The claim that science education is useful for people’s everyday engagement with science is often repeated but has little evidence. In an attempt to empirically test this shared assumption, we examined whether the level of science education people received predicted indicators of science-informed decision-making: adherence to experts’ recommendations, using science to justify science-related decisions, and relying on credible sources. Real-life COVID-19 dilemmas were used to examine this question in three studies: Study I involved a convenience sample of sports fans (n = 412); Study II involved a representative sample of the general population (n = 500), and Study III involved a sample of a religious minority group of Ultra-Orthodox Jews (n = 800) who do not receive mandatory level science education. In the three studies, science education did not predict adherence to social distancing guidelines, the use of science and health-related reasoning to justify one’s stance, or, for the most part, the ability of participants to choose credible information sources. Scientific knowledge played a role in predicting adherence to social distancing guidelines; however, this relationship disappeared when other commitments dominated. This study provides a starting point for a quantitative empirical research approach for testing the long-term transferability of science education to the personal lives of non-scientists.

An important goal of science education is to equip students with the scientific knowledge and evaluation skills necessary to identify misinformation. However, the specific role of science education and knowledge and the evaluation strategies most commonly relied on in this process remain unclear. The two studies presented here leverage educational diversity to explore these issues: Study I focused on a representative sample of the general population (n = 500), where science education is compulsory up to 10th grade. Study II focused on a representative sample from an ultra-Orthodox community (n = 800), where science education in school is not compulsory. Respondents in both studies were asked to share misinformation they heard during the COVID-19 pandemic and explain why they did not believe it. Using content analysis of participants’ open-ended answers, we found that about half of the general population and only a third of the ultra-Orthodox sample were able to identify misinformation when confronted with such. Science knowledge was correlated with accurately identifying misinformation in both studies, but science education was correlated with performance only among the general public who widely receives mandatory science education. Participants from the general public who justified their suspicion using content evaluation were more likely to identify misinformation correctly. At the same time, ultra-Orthodox were more likely to perform well when they justified their suspicion based on the evaluation of the source. These findings highlight the difficulty of recognizing misinformation in real life. Having scientific knowledge and awareness of sources doesn't guarantee protection from being misled—but it helps.

Scientists increasingly use generative artificial intelligence (GenAI) to aid in science communication tasks due to limited time and resources. GenAI can function as a writing assistant, idea generator, or collaborative tool. While it offers promising support, it is crucial to address potential pitfalls, such as misinformation due to its stochastic nature, dependency on prompt specificity, and the risk of reproducing biases and stereotypes. To mitigate these issues, scientists should be trained in competencies that foster ethical and effective interactions with GenAI, ensuring they develop what we call “Good Working Habits” for science communication with GenAI.

Participation in citizen science, a research approach in which nonscientists take part in performing research, is a growing practice in schools. A main premise in school-based citizen science is that through their participation, students and teachers make meaningful contributions to the advancement of science. However, such initiatives may encounter difficulties in drawing on students' and teachers' knowledge and incorporating their voice in research processes and outcomes, partly due to established knowledge hierarchies in both science and schools. This research theoretically examines misuses of students' and teachers' knowledge in school-based citizen science that can be defined as an epistemic injustice. This term describes wrongful evaluations and considerations of people's knowledge or perspectives. Based on existing theoretical work on epistemic injustice, we first map out epistemic justifications for public participation in science and discuss deficiencies in current forms of citizen science that lead to the perseverance of epistemic injustice. Then, we identify and characterize four forms through which epistemic injustice may be manifested in school-based citizen science. Our theoretical analysis is complemented by illustrative examples from citizen science projects enacted in schools, demonstrating cases where epistemic injustice toward students and teachers was either instigated or mitigated. We discuss implications toward educational goals and the design of school-based citizen science, suggesting that epistemic injustice can be reduced or avoided by delegating authorities to schools, maximizing teacher and student agency, and leveraging schools' community connections. Overall, this research establishes theoretical grounds for examinations of epistemic injustice in school-based citizen science.

This study explores the role of ChatGPT in science-related information retrieval, building on research conducted in 2023. Drawing on online survey data from seven countries—Australia, Denmark, Germany, Israel, South Korea, Taiwan, and the United States—and two data collection points (2023 and 2024), the study highlights ChatGPT’s growing role as an information intermediary, reflecting the rapid diffusion of generative AI (GenAI) in general. While GenAI adoption is a global phenomenon, distinct regional variations emerge in the use of ChatGPT for science-related searches. Additionally, the study finds that a specific subset of the population is more likely to use ChatGPT for science-related information retrieval. Across all countries surveyed, science-information seekers report higher levels of trust in GenAI compared to non-users. They also exhibit a stronger understanding of how (Gen)AI works and, with some notable exceptions, show greater awareness of its epistemic limitations.

Recent research has highlighted the role of science education in reducing beliefs in science-related misinformation and stressed its potential positive impact on decision-making and behavior. This study implemented the Elaboration Likelihood Model to explore how individuals' abilities and motivation interact with the type of processing of scientific information in the peripheral vs. central persuasion routes. A representative sample of adults (N = 500) completed an online questionnaire during the second wave of COVID-19 (November 2020) focused on two COVID-19-related dilemmas involving social distancing recommendations. First, we examined whether relying on misinformation was associated with participants' stances and the complexity of their arguments and found that relying on misinformation was associated with the intention to reject social distancing recommendations and with the use of simple arguments. Second, we explored how motivation, operationalized as personal relevance, and abilities, operationalized as the highest level of science education, science knowledge, and strategies to identify misinformation, were associated with viewpoints and justifications. We found that personal relevance was associated with the intention to reject the recommendations but also with more complex arguments, suggesting that people did not intend to reject scientific knowledge but rather tended to contextualize it. Abilities were not associated with stance but were positively correlated with argument complexity. Finally, we examined whether motivation and abilities are associated with relying on scientific misinformation when making science-related decisions. Respondents with higher levels of science education and motivation relied less on misinformation, even if they did not necessarily intend to follow the health recommendations. This implies that motivation directs people to greater usage of the central processing route, resulting in more deliberative use of information. Science education, it appears, impacts the information evaluation decision-making process more than its outcome.

In the recent decade, the proliferation of ICTs that require Wi-Fi routers in schools has been accompanied by public concerns about risks fueled in many cases by media reporting. The current study examines ways in which parents of school-age children perceive the issue of Wi-Fi radiation in schools by using a science literacy framework that examined engagement with Wi-Fi as a socio-scientific issue. In this messy epistemological space, where parents are faced with too much information of uneven quality, the science literacy literature expects them to reach an informed decision. This mixed-method study includes interviews (study I, n = 35) and questionnaires (study II, n = 513) with parents to explore their attitudes, decisions, and justifications regarding questions about Wi-Fi in schools. The interviews demonstrated heuristics and shortcuts used for decision-making. Considerations often did not include in-depth investigation or scientific knowledge. The questionnaire further examined the patterns identified in the interviews and how they related to socio-demographics and scientific background. Findings indicate that neither scientific reasoning nor relevant knowledge was necessarily connected with the decisions made or the justification given by the parents. This should be of interest to future educational programs focusing on promoting science literacy for informed citizenship.

Publicly accessible large language models like ChatGPT are emerging as novel information intermediaries, enabling easy access to a wide range of science-related information. This study presents survey data from seven countries (N = 4320) obtained in July and August 2023, focusing on the perception and use of GenAI for science-related information search. Despite the novelty of ChatGPT, a sizable proportion of respondents already reported using it to access science-related information. In addition, the study explores how these users perceive ChatGPT compared with traditional types of information intermediaries (e.g. Google Search), their knowledge of, and trust in GenAI, compared with nonusers as well as compared with those who use ChatGPT for other purposes. Overall, this study provides insights into the perception and use of GenAI at an early stage of adoption, advancing our understanding of how this emerging technology shapes public understanding of science issues as an information intermediary.

Numerous studies have explored internal factors such as cultural values and acquired knowledge accounting for how people engage with science. However, it remains unclear how external factors embedded in science texts relate to audience engagement. A content analysis of 298 text-based popular science news articles and their following 5852 reader comments was conducted in two Israeli audiences, science-minded and general readers, to explore how the accessibility strategies embedded in these articles relate to cognitive, affective, and behavioral engagement. Findings indicated similar patterns of relationship between accessibility strategies and engagement expressions for both audiences; however, the relationships were more pronounced for general readers compared to science-minded readers. Using jargon and a narrative writing style increased the odds of positive emotions in reader comments, whereas addressing socio-scientific issues increased the odds of cognitive expressions. These results may contribute to a fuller understanding of ways to drive meaningful public engagement.

In this response, we summarize the affirmations, extensions, and critiques of the framework for science communication training that we presented in Lewenstein and Baram-Tsabari (2022. How should we organize science communication trainings to achieve competencies? International Journal of Science Education – Part B: Communication and Public Engagement, 12(4), 289–308. https://doi.org/10.1080/21548455.2022.2136985). We ask how the comments collected in this special issue can, at a practical level, help push our field forward, increasing long-term promise for science communication. To address this question, we have posted online a version of our original framework, and we invite the community to co-create a refined version of the document.