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In this study, we have explored the effectiveness of two instructional approaches in the context of the motion of objects falling at terminal speed in the presence of air resistance. We ground these instructional approaches in dual-process theories of reasoning, which assert that human cognition relies on two thinking processes. Dual-process theories suggest multiple possible avenues by which instruction might impact student reasoning. In this paper, we compare two possible instructional approaches: one designed to reinforce the normative approach (improving the outputs of the intuitive process) and another that guides students to reflect on and analyze their initial ideas (supporting the analytic process). The results suggest that for students who have already demonstrated a minimum level of requisite knowledge, instruction that supports analysis of their likely intuitive mental model leads to greater learning benefits in the short term than instruction that focuses solely on providing practice with the normative mindware. These results have implications for the design of instructional materials and help to demonstrate how dual-process theories can be leveraged to explain the success of existing research-based materials. Published by the American Physical Society2024 

Over the course of the introductory calculus-based physics course, students are often expected to build conceptual understanding and develop and refine skills in problem solving and qualitative inferential reasoning. Many of the research-based materials developed over the past 30 years by the physics education research community use sequences of scaffolded questions to step students through a qualitative inferential reasoning chain. It is often tacitly assumed that, in addition to building conceptual understanding, such materials improve qualitative reasoning skills. However, clear documentation of the impact of such materials on qualitative reasoning skills is critical. New methodologies are needed to better study reasoning processes and to disentangle, to the extent possible, processes related to physics content from processes general to all human reasoning. As a result, we have employed network analysis methodologies to examine student responses to reasoning-related tasks in order to gain deeper insight into the nature of student reasoning in physics. In this paper, we show that network analysis metrics are both interpretable and valuable when applied to student reasoning data generated from . We also demonstrate that documentation of improvements in the articulation of specific lines of reasoning can be obtained from a network analysis of responses to reasoning chain construction tasks. Published by the American Physical Society2024 

ABSTRACT In undergraduate life sciences education, open educational resources (OERs) increase accessibility and retention for students, reduce costs, and save instructors time and effort. Despite increasing awareness and utilization of these resources, OERs are not centrally located, and many undergraduate instructors describe challenges in locating relevant materials for use in their classes. To address this challenge, we have designed a resource collection (referred to as Open Resources for Biology Education, ORBE) with 89 unique resources that are primarily relevant to undergraduate life sciences education. To identify the resources in ORBE, we asked undergraduate life sciences instructors to list what OERs they use in their teaching and curated their responses. Here, we summarize the contents of the ORBE and describe how educators can use this resource as a tool to identify suitable materials to use in their classroom context. By highlighting the breadth of unique resources openly available for undergraduate biology education, we intend for the ORBE to increase instructors’ awareness and use of OERs. 

Abstract BackgroundThe first day of class helps students learn about what to expect from their instructors and courses. Messaging used by instructors, which varies in content and approach on the first day, shapes classroom social dynamics and can affect subsequent learning in a course. Prior work established the non-content Instructor Talk Framework to describe the language that instructors use to create learning environments, but little is known about the extent to which students detect those messages. In this study, we paired first day classroom observation data with results from student surveys to measure how readily students in introductory STEM courses detect non-content Instructor Talk. ResultsTo learn more about the instructor and student first day experiences, we studied 11 introductory STEM courses at two different institutions. The classroom observation data were used to characterize course structure and use of non-content Instructor Talk. The data revealed that all instructors spent time discussing their instructional practices, building instructor/student relationships, and sharing strategies for success with their students. After class, we surveyed students about the messages their instructors shared during the first day of class and determined that the majority of students from within each course detected messaging that occurred at a higher frequency. For lower frequency messaging, we identified nuances in what students detected that may help instructors as they plan their first day of class. ConclusionsFor instructors who dedicate the first day of class to establishing positive learning environments, these findings provide support that students are detecting the messages. Additionally, this study highlights the importance of instructors prioritizing the messages they deem most important and giving them adequate attention to more effectively reach students. Setting a positive classroom environment on the first day may lead to long-term impacts on student motivation and course retention. These outcomes are relevant for all students, but in particular for students in introductory STEM courses which are often critical prerequisites for being in a major.