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Learning the language of organic chemistry, i.e., how to describe reaction mechanisms, is crucial to success in any postsecondary organic chemistry course. However, it is well-known that learners struggle with reasoning about and explaining reaction mechanisms beyond surface-level features. Multiple studies have sought to aid learners in developing these skills. Investigating the connections that learners make regarding reaction mechanisms through their explanations provides insight into how we can better promote the development of learners’ reasoning skills. In this study, we evaluate 20,000+ learner explanations of 90 reaction mechanisms. We use network analysis to explore patterns in keywords used by learners and visualize the word connections between them, based on their co-occurrence, within our entire data set, by reaction type, and by levels of explanation sophistication. Our results indicate that learners consistently rely on explicit surface-level features in their explanations with expected contextual variance by reaction type. This trend persists across the levels of sophistication, however, with improvements in the use of vocabulary and coherency as sophistication progresses. We hypothesize that this is evidence of learners actively working toward constructing understanding as they experiment with and refine their vocabulary until they are able to pare down their explanations in a coherent manner. This work offers insights for instructors seeking to promote the development of learners’ reasoning skills and for researchers interested in the development of machine-learning models to assist in evaluating learner explanations of reaction mechanisms. 

The association between student motivation and learning, and changes in motivation across a course, were evaluated for students enrolled in one-semester foundation-level inorganic chemistry courses at multiple postsecondary institutions across the United States. The Academic Motivation Scale for Chemistry (AMS-Chemistry) and the Foundations of Inorganic Chemistry American Chemical Society Exam (i.e., a content knowledge measure) were used in this study. Evidence of validity, reliability, and longitudinal measurement invariance for data obtained from the AMS-Chemistry instrument with this population were found using methodologies appropriate for ordinal, non-parametric data. Positive and significant associations between intrinsic motivation measures and academic performance corroborate theoretical and empirical investigations; however, a lack of pre/post changes in motivation suggest that motivation may be less malleable in courses primarily populated by chemistry majors. Implications for inorganic chemistry instructors include paths for incorporating engaging pedagogies known to promote intrinsic motivation and methods for incorporating affect measures into assessment practices. Implications for researchers include a need for more work that disaggregates chemistry majors when evaluating relationships between affect and learning, and when making pre/post comparisons. Additionally, this work provides an example of how to implement more appropriate methods for treating data in studies using Likert-type responses and nested data. 

Active learning pedagogies are shown to enhance the outcomes of students, particularly in disciplines known for high attrition rates. Despite the demonstrated benefits of active learning, didactic lecture continues to predominate in science, technology, engineering, and mathematics (STEM) courses. Change agents and professional development programs have historically placed emphasis on develop–disseminate efforts for the adoption of research-based instructional strategies (RBIS). With numerous reported barriers and motivators for trying out and adopting active learning, it is unclear to what extent these factors are associated with adoption of RBIS and the effectiveness of change strategies. We present the results of a large-scale, survey-based study of introductory chemistry, mathematics, and physics instructors and their courses in the United States. Herein, we evaluate the association of 17 malleable factors with the tryout and adoption of RBIS. Multilevel logistic regression analyses suggest that several contextual, personal, and teacher thinking factors are associated with different stages of RBIS adoption. These results are also compared with analogous results evaluating the association of these factors with instructors’ time spent lecturing. We offer actionable implications for change agents to provide targeted professional development programming and for institutional leaders to influence the adoption of active learning pedagogies in introductory STEM courses. 

Course-based undergraduate research experiences (CUREs) are a promising approach for incorporating inquiry-based instruction into the under- graduate chemistry laboratory curriculum. This study used data from a national survey of inorganic chemistry faculty members (n = 142) to investigate CURE implementation in the inorganic chemistry instructional laboratory. Results indicate that faculty members who implement CUREs place greater emphasis on a distinct set of instructional goals when compared to faculty members who do not implement CUREs. CURE implementation was further associated with a range of instructional and departmental characteristics, including group-only student work, independent course development by faculty instructors, limited graduate TA support, and ACS certification of degree programs. Findings from this investigation point toward (1) a need for increased efforts focused on supporting CURE implementation, (2) productive avenues through which curriculum designers and communities of practice can provide this support, and (3) needed areas of research that will further inform these efforts. 

Instructors’ interactions can foster knowledge sharing around teaching and the use of research-based instructional strategies (RBIS). Coordinated teaching presents an impetus for instructors’ interactions and creates opportunities for instructional improvement but also potentially limits an instructor’s autonomy. In this study, we sought to characterize the extent of coordination present in introductory undergraduate courses and to understand how departments and instructors implement and experience course coordination. We examined survey data from 3,641 chemistry, mathematics, and physics instructors at three institution types and conducted follow-up interviews with a subset of 24 survey respondents to determine what types of coordination existed, what factors led to coordination, how coordination constrained instruction, and how instructors maintained autonomy within coordinated contexts. We classified three approaches to coordination at both the overall course and course component levels: independent (i.e., not coordinated), collaborative (decision-making by instructor and others), controlled (decision-making by others, not instructor). Two course components, content coverage and textbooks, were highly coordinated. These curricular components were often decided through formal or informal committees, but these decisions were seldom revisited. This limited the ability for instructors to participate in the decision-making process, the level of interactions between instructors, and the pedagogical growth that could have occurred through these conversations. Decision-making around the other two course components, instructional methods and exams, was more likely to be independently determined by the instructors, who valued this autonomy. Participants in the study identified various ways in which collaborative coordination of courses can promote but also inhibit pedagogical growth. Our findings indicate that the benefits of collaborative course coordination can be realized when departments develop coordinated approaches that value each instructor’s autonomy, incorporate shared and ongoing decision-making, and facilitate collaborative interactions and knowledge sharing among instructors. 

Six common beliefs about the usage of active learning in introductory STEM courses are investigated using survey data from 3769 instructors. Three beliefs focus on contextual factors: class size, classroom setup, and teaching evaluations; three focus on individual factors: security of employment, research activity, and prior exposure. The analysis indicates that instructors in all situations can and do employ active learning in their courses. However, with the exception of security of employment, trends in the data are consistent with beliefs about the impact of these factors on usage of active learning. We discuss implications of these results for institutional and departmental policies to facilitate the use of active learning.