Research in Science Education最新文献

Generative Artificial Intelligence (GenAI) holds promise as a tool to assist teachers in addressing specific instructional design and implementation tasks. This study explores how teachers in a master’s-level elementary science methods course used Large Language Model AI, as one type of GenAI, to design lessons fostering students’ environmental science agency (ESA). The course introduced ESA as one of pedagogical constructs that emphasize the importance of science learning relevant and consequential to students’ lives, and encouraged teachers to use GenAI for their ESA-focused lesson design projects. Data sources included surveys, lesson design documents, GenAI chat logs, and field notes. Findings, derived through constant comparative analysis, highlight GenAI’s utility in three areas: (1) deepening teachers’ conceptual understanding; (2) developing detailed content of lesson components; and (3) integrating ESA into science instruction. Teachers also reported the challenges they encountered and addressed mainly in two ways: (1) ensuring the quality of GenAI-generated responses and (2) aligning these responses with their specific lesson visions. These findings were discussed in terms of teacher perspectives on ESA integration and their effort to take authorship and responsibility in their project process and outcomes. The study concludes by calling for follow-up teacher education practice and research focused on creating science learning opportunities, including those with proper and ethical use of GenAI, that go beyond knowledge enhancement to fostering civic participation aimed at justice-oriented and transformative changes, as envisioned by the concept and practices of ESA.

The prominence of multimodal generative artificial intelligence (GenAI) facilitates students’ comprehension of scientific knowledge through linguistic and visual modes. However, there is a lack of research that investigates how students read image-text outputs created in GenAI. We conceptualize a model of image-text reading of GenAI scientific texts that comprises the interpretation, exchange, and evaluation domains. Based on this theoretical model, we explored how 68 junior secondary students read two image-text socio-scientific texts created by GPT-4 with DALL.E plugins, one focusing on cognitive-epistemic aspects and another focusing on social-institutional aspects of climate change. Our findings indicated that these domains did not exhibit a hierarchical structure, while students’ performance in the evaluation domain in the cognitive-epistemic text was better than that in the social-institutional text. More importantly, students expressed a range of uninformed ideas regarding the nature of GenAI when they read the two texts, including equating GenAI to an Internet search engine, picture creators, and human. We discussed how teaching and learning can foster students’ image-text and epistemic reading by targeting the three domains of our theoretical model.

Students’ professional aspirations constitute an established area of research within the field of science education. To explore how students’ taste for science bridges the gap between their social background and professional aspirations, we developed the Taste for Science Test (TaSTe), which draws on Pierre Bourdieu’s theory of practice. We applied this test to a large sample of Brazilian students (n = 1582) for validation. Structural equation modelling (SEM) and analysis of variance (ANOVA) were the main data analytical tools utilized. The results indicated that the TaSTe is a reliable measure of students’ taste for science and mediates the relationship between social background and professional aspirations. Although the effects of family income and parental education on students’ taste for science are modest, their effects on students’ professional aspirations are notable. While parental education and family income modestly increase the taste for science, even most affluent middle-class families do not consistently demonstrate a positive relationship with science. These results highlight the importance of cultivating students’ taste for science to address denialism and the lack of STEM professionals in developing economies.

This study explores the knowledge-building of chemistry through images in secondary school chemistry textbooks, focusing on their changing abstraction and complexity across learning stages. Drawing on Semantics in Legitimation Code Theory, this study analyzes how these images develop across learning stages to cumulatively build chemistry knowledge in terms of their changing semantic gravity and semantic density and shifts of semantic codes in semantic planes. The findings reveal two typical patterns for the development of semantic gravity and semantic density of these images: (1) throughout the knowledge-building process, semantic gravity continuously weakens, while semantic density keeps strengthening; (2) semantic gravity weakens initially and then stabilizes at a certain level, while semantic density keeps strengthening throughout. These patterns correspond with two semantic pathways in semantic planes, respectively: 1) from a prosaic code through a worldly code to a rhizomatic code; (2) from a prosaic code to a rhizomatic code and then to a more right-positioned rhizomatic code. The first semantic pathway allows the images to present a concrete and everyday phenomenon, then provide an abstract and technical explanation for this phenomenon at the microscopic level, and finally develop a more abstract and complex theoretical explanation at the symbolic level. The second semantic pathway enables images to transition directly from a concrete and everyday phenomenon to an abstract and technical explanation of this phenomenon at the symbolic level and further to a more complex theoretical explanation at the symbolic level.

This study explores the influence of external resources on students’ construction of mental representations of curved spacetime and their understanding of General Relativity (GR). Using the Cognitive Mediation Networks Theory (CMNT) as the theoretical framework, a short extracurricular course with Year-12 students was developed. Through the course, we investigated how interactions with various external resources support the development of mental representations that facilitate reasoning about relativistic phenomena. Using a case study with qualitative analysis, data from pre/post-tests, interviews, gesture analysis, and student artifacts revealed distinct patterns between students with satisfactory and limited understanding of curved spacetime; students expressed their understanding using multiple representations that reflected their mental representations. Students with accurate conceptions exhibited similar imagistic mental representations associated with the rubber-sheet analogy within psychophysical and hypercultural tools, applying them to explain various situations. Conversely, students with limited curved spacetime conceptions attributed spatial phenomena to forces and associated time dilation with being in ‘outer space’. The findings underscore the importance of carefully selecting external resources, considering students’ prior knowledge, and addressing misconceptions in GR instruction.

Given the uncertain and complex challenges faced by the younger generation, it is essential to equip them with the competencies necessary to respond to these risks effectively. This study aimed to identify the Risk Response Competencies (RR-Competencies) that should be incorporated into science education for K-12 students. Using a three-round Delphi method, we gathered insights from 27 Korean experts across five professional domains: Science Education Research, School Science Teaching, Science and Engineering, Science/Risk Communication, and Science Education Policies. The research led to the development of a comprehensive framework comprising nine RR-Competencies, categorised into three primary contexts: (1) awareness of risk through scientific knowledge and thinking, (2) assessment of risk through scientific inquiry based on data, and (3) action on risk management through scientific problem solving and decision-making with collaborative, participatory, and resilient approaches. Clarifying these competencies can contribute to providing clear pedagogical goals for risk response in science education. This framework enhances our understanding of risk in science education and provides practical guidance for educators to develop tailored teaching strategies to cultivate these competencies among students.

This study analyzes the effectiveness of implementing flipped classroom instruction in elementary school education, with a specific focus on biology lessons and reducing student misconceptions. A pedagogical experiment was conducted in elementary schools where students in the experimental group (E) participated in lessons using the flipped classroom model, while the control group (C) followed traditional teaching methods. The experimental model included individual student preparation through video lessons and online quizzes prior to class, allowing classroom time to be dedicated to interactive and cooperative activities aimed at forming a deeper understanding and applying the material. The research results revealed a statistically better performance by students in the experimental group on the final test and the retest, compared to the control group. Furthermore, the experimental group recorded a significantly lower frequency of misconceptions during the final testing, confirming the advantages of this approach in addressing incorrect conceptual understandings. The results suggest that this model can significantly improve the efficiency of learning in elementary schools. Future research should explore the long-term effects of this approach at various educational levels and in different subject areas, as well as the potential for developing hybrid models that combine elements of the traditional and flipped classrooms. This study contributes to expanding knowledge about innovative pedagogical methods and their application in modern education.