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  1. Open Educational Resources (OER) are widely used instructional materials that are freely available and promote equitable access. OER research at the undergraduate level largely focuses on measuring student experiences with using the low cost resources, and instructor awareness of resources and perceived barriers to use. Little is known about how instructors work with materials based on their unique teaching context. To explore how instructors engage with OER, we surveyed users of CourseSource , an open-access, peer-reviewed journal that publishes lessons primarily for undergraduate biology courses. We asked questions aligned with the OER life cycle, which is a framework that includes the phases: Search , Evaluation , Adaptation , Use , and Share . The results show that OER users come from a variety of institution types and positions, generally have positions that focus more on teaching than research, and use scientific teaching practices. To determine how instructors engage throughout the OER life cycle, we examined the frequency of survey responses. Notable trends include that instructors search and evaluate OER based on alignment to course needs, quality of the materials, and ease of implementation. In addition, instructors frequently modify the published materials for their classroom context and use them in amore »variety of course environments. The results of this work can help developers design current and future OER repositories to better coincide with undergraduate instructor needs and aid content producers in creating materials that encourage implementation by their colleagues.« less
    Free, publicly-accessible full text available March 1, 2023
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  4. Abstract 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.more »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.

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  5. The construct of active learning permeates undergraduate education in science, technology, engineering, and mathematics (STEM), but despite its prevalence, the construct means different things to different people, groups, and STEM domains. To better understand active learning, we constructed this review through an innovative interdisciplinary collaboration involving research teams from psychology and discipline-based education research (DBER). Our collaboration examined active learning from two different perspectives (i.e., psychology and DBER) and surveyed the current landscape of undergraduate STEM instructional practices related to the modes of active learning and traditional lecture. On that basis, we concluded that active learning—which is commonly used to communicate an alternative to lecture and does serve a purpose in higher education classroom practice—is an umbrella term that is not particularly useful in advancing research on learning. To clarify, we synthesized a working definition of active learning that operates within an elaborative framework, which we call the construction-of-understanding ecosystem. A cornerstone of this framework is that undergraduate learners should be active agents during instruction and that the social construction of meaning plays an important role for many learners, above and beyond their individual cognitive construction of knowledge. Our proposed framework offers a coherent and actionable concept of active learningmore »with the aim of advancing future research and practice in undergraduate STEM education.« less
  6. 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.
  7. 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.
  8. Abstract

    Introductory STEM courses represent entry points into a major, and student experiences in these courses can affect both their persistence and success in STEM disciplines. Identifying course-based student concerns may help instructors detect negative perceptions, areas of struggle, and potential barriers to success. Using an open-response survey question, we identified 13 common concerns expressed by students in introductory STEM courses. We converted these student-generated concerns into closed-ended items that were administered at the beginning and middle of the semester to students in 22 introductory STEM course sections across three different institutions. Students were asked to reflect on each item on a scale from very concerned to not concerned. A subset of these concerns was used to create a summary score of course-based concern for each student. Overall levels of student concern decreased from the first week to the middle of the semester; however, this pattern varied across different demographic groups. In particular, when controlling for initial concern and course grades, female students held higher levels of concern than their peers. Since student perceptions can impact their experiences, addressing concerns through communication and instructional practices may improve students’ overall experiences and facilitate their success.

  9. Momsen, Jennifer L (Ed.)
    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 studentsmore »up for success.« less