Collaborative Two-Stage Exams Benefit Students in a Biology Laboratory Course

Collaborative two-stage exams provide an effective mechanism to incorporate group work into summative course assessments. We implemented these exams in an upper-level biology laboratory course over two terms, one with online exams and one with in-person exams. We compared student exam performance and perceptions of two-stage exams and group work across terms and demographic groups. Quantitative analyses revealed that across three exams per term, students in groups outperformed students who took the exams individually, and on average the group exam benefited all students, in particular students from groups recognized as persons historically excluded from science because of their ethnicity or race (PEERs). Student responses to both closed and open-ended questions indicated overall positive perceptions of both two-stage exams and group work. We found no significant differences in student perceptions based on PEER student status, gender, or the number of exams helped by group exams, but we found differences related to term and group exam approaches. These findings build upon the literature supporting student learning and perceptions from two-stage exams and provide novel insights for a role of group work in decreasing inequities in course assessments

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

“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 under- predicted 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

A framework for educating and empowering students by teaching about history and consequences of bias in STEM

Racism and bias are pervasive in society-and science, technology, engineering, and mathematics (STEM) fields are not immune to these issues. It is imperative that we educate ourselves and our students about the history and consequences of this bias in STEM, investigate the research showing bias toward marginalized groups, understand how to interpret misuses of science in perpetuating bias, and identify advances and solutions to overcome racism and bias throughout our professional and personal lives. Here, we present one model for teaching a universal course for participants of all professional stages to address these issues and initiate solutions. As very few institutions require students to enroll in courses on racism and bias in STEM or even offer such courses, our curriculum could be used as a blueprint for implementation across institutions. Ultimately, institutions and academic disciplines can incorporate this important material with more region and/or discipline specific studies of bias

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

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.Supplementary informationThe online version contains supplementary material available at 10.1186/s40594-021-00306-y

“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 under- predicted 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

What Questions Are on the Minds of STEM Undergraduate Students and How Can They Be Addressed?

Addressing common student questions in introductory STEM courses early in the term is one way that instructors can ensure that their students have all been presented with information about how to succeed in their courses. However, categorizing student questions and identifying evidence-based resources to address student questions takes time, and instructors may not be able to easily collect and respond to student questions at the beginning of every course. To help faculty effectively anticipate and respond to student questions, we 1) administered surveys in multiple STEM courses to identify common student questions, 2) conducted a qualitative analysis to determine categories of student questions (e.g., what are best practices for studying, how can in- and out-of- course time be effectively used), and 3) collaboratively identified advice on how course instructors can answer these questions. Here, we share tips, evidence-based strategies, and resources from faculty that instructors can use to develop their own responses for students. We hope that educators can use these common student questions as a starting point to proactively address questions throughout the course and that the compiled resources will allow instructors to easily find materials that can be considered for their own courses