As the site of folding for proteins of the secretory pathway, the endoplasmic reticulum (ER) must be equipped with an efficient quality control machinery. Through ER associated degradation (ERAD) misfolded lumenal and membrane-bound proteins are tagged with poly-ubiquitin chains and degraded in a proteasome-dependent manner. ERAD is a multi-step process which is initiated by the identification of the misfolded protein. While lumenal substrates degraded by the ERAD-L pathway appear to be recognized by a number of factors, it is unknown how misfolded membrane proteins are identified by the ERAD-M pathway. As a rate-limiting factor for ERAD, and a specificity factor as a ubiquitin ligase, we tested whether Hrd1p plays a role in the identification of misfolded proteins. By mutating a number of conserved and hydrophobic residues within the Hrd1p transmembrane domain, we illustrated that Hrd1p can distinguish between misfolded lumenal and membrane proteins, and that specific residues were important for the degradation of specific membrane proteins. Thus, in addition to Hrd1p's role as a ubiquitin ligase, it appears that this protein plays a role in the recognition of misfolded membrane proteins as well. Our studies also demonstrated that substrate binding does not appear to be sufficient to initiate ubiquitination, and that some type of signal is required following binding in order to activate the RING domain of Hrd1p. Following substrate ubiquitination, the protein must be removed from the ER in a process known as retrotranslocation, as the proteasome is located in the cytoplasm. To study retrotranslocation, we established an in vitro retrotranslocation assay, which we demonstrated was capable of retrotranslocating a natural ERAD-M substrate, Hmg2p. Retrotranslocated Hmg2p was soluble and full-length, and the process was dependent on Cdc48. With this assay, we were able to test the current model of retrotranslocation, in order to determine the core set of proteins which are essential for this process. This uncovered a role for the factors Ubx2p and Rad23p/Dsk2p in retrotranslocation, while demonstrating that the putative retrotranslocons Sec61p, Der1p/Dfm1p, and Hrd1p are dispensible for Hmg2p retrotranslocation. These studies have greatly increased our understanding of HRD-dependent degradation

Student attrition from STEM disciplines is one of the most pressing issues in higher education. To better understand the causes of this attrition, this study examines STEM students’ college experiences and uncovers their perspectives on the existing support systems with a specific focus on the role of academic advising. Our research reveals that students from a particular STEM major identified academic advising as problematic, serving as one of the main factors pushing them out of the major, while the STEM major they transferred to did not have this issue. We examined whether this difference was also evident in the perspectives of the student affairs offices by interviewing academic counselors. This research emphasizes the responsibility of academic counselors in students’ decisions to leave STEM majors and the importance of care in their work. The findings suggest a need for STEM departments to re-assess academic advising philosophies and practices while creating more supportive learning environments.

Quantitative data analysis skills are basic competencies students in a STEM field should master. In this article, we describe a classroom activity using isolated figures from papers as a simple exercise to practice data analysis skills. We call this approach Just Figures. With this technique, instructors find figures from primary papers that address key concepts related to several of their course learning objectives. These figures are assigned as homework prior to class discussion. In class, instructors teach the lesson and include a 10- to 20-minute discussion of the figures assigned. Frequent and repeated discussion of paper figures during class increased students' confidence in reading and analyzing data. The Just Figures approach also increased student accuracy when interpreting data. After six weeks of Just Figures practice, students scored, on average, three points higher on a 20-point data analysis assessment instrument than they had done before the Just Figures exercises. In addition, a course in which students consistently practiced Just Figures performed just as well on the data analysis assessment instrument and on a class exam dedicated to paper reading compared with courses where students practiced reading three entire papers. The Just Figures method is easy to implement and can effectively improve student data analysis skills in microbiology classrooms.

Teaching faculty are a potential mechanism to generate positive change in undergraduate STEM education. One such type of faculty is the Lecturer with Potential Security of Employment (L(P)SOE), a tenure-track faculty line within the University of California (UC) system. As a foundation for future studies, we sought to characterize individuals in the L(P)SOE position in terms of their background training, job expectations, and resources available for their success. Data were collected through an online survey completed by over 80% of STEM L(P)SOEs across the UC system, as well as interviews with over 20 deans and chairs in STEM departments at three UC campuses. From this work, we found that the majority of current L(P)SOEs were formally trained within their disciplines and not in an education field; however, they possessed substantial education experience, such as classroom teaching or participation in professional development opportunities. Expectations for time spent on teaching, research, and service are aligned between individuals within varying ranks of the L(P)SOE faculty and between L(P)SOEs and administrators. L(P)SOEs and administrators are also in agreement about what constitutes acceptable professional development activities. Interestingly, we identified differences that may reflect changes in the position over time, including increased start-up funds for more recently hired L(P)SOE faculty and a differing perspective on the role of discipline-based education research and scholarly activities between non-tenured and more senior L(P)SOEs. Overall, these data provide a snapshot of the L(P)SOE position that will aid in future work to identify the potential institutional impact of these individuals.

Promoting student understanding of biological concepts is a key part of biology education, and the ability to “understand” a concept forms one of the six categories of the oft-used Bloom’s Taxonomy. Despite this, there remains no consensus as to what it means to understand a concept. While several formal definitions have been offered, we investigated how biology instructors and biology education researchers define the term and how they perceived the skill sets needed for a student to understand a concept in the context of assessments. We found that there was no agreement on the definition of understanding, and that responses differed in the cognitive level required to reach “understanding” of a concept. We discuss these findings in the context of Bloom’s Taxonomy and variation theory and provide directions for future inquiries. We conclude by discussing implications for biology instructors and the importance of explicitly conveying expectations to better align student and instructor expectations.

In an effort to improve and assess student learning, there has been a push to increase the incorporation of discovery-driven modules and those that contain real-world relevance into laboratory curricula. To further this effort, we have developed, implemented, and assessed an undergraduate microbiology laboratory experiment that requires students to use the scientific method while brewing beer. The experiment allows students to brew their own beer and characterize it based on taste, alcohol content, calorie content, pH, and standard reference method. In addition, we assessed whether students were capable of achieving the module learning objectives through a pre-/posttest, student self-evaluation, exam-embedded questions, and an associated worksheet. These objectives included describing the role of the brewing ingredients and predicting how altering the ingredients would affect the characteristics of the beer, amongst others. By completing this experimental module, students accomplished the module objectives, had greater interest in brewing, and were more likely to view beer in scientific terms. Journal of Microbiology & Biology Education.

Abstract: Background: An instructor’s conceptions of teaching and learning contribute to the establishment of learning environments that may benefit or hinder student learning. Previous studies have defined the continuum of teaching and learning conceptions, ranging from limited to complete, as well as the instructional practices that they help to inform (instructor-centered to student-centered), and the corresponding learning environments that these conceptions and practices establish, ranging from traditional to student-centered. Using the case of one STEM department at a research-intensive, minority serving institution, we explored faculty’s conceptions of teaching and learning and their resulting instructional practices, as well as uncovered their perspectives on the intradepartmental faculty interactions related to teaching. The study participants were drawn from both teaching-focused (called Professors of Teaching, PoTs) and traditional research (whom we call Research Professors, RPs) tenure-track faculty lines to identify whether differences existed amongst these two populations. We used interviews to explore faculty conceptions and analyzed syllabi to unveil how these conceptions shape instructional environments. Results: Overall, PoTs exhibited complete conceptions of teaching and learning that emphasized student ownership of learning, whereas RPs possessed intermediate conceptions that focused more on transmitting knowledge and helping students prepare for subsequent courses. While both PoTs and RPs self-reported the use of active learning pedagogies, RPs were more likely to also highlight the importance of traditional lecture. The syllabi analysis revealed that PoTs enacted more student-centered practices in their classrooms compared to RPs. PoTs appeared to be more intentionally available to support students outside of class and encouraged student collaboration, while RPs focused more on the timeliness of assessments and enforcing more instructor-centered approaches in their courses. Finally, the data indicated that RPs recognized PoTs as individuals who were influential on their own teaching conceptions and practices. Conclusions: Our findings suggest that departments should consider leveraging instructional experts who also possess a disciplinary background (PoTs) to improve their educational programs, both due to their student-centered impacts on the classroom environment and positive influence on their colleagues (RPs). This work also highlights the need for higher education institutions to offer appropriate professional development resources to enable faculty to reflect on their teaching and learning conceptions, aid in their pedagogical evolution, and guide the implementation of these conceptions into practice.

Teaching faculty are a potential mechanism to generate positive change in undergraduate STEM education. One such type of faculty is the Lecturer with Potential Security of Employment (L(P)SOE), a tenure-track faculty line within the University of California (UC) system. As a foundation for future studies, we sought to characterize individuals in the L(P)SOE position in terms of their background training, job expectations, and resources available for their success. Data were collected through an online survey completed by over 80% of STEM L(P)SOEs across the UC system, as well as interviews with over 20 deans and chairs in STEM departments at three UC campuses. From this work, we found that the majority of current L(P)SOEs were formally trained within their disciplines and not in an education field; however, they possessed substantial education experience, such as classroom teaching or participation in professional development opportunities. Expectations for time spent on teaching, research, and service are aligned between individuals within varying ranks of the L(P)SOE faculty and between L(P)SOEs and administrators. L(P)SOEs and administrators are also in agreement about what constitutes acceptable professional development activities. Interestingly, we identified differences that may reflect changes in the position over time, including increased start-up funds for more recently hired L(P)SOE faculty and a differing perspective on the role of discipline-based education research and scholarly activities between non-tenured and more senior L(P)SOEs. Overall, these data provide a snapshot of the L(P)SOE position that will aid in future work to identify the potential institutional impact of these individuals.

During the past few decades, there has been a nationwide push to improve performance and persistence outcomes for STEM undergraduates. As part of this effort, recent research has emphasized the need for focus on not only improving the delivery of course content, but also addressing the social-psychological needs of students. One promising intervention type that has been proposed as a multifaceted way to address both cognitive and social-psychological aspects of the learning process is the learning community. Learning communities provide students with opportunities to build a strong support system in college and are generally associated with increased student engagement and integration with campus systems and cultures. In this study, we examine the impact of a learning community intervention for first-year biological sciences majors, the Enhanced Academic Success Experience (EASE) program. Incoming freshmen are assigned to EASE based on their SAT (or ACT equivalent) Math score, a metric demonstrated to be a key predictor of student success in the program. We find that enrollment in EASE is correlated with higher STEM course grades; an increase of 0.25 (on a 0-4 point scale) in cumulative first-year GPA; and gains in non-academic outcomes, such as measures of sense of belonging and academic integration. Further, these outcomes are more pronounced for particular subgroup populations. For example, whereas surveyed male students seemed to benefit academically from participating in a learning community, female students reported a greater sense of belonging in regard to the biological sciences major and reported higher values for behavioral indicators of academic integration. Lastly, we find that the EASE program is positively correlated with students' intention to stay in the biological sciences major. And, among the three race-oriented groups, this impact is most pronounced for under-represented students. In light of these findings, we discuss the potential of discipline-specific learning community programs to improve academic outcomes for students most at risk of leaving STEM majors, such as students underprepared for college level coursework.

The Classroom Observation Protocol for Undergraduate STEM (COPUS) provides descriptive feedback to instructors by capturing student and instructor behaviors occurring in the classroom. Due to the increasing prevalence of COPUS data collection, it is important to recognize how researchers determine whether groups of courses or instructors have unique classroom characteristics. One approach uses cluster analysis, highlighted by a recently developed tool, the COPUS Analyzer, that enables the characterization of COPUS data into one of seven clusters representing three groups of instructional styles (didactic, interactive, and student centered). Here, we examine a novel 250 course data set and present evidence that a predictive cluster analysis tool may not be appropriate for analyzing COPUS data. We perform a de novo cluster analysis and compare results with the COPUS Analyzer output and identify several contrasting outcomes regarding course characterizations. Additionally, we present two ensemble clustering algorithms: 1) k-means and 2) partitioning around medoids. Both ensemble algorithms categorize our classroom observation data into one of two clusters: traditional lecture or active learning. Finally, we discuss implications of these findings for education research studies that leverage COPUS data.