A National Snapshot of Introductory Chemistry Instructors and Their Instructional Practices.

The effectiveness of active learning on promoting students' academic outcomes and persistence has been established in the literature. However, despite the effort of purposeful change agents, the uptake of active learning in science, technology, engineering, and mathematics (STEM) is slow. While previous research from the chemistry education community has provided insights into the implementation of specific active learning strategies across the United States, the extent to which chemistry instructors leverage these strategies in general remains unknown. This article presents the results of a national survey aimed at exploring introductory chemistry instructors' knowledge and implementation of active learning, variations on this knowledge, and use across tenure statuses and institution types. This paper also aims to address the gap in the literature in our understanding of the characteristics of instructors of these courses. We thus provide a description of instructors' demographics, training, teaching experience, and teaching responsibilities. Our findings reveal that instructors in these courses are prominently males of European descent. Additionally, instructors come into their teaching position with minimal pedagogical training and participate mainly in short training once in their position. While the majority of instructors have knowledge of specific active learning strategies, their consistent implementation remains limited, with lecturing still being the instructional practice of choice. Variations were found between institution types and across tenure statuses within institutions in terms of pedagogical training, use of specific active learning strategies, and proportion of class time spent lecturing. The findings provide a baseline for future studies that aim to assess the effectiveness of interventions fostering the implementation of active learning in introductory chemistry courses and highlight the critical need for improved communication about teaching practices across institutions and tenure statuses.

Innovative teaching knowledge stays with users.

Programs seeking to transform undergraduate science, technology, engineering, and mathematics courses often strive for participating faculty to share their knowledge of innovative teaching practices with other faculty in their home departments. Here, we provide interview, survey, and social network analyses revealing that faculty who use innovative teaching practices preferentially talk to each other, suggesting that greater steps are needed for information about innovative practices to reach faculty more broadly.

Reflective Practices in Education: A Primer for Practitioners.

Reflective practices in education are widely advocated for and have become important components of professional reviews. The advantages of reflective practices are many; however, the literature often focuses on the benefits to students, rather than the benefits for the educators themselves. Additionally, the extant literature concerning reflective practices in education is laden with conflicting terminology and complex studies, which can inhibit educators' understanding of reflective practices and prevent their adoption. As such, this Essay serves as a primer for educators beginning reflective practices. It briefly describes the benefits to educators and different classifications and modalities of reflection and examines some of the challenges that educators may encounter.

Exploring the Complementarity of Measures of Instructional Practices.

The assessment of instructional quality has been and continues to be a desirable, yet difficult endeavor in higher education. The development of new teaching evaluation frameworks along with instruments to measure various aspects of teaching practices holds promise. The challenge rests in the implementation of these frameworks and measures in authentic settings. Part of this challenge is for instructors, researchers, and administrators to parse through and select a meaningful set of tools from the plethora of existing instruments. In this study, we aim to start clarifying the landscape of measures of instructional practice by exploring the complementarity of two existing instruments: the Classroom Observation Protocol for Undergraduate STEM (COPUS) and the Learner-Centered Teaching Rubrics (LCTR). We collected classroom observations and course artifacts from 28 science instructors from research-intensive institutions across the United States. Results show the need to use both instruments to capture nuanced and comprehensive description of a faculty member's instructional practice. This study highlights the messiness of measuring instructional quality and the need to explore the implementation of teaching evaluation frameworks and measures of instructional practices in authentic settings.

What really impacts the use of active learning in undergraduate STEM education? Results from a national survey of chemistry, mathematics, and physics 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.

Am I getting through? Surveying students on what messages they recall from the first day of STEM classes.

BACKGROUND: The 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. RESULTS: To 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. CONCLUSIONS: For 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40594-021-00306-y.

Making a First Impression: Exploring What Instructors Do and Say on the First Day of Introductory STEM Courses.

Student impressions formed during the first day of class can impact course satisfaction and performance. Despite its potential importance, little is known about how instructors format the first day of class. Here, we report on observations of the first day of class in 23 introductory science, technology, engineering, and math (STEM) courses. We first described how introductory STEM instructors structure their class time by characterizing topics covered on the first day through inductive coding of class videos. We found that all instructors discussed policies and basic information. However, a cluster analysis revealed two groups of instructors who differed primarily in their level of STEM content coverage. We then coded the videos with the noncontent Instructor Talk framework, which organizes the statements instructors make unrelated to disciplinary content into several categories and subcategories. Instructors generally focused on building the instructor-student relationship and establishing classroom culture. Qualitative analysis indicated that instructors varied in the specificity of their noncontent statements and may have sent mixed messages by making negatively phrased statements with seemingly positive intentions. These results uncovered variation in instructor actions on the first day of class and can help instructors more effectively plan this day by providing messages that set students up for success.

Classroom as Genome: Using the Tools of Genomics and Bioinformatics to Illuminate Classroom Observation Data.

Classroom observation protocols can provide an exceedingly rich form of data. However, this is a double-edged sword, as researchers often struggle to take full advantage of the detailed data outputs. In this essay, we introduce a new approach to the analysis of classroom observation data, termed "classroom as genome" (CAG). We illustrate how real-time classroom observation data and genomic data can be viewed as quite analogous, both conceptually and in terms of downstream analysis. We provide both abstract and concrete examples of how the tools of genomics and bioinformatics can be applied to classroom observation outputs. We also show how this philosophy of analysis allows for the layering of information from multiple observation protocols onto the same classroom data. The CAG approach enables biology education researchers to explore detailed patterns within observed classrooms in a highly scalable manner.

"What Will I Experience in My College STEM Courses?" An Investigation of Student Predictions about Instructional Practices in Introductory Courses.

The instructional practices used in introductory college courses often differ dramatically from those used in high school courses, and dissatisfaction with these practices is cited by students as a prominent reason for leaving science, technology, engineering, and mathematics (STEM) majors. To better characterize the transition to college course work, we investigated the extent to which incoming expectations of course activities differ based on student demographic characteristics, as well as how these expectations align with what students will experience. We surveyed more than 1500 undergraduate students in large introductory STEM courses at three research-intensive institutions during the first week of classes about their expectations regarding how class time would be spent in their courses. We found that first-generation and first-semester students predict less lecture than their peers and that class size had the largest effect on student predictions. We also collected classroom observation data from the courses and found that students generally underpredicted the amount of lecture observed in class. This misalignment between student predictions and experiences, especially for first-generation and first-semester college students and students enrolled in large- and medium-size classes, has implications for instructors and universities as they design curricula for introductory STEM courses with explicit retention goals.

Fidelity of Implementation: An Overlooked Yet Critical Construct to Establish Effectiveness of Evidence-Based Instructional Practices.

The discipline-based education research (DBER) community has been invested in the research and development of evidence-based instructional practices (EBIPs) for decades. Unfortunately, investigations of the impact of EBIPs on student outcomes typically do not characterize instructors' adherence to an EBIP, often assuming that implementation was as intended by developers. The validity of such findings is compromised, since positive or negative outcomes can be incorrectly attributed to an EBIP when other factors impacting implementation are often present. This methodological flaw can be overcome by developing measures to determine the fidelity of implementation (FOI) of an intervention, a construct extensively studied in other fields, such as healthcare. Unfortunately, few frameworks to measure FOI in educational settings exist, which likely contributes to a lack of FOI constructs in most impact studies of EBIPs in DBER. In this Essay, we leverage the FOI literature presented in other fields to propose an appropriate framework for FOI within the context of DBER. We describe how this framework enhances the validity of EBIP impact studies and provide methodological guidelines for how it should be integrated in such studies. Finally, we demonstrate the application of our framework to peer instruction, a commonly researched EBIP within the DBER community.

Research-based implementation of peer instruction: a literature review.

Current instructional reforms in undergraduate science, technology, engineering, and mathematics (STEM) courses have focused on enhancing adoption of evidence-based instructional practices among STEM faculty members. These practices have been empirically demonstrated to enhance student learning and attitudes. However, research indicates that instructors often adapt rather than adopt practices, unknowingly compromising their effectiveness. Thus, there is a need to raise awareness of the research-based implementation of these practices, develop fidelity of implementation protocols to understand adaptations being made, and ultimately characterize the true impact of reform efforts based on these practices. Peer instruction (PI) is an example of an evidence-based instructional practice that consists of asking students conceptual questions during class time and collecting their answers via clickers or response cards. Extensive research has been conducted by physics and biology education researchers to evaluate the effectiveness of this practice and to better understand the intricacies of its implementation. PI has also been investigated in other disciplines, such as chemistry and computer science. This article reviews and summarizes these various bodies of research and provides instructors and researchers with a research-based model for the effective implementation of PI. Limitations of current studies and recommendations for future empirical inquiries are also provided.

The best of both worlds: Building on the COPUS and RTOP observation protocols to easily and reliably measure various levels of reformed instructional practice.

Researchers, university administrators, and faculty members are increasingly interested in measuring and describing instructional practices provided in science, technology, engineering, and mathematics (STEM) courses at the college level. Specifically, there is keen interest in comparing instructional practices between courses, monitoring changes over time, and mapping observed practices to research-based teaching. While increasingly common observation protocols (Reformed Teaching Observation Protocol [RTOP] and Classroom Observation Protocol in Undergraduate STEM [COPUS]) at the postsecondary level help achieve some of these goals, they also suffer from weaknesses that limit their applicability. In this study, we leverage the strengths of these protocols to provide an easy method that enables the reliable and valid characterization of instructional practices. This method was developed empirically via a cluster analysis using observations of 269 individual class periods, corresponding to 73 different faculty members, 28 different research-intensive institutions, and various STEM disciplines. Ten clusters, called COPUS profiles, emerged from this analysis; they represent the most common types of instructional practices enacted in the classrooms observed for this study. RTOP scores were used to validate the alignment of the 10 COPUS profiles with reformed teaching. Herein, we present a detailed description of the cluster analysis method, the COPUS profiles, and the distribution of the COPUS profiles across various STEM courses at research-intensive universities.