Objective

To date, there are no studies of COVID-19 cases and deaths in the Navajo Nation, US. The primary objective of this manuscript is to understand whether counties with a higher proportion of Navajo (Diné) population also had higher cases and deaths of COVID-19 and whether these dropped with vaccination.

Method

We undertook a cross-sectional analysis of county level data from March 16, 2020-May 11, 2021. Data were obtained from public repositories and the US Census for the Navajo Nation, including northeastern Arizona, southeastern Utah, and northwestern New Mexico. The primary outcome measure is the number of individuals with confirmed cases or deaths of COVID-19. A secondary outcome was COVID-19 vaccinations.

Results

The 11 counties in Navajo Nation have a wide variation in the percent Navajo population, the resources available (ICU beds and occupancy), and COVID-19 outcomes. Overall, there was a substantial increase in the number of cases from March 16 -July 16, 2020 (the height of the pandemic) with a doubling time of 10.12 days on Navajo Nation. The percent Navajo population was a strong predictor of COVID-19 cases and deaths per million population. COVID-19 vaccinations were inversely associated with COVID-19 cases and deaths in these counties.

Conclusions

The COVID-19 pandemic on the Navajo Nation is a story of resilience. Navajo Nation was one of the hardest hit areas of the United States, with peak cases and deaths due to COVID-19. With an aggressive vaccination effort, these cases and deaths were strikingly curtailed, showing the resilience of the Navajo (Diné) people.

Members of the Joint Working Group on Improving Underrepresented Minorities (URMs) Persistence in Science, Technology, Engineering, and Mathematics (STEM)-convened by the National Institute of General Medical Sciences and the Howard Hughes Medical Institute-review current data and propose deliberation about why the academic "pathways" leak more for URM than white or Asian STEM students. They suggest expanding to include a stronger focus on the institutional barriers that need to be removed and the types of interventions that "lift" students' interests, commitment, and ability to persist in STEM fields. Using Kurt Lewin's planned approach to change, the committee describes five recommendations to increase URM persistence in STEM at the undergraduate level. These recommendations capitalize on known successes, recognize the need for accountability, and are framed to facilitate greater progress in the future. The impact of these recommendations rests upon enacting the first recommendation: to track successes and failures at the institutional level and collect data that help explain the existing trends.

Instructor Talk-noncontent language used by instructors in classrooms-is a recently defined and promising variable for better understanding classroom dynamics. Having previously characterized the Instructor Talk framework within the context of a single course, we present here our results surrounding the applicability of the Instructor Talk framework to noncontent language used by instructors in novel course contexts. We analyzed Instructor Talk in eight additional biology courses in their entirety and in 61 biology courses using an emergent sampling strategy. We observed widespread use of Instructor Talk with variation in the amount and category type used. The vast majority of Instructor Talk could be characterized using the originally published Instructor Talk framework, suggesting the robustness of this framework. Additionally, a new form of Instructor Talk-Negatively Phrased Instructor Talk, language that may discourage students or distract from the learning process-was detected in these novel course contexts. Finally, the emergent sampling strategy described here may allow investigation of Instructor Talk in even larger numbers of courses across institutions and disciplines. Given its widespread use, potential influence on students in learning environments, and ability to be sampled, Instructor Talk may be a key variable to consider in future research on teaching and learning in higher education.

Active-learning pedagogies have been repeatedly demonstrated to produce superior learning gains with large effect sizes compared with lecture-based pedagogies. Shifting large numbers of college science, technology, engineering, and mathematics (STEM) faculty to include any active learning in their teaching may retain and more effectively educate far more students than having a few faculty completely transform their teaching, but the extent to which STEM faculty are changing their teaching methods is unclear. Here, we describe the development and application of the machine-learning-derived algorithm Decibel Analysis for Research in Teaching (DART), which can analyze thousands of hours of STEM course audio recordings quickly, with minimal costs, and without need for human observers. DART analyzes the volume and variance of classroom recordings to predict the quantity of time spent on single voice (e.g., lecture), multiple voice (e.g., pair discussion), and no voice (e.g., clicker question thinking) activities. Applying DART to 1,486 recordings of class sessions from 67 courses, a total of 1,720 h of audio, revealed varied patterns of lecture (single voice) and nonlecture activity (multiple and no voice) use. We also found that there was significantly more use of multiple and no voice strategies in courses for STEM majors compared with courses for non-STEM majors, indicating that DART can be used to compare teaching strategies in different types of courses. Therefore, DART has the potential to systematically inventory the presence of active learning with ∼90% accuracy across thousands of courses in diverse settings with minimal effort.

Many efforts to improve science teaching in higher education focus on a few faculty members at an institution at a time, with limited published evidence on attempts to engage faculty across entire departments. We created a long-term, department-wide collaborative professional development program, Biology Faculty Explorations in Scientific Teaching (Biology FEST). Across 3 years of Biology FEST, 89% of the department's faculty completed a weeklong scientific teaching institute, and 83% of eligible instructors participated in additional semester-long follow-up programs. A semester after institute completion, the majority of Biology FEST alumni reported adding active learning to their courses. These instructor self-reports were corroborated by audio analysis of classroom noise and surveys of students in biology courses on the frequency of active-learning techniques used in classes taught by Biology FEST alumni and nonalumni. Three years after Biology FEST launched, faculty participants overwhelmingly reported that their teaching was positively affected. Unexpectedly, most respondents also believed that they had improved relationships with departmental colleagues and felt a greater sense of belonging to the department. Overall, our results indicate that biology department-wide collaborative efforts to develop scientific teaching skills can indeed attract large numbers of faculty, spark widespread change in teaching practices, and improve departmental relations.