Research in Science Education最新文献

There has been increased attention recently on models and modelling within the global science education field. Research has begun to skew towards a competence-based perspective of models and modelling, as teachers are experiencing challenges and do not have the required competence in modelling from either theoretical or practical perspectives. This study was designed to comparatively investigate pre-service science teachers’ (PSTs) and in-service science teachers’ (ISTs) modelling competence A rating scale questionnaire was developed to assess meta-modelling knowledge. Additionally, a Black Box modelling task was designed to evaluate modelling practices and products by using two techniques: think-aloud and drawings. The resulting data was then coded and scored with validated rubrics. Quantitative analysis revealed that ISTs outperformed the PSTs in meta-modelling knowledge but they had an almost equal level in modelling practices and products, which were not at a satisfactory level. Furthermore, modelling practices and products were positively related, but no significant relationships were found between meta-modelling knowledge, modelling practices and products. Results of qualitative analyses further indicated higher-level practices were reflected in the analysis of correct model products, which was accompanied by sophisticated scientific knowledge and other advanced scientific skills. Implications of this study for science education research and teacher professional development are discussed.

One of the critical goals of teaching chemistry is to enable learners to gain conceptual understanding. Traditional instruction has often been associated with rote memorisation, resulting in learners failing to explain observed chemical phenomena, make predictions based on acquired concepts, advance convincing arguments, and engage in meaningful problem-solving and critical thinking. Therefore, the study aimed to describe the conceptual understanding of the learners taught Reaction Kinetics using computer simulations supported by the Predict-Observe-Explain strategy. The study was guided by Holme, Luxford, and Brandriet’s five categories of conceptual understanding—transfer, translation, problem-solving, prediction, and depth as the conceptual framework. This was a descriptive study in which a case study research approach was used. Five purposively sampled grade 12 learners participated in the study, representing the range of cognitive abilities from a secondary school class of 53 learners. Semi-structured interviews were used to collect data. The responses of the five participants were analysed using the qualitative content analysis. The findings were that most of the learners’ responses were in the sound understanding sub-category, some were in the partial understanding sub-category, and a few were in the no understanding sub-category, which made us conclude that computer simulations supported by the Predict-Observe-Explain strategy assisted the learners in conceptual understanding. The learners gained an understanding of most concepts, although their responses in the partial understanding sub-category showed difficulties related to depth, transfer, and translation. These findings are expected to assist chemistry teachers, teacher educators, and curriculum planners in improving learners’ conceptual understanding of chemistry.

The use of Artificial Intelligence (AI) in education is transforming various dimensions of the education system, such as instructional practices, assessment strategies, and administrative processes. It also plays an active role in the progression of science education. This systematic review attempts to render an inherent understanding of the evidence-based interaction between AI and science education. Specifically, this study offers a consolidated analysis of AI’s impact on students’ learning outcomes, contexts of its adoption, students’ and teachers’ perceptions about its use, and the challenges of its use within science education. The present study followed the PRISMA guidelines to review empirical papers published from 2014 to 2023. In total, 74 records met the eligibility for this systematic study. Previous research provides evidence of AI integration into a variety of fields in physical and natural sciences in many countries across the globe. The results revealed that AI-powered tools are integrated into science education to achieve various pedagogical benefits, including enhancing the learning environment, creating quizzes, assessing students’ work, and predicting their academic performance. The findings from this paper have implications for teachers, educational administrators, and policymakers.

The understanding of complex molecular representations is crucial for comprehending molecular scientific phenomena, but many students struggle with them. Therefore, we investigated the effectiveness of short written clues in dealing with molecular representations, specifically their impact on performance, self-efficacy, and stress reactions. A total of 136 secondary school students participated and engaged in tasks involving complex molecular representations in a prior knowledge test and a main test. Half of the students received clues, while the other half did not. The results showed that students who received clues performed significantly better on the test, highlighting their effectiveness for improving performance. However, the clues had no influence on self-efficacy, which remained moderate for both groups. Physiological stress responses (heart rate variability) indicated that students without clues experienced increased stress during the main test, whereas those with clues maintained lower stress levels like those in the prior knowledge test. Subjective stress levels decreased for both groups from the prior knowledge test to the main test, with students who received clues tending to report lower stress levels. In conclusion, short written clues were found to be effective in improving performance and reducing stress levels when dealing with complex molecular representations, although long-term interventions may be required to enhance self-efficacy.

Science museums (SMs) are important places for informal science learning, with visitors’ self-directed social interactions affecting their learning outcomes. Analyzing group conversations with varying compositions in SMs can reveal visitor interactions characteristics, knowledge construction process, and emotional experiences during their visits. This is significant for exploring how group interactions affect their learning outcomes; however, most research focuses on family interactions, with less attention given to college student groups. This study recorded and analyzed the conversations of 24 groups of college student peers in SMs to capture their social interaction characteristics and explore the relationship between interaction types and learning outcomes. Results showed that (1) conversations between college student peers in SMs were mostly perceptual talks (i.e., talks focused on directing attention); (2) different exhibit designs excelled at stimulating various interaction types: interactive exhibits mainly stimulated affective (i.e., expressions of emotions) and strategic talks (i.e., discussions on how to interact with the exhibit), whereas audiovisual and graphic exhibits tended to stimulate more connecting talks (i.e., discussions that linked knowledge and experiences); (3) the improvement of learning outcomes was closely related to connecting talks, particularly to Life connection and Knowledge connection; (4) interest development was strongly linked to strategic talks. These findings provide a basis for recommendations to effectively enhance informal learning outcomes and increase interest in informal science learning for college students visiting SMs.

ChatGPT becomes a prominent tool for students’ learning of science when students read its scientific texts. Students read to learn about climate change misinformation using ChatGPT, while they develop critical awareness of the content, linguistic features as well as nature of AI and science to comprehend these texts. In this exploratory study, we investigated students’ reading performance in comprehending two ChatGPT-generated socio-scientific texts, with one focusing on cognitive-epistemic aspects of climate science and another one focusing on social-institutional aspects of climate science. We theorized such reading of ChatGPT-generated outputs as encompassing the content-interpretation, genre-reasoning and epistemic-evaluation domains. Combining Rasch partial-credit model and qualitative analysis, we explored and investigated how a total of 117 junior secondary students (grades 8 to 9) read such texts. Moreover, we also examined how 55 students’ holistic reading of socio-scientific texts on climate change in a ChatGPT scenario changes after a reading-science intervention. Our findings indicate that the content-interpretation was the easiest while the epistemic-evaluation domains were the most difficult. Interestingly, after the reading-science intervention, many students developed their tentative view on nature of science when they evaluated ChatGPT’s claims; while a small increase in number of students discussed reliability and non-epistemic nature of AI when they evaluated ChatGPT’s claims in relation to climate change. The findings also drive a pedagogical model that improves students’ holistic reading of socio-scientific texts generated by ChatGPT.

Unlike in other countries, heredity and genetics appear first in Spanish science standards in secondary levels. However, some researchers have suggested the need of progressively introducing some basic genetic ideas already from primary education levels. In this context of no formal instruction in early stages, the objectives of our work were to characterize the incipient heredity model of primary school pupils and to evaluate its progression, to identify the most appropriate time to introduce these ideas. We designed a 12-item questionnaire referred to two constructs: (1) the difference between biologically inherited and environmental acquired traits and (2) the mechanism of inheritance. 535 primary school pupils (6–12 years; grades 1–6) took part in the study. In addition, 1–2 pupils per class were interviewed, totalling 30 interviewees. The results showed that pupils clearly identified physical resemblance as inheritable but had more difficulties in assessing physiological traits. Most pupils (84%) correctly identified that accidentally acquired traits were not transmitted to the descendance. However, only 32,2% of them use terms related to inheritance (77,1% of them in G4 – G6). Regarding the mechanism of inheritance, the idea that siblings express traits of both parents becomes more prevalent from grade 3, even suggesting the appearance of new traits or the mixture of previous ones. Older pupils accepted that a trait could skip a generation, although most of them were unable to explain the mechanism, that involves the idea of dominance/ recessiveness. These results allow identifying key leverage points for constructing the inheritance model at Primary levels.

This paper examines professional growth of a STEM teacher from the entrepreneurial frame. Using a personal narrative together with a STEM/science lesson package developed by the participant teacher, we unpack a teacher’s professional growth by interpreting her beliefs and actions using characteristics of entrepreneurial thinking. Our analysis and interpretations revealed that risk-taking forms of behaviour manifest as willingness to take calculated risks to make ‘cold’ calls to different organisations to request sharing or learning opportunities. The motivation to succeed stems from a belief that STEM education can improve the lives of students and that all students can learn. Passion for the discipline of STEM and personal beliefs to uplift students propel the teacher to persevere in her professional development despite busy schedules and conflicting demands of school and home. This study and its findings bring a fresh perspective to the idea of teacher agency from an entrepreneurial lens positioning teachers as self-empowered as compared to individuals who depended on the system to provide enablers for professional growth in the teaching profession. While self-empowerment to enact a curriculum is catalytic, teachers’ capacity for change is circumscribed by teachers’ capacity to act and accumulate practical knowledge. These entrepreneurial actions of successful STEM teachers could be used to facilitate teacher reflection on their professional journey. As the narrative approach sought to present an in-depth examination of the relationship between entrepreneurial thinking and teacher professional growth, the generalisability power of the assertions made is limited. The entrepreneurial thinking framework together with narratives from successful teachers enable teachers to locate where they are in their personal professional development and where they can aspire to move towards in their personal goal settings. Future research can examine teachers’ levels of entrepreneurial thinking and compare them against narratives of their professional growth to distil the behaviours that could lead to growth of entrepreneurial thinking. Curriculum leaders can also use the ideas of entrepreneurial thinking for professional growth to counsel and coach their team.

Building on previous research that demonstrates the association of youth experiences in afterschool science and higher science identities, this paper presents a network study of 421 middle school students that examines afterschool science participation, friendship ties, and science identities. Participation in afterschool science clubs is associated with higher science identity, but the mechanisms and order of causality are unclear. Youth form friendships inside and outside of school, and peers may influence participation in afterschool activities, as empirical research on friendships shows that they are associated with youth interests. These peer interactions also have the potential to shape identity development during adolescence. In this study, we explore associations among youth participation in afterschool science clubs, peer friendship groups, and science identity. We find that youth who participate in afterschool science clubs have higher science identities than those who do not participate. Additionally, having friends in afterschool science clubs is associated with higher science identity, even among students who report not participating in clubs themselves. Results suggest that afterschool science clubs support youth science identities, even beyond those who directly participate.

The prevailing portrayal of science and scientists within the public domain is a multifaceted mix of conventional stereotypes. Our study investigates these perceptions among Mexican children, analyzing 816 drawings and descriptions collected from fourth to seventh graders in rural and urban schools in Northwestern Mexico. Drawings were analyzed for the scientist’s appearance, location, and activity using mDAST/DAST, and each category was subcategorized for deeper compressive. The results confirm stereotypical depictions in all categories, however, girls draw more female scientists, mainly characterized by Caucasian features. Likewise, although stereotypical lab depictions persist, many drawings show alternative lab research and outdoor activities. Our study highlights the importance of promoting a diverse and inclusive image of scientists and their work, starting from an early age, using inclusive textbooks and effective pedagogical strategies.