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This study examines the relationship between epistemic curiosity (EC) and perceived uncertainty, which is posited to form an inverted U-shape, in the context of uncertainty-driven science learning (UDSL). Using path analysis, survey data from 181 middle school students collected at multiple timepoints across a three-week photosynthesis unit designed to facilitate UDSL were analyzed. Results show that the inverted U-shaped relationship between EC and uncertainty does not consistently hold over time. Instead, prior uncertainty negatively affects this relationship unless mediated by EC or sustained uncertainty in subsequent activities. At the trait level, the study highlights the mediating role of epistemic orientation toward uncertainty in fostering trait EC in UDSL. The findings underscore the importance of supporting students' productive uncertainty navigation and signify the positive impacts of UDSL in fostering EC. 

Students’ Dispositions toward Scientific Uncertainty Navigation (DSUN) can play a pivotal role in impacting student learning achievement. However, understanding of the underlying mechanism of DSUN influencing learning achievement is limited. Drawing from related research, this study investigates the roles of epistemic curiosity and learning engagement in mediating the relationship between DSUN and learning achievement. A survey study design was employed, involving 1,137 middle school students who participated in an uncertainty-driven learning environment when learning solar energy. A sequential mediation model was tested using data collected through validated measures assessing DSUN, epistemic curiosity, learning engagement, and learning achievement. Results revealed that while DSUN positively predicts learning achievement, this relationship is sequentially mediated by epistemic curiosity and learning engagement, with epistemic curiosity not serving as a significant mediator on its own. These findings underscore the importance of fostering both epistemic curiosity and engagement in science classroom activities when students encounter scientific uncertainty. 

In a traditional lecturing environment, students possess limited agency in accepting or rejecting information provided by teachers. A higher level of student agency involves opportunities and actively identifying uncertainties and collaborating with peers to deepen understanding within the classroom community. Teachers play a crucial role in guiding students through sensemaking by addressing uncertainties and assisting in solution development. Student uncertainty is recognized as a pedagogical resource, engaging them in sensemaking and enhancing agency levels. This study analyzed 28 whole-class discussions led by seven science teachers, identifying three phases: problematization, coherence negotiation, and new understanding enactment. The teachers employed eight strategies leveraging student scientific uncertainty as pedagogical resources within three sequential methods: eliciting awareness of uncertainty (e.g., creating hybrid, ambiguous, and problem-solving spaces), seeking a coherent understanding (e.g., connecting students’ lived experiences to empirical data for coherence, juxtaposing different interpretations to build consensus, and weaving together student ideas for coherence), and demonstrating new understanding (e.g., transference, translation). By embracing uncertainty, students become agents of sensemaking, contributing to a collaborative learning environment. 

This article presents an innovative instructional approach that assists teachers in designing and implementing their science unit: The SUPeR (Student Uncertainty as Pedagogical Resources) approach. The SUPeR approach suggests four phases of student learning in scientific practices and posits that student uncertainties drive the trajectory of learning. By applying the SUPeR approach, teachers can foster student curiosity and ensure a student-centered science learning environment. A sixth-grade solar energy unit is described to show how a science unit can be designed and implemented using the SUPeR approach. The article elaborates on teacher guidance for applying the SUPeR approach, how student uncertainty is used to foster student curiosity and drive the learning trajectory, how student learning can be assessed from the SUPeR perspective, and how the SUPeR science unit aligns with the Next Generation Science Standards. 

Productive struggle is a process in which students expend effort to grapple with perplexing problems and make sense of something that is not immediately apparent and beyond their current level of understanding and capacity. The experience encourages students to reflect on and restructure their existing knowledge toward a new understanding of scientific concepts and practice. Scientific uncertainty is common in scientific sensemaking practice and is one of the major factors provoking student struggle. A teaching approach called Student Uncertainty as a Pedagogical Resource (SUPeR) is introduced to encourage teachers to engage students in the practice of productive struggle. The SUPeR approach is composed of four phases: (1) problematize a phenomenon, (2) engage in material practice, (3) participate in argumentative practice, and (4) engage in reflection, transformation, and application. An example from an eighth-grade biology class unit on Mendel’s Law of Segregation is used to demonstrate how the SUPeR approach can be implemented in the classroom. 

Abstract Grappling with uncertainty is an essential element of students' science learning and sense‐making processes, yet literature is limited regardinghowteachers can facilitate and use student scientific uncertainty as a pedagogical resource in their classrooms. Furthermore, progress on pedagogical practice depends on both the ability to notice one's perceptions and engage in opportunities to experience and reflect on new instructional approaches. To date, there are few professional development experiences explored in literature that explicitly aim to enhance teachers' awareness and pedagogical practice regarding the use and facilitation of student scientific uncertainty. As such, this qualitative study follows a group of 11 middle school science teachers before and after participating in a week‐long practice‐based professional development (P‐BPD) specifically designed to foster teachers' ability to use student uncertainty as a pedagogical resource. Interviews were conducted and analyzed prior to the P‐BPD, immediately after the P‐BPD, and the year following to measure shifts in perceptions over time. Additionally, classroom practice was observed both before and the year following the P‐BPD. Overall, we found that teachers' awareness of how to use student scientific uncertainty grew both in their expressed perceptions and in their observed classroom enactment. After engaging in the P‐BPD, many teachers expressed an enhanced awareness of the productive potential uncertainty can have, as well as increased understanding of potential sources and responses to student uncertainty. Additionally, in the post‐implementation observations, most of the teachers demonstrated more diverse use of uncertainty navigation strategies, intentionally raising, maintaining, and reducing scientific uncertainty more often. Teachers were observed using student ideas and uncertainties to drive the trajectory of their lessons more consistently. Notably, we report counterexamples for teachers who demonstrated less or no shifts in perceptions or practice. Furthermore, teachers explicitly identified experiences from the P‐BPD that fostered shifts in both their perceptions and practice. 

Sensemaking is conceptualized as a trajectory to develop better understanding and is advocated as one of the fundamental practices in science education. However, the field is lacking of a framework to view the prolonged process of sensemaking that starts from a raise of uncertainty of a target phenomenon to a grasping of a better understanding of a target phenomenon. The process requires teachers to recognize the role of scientific uncertainty in different phases of sensemaking and develop responsive instructional supports to help students navigate the uncertainties. With an attention on student scientific uncertainty as a potential driver of the trajectory of sensemaking, this study aims to identify different phases of sensemaking that can be developed with students’ scientific uncertainty. This study especially attends to two types of scientific uncertainty—conceptual and epistemic uncertainties. Conceptual uncertainty refers to student struggle of using conceptual understanding (e.g., mastery of content and everyday knowledge) to respond to an encountered phenomenon. Epistemic uncertainty emerges from struggles in using epistemic understanding to generate new ideas. Based on the multiple case study method, we examined sensemaking activities in two Korean science classrooms and one American science classroom and identified three phases of sensemaking: (a) focusing on a driving question related to a target phenomenon, (b) delving into multiple resources to develop plausible explanation(s), and (c) examining the successfulness of the new understanding and concretizing it. Based on the findings, we discuss two emerging themes. First, sensemaking progresses through three distinctive phases driven by students’ dynamically evolving scientific uncertainty. Second, attending to both epistemic and conceptual uncertainties can support developing sensemaking coherent with students’ view. 

Building a skilled cybersecurity workforce is paramount to building a safer digital world. However, the diverse skill set, constantly emerging vulnerabilities, and deployment of new cyber threats make learning cybersecurity challenging. Traditional education methods struggle to cope with cybersecurity's rapidly evolving landscape and keep students engaged and motivated. Different studies on students' behaviors show that an interactive mode of education by engaging through a question-answering system or dialoguing is one of the most effective learning methodologies. There is a strong need to create advanced AI-enabled education tools to promote interactive learning in cybersecurity. Unfortunately, there are no publicly available standard question-answer datasets to build such systems for students and novice learners to learn cybersecurity concepts, tools, and techniques. The education course material and online question banks are unstructured and need to be validated and updated by domain experts, which is tedious when done manually. In this paper, we propose CyberGen, a novel unification of large language models (LLMs) and knowledge graphs (KG) to generate the questions and answers for cybersecurity automatically. Augmenting the structured knowledge from knowledge graphs in prompts improves factual reasoning and reduces hallucinations in LLMs. We used the knowledge triples from cybersecurity knowledge graphs (AISecKG) to design prompts for ChatGPT and generate questions and answers using different prompting techniques. Our question-answer dataset, CyberQ, contains around 4k pairs of questions and answers. The domain expert manually evaluated the random samples for consistency and correctness. We train the generative model using the CyberQ dataset for question answering task.