelligence in assessments. Implications for practiceThe study findings contribute to understanding medical imaging and radiation sciences students’ use of artificial intelligence and may be used to develop evidence-based strategies for integrating artificial intelligence into the curriculum to enhance medical imaging and radiation sciences education and support students.

Triple-loop learning as a framework for advancing health systems science in medical education: a transformational change approach

Purpose The American Medical Association has recently adopted health systems science (HSS) as the third pillar of medical education to provide comprehensive and holistic patient care. The purpose of this paper is to propose a novel organizational learning perspective in considering how medical schools can facilitate a transformational HSS curriculum change. Design/methodology/approach This is a conceptual paper seeking to present triple-loop learning as a potential approach to HSS curriculum change. Findings Due to its potential for structural accountability and sustainability stemming from the inclusion of diverse voices, the authors argue that HSS curriculum change, guided by the principles of triple-loop learning, is likely to lead to the development of medical curricula that are more adaptive and responsive to the constantly changing health-care landscape. The authors advocate for the deliberate inclusion of stakeholders who have historically been excluded or marginalized in the HSS curriculum change process, such as patients and those in sentinel roles (e.g. nurses, social workers). The authors also suggest an integrated, multilevel transformation that involves collaboration among medical schools, accreditation organizations, licensing boards and health-care systems. Originality/value To the best of the authors’ knowledge, this paper represents the first attempt to apply the theory of triple-loop learning in the context of HSS curriculum change. It highlights how this critical systemic learning approach uniquely contributes to HSS curriculum change, and subsequently to the necessary, larger cultural changes demanded in medical education as a whole.

How did educational institutions respond to students with special needs during COVID-19: considerations for policy?

This bibliometric study analyzes the scientific production on the educational response of institutions to families with children with special educational needs (SEN) during the COVID-19 pandemic. The research identifies emerging trends and distinctive characteristics, providing a foundation for improving strategies in schools. The analysis reveals an increase in publications from 2020 to 2023, peaking at 24 articles in 2022. A total of 246 researchers participated, with Castro-Kemp S and McIntyre LL standing out for their productivity and citations. Institutions such as UCL and the University of Oregon led in publications, while the University of California, Santa Barbara, topped the citations. In terms of scientific production, the United States had the most articles, followed by the United Kingdom and Spain. However, the United Kingdom led in global citations, indicating a high level of interest in the topic. The main journals in this field include Frontiers in Education and Education Science. Twelve collaboration networks among authors were identified, with a primary network of seven closely collaborating researchers. The pandemic exacerbated pre-existing difficulties in the education of children with SEN, increasing stress and emotional burden on parents. The transition to home education and the lack of adapted resources presented significant challenges. However, some strategies, such as dialogic literary gatherings and collaboration between schools and families, proved effective in mitigating negative impacts. The study underscores the need for inclusive public policies that address disparities in educational support and prioritize the psychological well-being of children with SEN. It recommends a proactive and equitable approach in school psychology training and educational practice. In conclusion, this analysis provides a solid foundation for future research and improvements in schools, promoting an inclusive and resilient educational environment.

Potential of quantum scientific machine learning applied to weather modeling

Potential of quantum scientific machine learning applied to weather modeling

Are They Ready to Teach? Generative AI as a Means to Uncover Pre-Service Science Teachers’ PCK and Enhance Their Preparation Program

AbstractIntegrating generative artificial intelligence (GenAI) in pre-service teachers’ education programs offers a transformative opportunity to enhance the pedagogical development of future science educators. This conceptual paper suggests applying the GenAI tool to evaluate pedagogical content knowledge (PCK) among pre-service science teachers. By holding interactive dialogues with GenAI, pre-service teachers engage in lesson planning in a way that reveals their understanding of content, pedagogy, and PCK while facilitating the practical application of theoretical knowledge. Interpretation of these interactions provides insights into teachers-to-be knowledge and skills, enabling personalized learning experiences and targeted program adjustments. The paper underscores the need to equip pre-service teachers with the necessary competencies to utilize GenAI effectively in their future teaching practices. It contributes to the ongoing discourse on technology’s role in teacher preparation programs, highlighting the potential of addressing existing challenges in evaluating and developing teacher knowledge via GenAI. The suggested future research directions aim to further investigate the GenAI usage implications in educational contexts.

Computational transformations of early childhood education: Pathways toward child‐centred computing in two educational change projects

AbstractProgramming is becoming a key subject in early education globally, with surging problems of how computer science can become a subject for children of all ages and backgrounds. Problems of implementing new technologies in the old curricula have long been noted, and lately, concern over computer science education goals is often too narrow and skills‐based without concerns for the critical educational potential. This study follows the change process of two case preschool departments implementing programming with a floor robot across a seven‐month design process. Mixed analytical techniques based on activity theory are used to examine the tensions, conflicts and development of pedagogical alternatives. The studies show the strenuous change processes involving local transformations toward a child‐centred, inclusive early computer science education and development of projects centring making, children's exploration, tinkering and play as key parts of the learning process. It discusses how the considerable change processes enabled pedagogical solutions coherent with important concepts in computer programming and how computing education can build on child‐centred pedagogies through local adaptations and age‐appropriate designs. Practitioner notesWhat is already known about this topic Computer science and programming are becoming part of early education worldwide. Less is known about how to implement computing with ever‐younger age groups, especially for those under three. That technological change can be a strenuous change process building on societal, historical and educational tensions, requiring individual learning and organisational change. What this paper adds Two cases of change designing computing education for 1–2‐ and 3–5‐year‐olds. Design processes raising critical questions about current standard childhood programming materials being resolved to enable a child‐centred computing education. Challenges and potentials specific to early childhood in adopting computer science education. Implications for practice and/or policy Computing education challenges pedagogical notions, such as the role of failure in education. Computing education can be developed for very young children. However, there are considerable critical challenges to resolve in developing a child‐centred approach. Childhood fundamentals such as play‐based pedagogy can work synergistically with computer science activities, providing educational potential, also relevant for computer science education at large.

Embracing AI Assistants: Unraveling Young Researchers’ Journey with ChatGPT in Science Education Thesis Writing

Embracing AI Assistants: Unraveling Young Researchers’ Journey with ChatGPT in Science Education Thesis Writing

Shaping National Character in Early Grade Elementary School Students Through Social Sciences Learning in the Medeka Curriculum Era

By looking at the Merdeka curriculum in primary schools, this research investigates the role of social studies education in fostering Indonesian character in primary school students. This curriculum aims to provide students with a strong, genuine understanding and respect for Indonesian culture while adhering to the values derived from Pancasila, which is the identity of the Indonesian nation. Social studies education becomes important in order to foster the character of students, including the cultivation of moral values in themselves both in the home, school and community environment. The data collected in this study were collected through surveys and analyzed through the literature study method. Data were obtained from various sources, including academic journals, student documents, and relevant research topics. This research found that social studies education can improve students' understanding of the daily life that must be carried out by applying the nation's values in their daily lives. It can also help them learn academically and support them in interacting and collaborating to solve everyday problems, which helps them in making the right choices for their brighter future.

How free are classroom teachers? Understanding teacher academic freedom in the United States and Canada

ABSTRACT This paper presents the results of an international survey of teachers’ perspectives on academic freedom. We surveyed 173 social studies and science teachers from the United States and Canada about the importance of academic freedom, their comfort level broaching controversial topics in four broad areas (politics, economics, health and safety, and science), and the factors that influence their decision-making around discussing controversial topics. The study found that teachers value academic freedom despite being aware of how limited their freedom is in practice. Particularly controversial topics included safe injection sites, abortion, prisons, medically assisted dying, and same-sex marriage. Analysis via Mann-Whitney U tests was conducted to analyse whether teachers’ individual differences (e.g., experience, gender, or job status) influenced their pedagogical approach. Gender and years of experience had little influence, but teachers’ cautiousness was significantly influenced by whether they have tenure and the political climate of the area where they work.

Teachers’ Variables and Academic Achievement of Community Health Students in Basic Science in Cross River State

Many factors are attributable to the academic achievements of students among which Teachers’ variable is a major attribute. The limitations of the teacher as a supporting agent in the area of Basic Science hinder academic achievement of students in learning of Basic Sciences. The quality of instructions from the teacher at all levels of education determines the acquisition of competencies necessary for self-reliance and effective service delivery. The teacher’s attitude to work, knowledge of subject matter and instructional competence have a relationship with students’ academic achievements. The poor quality of students’ academic quality among community health students’ in Basic Sciences in CrossRiver State may be as a result of these variables. This study therefore examined Teachers’ variable and academic achievement of community health students’ in Basic Sciences in Cross River State. To achieve the purpose of this study, four (4)specific objectives were raised to guide the study, which were then converted to four (4) research questions and transformed to research hypotheses. Related literatures we reviewed in line with the variables of the study. The study adopted correlationalresearch design, which is a non-experimental approach between a set of variables and naturally cannot be manipulated. The research area is Cross River State, Nigeria. The target population of study was year 1 Community Health students. Sample of study was415 students randomly selected from ten schools for the 2023/2024 academic session. The instrument employed was questionnaire designed by the researcher. Cronbach Alpha reliability method was used to determine the reliability estimate of the instrument which range from 0.73 to 0.81. Data was analysed using Multiple Linear regression.The findings of the study revealed that all teachers’variables had significant positive relationship with students’ academic performance in Basic Sciences in Cross River State. It was recommended among others that teachers should adopt positive attitudetowards their teaching profession especially in secondary schools.

Impact of tooth loss and patient characteristics on coronary artery calcium score classification and prediction.

This study, for the first time, explores the integration of data science and machine learning for the classification and prediction of coronary artery calcium (CAC) scores. It focuses on tooth loss and patient characteristics as key input features to enhance the accuracy of classifying CAC scores into tertiles and predicting their values. Advanced analytical techniques were employed to assess the effectiveness of tooth loss and patient characteristics in the classification and prediction of CAC scores. The study utilized data science and machine learning methodologies to analyze the relationships between these input features and CAC scores. The research evaluated the individual and combined contributions of patient characteristics and tooth loss on the accuracy of identifying individuals at higher risk of cardiovascular issues related to CAC. The findings indicated that patient characteristics were particularly effective for tertile classification of CAC scores, achieving a classification accuracy of 75%. Tooth loss alone provided more accurate predicted CAC scores with the smallest average mean squared error of regression and with a classification accuracy of 71%. The combination of patient characteristics and tooth loss demonstrated improved accuracy in identifying individuals at higher risk with the best sensitivity rate of 92% over patient characteristics (85%) and tooth loss (88%). The results highlight the significance of both oral health indicators and patient characteristics in predictive modeling and classification tasks for CAC scores. By integrating data science and machine learning techniques, the research provides a foundation for further exploration of the connections between oral health, patient characteristics, and cardiovascular outcomes, emphasizing their importance in advancing the accuracy of CAC score classification and prediction.

Improving the Learning Outcomes of Class VIII Students Through the Implementation of the Project-Based Learning (PjBL) Model in Science Learning

This research aims to improve the learning outcomes of junior high school students in science learning.This research is a type of classroom action research carried out in one of the public junior high schools in the Madiun district. The study population was class VIII with class VIII E samples. The data analysis technique used was to compare learning outcomes in the pre-cycle to the next cycle. The results of the analysis showed that the project-based learning (PjBL) learning model was able to improve the cognitive learning outcomes of junior high school students. The success indicator of the study was seen in the improvement in cognitive learning outcomes of students who achieved a minimum completeness criteria (MCC) score of 75. While the tang performance indicator used in this study is the success rate of cognitive learning outcomes up to 75%, in the pre-cycle, as many as 71.43% of the total students have not reached the specified minimum completeness criteria (MCC). While the remaining 38.10% have reached minimum completeness criteria (MCC). The implementation of the project-based learning (PjBL) learning model shows an increase in student success in learning. In cycle I, the percentage of student success reached 61.9%. In the second cycle, the percentage of student success reached 76.1%, so there was an increase of 33.4%.