The Role of Research Process Presentations in Science Education: Perceptions of Credibility and Tentativeness in Research Findings

The Role of Research Process Presentations in Science Education: Perceptions of Credibility and Tentativeness in Research Findings | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article The Role of Research Process Presentations in Science Education: Perceptions of Credibility and Tentativeness in Research Findings Julia Cathérine Thomas, Katharina Düsing, Vanessa van den Bogaert, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5872938/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract Laypeople often struggle to understand the provisional nature of scientific knowledge. While scientific knowledge may be widely accepted within the scientific community, it is continually subject to revision and further development as new studies are published. These characteristics of science, where findings build upon each other over time rather than being entirely replaced by new discoveries, are not always well understood by the public. This becomes particularly problematic when research process presentations that emphasize the evolving, provisional nature of scientific knowledge are perceived as less credible, reinforcing misconceptions about the integrity and nature of science. In two experimental online studies on science education ( n 1 = 99; n 2 = 184), we examined how different representations of the scientific process affect perceptions of credibility and tentativeness using text- and video-based presentations in the context of bat ecology as an example. In both studies, we varied the presentation of scientific practices (without explanations vs. with explanations) and the portrayal of the scientist’s deliberations (canonized vs. authentic). Our findings indicate that, although scientific knowledge is perceived as provisional, the way it is communicated can influence its perceived credibility. In both studies, perceived tentativeness was negatively correlated with perceived credibility, highlighting a challenge in science communication: the need to convey the evolving nature of scientific knowledge without undermining trust in its reliability. Social science/Education Social science/Psychology Science communication research process scientific inquiry tentativeness credibility scientific uncertainty research findings Introduction In today’s technology-driven society, public trust in science and the credibility of scientific findings are fundamental for addressing global challenges. Effective science communication should not only convey results but also promote an understanding of how these findings are generated and validated. A key component of this process is the provisional nature of scientific knowledge, which is often misinterpreted as a lack of credibility rather than a strength of the scientific process. Clarifying the evolving, evidence-based nature of science can enhance trust and confidence in research outcomes. Central to this issue are two related but distinct concepts: tentativeness and uncertainty. Scientific tentativeness refers to the provisional status of scientific conclusions, acknowledging that they are based on the best available evidence but remain open to revision as new data emerge (Bromme & Goldman, 2014 ; Duschl, 1988 ; Richter et al., 2019 ). This aspect is inherent to the scientific process and reflects its self-correcting nature. In contrast, uncertainty refers to the degree of precision or confidence in scientific measurements, models, or predictions. While scientific uncertainty can often be quantified and reduced through mathematical approaches (Van der Bles et al., 2019 ), tentativeness persists as an epistemic feature of scientific reasoning (Flemming et al., 2020 ; Sinatra & Chinn, 2012). Despite their distinct meanings, these concepts are frequently conflated in science communication, leading to misunderstandings about the credibility, integrity, and reliability of research findings (Fischhoff & Davis, 2014 ). From a communication standpoint, scientists face a significant dilemma: emphasizing uncertainty or the tentative nature of their findings may be perceived as diminishing their credibility. Conversely, neglecting these aspects risks oversimplifying the scientific process and eroding public trust when findings inevitably evolve (Flemming et al., 2017 ; Van der Bles et al., 2019 ). This tension highlights the urgent need for science communication strategies that effectively convey the provisional nature of scientific knowledge while preserving trust and confidence in scientific outcomes. Scientific uncertainty is an inherent feature of research and knowledge generation (Van der Bles et al., 2019 ; Gustafson & Rice, 2019 , 2020 ). However, it is frequently overlooked or inadequately communicated to the public (Maier et al., 2016 ). Effective communication of this uncertainty plays a pivotal role in fostering understanding and trust, making it a critical aspect of science communication (Gustafson & Rice, 2019 ; Simis, 2013 ). Nevertheless, the perception that uncertainty undermines credibility presents a significant challenge. Many researchers prefer to present their findings as definitive, fearing that emphasizing their provisional nature might be misconstrued as a sign of weakness or unreliability (Flemming et al., 2017 ; Van der Bles et al., 2019 ). This reluctance exacerbates a broader misunderstanding of the iterative and self-correcting nature of scientific knowledge development. A deeper public understanding of how scientific knowledge is generated is essential for accurately evaluating research results. While scientific results are often presented as definitive and conclusive, within the academic community they are typically regarded as provisional and subject to revision (Bromme & Goldman, 2014 ; Duschl, 1988 ; Flemming et al., 2017 ; Kimmerle et al., 2015 ). Tentativeness refers to the acknowledgement that scientific conclusions are based on current evidence and may change as new data emerge. Unfortunately, this aspect is rarely communicated effectively to non-specialist audiences, resulting in widespread misconceptions about the value, significance, and reliability of scientific evidence (Flemming et al., 2017 ). Even when scientists accurately communicate the provisional nature of their findings, it is often misunderstood by lay audiences (Fischhoff & Davis, 2014 ). Individual perceptions and interpretive frameworks play a critical role in how such information is received and understood (Fischhoff & Davis, 2014 ). It is therefore imperative for the public to grasp the importance of uncertainty as a fundamental aspect of the scientific process (Van der Bles et al., 2019 ). Recognizing that scientific findings are inherently subject to change and gradual refinement is fundamental to understanding the nature of the scientific process. Despite this provisional nature, scientists are required to make well-justified decisions within these parameters, ensuring that their research methods and conclusions are both robust and credible. This balance underscores the responsibility of scientists to uphold consistency and rigor, particularly when addressing complex problems and engaging in deliberative processes (Maier et al., 2016 ). A theoretical lens through which to examine this challenge is offered by process models of trust formation, such as those proposed by Mayer et al. ( 1995 ). These models highlight the dynamic interplay of competence, integrity, and benevolence as critical components in building trust (Hendriks et al., 2017 ). Within the realm of science communication, trust is shaped not only by the content's accuracy and methodological rigor but also by how information or uncertainty is framed and delivered (Simis, 2013 ). Presenting scientific findings as tentative, while transparently acknowledging uncertainties, can bolster perceptions of integrity and openness, thereby fostering trust even amidst evolving evidence. To address these concerns, the present study explores how different communication styles influence public perceptions of scientific reasoning, tentativeness, and uncertainty. Drawing on a framework that differentiates between the presentation of thinking processes of scientists as authentic in the sense of science-in-the-making (de Boer et al., 2021 ) - emphasizing the iterative and uncertain nature of science - and the presentation of thinking processes of scientists as canonized, which highlights fixed and authoritative conclusions, we investigate how these approaches affect laypeople’s understanding and trust. By analyzing declarative, procedural, and epistemic dimensions of scientific knowledge, this research seeks to illuminate how the portrayal of scientists' deliberations as authentic or canonized can either strengthen or diminish public trust and confidence in science. Scientific inquiry and communication: Bridging uncertainty and understanding To grasp the inherent uncertainty and tentativeness of scientific findings, it is crucial to first understand the scientific process itself. Rather than being a static or linear endeavor, this process is characterized by a dynamic interplay of hypothesis generation, experimentation, and the iterative refinement of theories considering new evidence. The scientific method–anchored in principles of inductive and deductive reasoning as well as the systematic falsification of hypotheses–provides a structured framework for navigating and productively engaging with uncertainty (Kind & Osborne, 2017 ). Stakeholders who rely on scientific insights, including policymakers, educators, and the public, often face challenges in interpreting scientific evidence without a foundational understanding of these processes. Decision-makers, for instance, must assess whether research adheres to rigorous methodological standards and whether its conclusions are substantiated by reliable evidence. Similarly, innovators and practitioners seeking to translate research into practical applications require a nuanced comprehension of the processes that underpin discovery and progress (Fischhoff & Davis, 2014 ). By addressing these uncertainties explicitly, science communication and science education can foster broader engagement with scientific topics, enabling diverse audiences to appreciate the iterative nature of scientific inquiry. Such an approach promotes critical thinking and informed decision-making, empowering stakeholders to evaluate scientific evidence more effectively and to participate in discussions about its implications with greater confidence. Scientific literacy as a foundation Scientific inquiry operates within two interconnected problem spaces: the hypothesis space and the experimental space, as described by the Scientific Discovery as Dual-Search (SDDS) model (Dunbar & Klahr, 1988 ). This framework underscores the iterative nature of scientific reasoning, encompassing both the generation of plausible explanations and the systematic design of experiments to test them. These processes align closely with the objectives of scientific literacy, which emphasize understanding both the foundational concepts and methodologies of the natural sciences (Bybee, 2002 ). The process of scientific inquiry draws upon a variety of reasoning methods, each contributing to the acquisition of knowledge and the derivation of conclusions from empirical data. Key reasoning processes include inductive reasoning, where general principles are inferred from specific observations; deductive reasoning, which applies general principles to specific cases; and the falsification of hypotheses, a cornerstone of scientific methodology (Kind & Osborne, 2017 ). While traditional models, such as Chalmers’ ( 2007 ) portrayal of the scientific method, present a structured, step-by-step approach, such frameworks have been criticized for oversimplifying the inherently dynamic and flexible nature of scientific practice. In reality, scientific inquiry is a fluid and context-dependent process that incorporates diverse reasoning styles. These styles integrate declarative knowledge (factual content), procedural knowledge (the methodologies employed), and epistemic knowledge (the values and assumptions underpinning scientific practices). Together, these dimensions facilitate the iterative refinement and testing of scientific knowledge, ensuring its evolution in response to new evidence (Kind & Osborne, 2017 ). Understanding the mechanisms of scientific inquiry is essential not only for scientists but also for the public (Kimmerle et al., 2015 ). Enhanced scientific literacy enables individuals to critically evaluate information, discern credible sources, and make informed decisions on science-related issues. However, despite its importance, formal education often neglects the dynamic and uncertain nature of the scientific process. Science curricula frequently prioritize established findings over the processes through which those findings were discovered, missing a critical opportunity to cultivate critical thinking and scientific literacy (Lederman et al., 2002 , 2013 ; Valladares, 2021 ). By addressing the iterative and evolving nature of scientific inquiry, education can help students move beyond perceiving science as a static body of facts. Instead, students can come to appreciate the provisional and evidence-driven nature of scientific knowledge, equipping them to navigate complex, real-world issues (Feinkohl et al., 2016 ). Empowering learners with this perspective not only fosters critical engagement but also prepares them to develop evidence-based solutions in an increasingly complex and scientifically informed society. A more critical engagement can thereby enhance comprehension and trust (Peffer & Ramezani, 2019 ; Windschitl et al., 2008 ). This educational gap becomes even more problematic when scientific uncertainties are communicated to the public. Research has shown that presenting findings as tentative can sometimes reduce public trust in science, as perceived tentativeness may appear contradictory to credibility (Flemming et al., 2020 ; Hendriks et al., 2017 ; Kimmerle et al., 2015 ). However, these effects are often mediated by the public’s familiarity with the iterative and uncertain nature of scientific inquiry. A shift from factual knowledge toward epistemic understanding–how knowledge is constructed, tested, and refined–may mitigate these challenges (Kind & Osborne, 2017 ). Communicating scientific uncertainty effectively requires a transparent portrayal of the evolving nature of research and the role of evidence in shaping conclusions. By framing uncertainty as an integral and valuable aspect of scientific work, communicators can foster a deeper, more nuanced public understanding of science. This approach enhances credibility and trust while highlighting the interconnected dimensions of scientific reasoning, methodology, and epistemology. Research objectives and design The research presented here investigates how different communication styles and media formats influence people’s perceptions of scientific processes, the credibility of research, and the inherent tentativeness of research findings. The primary aim is to enhance scientific literacy by identifying effective strategies for communicating complex scientific concepts and fostering trust in scientific research. Previous research has shown that the presentation of scientific information significantly shapes people’s perception (Ophir & Jamieson, 2021 ). Studies on scientific literacy highlight the need to promote deeper, more critical engagement with scientific information to improve both understanding and trust (Peffer & Ramezani, 2019 ; Windschitl et al., 2008 ). Grounded in the framework proposed by Kind and Osborne ( 2017 ), which categorizes scientific reasoning into declarative, procedural, and epistemic dimensions, this research examines how these elements influence comprehension and trust. Specifically, it explores the impact of two key factors: the presentation of steps of scientific practices (with explanations vs. without explanations) and the portrayal of scientists’ deliberations (authentic vs. canonized). Detailed explanations provide context for scientific practices by linking the "what" of scientific activities with the "why" and "how." This approach draws on Kind and Osborne’s ( 2017 ) distinction of six styles of scientific reasoning, each encompassing declarative knowledge (factual content), procedural knowledge (methods used to generate and validate knowledge), and epistemic knowledge (the values and assumptions underlying scientific practices). By systematically incorporating these dimensions, we aim to foster a comprehensive understanding of scientific reasoning and its contextual application. Theoretical models such as Elaboration Theory (Reigeluth, 1999) suggest that such explanations deepen understanding by helping people integrate new information with prior knowledge. However, Cognitive Load Theory (Sweller, 1988 ; Sweller et al., 2011 ) highlights the challenges of overly detailed content, particularly for individuals with limited prior knowledge. Authentic portrayals of scientific decision-making processes emphasize transparency, personal engagement, and epistemic openness (Saffran et al., 2020 ; Molleda, 2010 ). In this approach, scientists explicitly articulate the factors they consider before making a decision. For example, in bat ecology, when determining sample size, researchers must weigh animal welfare, budget constraints, and methodological considerations. This type of portrayal not only presents the final decision but also highlights the uncertainties and the iterative nature of scientific inquiry. Such transparency fosters trust and strengthens the connection between scientists and their audience (Hovland et al., 1953 ; Schriebl, Müller, & Robin, 2023 ). In contrast, standardized portrayals, often found in scientific literature, offer a post-hoc reconstruction of the research process. While addressing similar topics (e.g., sample size trade-offs, dealing with unexpected results, material selection, and reflections on the nature of science), these portrayals focus on the final decision. The decision is presented first, followed by an explanation of the rationale behind it, without verbalizing the deliberative process itself. This approach presents science as a polished, well-thought-out, and often finalized process (Düsing et al., accepted). Beyond communication style, the medium through which scientific information is conveyed plays a significant role in shaping audience perceptions. Text-based formats encourage detailed analysis and critical reflection, allowing readers to process complex ideas at their own pace (Rovai & Wighting, 2005). Video-based formats, on the other hand, leverage visual and auditory modalities to enhance accessibility and emotional engagement, catering to diverse learning preferences (Zydney et al., 2012 ; Liu et al., 2022 ). Videos are particularly effective in fostering a sense of social presence, which can increase trust and credibility in scientific communication (Garrison et al., 1999 ). To explore these dynamics, the study employs a 2x2 factorial design, manipulating two independent variables: the presentation of scientific practices (with or without explanations) and the portrayal of scientists’ deliberations (authentic vs. canonized). The aim is to examine how these factors, in combination with the chosen communication medium (text-based vs. video-based), influence participants’ perceptions of scientists’ credibility, the credibility of research findings, and the perceived tentativeness of those findings. The study emphasizes the importance of transparency in the research process and the need to convey the inherent uncertainties in scientific work (Jain et al., 2014 ; Lederman & O'Malley, 1990). This approach builds on research that highlights the necessity of tailoring communication strategies to audience needs. While detailed explanations enhance understanding for audiences with sufficient prior knowledge, minimizing cognitive load through simplified explanations benefits those less familiar with scientific concepts. Similarly, authentic communication styles foster transparency and trust, while canonized styles maintain professionalism and objectivity. By systematically examining these variables, this research seeks to provide actionable insights for educators and communicators striving to improve public understanding of scientific processes and build greater trust in science. Recent research suggests that authenticity in science communication is a multifaceted construct, encompassing elements such as transparency, personal engagement, and epistemic openness (Molleda, 2010 ; Schriebl et al., 2023 ). Transparency involves openly addressing uncertainties and the evolving nature of scientific findings, while personal engagement highlights the human side of scientific work, including scientists’ motivations, values, and deliberations. Epistemic openness emphasizes the provisional nature of knowledge and the methods of scientific inquiry. Together, these facets contribute to the perception of authenticity, aligning with the concept of social presence and increasing the perceived connection between the audience and the communicator (Short et al., 1977 ). In contrast, canonized communication follows standardized scientific norms, aiming to maintain objectivity and professionalism but may be perceived as more distant or impersonal (Fischhoff & Davis, 2014 ). By investigating both variables in a controlled study, this research aims to understand their combined effect on audience perception, comprehension, and trust in science. Present research and hypotheses In two experimental studies, we utilized the same material, which differed only in format: a text-based presentation in Study 1 and a video-based presentation in Study 2. The content centered on research about the ecology of bats based on a real field study of a wildlife research institute. The overall research question for both studies was: How does the presentation of the scientific practices and the portrayal of the scientist’s deliberations influence the tentativeness and credibility of research findings? We formulated the following hypotheses: Perception of the scientist’s credibility H1: A presentation that transparently communicates scientists’ thinking processes (authentic) will be perceived as more credible than a presentation that focuses on polished, finalized results (canonized). Perception of the credibility of research findings H2: Presenting the scientific process with explanations will lead to the research findings being perceived as more credible than merely showing the process without explanations. H3: A presentation that adopts the science-in-the-making approach, transparently showcasing the evolving nature of scientific research processes and scientists’ thinking processes (authentic), will enhance the perceived credibility of the research findings compared to a presentation that follows the polished and finalized argumentation structure of scientific papers (canonized). Perceived tentativeness of research findings H4: Presenting the scientific process with explanations will result in the research findings being perceived as more tentative, highlighting the ongoing nature of scientific inquiry, than presenting the process without explanations. It was an open research question whether there would be interaction effects of the two independent variables on any of the dependent variables. Our research assumptions for the two studies were pre-registered before data collection on AsPredicted.org (Study 1: https://aspredicted.org/z9c6-svt7.pdf ; Study 2: https://aspredicted.org/t2jn-ccmd.pdf ). Ethics statement Both studies received approval from the Institutional Ethics Committee of the [anonymized for peer review] (approval number: LEK 2023/055). All participants were volunteers, and their identities were kept anonymous. Participants were thoroughly informed about privacy protection measures and their right to withdraw from the study at any time without consequences. Written informed consent was obtained from all participants prior to their participation. A debriefing session was conducted at the conclusion of the experiments. Power analysis An a priori power analysis was conducted to determine the required sample size for both studies included in this paper. The analysis was performed for a 2x2 analysis of variance (ANOVA) design using R. Assuming an interaction effect size of 0.35 points (on the averaged 7-point scales for each dependent variable) and a standard error of 1.2, the required sample size to achieve 80% power at an alpha level of .05 was calculated. The results indicated that a total sample size of n = 100 participants ( n = 25 per condition) would be necessary to detect the specified effect size with the desired power. For Study 2, however, a larger sample size was chosen to increase the likelihood of detecting effects. This decision was made to account for potential variability in responses and to ensure sufficient sensitivity to identify effects that might deviate from the assumptions of the initial power analysis. Study 1: Text-based presentation Methods Sample Participants were recruited via the [anonymized for peer review] mailing list and notices posted on university buildings in [anonymized for peer review]. To be eligible, participants had to be at least 16 years old and possess a good command of the German language. In return for their participation, they were entered into a draw to win gift vouchers worth 3 × 50 Euros and 2 × 25 Euros. The final sample consisted of n 1 = 99 participants, including 62 women, 34 men, two non-binary persons, and one individual who did not disclose their gender. The mean age of participants was M = 24.57 years ( SD = 6.80 years). The educational background of participants was diverse: 57.6% had completed a university entrance qualification, 35.4% had earned a university degree, and 7.1% had other qualifications. Most participants studied medicine, health sciences, sports science, and psychology, with a notable presence in fields such as mathematics and science, education and teaching, and other areas. Design and procedure We conducted an online experiment using a 2x2 between-groups design. Participants were randomly assigned to one of four experimental conditions, where they were exposed to a presentation of scientific practices (with explanation vs. without explanation) and to a portrayal of the scientist’s deliberations (authentic vs. canonized), reflecting different ways of communicating scientific reasoning and processes rather than different individuals. We collected data from participants in the following conditions: “authentic - without explanation” ( n = 26), “authentic - with explanation” ( n = 22), “canonized - without explanation” ( n = 24), and “canonized - with explanation” ( n = 27). After recruitment, participants were required to read one of four texts. These texts were film scripts of the videos used in Study 2. The material was developed for use in educational settings to provide students with deeper insights into both the practice of fieldwork and the principles underpinning the process of scientific inquiry. Our storytelling of the research process to foster scientific literacy was grounded in the structure model of scientific reasoning (Mayer et al., 2008 ). We subdivided the process variables into: Formulating the research question and hypothesis. Planning and conducting an investigation. Analyzing and interpreting data. To ensure data quality, we excluded all participants who did not engage with the text or video presentation or failed an attention check question after reading or watching. The attention check question asked about the bat species presented in the material, ensuring that participants had actively engaged with the provided content. To explore the material’s impact and the relationships between our dependent variables, each group completed questionnaires designed to measure the dependent variables of the perception of the scientist’s credibility, the perception of the credibility of research findings, and the perceived tentativeness of research findings. Material and measures Text-based presentation Participants read a text that represented the video scripts of the videos used in Study 2. The material was designed to explain scientific research processes based on a field study on bat ecology in Thailand (see Table 1). The texts consisted of 1900 to 2420 words, with a median reading time of around 8 minutes. Table 1 Explanation of the conditions. Presentation of scientific practices Video script excerpts Without explanation As Daniel is very familiar with the current state of knowledge , his research question is: How does the use of airspace differ between the bulldog and tomb bat? With explanation Daniel starts by looking at the current state of knowledge about the two bat species. However, current knowledge about bats is limited . This is not only true for knowledge about bats, but also for scientific knowledge in general . Overall, very little is known about these two species. Having analyzed the previous studies in detail, Daniel can continue his search for new knowledge and formulate his research question. This is: How does the use of airspace differ between the bulldog and tomb bat? The research question is the basis for further investigation and should be answered at the end. Portrayal of the scientist’s deliberations Video script excerpts Authentic - Biologist Daniel wants to find out more about the flying behavior of these wild animals. He investigates the ecology of bats. In Daniel's current study, he is also looking for answers about the ecology of bats. - “All the values are summarized in the tables, but you can't see so much in the tables. It's much easier to visualize the values as a graph.” (Authentic representation of the decision to check data visually). - “There are always unexpected values, particularly large or particularly small values, where you have to consider whether these values really come from the animals or whether there are technical problems.” (Authentic reflection on data quality). Canonized - Biologist Daniel is familiar with the flight behavior of these wild animals. He is an expert in the ecology of bats. Daniel's current study also focuses on the ecology of bats. - “The result of the statistical test shows that the flight altitudes of the two species of bats are systematically different.” Daniel has already defined the appropriate statistical test in his experimental design. (Canonized procedure for confirming hypotheses). - To relate the results to the hypothesis, Daniel revisits the prediction he made at the beginning of the study. The data match the prediction. The hypothesis can be maintained. (Canonized method of hypothesis testing). Perception of the scientist’s credibility The perception of the scientist’s credibility was assessed using 14 items from the Muenster Epistemic Trustworthiness Inventory ( METI ) questionnaire (Hendriks et al., 2017 ), utilizing a 7-point semantic differential scale. This instrument is specifically designed to evaluate the trustworthiness judgments attributed to individuals who share their knowledge publicly, making it well-suited for measuring the trust assessments that laypersons form about experts. The 14 items were structured as bipolar adjective pairs, each addressing one of three dimensions of epistemic trustworthiness: expertise, integrity, and benevolence. The adjectives were derived from theoretical considerations of trustworthiness and sourced from existing scales measuring trustworthiness and credibility. The scale ranged from 1 ( negative pole ) to 7 ( positive pole ) and included example adjective pairs such as: “Incompetent – competent” ( expertise ), “Dishonest – honest” ( integrity ), and “Immoral – moral” ( benevolence ). The full list of adjective pairs is provided in Appendix 1. The internal consistency of the overall scale was excellent, with a Cronbach’s alpha of α = .93. Perception of the credibility of research findings Participants’ perceptions of the scientific credibility of the research findings presented in the video scripts were measured using a 7-point semantic differential scale. The questionnaire was based on items from the METI questionnaire (Hendriks et al., 2017 ) and the Perceived Scientific Credibility Scale (Kimmerle et al., 2015 ). The scale ranged from 1 ( negative pole ) to 7 ( positive pole ) and included bipolar adjective pairs such as: “Not credible – credible”, “Not trustworthy – trustworthy” and “Not reliable – reliable”. The full list of adjective pairs is provided in Appendix 2. Participants were instructed to indicate their opinion for each pair of adjectives. The internal consistency of the scale was excellent, with a Cronbach’s alpha of α = .93. Perceived tentativeness of research findings To evaluate participants’ perceptions of the tentativeness of the research findings presented in the text, we employed the Perceived Tentativeness Scale (Feinkohl et al., 2016 ; Flemming et al., 2017 , 2020 ). This scale consists of six statements, which participants rated on a 7-point Likert scale ranging from 1 ( I don’t agree at all ) to 7 ( I fully agree ). Higher scores indicate greater perceived tentativeness of the research findings. Example items include: “The results of the study are not very definite”, “The study is conclusive” ( reversed item ), and “The results of the study should be viewed as tentative”. We adapted the German version of the questionnaire to align with the topic of bat ecology. After re-coding the reversed items, we calculated the mean score across all tentativeness items. The internal consistency of the scale was moderate, with a Cronbach’s alpha of α = .65, which is considered acceptable for exploratory research stages. The full list of items is provided in Appendix 3. Correlation analysis To explore the relationships between the various scales, Pearson correlation coefficients were computed. Pearson correlations were chosen because they represent a parametric test that measures the linear relationship between two continuous variables. This test assumes that the data are normally distributed and that the relationship between the variables is linear. The correlation coefficients were calculated to assess the strength and direction of associations between the scales. A significance level of p < .05 was used for all tests. Results Hypotheses testing To analyze our hypotheses, we used separate two-way ANOVAs. Perception of the scientist’s credibility Neither the portrayal of the scientist’s deliberations, F (1, 95) = 0.01, p = .938, nor the presentation of scientific practices, F (1, 95) = 1.50, p = .224, showed main effects for the perception of the scientist’s credibility. Additionally, the interaction effect between portrayal of the scientist’s deliberations and presentation of scientific practices was not significant, F (1, 95) = 0.02, p = .882. This means the data did not support H1. Perception of the credibility of research findings We did not find a main effect of portrayal, F (1, 95) = 1.31, p = .256, or presentation, F (1, 95) = 1.43, p = .236, for perception of the credibility of research findings. Similarly, the interaction between portrayal of the scientist’s deliberations and presentation of scientific practices was not significant, F (1, 95) < 0.01, p = .972. These results do not support H2 and H3. Perceived tentativeness of research findings The ANOVA revealed a significant main effect of the presentation of scientific practices on the perceived tentativeness of research findings, F (1,95) = 5.94, p = .017, 𝜂 𝘱 ² = .06. Participants in the without explanation condition rated the tentativeness of findings, on average, higher ( M = 4.00, SD = 0.80) compared to those in the with explanation condition ( M = 3.66, SD = 0.53). This result contradicted H4. We also observed a trend for the main effect of the portrayal of the scientist’s deliberations on the perceived tentativeness of research findings, F (1,95) = 3.56, p = .062, 𝜂 𝘱 ² = .04. On average, findings presented as authentic ( M = 3.95, SD = 0.80) were rated slightly higher in tentativeness compared to findings presented as canonized ( M = 3.71, SD = 0.57). The interaction effect between the portrayal of the scientist’s deliberations and the presentation of scientific practices was not significant F (1,95) = 1.73, p = .191. This suggests that the effect of the presentation of scientific practices on perceived tentativeness did not differ significantly between authentic and canonized portrayals of the scientist’s deliberations. Further analysis: Correlation analysis The results of the Pearson correlation coefficients provide valuable insights into the relationships among the various scales. Three correlations were examined to explore these associations (see Table 2). Table 2 Correlation matrix of Study 1. Tentativeness of research findings Credibility of research findings Credibility of research findings − .64*** - Scientist’s credibility − .46*** .65*** A significant negative correlation was found between the perceptions of the tentativeness of research findings and the credibility of research findings (Pearson's r = − .64, p < .001), suggesting a strong inverse relationship. Additionally, a moderate but significant negative correlation was observed between the perceived tentativeness of research findings and the perception of the scientist’s credibility (Pearson's r = − .46, p < .001). Lastly, a strong and significant positive correlation was identified between the perceptions of the credibility of research findings and the credibility of the scientist (Pearson's r = .65, p < .001). Discussion The findings from the hypothesis tests underscore the importance of how scientific practices are presented in shaping perceived tentativeness. While the portrayal of scientists' deliberations and interaction effects did not significantly influence other measured scales, the results from H4 revealed an unexpected outcome: The absence of an explanation led to higher perceived tentativeness, contrary to the original hypothesis. Correlation analyses provided further insights. A strong, negative correlation between perceived tentativeness and the credibility of research findings indicates that higher tentativeness is associated with reduced credibility. Similarly, a moderate, negative correlation between perceived tentativeness and the credibility of the scientist suggests that increased tentativeness diminishes the perceived credibility of the scientist. Finally, a strong, positive correlation between the credibility of research findings and the credibility of the scientist highlights the interdependence of these two dimensions in participants’ perceptions. The observed correlations align with broader concerns about deficits in scientific literacy, as highlighted in earlier research (Bell et al., 2003 ; Broadhurst, 1970 ; Duschl, 1988 ; Lederman & O’Malley, 1990 ; Matthews, 1994 ). Participants’ responses suggest a limited understanding of the dynamic and iterative nature of scientific inquiry, which may contribute to their reliance on perceived certainty as a marker of credibility. The findings are also consistent with previous studies, which emphasize the challenges of communicating scientific uncertainty (Flemming et al., 2017 ; Hendriks et al., 2017 ; Kimmerle et al., 2015 ). The results show that high perceived tentativeness can erode public trust in scientific claims (Flemming et al., 2020 ), further underscoring the need for effective science communication strategies. This is particularly relevant for decision-makers who rely on scientific insights to make informed choices. The observed correlations highlight the critical need for communication strategies that not only convey the iterative and uncertain nature of scientific inquiry but also maintain credibility. Although effective communication of uncertainties did not diminish the credibility of the scientist or the research findings, it appeared to shift focus toward the perceived tentativeness of research findings. This dynamic suggests that while transparency may bolster credibility, it simultaneously alters how the provisional nature of findings is perceived. These results complicate Fischhoff and Davis’s ( 2014 ) assertion that fostering a deeper understanding of scientific processes improves decision-making and promotes broader knowledge acquisition. If transparency significantly enhances perceived credibility to the point where it inversely correlates with perceived tentativeness–even when tentativeness is explicitly communicated–it raises critical questions about the practical feasibility of leveraging transparency to simultaneously strengthen trust and accurately convey the provisional nature of scientific findings. Expanding on these findings, Study 2 explored whether video-based presentations yield similar patterns. Multimedia formats, combining visual and auditory elements, may alter perceptions of tentativeness and credibility compared to text-based materials. Research indicates that video presentations can reduce perceived uncertainty (Lim et al., 2000), potentially mitigating the effects of tentativeness observed in textual formats. This comparative approach provides critical insights into the role of presentation styles in interpretations of scientific information. By examining the interplay between media formats and perceptions of scientific uncertainty, this study contributes to a deeper understanding of how to foster scientific literacy and trust in research outcomes. Study 2: Video-based presentation Methods Objective Building on the findings of Study 1, the goal of Study 2 was to assess whether using videos instead of texts would yield similar effects on participants’ perceptions. Given the increasing prevalence and effectiveness of videos in science communication and science education (Berk, 2009 ; Criswell, Krall, & Ringl, 2022 ; Forsythe et al., 2022 ; Grosser et al., 2019 ), we assumed that videos would have a more pronounced and distinct impact on participants’ perceptions compared to texts. Videos offer unique advantages, such as the ability to combine auditory and visual elements, which can make complex information more accessible and engaging. By visually illustrating each step of the research process (e.g., including research questions and hypotheses as well as scientific box plots for graphical presentation of results), the videos aimed to create a more immersive and intuitive learning experience, potentially enhancing participants’ comprehension. Moreover, the dynamic nature of videos allows for the integration of narrative techniques, animations, and visual cues that can highlight key aspects of the research, making abstract concepts easier to grasp and more relatable. These features make videos particularly well-suited to fostering a deeper understanding of scientific processes, especially for audiences with diverse learning preferences. Sample The study involved n 2 = 184 participants (131 women, 49 men, 4 non-binary), with an average age of M = 30.10 years ( SD = 14.50 years). Participants were required to be at least 16 years old and have a C1 level of German proficiency. Recruitment was conducted via the [anonymized for peer review] mailing list and on-campus notices, with incentives including gift voucher draws. The educational background of participants varied: 50.8% held a university degree, 34.4% had completed a university entrance qualification, and 14.8% had other qualifications. Their main fields of study included mathematics, natural sciences, medicine, health sciences, psychology, and education. Design and procedure Participants were excluded if they did not watch at least 10 minutes of the video or failed an attention check question. The final analysis included four conditions: “authentic - without explanation” ( n = 42), “authentic - with explanation” ( n = 47), “canonized - without explanation” ( n = 43), and “canonized - with explanation” ( n = 51). To ensure methodological consistency, the procedure mirrored Study 1, maintaining the same design and measurement tools. Reliability tests showed that the Perceived Tentativeness Scale had a low internal consistency (Cronbach’s alpha of α = .60), suggesting that the scale requires improvement or revision. In contrast, both the Perceived Scientific Credibility Scale and the METI demonstrated in each case a high reliability (Cronbach’s alpha of α = .91). Material and measures Video-based presentation Participants watched videos documenting a real scientific research process on bat ecology in Thailand, illustrating the entire process from start to finish. The videos were developed by a professional media company and its filming crew in collaboration with educational experts, resulting in four distinct versions. Each video lasted between 14 and 18 minutes. The videos aimed to effectively visualize and explain scientific research, providing a more dynamic and engaging learning experience compared to text-based materials. This format was expected to enhance participants’ understanding of the research process and reduce misconceptions about scientific tentativeness and credibility. Results Hypotheses testing To analyze our hypotheses, we conducted separate two-way ANOVAs. Perception of the scientist’s credibility The ANOVA results revealed that neither portrayal F (1, 179) = 0.01, p = .930, nor presentation F (1, 179) = 3.69, p = .056, 𝜂 𝘱 ² = 0.02, nor their interaction F (1, 179) = 0.04, p = .845, had a statistically significant effect on the perceived credibility of the scientist. Despite the non-significant result for presentation, a discernible trend emerged, suggesting that participants in the without explanation condition rated the scientist’s credibility slightly lower ( M = 5.95, SD = 0.77) compared to those in the with explanation condition ( M = 6.16, SD = 0.58). This trend was observed across both presentation conditions. However, the data did not support H1. Perception of the credibility of research findings The ANOVA revealed a significant main effect of the presentation of scientific practices on the perceived credibility of the research findings, F (1,179) = 10.14, p = .002, 𝜂 𝘱 ² = 0.05. Participants in the with explanation condition rated the credibility, on average, higher ( M = 6.31, SD = 0.73) compared to those in the without explanation condition ( M = 5.96, SD = 0.76). This finding supports H2, suggesting that providing explanations enhances the perceived credibility of the research findings. The main effect of portrayal type was not significant, F (1,179) < 0.01, p = .988. Similarly, the interaction effect between portrayal of the scientist’s deliberations and the presentation of scientific practices was not significant, F (1,179) = 0.11, p = .738. These results indicate that the portrayal of the scientist’s deliberations and its interaction with the presentation of scientific practices did not influence perceived credibility. Perceived tentativeness of research findings The ANOVA results indicated that neither the portrayal F (1, 179) = 0.06, p = .805, nor the presentation F (1, 179) = 2.62, p = .108, or their interaction F (1, 179) = 0.46, p = .498 had a significant effect on the perceived tentativeness of the research findings. Thus, H4 was not supported by the data. Further analysis: Correlation analysis The correlation analysis conducted in Study 2 yielded insightful findings regarding the relationships among the various scales. The results of the Pearson correlation coefficients revealed several key associations (see Table 3). Table 3 Correlation matrix Study 2. Tentativeness of research findings Credibility of research findings Credibility of research findings − .53*** - Scientist’s credibility − .41*** .69*** A significant negative correlation was found between the perception of the tentativeness of research findings and the credibility of those findings (Pearson’s r = − .53, p < .001). Furthermore, a negative correlation was observed between the perceived tentativeness of research findings and the perception of the scientist's credibility (Pearson’s r = − .41, p < .001). Lastly, a strong and significant positive correlation was identified between the perception of the credibility of research findings and the credibility of the scientist (Pearson’s r = .69, p < .001). Discussion The findings of the correlation analysis in Study 2 offer valuable insights into the relationships between participants’ perceptions of scientific tentativeness, the credibility of research findings, and the scientist’s credibility. The significant negative correlations between perceived tentativeness and both the credibility of research findings and the scientist’s credibility suggest that when research findings are perceived as tentative or uncertain, they are viewed as less credible. This aligns with previous studies (Flemming et al., 2017 , 2020 ; Hendriks et al., 2017 ; Kimmerle et al., 2015 ), which also found that uncertainty in research is often associated with a decrease in perceived credibility. Despite efforts to emphasize that tentativeness is inherent in the scientific process and not a sign of poor research, participants still seemed to view tentative findings as less trustworthy. This highlights a key challenge in science communication: people ’s tendency to equate uncertainty with unreliability. Furthermore, the strong positive correlation between the credibility of research findings and the credibility of the scientist supports the idea that these two dimensions of credibility are closely intertwined in the minds of participants. This finding emphasizes the importance of establishing trust not only in research results but also in the scientists behind those results. When people perceive scientists as credible, they are more likely to trust the research they produce. This connection underscores the critical role of scientist credibility in shaping public perceptions of scientific findings and the need for science communicators to foster trust in both research and the individuals conducting it. These results further contribute to the understanding of how scientific uncertainty is communicated and perceived. While it is essential for scientific knowledge to be presented transparently, the current findings suggest that the communication of uncertainty might inadvertently diminish the perceived credibility of research. This echoes previous research, which has found that the public often struggles to accept scientific uncertainty without undermining trust in the findings themselves (Fischhoff & Davis, 2014 ; Simis, 2013 ). Considering these findings, future research should explore ways to communicate uncertainty that preserve both the credibility of the findings and the trust in the scientists who conduct the research. Additionally, the negative correlation between tentativeness and both credibility scales suggests that participants may have difficulty reconciling the provisional nature of scientific knowledge with their expectations of certainty and trustworthiness. Despite efforts to clarify that scientific research is an ongoing process, the perception of uncertainty seemed to trigger doubts about the reliability of the findings. This highlights a persistent issue in science communication: how to balance the need for transparency with the need to maintain public confidence in science. The ANOVA revealed that the presentation of scientific practices significantly impacted the perceived credibility of research findings. Participants who received an explanation rated the credibility higher than those who did not receive an explanation. This suggests that while explanations of uncertainty alone may not be sufficient, explanations of scientific practices can positively influence credibility perceptions. In conclusion, the findings from this study underscore the complex relationship between the perceived tentativeness of research and its credibility. They highlight the challenge of communicating uncertainty in science in a way that does not undermine trust in the findings or the scientists behind them. These insights have important implications for science communicators, policymakers, and researchers, who must carefully navigate the delicate balance between transparency and trust in their efforts to engage the public with scientific knowledge. General discussion Understanding the intricate relationship between the presentation of scientific practices, scientific uncertainty, and public trust is crucial for advancing science communication practices and fostering scientific literacy. The findings of the research presented here underscore the pivotal role of how scientific practices are presented in shaping perceptions of tentativeness and credibility. This research highlights the importance of balancing perceptions of tentativeness and credibility, ensuring they are not perceived as inherently opposing attributes. Both studies revealed negative correlations between the perceived tentativeness of research findings and the credibility of both the scientist and their research. These results emphasize the need for communication strategies that transparently convey scientific uncertainty while maintaining trust in the credibility of the findings and the scientist. By exploring how different presentation formats influence people’s perceptions, the findings provide valuable insights for both researchers and practitioners of science communication. Key findings and interpretations Presentation formats Shorter text-based explanations were more effective in influencing perceptions of tentativeness, suggesting that brevity and clarity increase awareness of uncertainty. In contrast, video-based presentations showed no significant effects on perceived tentativeness, indicating potential differences in how people process information across modalities. These findings suggest that while text-based materials may encourage straightforward interpretation, the multimodal nature of video presentations could dilute perceived tentativeness. Future studies should explore how the richness of video presentations might be optimized to clarify uncertainty without compromising credibility. These findings highlight the role of cognitive demands in shaping audience perceptions, with text encouraging more analytical processing and video potentially fostering a broader, less detail-focused engagement. Credibility and tentativeness of research findings Both studies consistently revealed a negative correlation between perceived tentativeness and the credibility of research findings. This suggests that while acknowledging uncertainty enhances understanding of the provisional nature of science, it can inadvertently diminish trust in the findings. Balancing these perceptions is crucial, particularly in contexts where public trust in science is critical, such as public health, climate science, and emerging technologies. By integrating these findings into science communication strategies, future efforts can focus on refining presentation methods and improving experimental manipulations to achieve a more balanced and effective communication strategy. For instance, the findings highlight the need for nuanced approaches to address the trade-off between transparency and credibility. These approaches should consider tailoring messages to specific audiences while maintaining a consistent focus on the dynamic nature of scientific knowledge (Fischhoff & Davis, 2014 ; Gustafson & Rice, 2019 ; Simis, 2013 ). Educational implications: Promoting scientific literacy To address misconceptions about the tentativeness and credibility of scientific research, educational resources should prioritize fostering scientific literacy. Educational resources must emphasize that science is not a static body of knowledge but a dynamic, evolving process. It is essential to highlight the iterative nature of science. By discussing how research evolves with new data and findings, students might better understand that science is a continuous cycle of testing, refining, and revising theories. This process would help them appreciate the provisional nature of scientific knowledge. Understanding tentative findings is also crucial. It is important to teach students that tentative findings - whether from early fieldwork, climate models, or preliminary medical trials - are not failures, but rather vital steps toward more robust conclusions. Recognizing the value of uncertainty in research as a natural and necessary part of scientific progress, rather than a sign of unreliability, is essential for developing a nuanced understanding of science (Matthews, 1994 ; Pielke, 2008 ). Our studies underline the significance of transparent communication in science education, particularly regarding the provisional nature of scientific knowledge. The results suggest that the presentation of scientific practices can influence how students perceive the credibility of scientific findings. By offering detailed explanations or no explanations at all, and portraying scientists as either canonized or authentically deliberating individuals, educators can shape students' perceptions. Enhancing understanding of the scientific process is essential. Students who understand how scientific inquiry works, such as hypothesis testing and theory revision, are more likely to see science as a dynamic, evolving field rather than a fixed collection of facts. To foster a deeper appreciation of the scientific process, curricula should incorporate both procedural and epistemic knowledge. This includes teaching not only the “what” of scientific activities but also the “why” and “how.” Emphasizing that scientific knowledge is provisional, evolving with new evidence, and that uncertainty is a necessary part of this process is vital. By integrating these principles into educational resources, we can help students critically engage with scientific content, reducing misconceptions about science’s reliability and fostering scientific literacy. Explicitly addressing the relationship between tentativeness and credibility could help learners develop the critical thinking skills needed to evaluate scientific claims. For example, case studies showing how tentative findings have led to significant breakthroughs can help normalize uncertainty as part of the scientific process (Chen & Song, 2017 ; Yang & Deng, 2024 ). Strengths and weaknesses of the studies The studies presented offer significant insights into the field of science communication and science education, particularly regarding the ways in which uncertainty and credibility are perceived by scientific laypeople. One of the main strengths of these studies lies in their methodological diversity. By combining both text- and video-based presentations, the research enabled a more nuanced analysis of how different formats affect the perception of scientific uncertainty and credibility. This approach provided a rich dataset that captures the complexities of communicating science across various media, which is particularly valuable in today’s media landscape. Furthermore, the findings offer suggestions for communicating scientific uncertainty, which is crucial for fostering public trust and engagement in critical scientific issues. These insights could inform communication strategies that help bridge the gap between scientific experts and the public, particularly in contexts where uncertainty is an inherent aspect of the scientific process. However, there are also notable weaknesses in the studies that should be addressed in future research. A primary limitation is the heavy reliance on self-reported data. While self-reports can provide valuable insights into perceptions and attitudes, they are also susceptible to biases such as social desirability or recall bias, which may distort the findings. Additionally, the sample diversity was limited, with the participant groups not fully representing the broader population. This lack of diversity in the sample raises questions about the generalizability of the results, particularly when it comes to different cultural and demographic groups. Lastly, the studies primarily offer snapshot data, capturing perceptions at a single point in time, without providing insights into how these perceptions evolve over time or with repeated exposure to scientific communication. Future Directions for Research To address these limitations and build on the strengths of the existing studies, future research should focus on several key areas. First, longitudinal studies could provide valuable insights into how public perceptions of uncertainty and credibility change over time. In fields such as climate science and medicine, where new findings and updates are frequent, understanding how people’s views shift as new information is presented could help refine communication strategies. It is particularly important to consider how people’s expectations, shaped by prior communication norms, influence their perceptions of credibility. If they are accustomed to scientists being portrayed as authoritative figures presenting immutable facts, they may view scientists who communicate uncertainty as less credible. However, if uncertainty were more routinely incorporated into public understandings of science, these perceptions might shift, allowing for a more accurate view of scientific work as an ongoing, iterative process. Another area for future research is the diversification of participant samples. Including individuals from a broader range of demographic and cultural backgrounds would enhance the external validity of the findings, making them more applicable to diverse audiences. This is especially crucial in the context of global science communication, where messages need to resonate across different social, cultural, and educational contexts. Moreover, the studies could be strengthened by integrating objective measurement methods alongside self-reported data. While self-reports provide valuable insights into subjective perceptions, they do not capture the full scope of audience engagement. Future research could include behavioral measures such as audience engagement, trust in scientific sources, and changes in decision-making due to exposure to different communication formats. These objective data could provide a more comprehensive understanding of how different communication strategies influence behavior and perceptions. Finally, refining the manipulation techniques used in the studies could offer deeper insights into how specific communication elements affect perceptions. By experimenting with more distinct variations in the framing of scientific uncertainty, researchers could isolate the effects of particular aspects of communication, such as the language used to convey uncertainty or the visual presentation of scientific information and gain a clearer understanding of how these factors shape people’s understanding. Broader applications The findings from these studies offer insights into how to effectively communicate scientific uncertainty. This research lays the foundation for developing communication strategies that can be tailored to various contexts, from public health campaigns to educational outreach programs. Understanding how to communicate uncertainty clearly, accessible, and engaging is crucial for fostering a more informed and scientifically literate public. In an era where scientific knowledge is increasingly complex and rapidly evolving, the ability to effectively convey uncertainty can empower individuals to make more informed decisions, engage with science in meaningful ways, and contribute to the public discourse on pressing scientific issues such as climate change and public health (Chi et al., 2022 ; Pielke, 2008 ). Conclusion This research underscores the critical importance of balancing transparency and credibility in science communication. While acknowledging the provisional nature of scientific knowledge is essential for public understanding, it must be communicated in a way that maintains and nurtures trust. The theoretical foundation for our findings is grounded in two key aspects of scientific communication: Communicating procedural and epistemic knowledge regarding the steps of scientific inquiry; and representing the thought processes of scientists. Educational resources and communication strategies should incorporate these insights to address misconceptions, promote scientific literacy, and encourage critical thinking. By doing so, educators can empower future generations to engage with the complexities of scientific knowledge and foster a deeper understanding between scientists and the public. These efforts may contribute to enhancing the public’s ability to engage with scientific topics and make informed decisions (Fischhoff & Davis, 2014 ; Matthews, 1994 ). Abbreviations ANOVA Analysis of Variance METI Muenster Epistemic Trustworthiness Inventory SDDS Scientific Discovery as Dual-Search Declarations Competing interests The author(s) declare no competing interests. Data availability The datasets generated during and/or analysed during the current study are available in the Open Science Framework (OSF) repository, https://osf.io/cah39/?view_only=fd98e0280e864776a925619174ec7256 Ethical approval All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. The study was approved from the Institutional Ethics Committee of the [anonymized for peer review] (approval number: LEK 2023/055). Informed consent Obtained. Author contributions JCT: Methodology, Conceptualization, Data curation, Formal analysis, Investigation, Writing – original draft; KD: Methodology, Conceptualization, Writing – review & editing; VB: Methodology, Conceptualization, Writing – review & editing; HG: Methodology, Conceptualization, Writing – review & editing; TB: Methodology, Conceptualization, Writing – review & editing; AS: Conceptualization, Writing – review & editing; MB: Conceptualization, Writing – review & editing; DL: Conceptualization, Writing – review & editing; CV: Conceptualization, Writing – review & editing; JK: Conceptualization, Funding acquisition, Supervision, Writing – review & editing. Funding The research reported here was funded by a grant from the German Federal Ministry of Education and Research (Grant ID 01IO2104C). References Bell, R. L., Blair, L. M., Crawford, B. A., & Lederman, N. G. (2003). Just do it? 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Cognitive load during problem solving: Effects on learning. Cognitive Science , 12 (2), 257–285. https://doi.org/10.1016/0364-0213(88)90023-7 Sweller, J., Ayres, P., & Kalyuga, S. (2011). Cognitive Load Theory (Vol. 1). Springer New York. Valladares, L. (2021). Scientific literacy and social transformation: Critical perspectives about science participation and emancipation. Science & Education, 30 (3), 557–587. https://doi.org/10.1007/s11191-021-00205-2 Van der Bles, A. M., Van der Linden, S., Freeman, A. L. J., Mitchell, J., Galvao, A. B., Zaval, L., & Spiegelhalter, D. J. (2019). Communicating uncertainty about facts, numbers and science. Royal Society Open Science , 6 (5), 181870. https://doi.org/10.1098/rsos.181870 Windschitl, M., Thompson, J., & Braaten, M. (2008). Beyond the scientific method: Model-based inquiry as a new paradigm of preference for school science investigations. Science Education , 92 (6), 941–967. https://doi.org/10.1002/sce.20259 Yang, A. J., & Deng, S. (2024). Dynamic patterns of the disruptive and consolidating knowledge flows in Nobel-winning scientific breakthroughs. Quantitative Science Studies, 1 (1), 1–17. https://doi.org/10.1162/qss_a_00323 Zydney, J. M., deNoyelles, A., & Seo, K. K.-J. (2012). Creating a community of inquiry in online environments: An exploratory study on the effect of a protocol on interactions within asynchronous discussions. Computers & Education , 58 (1), 77–87. https://doi.org/10.1016/j.compedu.2011.07.009 Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5872938","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":409104639,"identity":"24b3f56b-8a8a-4482-b36b-6810a4e06353","order_by":0,"name":"Julia Cathérine 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Hannover","correspondingAuthor":false,"prefix":"","firstName":"Till","middleName":"","lastName":"Bruckermann","suffix":""},{"id":409104644,"identity":"7c6959c4-3944-4f11-bb20-9d4316f414c7","order_by":5,"name":"Anke Schumann","email":"","orcid":"","institution":"Leibniz Institute for Zoo and Wildlife Research","correspondingAuthor":false,"prefix":"","firstName":"Anke","middleName":"","lastName":"Schumann","suffix":""},{"id":409104645,"identity":"3d9d04a9-ff02-48f0-a6bc-d371f0887542","order_by":6,"name":"Miriam Brandt","email":"","orcid":"","institution":"Leibniz Institute for Zoo and Wildlife Research","correspondingAuthor":false,"prefix":"","firstName":"Miriam","middleName":"","lastName":"Brandt","suffix":""},{"id":409104646,"identity":"8ee26fd5-a501-4b73-9375-4f0ebfb30158","order_by":7,"name":"Daniel Lewanzik","email":"","orcid":"","institution":"Leibniz Institute for Zoo and Wildlife 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11:08:18","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5872938/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5872938/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":75326065,"identity":"1a8baae3-b0b1-44e4-81b6-311a8bd3ec63","added_by":"auto","created_at":"2025-02-03 11:20:03","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1727171,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5872938/v1/3eba1d5f-ae8e-43be-91e3-dc71def627d8.pdf"},{"id":75324637,"identity":"c4d03ae8-e6ba-41f5-93d2-d9873d56fd75","added_by":"auto","created_at":"2025-02-03 11:04:02","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":16093,"visible":true,"origin":"","legend":"","description":"","filename":"Appendix.docx","url":"https://assets-eu.researchsquare.com/files/rs-5872938/v1/77dc82eb8b597e5656a3382a.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"The Role of Research Process Presentations in Science Education: Perceptions of Credibility and Tentativeness in Research Findings","fulltext":[{"header":"Introduction","content":"\u003cp\u003eIn today\u0026rsquo;s technology-driven society, public trust in science and the credibility of scientific findings are fundamental for addressing global challenges. Effective science communication should not only convey results but also promote an understanding of how these findings are generated and validated. A key component of this process is the provisional nature of scientific knowledge, which is often misinterpreted as a lack of credibility rather than a strength of the scientific process. Clarifying the evolving, evidence-based nature of science can enhance trust and confidence in research outcomes.\u003c/p\u003e \u003cp\u003eCentral to this issue are two related but distinct concepts: tentativeness and uncertainty. Scientific tentativeness refers to the provisional status of scientific conclusions, acknowledging that they are based on the best available evidence but remain open to revision as new data emerge (Bromme \u0026amp; Goldman, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Duschl, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e1988\u003c/span\u003e; Richter et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). This aspect is inherent to the scientific process and reflects its self-correcting nature. In contrast, uncertainty refers to the degree of precision or confidence in scientific measurements, models, or predictions. While scientific uncertainty can often be quantified and reduced through mathematical approaches (Van der Bles et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), tentativeness persists as an epistemic feature of scientific reasoning (Flemming et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Sinatra \u0026amp; Chinn, 2012). Despite their distinct meanings, these concepts are frequently conflated in science communication, leading to misunderstandings about the credibility, integrity, and reliability of research findings (Fischhoff \u0026amp; Davis, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFrom a communication standpoint, scientists face a significant dilemma: emphasizing uncertainty or the tentative nature of their findings may be perceived as diminishing their credibility. Conversely, neglecting these aspects risks oversimplifying the scientific process and eroding public trust when findings inevitably evolve (Flemming et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Van der Bles et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). This tension highlights the urgent need for science communication strategies that effectively convey the provisional nature of scientific knowledge while preserving trust and confidence in scientific outcomes.\u003c/p\u003e \u003cp\u003eScientific uncertainty is an inherent feature of research and knowledge generation (Van der Bles et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Gustafson \u0026amp; Rice, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2019\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). However, it is frequently overlooked or inadequately communicated to the public (Maier et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Effective communication of this uncertainty plays a pivotal role in fostering understanding and trust, making it a critical aspect of science communication (Gustafson \u0026amp; Rice, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Simis, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Nevertheless, the perception that uncertainty undermines credibility presents a significant challenge. Many researchers prefer to present their findings as definitive, fearing that emphasizing their provisional nature might be misconstrued as a sign of weakness or unreliability (Flemming et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Van der Bles et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). This reluctance exacerbates a broader misunderstanding of the iterative and self-correcting nature of scientific knowledge development.\u003c/p\u003e \u003cp\u003eA deeper public understanding of how scientific knowledge is generated is essential for accurately evaluating research results. While scientific results are often presented as definitive and conclusive, within the academic community they are typically regarded as provisional and subject to revision (Bromme \u0026amp; Goldman, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Duschl, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e1988\u003c/span\u003e; Flemming et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Kimmerle et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Tentativeness refers to the acknowledgement that scientific conclusions are based on current evidence and may change as new data emerge. Unfortunately, this aspect is rarely communicated effectively to non-specialist audiences, resulting in widespread misconceptions about the value, significance, and reliability of scientific evidence (Flemming et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eEven when scientists accurately communicate the provisional nature of their findings, it is often misunderstood by lay audiences (Fischhoff \u0026amp; Davis, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Individual perceptions and interpretive frameworks play a critical role in how such information is received and understood (Fischhoff \u0026amp; Davis, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). It is therefore imperative for the public to grasp the importance of uncertainty as a fundamental aspect of the scientific process (Van der Bles et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eRecognizing that scientific findings are inherently subject to change and gradual refinement is fundamental to understanding the nature of the scientific process. Despite this provisional nature, scientists are required to make well-justified decisions within these parameters, ensuring that their research methods and conclusions are both robust and credible. This balance underscores the responsibility of scientists to uphold consistency and rigor, particularly when addressing complex problems and engaging in deliberative processes (Maier et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eA theoretical lens through which to examine this challenge is offered by process models of trust formation, such as those proposed by Mayer et al. (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e1995\u003c/span\u003e). These models highlight the dynamic interplay of competence, integrity, and benevolence as critical components in building trust (Hendriks et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Within the realm of science communication, trust is shaped not only by the content's accuracy and methodological rigor but also by how information or uncertainty is framed and delivered (Simis, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Presenting scientific findings as tentative, while transparently acknowledging uncertainties, can bolster perceptions of integrity and openness, thereby fostering trust even amidst evolving evidence.\u003c/p\u003e \u003cp\u003eTo address these concerns, the present study explores how different communication styles influence public perceptions of scientific reasoning, tentativeness, and uncertainty. Drawing on a framework that differentiates between the presentation of thinking processes of scientists as authentic in the sense of science-in-the-making (de Boer et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) - emphasizing the iterative and uncertain nature of science - and the presentation of thinking processes of scientists as canonized, which highlights fixed and authoritative conclusions, we investigate how these approaches affect laypeople\u0026rsquo;s understanding and trust. By analyzing declarative, procedural, and epistemic dimensions of scientific knowledge, this research seeks to illuminate how the portrayal of scientists' deliberations as authentic or canonized can either strengthen or diminish public trust and confidence in science.\u003c/p\u003e\n\u003ch3\u003eScientific inquiry and communication: Bridging uncertainty and understanding\u003c/h3\u003e\n\u003cp\u003eTo grasp the inherent uncertainty and tentativeness of scientific findings, it is crucial to first understand the scientific process itself. Rather than being a static or linear endeavor, this process is characterized by a dynamic interplay of hypothesis generation, experimentation, and the iterative refinement of theories considering new evidence. The scientific method\u0026ndash;anchored in principles of inductive and deductive reasoning as well as the systematic falsification of hypotheses\u0026ndash;provides a structured framework for navigating and productively engaging with uncertainty (Kind \u0026amp; Osborne, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eStakeholders who rely on scientific insights, including policymakers, educators, and the public, often face challenges in interpreting scientific evidence without a foundational understanding of these processes. Decision-makers, for instance, must assess whether research adheres to rigorous methodological standards and whether its conclusions are substantiated by reliable evidence. Similarly, innovators and practitioners seeking to translate research into practical applications require a nuanced comprehension of the processes that underpin discovery and progress (Fischhoff \u0026amp; Davis, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eBy addressing these uncertainties explicitly, science communication and science education can foster broader engagement with scientific topics, enabling diverse audiences to appreciate the iterative nature of scientific inquiry. Such an approach promotes critical thinking and informed decision-making, empowering stakeholders to evaluate scientific evidence more effectively and to participate in discussions about its implications with greater confidence.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eScientific literacy as a foundation\u003c/h2\u003e \u003cp\u003eScientific inquiry operates within two interconnected problem spaces: the hypothesis space and the experimental space, as described by the Scientific Discovery as Dual-Search (SDDS) model (Dunbar \u0026amp; Klahr, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e1988\u003c/span\u003e). This framework underscores the iterative nature of scientific reasoning, encompassing both the generation of plausible explanations and the systematic design of experiments to test them. These processes align closely with the objectives of scientific literacy, which emphasize understanding both the foundational concepts and methodologies of the natural sciences (Bybee, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2002\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe process of scientific inquiry draws upon a variety of reasoning methods, each contributing to the acquisition of knowledge and the derivation of conclusions from empirical data. Key reasoning processes include inductive reasoning, where general principles are inferred from specific observations; deductive reasoning, which applies general principles to specific cases; and the falsification of hypotheses, a cornerstone of scientific methodology (Kind \u0026amp; Osborne, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). While traditional models, such as Chalmers\u0026rsquo; (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2007\u003c/span\u003e) portrayal of the scientific method, present a structured, step-by-step approach, such frameworks have been criticized for oversimplifying the inherently dynamic and flexible nature of scientific practice.\u003c/p\u003e \u003cp\u003eIn reality, scientific inquiry is a fluid and context-dependent process that incorporates diverse reasoning styles. These styles integrate declarative knowledge (factual content), procedural knowledge (the methodologies employed), and epistemic knowledge (the values and assumptions underpinning scientific practices). Together, these dimensions facilitate the iterative refinement and testing of scientific knowledge, ensuring its evolution in response to new evidence (Kind \u0026amp; Osborne, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eUnderstanding the mechanisms of scientific inquiry is essential not only for scientists but also for the public (Kimmerle et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Enhanced scientific literacy enables individuals to critically evaluate information, discern credible sources, and make informed decisions on science-related issues. However, despite its importance, formal education often neglects the dynamic and uncertain nature of the scientific process. Science curricula frequently prioritize established findings over the processes through which those findings were discovered, missing a critical opportunity to cultivate critical thinking and scientific literacy (Lederman et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2002\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Valladares, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eBy addressing the iterative and evolving nature of scientific inquiry, education can help students move beyond perceiving science as a static body of facts. Instead, students can come to appreciate the provisional and evidence-driven nature of scientific knowledge, equipping them to navigate complex, real-world issues (Feinkohl et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Empowering learners with this perspective not only fosters critical engagement but also prepares them to develop evidence-based solutions in an increasingly complex and scientifically informed society. A more critical engagement can thereby enhance comprehension and trust (Peffer \u0026amp; Ramezani, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Windschitl et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2008\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThis educational gap becomes even more problematic when scientific uncertainties are communicated to the public. Research has shown that presenting findings as tentative can sometimes reduce public trust in science, as perceived tentativeness may appear contradictory to credibility (Flemming et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Hendriks et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Kimmerle et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). However, these effects are often mediated by the public\u0026rsquo;s familiarity with the iterative and uncertain nature of scientific inquiry. A shift from factual knowledge toward epistemic understanding\u0026ndash;how knowledge is constructed, tested, and refined\u0026ndash;may mitigate these challenges (Kind \u0026amp; Osborne, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eCommunicating scientific uncertainty effectively requires a transparent portrayal of the evolving nature of research and the role of evidence in shaping conclusions. By framing uncertainty as an integral and valuable aspect of scientific work, communicators can foster a deeper, more nuanced public understanding of science. This approach enhances credibility and trust while highlighting the interconnected dimensions of scientific reasoning, methodology, and epistemology.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eResearch objectives and design\u003c/h3\u003e\n\u003cp\u003eThe research presented here investigates how different communication styles and media formats influence people\u0026rsquo;s perceptions of scientific processes, the credibility of research, and the inherent tentativeness of research findings. The primary aim is to enhance scientific literacy by identifying effective strategies for communicating complex scientific concepts and fostering trust in scientific research.\u003c/p\u003e \u003cp\u003ePrevious research has shown that the presentation of scientific information significantly shapes people\u0026rsquo;s perception (Ophir \u0026amp; Jamieson, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Studies on scientific literacy highlight the need to promote deeper, more critical engagement with scientific information to improve both understanding and trust (Peffer \u0026amp; Ramezani, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Windschitl et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Grounded in the framework proposed by Kind and Osborne (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), which categorizes scientific reasoning into declarative, procedural, and epistemic dimensions, this research examines how these elements influence comprehension and trust. Specifically, it explores the impact of two key factors: the presentation of steps of scientific practices (with explanations vs. without explanations) and the portrayal of scientists\u0026rsquo; deliberations (authentic vs. canonized).\u003c/p\u003e \u003cp\u003eDetailed explanations provide context for scientific practices by linking the \"what\" of scientific activities with the \"why\" and \"how.\" This approach draws on Kind and Osborne\u0026rsquo;s (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) distinction of six styles of scientific reasoning, each encompassing declarative knowledge (factual content), procedural knowledge (methods used to generate and validate knowledge), and epistemic knowledge (the values and assumptions underlying scientific practices). By systematically incorporating these dimensions, we aim to foster a comprehensive understanding of scientific reasoning and its contextual application.\u003c/p\u003e \u003cp\u003eTheoretical models such as Elaboration Theory (Reigeluth, 1999) suggest that such explanations deepen understanding by helping people integrate new information with prior knowledge. However, Cognitive Load Theory (Sweller, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e1988\u003c/span\u003e; Sweller et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) highlights the challenges of overly detailed content, particularly for individuals with limited prior knowledge.\u003c/p\u003e \u003cp\u003eAuthentic portrayals of scientific decision-making processes emphasize transparency, personal engagement, and epistemic openness (Saffran et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Molleda, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). In this approach, scientists explicitly articulate the factors they consider before making a decision. For example, in bat ecology, when determining sample size, researchers must weigh animal welfare, budget constraints, and methodological considerations. This type of portrayal not only presents the final decision but also highlights the uncertainties and the iterative nature of scientific inquiry. Such transparency fosters trust and strengthens the connection between scientists and their audience (Hovland et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e1953\u003c/span\u003e; Schriebl, M\u0026uuml;ller, \u0026amp; Robin, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn contrast, standardized portrayals, often found in scientific literature, offer a post-hoc reconstruction of the research process. While addressing similar topics (e.g., sample size trade-offs, dealing with unexpected results, material selection, and reflections on the nature of science), these portrayals focus on the final decision. The decision is presented first, followed by an explanation of the rationale behind it, without verbalizing the deliberative process itself. This approach presents science as a polished, well-thought-out, and often finalized process (D\u0026uuml;sing et al., accepted).\u003c/p\u003e \u003cp\u003eBeyond communication style, the medium through which scientific information is conveyed plays a significant role in shaping audience perceptions. Text-based formats encourage detailed analysis and critical reflection, allowing readers to process complex ideas at their own pace (Rovai \u0026amp; Wighting, 2005). Video-based formats, on the other hand, leverage visual and auditory modalities to enhance accessibility and emotional engagement, catering to diverse learning preferences (Zydney et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Liu et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Videos are particularly effective in fostering a sense of social presence, which can increase trust and credibility in scientific communication (Garrison et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e1999\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTo explore these dynamics, the study employs a 2x2 factorial design, manipulating two independent variables: the presentation of scientific practices (with or without explanations) and the portrayal of scientists\u0026rsquo; deliberations (authentic vs. canonized). The aim is to examine how these factors, in combination with the chosen communication medium (text-based vs. video-based), influence participants\u0026rsquo; perceptions of scientists\u0026rsquo; credibility, the credibility of research findings, and the perceived tentativeness of those findings.\u003c/p\u003e \u003cp\u003eThe study emphasizes the importance of transparency in the research process and the need to convey the inherent uncertainties in scientific work (Jain et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Lederman \u0026amp; O'Malley, 1990). This approach builds on research that highlights the necessity of tailoring communication strategies to audience needs. While detailed explanations enhance understanding for audiences with sufficient prior knowledge, minimizing cognitive load through simplified explanations benefits those less familiar with scientific concepts. Similarly, authentic communication styles foster transparency and trust, while canonized styles maintain professionalism and objectivity. By systematically examining these variables, this research seeks to provide actionable insights for educators and communicators striving to improve public understanding of scientific processes and build greater trust in science.\u003c/p\u003e \u003cp\u003eRecent research suggests that authenticity in science communication is a multifaceted construct, encompassing elements such as transparency, personal engagement, and epistemic openness (Molleda, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Schriebl et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Transparency involves openly addressing uncertainties and the evolving nature of scientific findings, while personal engagement highlights the human side of scientific work, including scientists\u0026rsquo; motivations, values, and deliberations. Epistemic openness emphasizes the provisional nature of knowledge and the methods of scientific inquiry. Together, these facets contribute to the perception of authenticity, aligning with the concept of social presence and increasing the perceived connection between the audience and the communicator (Short et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e1977\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn contrast, canonized communication follows standardized scientific norms, aiming to maintain objectivity and professionalism but may be perceived as more distant or impersonal (Fischhoff \u0026amp; Davis, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). By investigating both variables in a controlled study, this research aims to understand their combined effect on audience perception, comprehension, and trust in science.\u003c/p\u003e\n\u003ch3\u003ePresent research and hypotheses\u003c/h3\u003e\n\u003cp\u003eIn two experimental studies, we utilized the same material, which differed only in format: a text-based presentation in Study 1 and a video-based presentation in Study 2. The content centered on research about the ecology of bats based on a real field study of a wildlife research institute. The overall research question for both studies was: How does the presentation of the scientific practices and the portrayal of the scientist\u0026rsquo;s deliberations influence the tentativeness and credibility of research findings?\u003c/p\u003e \u003cp\u003eWe formulated the following hypotheses:\u003c/p\u003e\n\u003ch3\u003ePerception of the scientist’s credibility\u003c/h3\u003e\n\u003cp\u003eH1: A presentation that transparently communicates scientists\u0026rsquo; thinking processes (authentic) will be perceived as more credible than a presentation that focuses on polished, finalized results (canonized).\u003c/p\u003e\n\u003ch3\u003ePerception of the credibility of research findings\u003c/h3\u003e\n\u003cp\u003eH2: Presenting the scientific process with explanations will lead to the research findings being perceived as more credible than merely showing the process without explanations.\u003c/p\u003e \u003cp\u003eH3: A presentation that adopts the science-in-the-making approach, transparently showcasing the evolving nature of scientific research processes and scientists\u0026rsquo; thinking processes (authentic), will enhance the perceived credibility of the research findings compared to a presentation that follows the polished and finalized argumentation structure of scientific papers (canonized).\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003ePerceived tentativeness of research findings\u003c/h2\u003e \u003cp\u003eH4: Presenting the scientific process with explanations will result in the research findings being perceived as more tentative, highlighting the ongoing nature of scientific inquiry, than presenting the process without explanations.\u003c/p\u003e \u003cp\u003eIt was an open research question whether there would be interaction effects of the two independent variables on any of the dependent variables. Our research assumptions for the two studies were pre-registered before data collection on AsPredicted.org (Study 1: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://aspredicted.org/z9c6-svt7.pdf\u003c/span\u003e\u003cspan address=\"https://aspredicted.org/z9c6-svt7.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e; Study 2: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://aspredicted.org/t2jn-ccmd.pdf\u003c/span\u003e\u003cspan address=\"https://aspredicted.org/t2jn-ccmd.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e).\u003c/span\u003e\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eEthics statement\u003c/h3\u003e\n\u003cp\u003e Both studies received approval from the Institutional Ethics Committee of the [anonymized for peer review] (approval number: LEK 2023/055). All participants were volunteers, and their identities were kept anonymous. Participants were thoroughly informed about privacy protection measures and their right to withdraw from the study at any time without consequences. Written informed consent was obtained from all participants prior to their participation. A debriefing session was conducted at the conclusion of the experiments.\u003c/p\u003e\n\u003ch3\u003ePower analysis\u003c/h3\u003e\n\u003cp\u003eAn a priori power analysis was conducted to determine the required sample size for both studies included in this paper. The analysis was performed for a 2x2 analysis of variance (ANOVA) design using R. Assuming an interaction effect size of 0.35 points (on the averaged 7-point scales for each dependent variable) and a standard error of 1.2, the required sample size to achieve 80% power at an alpha level of .05 was calculated. The results indicated that a total sample size of \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;100 participants (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;25 per condition) would be necessary to detect the specified effect size with the desired power.\u003c/p\u003e \u003cp\u003eFor Study 2, however, a larger sample size was chosen to increase the likelihood of detecting effects. This decision was made to account for potential variability in responses and to ensure sufficient sensitivity to identify effects that might deviate from the assumptions of the initial power analysis.\u003c/p\u003e "},{"header":"Study 1: Text-based presentation","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003cdiv id=\"Sec12\" class=\"Section3\"\u003e \u003ch2\u003eMethods\u003c/h2\u003e \u003cdiv id=\"Sec13\" class=\"Section4\"\u003e \u003ch2\u003eSample\u003c/h2\u003e \u003cp\u003eParticipants were recruited via the [anonymized for peer review] mailing list and notices posted on university buildings in [anonymized for peer review]. To be eligible, participants had to be at least 16 years old and possess a good command of the German language. In return for their participation, they were entered into a draw to win gift vouchers worth 3 \u0026times; 50 Euros and 2 \u0026times; 25 Euros. The final sample consisted of \u003cem\u003en\u003c/em\u003e\u003csub\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;\u003cem\u003e=\u003c/em\u003e\u0026thinsp;99 participants, including 62 women, 34 men, two non-binary persons, and one individual who did not disclose their gender. The mean age of participants was \u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;24.57 years (\u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;6.80 years). The educational background of participants was diverse: 57.6% had completed a university entrance qualification, 35.4% had earned a university degree, and 7.1% had other qualifications. Most participants studied medicine, health sciences, sports science, and psychology, with a notable presence in fields such as mathematics and science, education and teaching, and other areas.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eDesign and procedure\u003c/h2\u003e \u003cp\u003eWe conducted an online experiment using a 2x2 between-groups design. Participants were randomly assigned to one of four experimental conditions, where they were exposed to a presentation of scientific practices (with explanation vs. without explanation) and to a portrayal of the scientist\u0026rsquo;s deliberations (authentic vs. canonized), reflecting different ways of communicating scientific reasoning and processes rather than different individuals. We collected data from participants in the following conditions: \u0026ldquo;authentic - without explanation\u0026rdquo; (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;26), \u0026ldquo;authentic - with explanation\u0026rdquo; (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;22), \u0026ldquo;canonized - without explanation\u0026rdquo; (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;24), and \u0026ldquo;canonized - with explanation\u0026rdquo; (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;27).\u003c/p\u003e \u003cp\u003eAfter recruitment, participants were required to read one of four texts. These texts were film scripts of the videos used in Study 2. The material was developed for use in educational settings to provide students with deeper insights into both the practice of fieldwork and the principles underpinning the process of scientific inquiry. Our storytelling of the research process to foster scientific literacy was grounded in the structure model of scientific reasoning (Mayer et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). We subdivided the process variables into:\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eFormulating the research question and hypothesis.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003ePlanning and conducting an investigation.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eAnalyzing and interpreting data.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003eTo ensure data quality, we excluded all participants who did not engage with the text or video presentation or failed an attention check question after reading or watching. The attention check question asked about the bat species presented in the material, ensuring that participants had actively engaged with the provided content.\u003c/p\u003e \u003cp\u003eTo explore the material\u0026rsquo;s impact and the relationships between our dependent variables, each group completed questionnaires designed to measure the dependent variables of the perception of the scientist\u0026rsquo;s credibility, the perception of the credibility of research findings, and the perceived tentativeness of research findings.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eMaterial and measures\u003c/h2\u003e \u003cdiv id=\"Sec16\" class=\"Section3\"\u003e \u003ch2\u003eText-based presentation\u003c/h2\u003e \u003cp\u003eParticipants read a text that represented the video scripts of the videos used in Study 2. The material was designed to explain scientific research processes based on a field study on bat ecology in Thailand (see Table\u0026nbsp;1). The texts consisted of 1900 to 2420 words, with a median reading time of around 8 minutes.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eExplanation of the conditions.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePresentation of\u003c/p\u003e \u003cp\u003escientific practices\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVideo script\u0026nbsp;excerpts\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWithout explanation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAs \u003cb\u003eDaniel is very familiar with the current state of knowledge\u003c/b\u003e, his research question is: How does the use of airspace differ between the bulldog and tomb bat?\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWith explanation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDaniel \u003cb\u003estarts by looking at the current state of knowledge\u003c/b\u003e about the two bat species. However, \u003cb\u003ecurrent knowledge about bats is limited\u003c/b\u003e. \u003cb\u003eThis is not only true for knowledge about bats, but also for scientific knowledge in general\u003c/b\u003e. Overall, \u003cb\u003every little is known\u003c/b\u003e about these two species.\u003c/p\u003e \u003cp\u003eHaving analyzed the previous studies in detail, \u003cb\u003eDaniel can continue his search for new knowledge and formulate his research question.\u003c/b\u003e This is: How does the use of airspace differ between the bulldog and tomb bat?\u003c/p\u003e \u003cp\u003e\u003cb\u003eThe research question is the basis for further investigation and should be answered at the end.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePortrayal of the scientist\u0026rsquo;s deliberations\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eVideo script\u0026nbsp;excerpts\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAuthentic\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e- Biologist Daniel \u003cb\u003ewants to find out more\u003c/b\u003e about the flying behavior of these wild animals. He \u003cb\u003einvestigates\u003c/b\u003e the ecology of bats. In Daniel's current study, he is also \u003cb\u003elooking for answers\u003c/b\u003e about the ecology of bats.\u003c/p\u003e \u003cp\u003e- \u003cem\u003e\u0026ldquo;All the values are summarized in the tables, but you can't see so much in the tables. It's much easier to visualize the values as a graph.\u0026rdquo;\u003c/em\u003e (Authentic representation of the decision to check data visually).\u003c/p\u003e \u003cp\u003e- \u003cem\u003e\u0026ldquo;There are always unexpected values, particularly large or particularly small values, where you have to consider whether these values really come from the animals or whether there are technical problems.\u0026rdquo;\u003c/em\u003e (Authentic reflection on data quality).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCanonized\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e- Biologist Daniel \u003cb\u003eis familiar with\u003c/b\u003e the flight behavior of these wild animals. He \u003cb\u003eis an expert\u003c/b\u003e in the ecology of bats. Daniel's current study also \u003cb\u003efocuses\u003c/b\u003e on the ecology of bats.\u003c/p\u003e \u003cp\u003e- \u003cem\u003e\u0026ldquo;The result of the statistical test shows that the flight altitudes of the two species of bats are systematically different.\u0026rdquo;\u003c/em\u003e Daniel has already defined the appropriate statistical test in his experimental design. (Canonized procedure for confirming hypotheses).\u003c/p\u003e \u003cp\u003e- To relate the results to the hypothesis, Daniel revisits the prediction he made at the beginning of the study. The data match the prediction. The hypothesis can be maintained. (Canonized method of hypothesis testing).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003ePerception of the scientist\u0026rsquo;s credibility\u003c/h2\u003e \u003cp\u003eThe perception of the scientist\u0026rsquo;s credibility was assessed using 14 items from the Muenster Epistemic Trustworthiness Inventory (\u003cem\u003eMETI\u003c/em\u003e) questionnaire (Hendriks et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), utilizing a 7-point semantic differential scale. This instrument is specifically designed to evaluate the trustworthiness judgments attributed to individuals who share their knowledge publicly, making it well-suited for measuring the trust assessments that laypersons form about experts.\u003c/p\u003e \u003cp\u003eThe 14 items were structured as bipolar adjective pairs, each addressing one of three dimensions of epistemic trustworthiness: expertise, integrity, and benevolence. The adjectives were derived from theoretical considerations of trustworthiness and sourced from existing scales measuring trustworthiness and credibility.\u003c/p\u003e \u003cp\u003eThe scale ranged from 1 (\u003cem\u003enegative pole\u003c/em\u003e) to 7 (\u003cem\u003epositive pole\u003c/em\u003e) and included example adjective pairs such as: \u0026ldquo;Incompetent \u0026ndash; competent\u0026rdquo; (\u003cem\u003eexpertise\u003c/em\u003e), \u0026ldquo;Dishonest \u0026ndash; honest\u0026rdquo; (\u003cem\u003eintegrity\u003c/em\u003e), and \u0026ldquo;Immoral \u0026ndash; moral\u0026rdquo; (\u003cem\u003ebenevolence\u003c/em\u003e).\u003c/p\u003e \u003cp\u003eThe full list of adjective pairs is provided in \u003cspan refid=\"Sec49\" class=\"InternalRef\"\u003eAppendix\u003c/span\u003e 1. The internal consistency of the overall scale was excellent, with a Cronbach\u0026rsquo;s alpha of \u003cem\u003eα\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.93.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003ePerception of the credibility of research findings\u003c/h2\u003e \u003cp\u003eParticipants\u0026rsquo; perceptions of the scientific credibility of the research findings presented in the video scripts were measured using a 7-point semantic differential scale. The questionnaire was based on items from the \u003cem\u003eMETI\u003c/em\u003e questionnaire (Hendriks et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) and the \u003cem\u003ePerceived Scientific Credibility Scale\u003c/em\u003e (Kimmerle et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe scale ranged from 1 (\u003cem\u003enegative pole\u003c/em\u003e) to 7 (\u003cem\u003epositive pole\u003c/em\u003e) and included bipolar adjective pairs such as: \u0026ldquo;Not credible \u0026ndash; credible\u0026rdquo;, \u0026ldquo;Not trustworthy \u0026ndash; trustworthy\u0026rdquo; and \u0026ldquo;Not reliable \u0026ndash; reliable\u0026rdquo;. The full list of adjective pairs is provided in \u003cspan refid=\"Sec49\" class=\"InternalRef\"\u003eAppendix\u003c/span\u003e 2. Participants were instructed to indicate their opinion for each pair of adjectives. The internal consistency of the scale was excellent, with a Cronbach\u0026rsquo;s alpha of \u003cem\u003eα\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.93.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003ePerceived tentativeness of research findings\u003c/h2\u003e \u003cp\u003eTo evaluate participants\u0026rsquo; perceptions of the tentativeness of the research findings presented in the text, we employed the \u003cem\u003ePerceived Tentativeness Scale\u003c/em\u003e (Feinkohl et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Flemming et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2017\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). This scale consists of six statements, which participants rated on a 7-point Likert scale ranging from 1 (\u003cem\u003eI don\u0026rsquo;t agree at all\u003c/em\u003e) to 7 (\u003cem\u003eI fully agree\u003c/em\u003e). Higher scores indicate greater perceived tentativeness of the research findings. Example items include: \u0026ldquo;The results of the study are not very definite\u0026rdquo;, \u0026ldquo;The study is conclusive\u0026rdquo; (\u003cem\u003ereversed item\u003c/em\u003e), and \u0026ldquo;The results of the study should be viewed as tentative\u0026rdquo;.\u003c/p\u003e \u003cp\u003eWe adapted the German version of the questionnaire to align with the topic of bat ecology. After re-coding the reversed items, we calculated the mean score across all tentativeness items. The internal consistency of the scale was moderate, with a Cronbach\u0026rsquo;s alpha of \u003cem\u003eα\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.65, which is considered acceptable for exploratory research stages. The full list of items is provided in \u003cspan refid=\"Sec49\" class=\"InternalRef\"\u003eAppendix\u003c/span\u003e 3.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eCorrelation analysis\u003c/h2\u003e \u003cp\u003eTo explore the relationships between the various scales, Pearson correlation coefficients were computed. Pearson correlations were chosen because they represent a parametric test that measures the linear relationship between two continuous variables. This test assumes that the data are normally distributed and that the relationship between the variables is linear. The correlation coefficients were calculated to assess the strength and direction of associations between the scales. A significance level of \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.05 was used for all tests.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eResults\u003c/h3\u003e\n\u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eHypotheses testing\u003c/h2\u003e \u003cp\u003eTo analyze our hypotheses, we used separate two-way ANOVAs.\u003c/p\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003ePerception of the scientist\u0026rsquo;s credibility\u003c/h2\u003e \u003cp\u003eNeither the portrayal of the scientist\u0026rsquo;s deliberations, \u003cem\u003eF\u003c/em\u003e(1, 95)\u0026thinsp;=\u0026thinsp;0.01, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.938, nor the presentation of scientific practices, \u003cem\u003eF\u003c/em\u003e(1, 95)\u0026thinsp;=\u0026thinsp;1.50, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.224, showed main effects for the perception of the scientist\u0026rsquo;s credibility. Additionally, the interaction effect between portrayal of the scientist\u0026rsquo;s deliberations and presentation of scientific practices was not significant, \u003cem\u003eF\u003c/em\u003e(1, 95)\u0026thinsp;=\u0026thinsp;0.02, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.882. This means the data did not support H1.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003ePerception of the credibility of research findings\u003c/h2\u003e \u003cp\u003eWe did not find a main effect of portrayal, \u003cem\u003eF\u003c/em\u003e(1, 95)\u0026thinsp;=\u0026thinsp;1.31, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.256, or presentation, \u003cem\u003eF\u003c/em\u003e(1, 95)\u0026thinsp;=\u0026thinsp;1.43, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.236, for perception of the credibility of research findings. Similarly, the interaction between portrayal of the scientist\u0026rsquo;s deliberations and presentation of scientific practices was not significant, \u003cem\u003eF\u003c/em\u003e(1, 95)\u0026thinsp;\u0026lt;\u0026thinsp;0.01, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.972. These results do not support H2 and H3.\u003c/p\u003e \u003cdiv id=\"Sec25\" class=\"Section3\"\u003e \u003ch2\u003ePerceived tentativeness of research findings\u003c/h2\u003e \u003cp\u003eThe ANOVA revealed a significant main effect of the presentation of scientific practices on the perceived tentativeness of research findings, \u003cem\u003eF\u003c/em\u003e(1,95)\u0026thinsp;=\u0026thinsp;5.94, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.017, \u0026#120578;\u003csub\u003e\u0026#120369;\u003c/sub\u003e\u0026sup2; = .06. Participants in the without explanation condition rated the tentativeness of findings, on average, higher (\u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;4.00, \u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.80) compared to those in the with explanation condition (\u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3.66, \u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.53). This result contradicted H4.\u003c/p\u003e \u003cp\u003eWe also observed a trend for the main effect of the portrayal of the scientist\u0026rsquo;s deliberations on the perceived tentativeness of research findings, \u003cem\u003eF\u003c/em\u003e(1,95)\u0026thinsp;=\u0026thinsp;3.56, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.062, \u0026#120578;\u003csub\u003e\u0026#120369;\u003c/sub\u003e\u0026sup2; = .04. On average, findings presented as authentic (\u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3.95, \u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.80) were rated slightly higher in tentativeness compared to findings presented as canonized (\u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3.71, \u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.57).\u003c/p\u003e \u003cp\u003eThe interaction effect between the portrayal of the scientist\u0026rsquo;s deliberations and the presentation of scientific practices was not significant \u003cem\u003eF\u003c/em\u003e(1,95)\u0026thinsp;=\u0026thinsp;1.73, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.191. This suggests that the effect of the presentation of scientific practices on perceived tentativeness did not differ significantly between authentic and canonized portrayals of the scientist\u0026rsquo;s deliberations.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec26\" class=\"Section3\"\u003e \u003ch2\u003eFurther analysis: Correlation analysis\u003c/h2\u003e \u003cp\u003eThe results of the Pearson correlation coefficients provide valuable insights into the relationships among the various scales. Three correlations were examined to explore these associations (see Table\u0026nbsp;2).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCorrelation matrix of Study 1.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTentativeness of research findings\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCredibility of research findings\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCredibility of research findings\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.64***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eScientist\u0026rsquo;s credibility\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.46***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.65***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eA significant negative correlation was found between the perceptions of the tentativeness of research findings and the credibility of research findings (Pearson's \u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;.64, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001), suggesting a strong inverse relationship. Additionally, a moderate but significant negative correlation was observed between the perceived tentativeness of research findings and the perception of the scientist\u0026rsquo;s credibility (Pearson's \u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;.46, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001). Lastly, a strong and significant positive correlation was identified between the perceptions of the credibility of research findings and the credibility of the scientist (Pearson's \u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.65, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e\n\u003ch3\u003eDiscussion\u003c/h3\u003e\n\u003cp\u003eThe findings from the hypothesis tests underscore the importance of how scientific practices are presented in shaping perceived tentativeness. While the portrayal of scientists' deliberations and interaction effects did not significantly influence other measured scales, the results from H4 revealed an unexpected outcome: The absence of an explanation led to higher perceived tentativeness, contrary to the original hypothesis.\u003c/p\u003e \u003cp\u003eCorrelation analyses provided further insights. A strong, negative correlation between perceived tentativeness and the credibility of research findings indicates that higher tentativeness is associated with reduced credibility. Similarly, a moderate, negative correlation between perceived tentativeness and the credibility of the scientist suggests that increased tentativeness diminishes the perceived credibility of the scientist. Finally, a strong, positive correlation between the credibility of research findings and the credibility of the scientist highlights the interdependence of these two dimensions in participants\u0026rsquo; perceptions.\u003c/p\u003e \u003cp\u003eThe observed correlations align with broader concerns about deficits in scientific literacy, as highlighted in earlier research (Bell et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Broadhurst, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e1970\u003c/span\u003e; Duschl, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e1988\u003c/span\u003e; Lederman \u0026amp; O\u0026rsquo;Malley, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e1990\u003c/span\u003e; Matthews, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e1994\u003c/span\u003e). Participants\u0026rsquo; responses suggest a limited understanding of the dynamic and iterative nature of scientific inquiry, which may contribute to their reliance on perceived certainty as a marker of credibility. The findings are also consistent with previous studies, which emphasize the challenges of communicating scientific uncertainty (Flemming et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Hendriks et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Kimmerle et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). The results show that high perceived tentativeness can erode public trust in scientific claims (Flemming et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), further underscoring the need for effective science communication strategies. This is particularly relevant for decision-makers who rely on scientific insights to make informed choices. The observed correlations highlight the critical need for communication strategies that not only convey the iterative and uncertain nature of scientific inquiry but also maintain credibility.\u003c/p\u003e \u003cp\u003eAlthough effective communication of uncertainties did not diminish the credibility of the scientist or the research findings, it appeared to shift focus toward the perceived tentativeness of research findings. This dynamic suggests that while transparency may bolster credibility, it simultaneously alters how the provisional nature of findings is perceived.\u003c/p\u003e \u003cp\u003eThese results complicate Fischhoff and Davis\u0026rsquo;s (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) assertion that fostering a deeper understanding of scientific processes improves decision-making and promotes broader knowledge acquisition. If transparency significantly enhances perceived credibility to the point where it inversely correlates with perceived tentativeness\u0026ndash;even when tentativeness is explicitly communicated\u0026ndash;it raises critical questions about the practical feasibility of leveraging transparency to simultaneously strengthen trust and accurately convey the provisional nature of scientific findings.\u003c/p\u003e \u003cp\u003eExpanding on these findings, Study 2 explored whether video-based presentations yield similar patterns. Multimedia formats, combining visual and auditory elements, may alter perceptions of tentativeness and credibility compared to text-based materials. Research indicates that video presentations can reduce perceived uncertainty (Lim et al., 2000), potentially mitigating the effects of tentativeness observed in textual formats.\u003c/p\u003e \u003cp\u003eThis comparative approach provides critical insights into the role of presentation styles in interpretations of scientific information. By examining the interplay between media formats and perceptions of scientific uncertainty, this study contributes to a deeper understanding of how to foster scientific literacy and trust in research outcomes.\u003c/p\u003e "},{"header":"Study 2: Video-based presentation","content":"\u003cdiv id=\"Sec28\" class=\"Section2\"\u003e \u003cdiv id=\"Sec29\" class=\"Section3\"\u003e \u003ch2\u003eMethods\u003c/h2\u003e \u003cdiv id=\"Sec30\" class=\"Section4\"\u003e \u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003eBuilding on the findings of Study 1, the goal of Study 2 was to assess whether using videos instead of texts would yield similar effects on participants\u0026rsquo; perceptions. Given the increasing prevalence and effectiveness of videos in science communication and science education (Berk, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Criswell, Krall, \u0026amp; Ringl, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Forsythe et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Grosser et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), we assumed that videos would have a more pronounced and distinct impact on participants\u0026rsquo; perceptions compared to texts. Videos offer unique advantages, such as the ability to combine auditory and visual elements, which can make complex information more accessible and engaging. By visually illustrating each step of the research process (e.g., including research questions and hypotheses as well as scientific box plots for graphical presentation of results), the videos aimed to create a more immersive and intuitive learning experience, potentially enhancing participants\u0026rsquo; comprehension. Moreover, the dynamic nature of videos allows for the integration of narrative techniques, animations, and visual cues that can highlight key aspects of the research, making abstract concepts easier to grasp and more relatable. These features make videos particularly well-suited to fostering a deeper understanding of scientific processes, especially for audiences with diverse learning preferences.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec31\" class=\"Section2\"\u003e \u003ch2\u003eSample\u003c/h2\u003e \u003cp\u003eThe study involved \u003cem\u003en\u003c/em\u003e\u003csub\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;184 participants (131 women, 49 men, 4 non-binary), with an average age of \u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;30.10 years (\u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;14.50 years). Participants were required to be at least 16 years old and have a C1 level of German proficiency. Recruitment was conducted via the [anonymized for peer review] mailing list and on-campus notices, with incentives including gift voucher draws. The educational background of participants varied: 50.8% held a university degree, 34.4% had completed a university entrance qualification, and 14.8% had other qualifications. Their main fields of study included mathematics, natural sciences, medicine, health sciences, psychology, and education.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec32\" class=\"Section2\"\u003e \u003ch2\u003eDesign and procedure\u003c/h2\u003e \u003cp\u003eParticipants were excluded if they did not watch at least 10 minutes of the video or failed an attention check question. The final analysis included four conditions: \u0026ldquo;authentic - without explanation\u0026rdquo; (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;42), \u0026ldquo;authentic - with explanation\u0026rdquo; (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;47), \u0026ldquo;canonized - without explanation\u0026rdquo; (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;43), and \u0026ldquo;canonized - with explanation\u0026rdquo; (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;51). To ensure methodological consistency, the procedure mirrored Study 1, maintaining the same design and measurement tools. Reliability tests showed that the \u003cem\u003ePerceived Tentativeness Scale\u003c/em\u003e had a low internal consistency (Cronbach\u0026rsquo;s alpha of \u003cem\u003eα\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.60), suggesting that the scale requires improvement or revision. In contrast, both the \u003cem\u003ePerceived Scientific Credibility Scale\u003c/em\u003e and the \u003cem\u003eMETI\u003c/em\u003e demonstrated in each case a high reliability (Cronbach\u0026rsquo;s alpha of \u003cem\u003eα\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.91).\u003c/p\u003e \u003cdiv id=\"Sec33\" class=\"Section3\"\u003e \u003ch2\u003eMaterial and measures\u003c/h2\u003e \u003c/div\u003e \u003cdiv id=\"Sec34\" class=\"Section3\"\u003e \u003ch2\u003eVideo-based presentation\u003c/h2\u003e \u003cp\u003e Participants watched videos documenting a real scientific research process on bat ecology in Thailand, illustrating the entire process from start to finish. The videos were developed by a professional media company and its filming crew in collaboration with educational experts, resulting in four distinct versions. Each video lasted between 14 and 18 minutes. The videos aimed to effectively visualize and explain scientific research, providing a more dynamic and engaging learning experience compared to text-based materials. This format was expected to enhance participants\u0026rsquo; understanding of the research process and reduce misconceptions about scientific tentativeness and credibility.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e\n\u003ch3\u003eResults\u003c/h3\u003e\n\u003cdiv id=\"Sec36\" class=\"Section2\"\u003e \u003ch2\u003eHypotheses testing\u003c/h2\u003e \u003cp\u003eTo analyze our hypotheses, we conducted separate two-way ANOVAs.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec37\" class=\"Section2\"\u003e \u003ch2\u003ePerception of the scientist\u0026rsquo;s credibility\u003c/h2\u003e \u003cp\u003eThe ANOVA results revealed that neither portrayal \u003cem\u003eF\u003c/em\u003e(1, 179)\u0026thinsp;=\u0026thinsp;0.01, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.930, nor presentation \u003cem\u003eF\u003c/em\u003e(1, 179)\u0026thinsp;=\u0026thinsp;3.69, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.056, \u0026#120578;\u003csub\u003e\u0026#120369;\u003c/sub\u003e\u0026sup2; = 0.02, nor their interaction \u003cem\u003eF\u003c/em\u003e(1, 179)\u0026thinsp;=\u0026thinsp;0.04, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.845, had a statistically significant effect on the perceived credibility of the scientist. Despite the non-significant result for presentation, a discernible trend emerged, suggesting that participants in the without explanation condition rated the scientist\u0026rsquo;s credibility slightly lower (\u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;5.95, \u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.77) compared to those in the with explanation condition (\u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;6.16, \u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.58). This trend was observed across both presentation conditions. However, the data did not support H1.\u003c/p\u003e \u003cdiv id=\"Sec38\" class=\"Section3\"\u003e \u003ch2\u003ePerception of the credibility of research findings\u003c/h2\u003e \u003cp\u003eThe ANOVA revealed a significant main effect of the presentation of scientific practices on the perceived credibility of the research findings, \u003cem\u003eF\u003c/em\u003e(1,179)\u0026thinsp;=\u0026thinsp;10.14, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.002, \u0026#120578;\u003csub\u003e\u0026#120369;\u003c/sub\u003e\u0026sup2; = 0.05. Participants in the with explanation condition rated the credibility, on average, higher (\u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;6.31, \u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.73) compared to those in the without explanation condition (\u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;5.96, \u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.76). This finding supports H2, suggesting that providing explanations enhances the perceived credibility of the research findings.\u003c/p\u003e \u003cp\u003eThe main effect of portrayal type was not significant, \u003cem\u003eF\u003c/em\u003e(1,179)\u0026thinsp;\u0026lt;\u0026thinsp;0.01, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.988. Similarly, the interaction effect between portrayal of the scientist\u0026rsquo;s deliberations and the presentation of scientific practices was not significant, \u003cem\u003eF\u003c/em\u003e(1,179)\u0026thinsp;=\u0026thinsp;0.11, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.738. These results indicate that the portrayal of the scientist\u0026rsquo;s deliberations and its interaction with the presentation of scientific practices did not influence perceived credibility.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec39\" class=\"Section2\"\u003e \u003ch2\u003ePerceived tentativeness of research findings\u003c/h2\u003e \u003cp\u003eThe ANOVA results indicated that neither the portrayal \u003cem\u003eF\u003c/em\u003e(1, 179)\u0026thinsp;=\u0026thinsp;0.06, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.805, nor the presentation \u003cem\u003eF\u003c/em\u003e(1, 179)\u0026thinsp;=\u0026thinsp;2.62, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.108, or their interaction \u003cem\u003eF\u003c/em\u003e(1, 179)\u0026thinsp;=\u0026thinsp;0.46, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.498 had a significant effect on the perceived tentativeness of the research findings. Thus, H4 was not supported by the data.\u003c/p\u003e \u003cdiv id=\"Sec40\" class=\"Section3\"\u003e \u003ch2\u003eFurther analysis: Correlation analysis\u003c/h2\u003e \u003cp\u003eThe correlation analysis conducted in Study 2 yielded insightful findings regarding the relationships among the various scales. The results of the Pearson correlation coefficients revealed several key associations (see Table\u0026nbsp;3).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCorrelation matrix Study 2.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTentativeness of research findings\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCredibility of research findings\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCredibility of research findings\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.53***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eScientist\u0026rsquo;s credibility\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.41***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.69***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eA significant negative correlation was found between the perception of the tentativeness of research findings and the credibility of those findings (Pearson\u0026rsquo;s r\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;.53, p\u0026thinsp;\u0026lt;\u0026thinsp;.001). Furthermore, a negative correlation was observed between the perceived tentativeness of research findings and the perception of the scientist's credibility (Pearson\u0026rsquo;s r\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;.41, p\u0026thinsp;\u0026lt;\u0026thinsp;.001). Lastly, a strong and significant positive correlation was identified between the perception of the credibility of research findings and the credibility of the scientist (Pearson\u0026rsquo;s r\u0026thinsp;=\u0026thinsp;.69, p\u0026thinsp;\u0026lt;\u0026thinsp;.001).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e\n\u003ch3\u003eDiscussion\u003c/h3\u003e\n\u003cp\u003eThe findings of the correlation analysis in Study 2 offer valuable insights into the relationships between participants\u0026rsquo; perceptions of scientific tentativeness, the credibility of research findings, and the scientist\u0026rsquo;s credibility. The significant negative correlations between perceived tentativeness and both the credibility of research findings and the scientist\u0026rsquo;s credibility suggest that when research findings are perceived as tentative or uncertain, they are viewed as less credible. This aligns with previous studies (Flemming et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2017\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Hendriks et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Kimmerle et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), which also found that uncertainty in research is often associated with a decrease in perceived credibility. Despite efforts to emphasize that tentativeness is inherent in the scientific process and not a sign of poor research, participants still seemed to view tentative findings as less trustworthy. This highlights a key challenge in science communication: people \u0026rsquo;s tendency to equate uncertainty with unreliability.\u003c/p\u003e \u003cp\u003eFurthermore, the strong positive correlation between the credibility of research findings and the credibility of the scientist supports the idea that these two dimensions of credibility are closely intertwined in the minds of participants. This finding emphasizes the importance of establishing trust not only in research results but also in the scientists behind those results. When people perceive scientists as credible, they are more likely to trust the research they produce. This connection underscores the critical role of scientist credibility in shaping public perceptions of scientific findings and the need for science communicators to foster trust in both research and the individuals conducting it.\u003c/p\u003e \u003cp\u003eThese results further contribute to the understanding of how scientific uncertainty is communicated and perceived. While it is essential for scientific knowledge to be presented transparently, the current findings suggest that the communication of uncertainty might inadvertently diminish the perceived credibility of research. This echoes previous research, which has found that the public often struggles to accept scientific uncertainty without undermining trust in the findings themselves (Fischhoff \u0026amp; Davis, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Simis, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Considering these findings, future research should explore ways to communicate uncertainty that preserve both the credibility of the findings and the trust in the scientists who conduct the research.\u003c/p\u003e \u003cp\u003eAdditionally, the negative correlation between tentativeness and both credibility scales suggests that participants may have difficulty reconciling the provisional nature of scientific knowledge with their expectations of certainty and trustworthiness. Despite efforts to clarify that scientific research is an ongoing process, the perception of uncertainty seemed to trigger doubts about the reliability of the findings. This highlights a persistent issue in science communication: how to balance the need for transparency with the need to maintain public confidence in science.\u003c/p\u003e \u003cp\u003eThe ANOVA revealed that the presentation of scientific practices significantly impacted the perceived credibility of research findings. Participants who received an explanation rated the credibility higher than those who did not receive an explanation. This suggests that while explanations of uncertainty alone may not be sufficient, explanations of scientific practices can positively influence credibility perceptions.\u003c/p\u003e \u003cp\u003eIn conclusion, the findings from this study underscore the complex relationship between the perceived tentativeness of research and its credibility. They highlight the challenge of communicating uncertainty in science in a way that does not undermine trust in the findings or the scientists behind them. These insights have important implications for science communicators, policymakers, and researchers, who must carefully navigate the delicate balance between transparency and trust in their efforts to engage the public with scientific knowledge.\u003c/p\u003e"},{"header":"General discussion","content":"\u003cp\u003eUnderstanding the intricate relationship between the presentation of scientific practices, scientific uncertainty, and public trust is crucial for advancing science communication practices and fostering scientific literacy. The findings of the research presented here underscore the pivotal role of how scientific practices are presented in shaping perceptions of tentativeness and credibility. This research highlights the importance of balancing perceptions of tentativeness and credibility, ensuring they are not perceived as inherently opposing attributes. Both studies revealed negative correlations between the perceived tentativeness of research findings and the credibility of both the scientist and their research. These results emphasize the need for communication strategies that transparently convey scientific uncertainty while maintaining trust in the credibility of the findings and the scientist. By exploring how different presentation formats influence people\u0026rsquo;s perceptions, the findings provide valuable insights for both researchers and practitioners of science communication.\u003c/p\u003e\n\u003ch3\u003eKey findings and interpretations\u003c/h3\u003e\n\u003cp\u003e \u003cb\u003ePresentation formats\u003c/b\u003e \u003c/p\u003e \u003cp\u003eShorter text-based explanations were more effective in influencing perceptions of tentativeness, suggesting that brevity and clarity increase awareness of uncertainty. In contrast, video-based presentations showed no significant effects on perceived tentativeness, indicating potential differences in how people process information across modalities. These findings suggest that while text-based materials may encourage straightforward interpretation, the multimodal nature of video presentations could dilute perceived tentativeness. Future studies should explore how the richness of video presentations might be optimized to clarify uncertainty without compromising credibility. These findings highlight the role of cognitive demands in shaping audience perceptions, with text encouraging more analytical processing and video potentially fostering a broader, less detail-focused engagement.\u003c/p\u003e \u003cp\u003e \u003cb\u003eCredibility and tentativeness of research findings\u003c/b\u003e \u003c/p\u003e \u003cp\u003eBoth studies consistently revealed a negative correlation between perceived tentativeness and the credibility of research findings. This suggests that while acknowledging uncertainty enhances understanding of the provisional nature of science, it can inadvertently diminish trust in the findings. Balancing these perceptions is crucial, particularly in contexts where public trust in science is critical, such as public health, climate science, and emerging technologies. By integrating these findings into science communication strategies, future efforts can focus on refining presentation methods and improving experimental manipulations to achieve a more balanced and effective communication strategy. For instance, the findings highlight the need for nuanced approaches to address the trade-off between transparency and credibility. These approaches should consider tailoring messages to specific audiences while maintaining a consistent focus on the dynamic nature of scientific knowledge (Fischhoff \u0026amp; Davis, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Gustafson \u0026amp; Rice, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Simis, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eEducational implications: Promoting scientific literacy\u003c/h3\u003e\n\u003cp\u003eTo address misconceptions about the tentativeness and credibility of scientific research, educational resources should prioritize fostering scientific literacy. Educational resources must emphasize that science is not a static body of knowledge but a dynamic, evolving process. It is essential to highlight the iterative nature of science. By discussing how research evolves with new data and findings, students might better understand that science is a continuous cycle of testing, refining, and revising theories. This process would help them appreciate the provisional nature of scientific knowledge.\u003c/p\u003e \u003cp\u003eUnderstanding tentative findings is also crucial. It is important to teach students that tentative findings - whether from early fieldwork, climate models, or preliminary medical trials - are not failures, but rather vital steps toward more robust conclusions. Recognizing the value of uncertainty in research as a natural and necessary part of scientific progress, rather than a sign of unreliability, is essential for developing a nuanced understanding of science (Matthews, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e1994\u003c/span\u003e; Pielke, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2008\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOur studies underline the significance of transparent communication in science education, particularly regarding the provisional nature of scientific knowledge. The results suggest that the presentation of scientific practices can influence how students perceive the credibility of scientific findings. By offering detailed explanations or no explanations at all, and portraying scientists as either canonized or authentically deliberating individuals, educators can shape students' perceptions. Enhancing understanding of the scientific process is essential. Students who understand how scientific inquiry works, such as hypothesis testing and theory revision, are more likely to see science as a dynamic, evolving field rather than a fixed collection of facts.\u003c/p\u003e \u003cp\u003eTo foster a deeper appreciation of the scientific process, curricula should incorporate both procedural and epistemic knowledge. This includes teaching not only the \u0026ldquo;what\u0026rdquo; of scientific activities but also the \u0026ldquo;why\u0026rdquo; and \u0026ldquo;how.\u0026rdquo; Emphasizing that scientific knowledge is provisional, evolving with new evidence, and that uncertainty is a necessary part of this process is vital. By integrating these principles into educational resources, we can help students critically engage with scientific content, reducing misconceptions about science\u0026rsquo;s reliability and fostering scientific literacy.\u003c/p\u003e \u003cp\u003eExplicitly addressing the relationship between tentativeness and credibility could help learners develop the critical thinking skills needed to evaluate scientific claims. For example, case studies showing how tentative findings have led to significant breakthroughs can help normalize uncertainty as part of the scientific process (Chen \u0026amp; Song, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Yang \u0026amp; Deng, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eStrengths and weaknesses of the studies\u003c/h3\u003e\n\u003cp\u003eThe studies presented offer significant insights into the field of science communication and science education, particularly regarding the ways in which uncertainty and credibility are perceived by scientific laypeople. One of the main strengths of these studies lies in their methodological diversity. By combining both text- and video-based presentations, the research enabled a more nuanced analysis of how different formats affect the perception of scientific uncertainty and credibility. This approach provided a rich dataset that captures the complexities of communicating science across various media, which is particularly valuable in today\u0026rsquo;s media landscape.\u003c/p\u003e \u003cp\u003eFurthermore, the findings offer suggestions for communicating scientific uncertainty, which is crucial for fostering public trust and engagement in critical scientific issues. These insights could inform communication strategies that help bridge the gap between scientific experts and the public, particularly in contexts where uncertainty is an inherent aspect of the scientific process.\u003c/p\u003e \u003cp\u003eHowever, there are also notable weaknesses in the studies that should be addressed in future research. A primary limitation is the heavy reliance on self-reported data. While self-reports can provide valuable insights into perceptions and attitudes, they are also susceptible to biases such as social desirability or recall bias, which may distort the findings. Additionally, the sample diversity was limited, with the participant groups not fully representing the broader population. This lack of diversity in the sample raises questions about the generalizability of the results, particularly when it comes to different cultural and demographic groups. Lastly, the studies primarily offer snapshot data, capturing perceptions at a single point in time, without providing insights into how these perceptions evolve over time or with repeated exposure to scientific communication.\u003c/p\u003e\n\u003ch3\u003eFuture Directions for Research\u003c/h3\u003e\n\u003cp\u003eTo address these limitations and build on the strengths of the existing studies, future research should focus on several key areas. First, longitudinal studies could provide valuable insights into how public perceptions of uncertainty and credibility change over time. In fields such as climate science and medicine, where new findings and updates are frequent, understanding how people\u0026rsquo;s views shift as new information is presented could help refine communication strategies. It is particularly important to consider how people\u0026rsquo;s expectations, shaped by prior communication norms, influence their perceptions of credibility. If they are accustomed to scientists being portrayed as authoritative figures presenting immutable facts, they may view scientists who communicate uncertainty as less credible. However, if uncertainty were more routinely incorporated into public understandings of science, these perceptions might shift, allowing for a more accurate view of scientific work as an ongoing, iterative process.\u003c/p\u003e \u003cp\u003eAnother area for future research is the diversification of participant samples. Including individuals from a broader range of demographic and cultural backgrounds would enhance the external validity of the findings, making them more applicable to diverse audiences. This is especially crucial in the context of global science communication, where messages need to resonate across different social, cultural, and educational contexts.\u003c/p\u003e \u003cp\u003eMoreover, the studies could be strengthened by integrating objective measurement methods alongside self-reported data. While self-reports provide valuable insights into subjective perceptions, they do not capture the full scope of audience engagement. Future research could include behavioral measures such as audience engagement, trust in scientific sources, and changes in decision-making due to exposure to different communication formats. These objective data could provide a more comprehensive understanding of how different communication strategies influence behavior and perceptions.\u003c/p\u003e \u003cp\u003eFinally, refining the manipulation techniques used in the studies could offer deeper insights into how specific communication elements affect perceptions. By experimenting with more distinct variations in the framing of scientific uncertainty, researchers could isolate the effects of particular aspects of communication, such as the language used to convey uncertainty or the visual presentation of scientific information and gain a clearer understanding of how these factors shape people\u0026rsquo;s understanding.\u003c/p\u003e\n\u003ch3\u003eBroader applications\u003c/h3\u003e\n\u003cp\u003eThe findings from these studies offer insights into how to effectively communicate scientific uncertainty. This research lays the foundation for developing communication strategies that can be tailored to various contexts, from public health campaigns to educational outreach programs. Understanding how to communicate uncertainty clearly, accessible, and engaging is crucial for fostering a more informed and scientifically literate public. In an era where scientific knowledge is increasingly complex and rapidly evolving, the ability to effectively convey uncertainty can empower individuals to make more informed decisions, engage with science in meaningful ways, and contribute to the public discourse on pressing scientific issues such as climate change and public health (Chi et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Pielke, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2008\u003c/span\u003e).\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis research underscores the critical importance of balancing transparency and credibility in science communication. While acknowledging the provisional nature of scientific knowledge is essential for public understanding, it must be communicated in a way that maintains and nurtures trust.\u003c/p\u003e \u003cp\u003eThe theoretical foundation for our findings is grounded in two key aspects of scientific communication: Communicating procedural and epistemic knowledge regarding the steps of scientific inquiry; and representing the thought processes of scientists. Educational resources and communication strategies should incorporate these insights to address misconceptions, promote scientific literacy, and encourage critical thinking. By doing so, educators can empower future generations to engage with the complexities of scientific knowledge and foster a deeper understanding between scientists and the public. These efforts may contribute to enhancing the public\u0026rsquo;s ability to engage with scientific topics and make informed decisions (Fischhoff \u0026amp; Davis, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Matthews, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e1994\u003c/span\u003e).\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eANOVA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAnalysis of Variance\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMETI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMuenster Epistemic Trustworthiness Inventory\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSDDS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eScientific Discovery as Dual-Search\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe author(s) declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated during and/or analysed during the current study are available in the Open Science Framework (OSF) repository, https://osf.io/cah39/?view_only=fd98e0280e864776a925619174ec7256\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. The study was approved from the Institutional Ethics Committee of the [anonymized for peer review] (approval number: LEK 2023/055).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInformed consent\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eObtained.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eJCT: Methodology, Conceptualization, Data curation, Formal analysis, Investigation, Writing\u003c/p\u003e\n\u003cp\u003e\u0026ndash; original draft; KD: Methodology, Conceptualization, Writing \u0026ndash; review \u0026amp; editing; VB:\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMethodology, Conceptualization, Writing \u0026ndash; review \u0026amp; editing; HG: Methodology,\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eConceptualization, Writing \u0026ndash; review \u0026amp; editing; TB: Methodology, Conceptualization, Writing \u0026ndash;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ereview \u0026amp; editing; AS: Conceptualization, Writing \u0026ndash; review \u0026amp; editing; MB: Conceptualization,\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWriting \u0026ndash; review \u0026amp; editing; DL: Conceptualization, Writing \u0026ndash; review \u0026amp; editing; CV:\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eConceptualization, Writing \u0026ndash; review \u0026amp; editing; JK: Conceptualization, Funding acquisition,\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSupervision, Writing \u0026ndash; review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe research reported here was funded by a grant from the German Federal Ministry of Education and Research (Grant ID 01IO2104C).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBell, R. 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Creating a community of inquiry in online environments: An exploratory study on the effect of a protocol on interactions within asynchronous discussions. \u003cem\u003eComputers \u0026amp; Education\u003c/em\u003e, \u003cem\u003e58\u003c/em\u003e(1), 77\u0026ndash;87. https://doi.org/10.1016/j.compedu.2011.07.009\u003cstrong\u003e\u003c/strong\u003e\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"humanities-and-social-sciences-communications","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"palcomms","sideBox":"Learn more about [Humanities \u0026 Social Sciences Communications](http://www.nature.com/palcomms/)","snPcode":"41599","submissionUrl":"https://submission.springernature.com/new-submission/41599/3","title":"Humanities and Social Sciences Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Science communication, research process, scientific inquiry, tentativeness, credibility, scientific uncertainty, research findings","lastPublishedDoi":"10.21203/rs.3.rs-5872938/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5872938/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eLaypeople often struggle to understand the provisional nature of scientific knowledge. While scientific knowledge may be widely accepted within the scientific community, it is continually subject to revision and further development as new studies are published. These characteristics of science, where findings build upon each other over time rather than being entirely replaced by new discoveries, are not always well understood by the public. This becomes particularly problematic when research process presentations that emphasize the evolving, provisional nature of scientific knowledge are perceived as less credible, reinforcing misconceptions about the integrity and nature of science. In two experimental online studies on science education (\u003cem\u003en\u003c/em\u003e\u003csub\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;99; \u003cem\u003en\u003c/em\u003e\u003csub\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;184), we examined how different representations of the scientific process affect perceptions of credibility and tentativeness using text- and video-based presentations in the context of bat ecology as an example. In both studies, we varied the presentation of scientific practices (without explanations vs. with explanations) and the portrayal of the scientist\u0026rsquo;s deliberations (canonized vs. authentic). Our findings indicate that, although scientific knowledge is perceived as provisional, the way it is communicated can influence its perceived credibility. In both studies, perceived tentativeness was negatively correlated with perceived credibility, highlighting a challenge in science communication: the need to convey the evolving nature of scientific knowledge without undermining trust in its reliability.\u003c/p\u003e","manuscriptTitle":"The Role of Research Process Presentations in Science Education: Perceptions of Credibility and Tentativeness in Research Findings","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-02-03 11:03:57","doi":"10.21203/rs.3.rs-5872938/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-12-04T14:21:24+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-07T17:00:01+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"156768549102380783179778763322049187846","date":"2025-07-21T13:29:50+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"303941198500675450198385733699045500661","date":"2025-07-15T13:23:09+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"157932615536540011890775008526586376385","date":"2025-04-07T02:27:16+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-02-05T14:25:35+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-02-05T12:57:08+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-02-05T12:53:57+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-01-30T12:51:03+00:00","index":"","fulltext":""},{"type":"submitted","content":"Humanities and Social Sciences Communications","date":"2025-01-21T10:55:50+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"humanities-and-social-sciences-communications","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"palcomms","sideBox":"Learn more about [Humanities \u0026 Social Sciences Communications](http://www.nature.com/palcomms/)","snPcode":"41599","submissionUrl":"https://submission.springernature.com/new-submission/41599/3","title":"Humanities and Social Sciences Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"da923aa8-84f1-451c-b738-71ad1fd01b8c","owner":[],"postedDate":"February 3rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":43624204,"name":"Social science/Education"},{"id":43624205,"name":"Social science/Psychology"}],"tags":[],"updatedAt":"2026-05-18T15:23:17+00:00","versionOfRecord":[],"versionCreatedAt":"2025-02-03 11:03:57","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5872938","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5872938","identity":"rs-5872938","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}