An official website of the United States government
Abstract 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.
more »
« less
Exploring how course social and cultural environmental features influence student engagement in STEM active learning courses: a controlâvalue theory approach
Abstract BackgroundActive learning, on average, increases student performance in STEM courses. Yet, there is also large variation in the effectiveness of these implementations. A consistent goal of active learning is moving students towards becoming active constructors of their knowledge. This emphasis means student engagement is of central importance. Thus, variation in student engagement could help explain variation in outcomes from active learning. In this study, we employ Pekrunâs ControlâValue Theory to examine the impact of four aspects of course social and cultural environments on student engagement. This theory posits that social and cultural features of the course environment influence studentsâ appraisals of their ability to control their academic outcomes from the course and the value they see in those outcomes. Control and value in turn influence the emotions students experience in the course and their behaviors. We selected four features of the course environment suggested in the literature to be important in active learning courses: course goal structure, relevance of course content, studentsâ trust in their instructor, and perceived course competition. ResultsWe surveyed students in 13 introductory STEM courses. We used structural equation modeling to map how features of the course environment related to control, value, and academic emotions, as well as how control, value, and academic emotions influenced engagement. We found engagement was positively related to control and value as well as the emotion of curiosity. Engagement was negatively related to the emotion of boredom. Importantly, features of the course environment influenced these four variables. All features influenced control: goal structure, relevance, and instructor trust increased it, while competition decreased it. All features except competition were related positively to value. Relevance and instructor trust increased curiosity. Goal structure, relevance, and instructor trust all reduced boredom, while competition increased it. ConclusionOverall, our study suggests that the way instructors structure the social and cultural environment in active learning courses can impact engagement. Building positive instructorâstudent relationships, reducing course competition, emphasizing mastery and the relevance of the course to students can all increase engagement in course activities.
more »
« less
- PAR ID:
- 10567392
- Publisher / Repository:
- Springer Science + Business Media
- Date Published:
- Journal Name:
- International Journal of STEM Education
- Volume:
- 12
- Issue:
- 1
- ISSN:
- 2196-7822
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Abstract BackgroundA predictor of student success, sense of belonging (SB) is often inhibited for minoritized students in engineering environments and difficult to foster in online courses. A shift to remote learning formats necessitated by COVIDâ19, therefore, posed an additive threat to SB for engineering firstâyear students, especially those with minoritized identities. Research is needed to understand impacts of online learning to SB for engineering students. Purpose Hypothesis(es)The study examined factors that promoted or detracted from SB in engineering in remote courses and ways in which identity related to SB. Design MethodPart of a larger mixedâmethods study, this article examines focus group data from 31 firstâyear engineering students in 2020 to characterize student experiences in engineering courses moved online during COVIDâ19. ResultsIn addition to the mutually reinforcing nature of SB and learning, findings reveal that the major factors of (a) peer interactions, (b) instructor behavior and course design, (c) environmental identity cues, and (d) personal and psychological factors influenced SB. Examples of factors that positively contributed to SB in remoteâdelivery courses included platforms for open communication with peers, âliveâ ability to ask complex questions, and a critical mass of peers of similar identity; example factors hindering SB included limited use of cameras in synchronous classes, elitist peer interactions, instructor focus on academic performance (vs. growth), and feelings of selfâdoubt. ConclusionsBoth identity and COVIDâ19 impacted SB for students, with results showing four pathways to support SB and learning for diverse students in engineering across course formats.more » « less
-
A central goal of the Learning Assistant (LA) model is to improve studentsâ learning of science through the transformation of instructor practices. There is minimal existing research on the impact of college physics instructor experiences on their effectiveness. To investigate the association between college introductory physics instructorsâ experiences with and without LAs and student learning, we drew on data from the Learning About STEM Student Outcomes (LASSO) database. The LASSO database provided us with student-level data (concept inventory scores and demographic data) for 4,365 students and course-level data (instructor experience and course features) for the studentsâ 93 mechanics courses. We performed Hierarchical Multiple Imputation to impute missing data and Hierarchical Linear Modeling to nest students within courses when modeling the associations be- tween instructor experience and student learning. Our models predict that instructorsâ effectiveness decreases as they gain experience teaching without LAs. However, LA supported environments appear to remediate this decline in effectiveness as instructor effectiveness is maintained while they gain experience teaching with LAs.more » « less
-
Abstract Substantial gender equity gaps in postsecondary degree completion persist within many science, technology, engineering, and mathematics (STEM) disciplines, and these disparities have not narrowed during the 21st century. Various explanations of this phenomenon have been offered; one possibility that has received limited attention is that the sparse representation of women itself has adverse effects on the academic achievementâand ultimately the persistence and graduationâof women who take STEM courses. This study explored the relationship between two forms of gender representation (i.e., the proportion of female students within a course and the presence of a female instructor) and grades within a sample of 11,958 STEMâinterested undergraduates enrolled in 8686 different STEM courses at 20 colleges and universities. Female student representation within a course predicted greater academic achievement in STEM for all students, and these findings were generally stronger among female students than male students. Female students also consistently benefitted more than male students from having a female STEM instructor. These findings were largely similar across a range of student and course characteristics and were robust to different analytic approaches; a notable exception was that female student representation had particularly favorable outcomes for female students (relative to male students) within mathematics/statistics and computer science courses.more » « less
-
Recent work has shown that student trust in their instructor is a key moderator of STEM student buy-in to evidence-based teaching practices (EBTs), enhancing positive student outcomes such as performance, engagement, and persistence. Although trust in instructor has been previously operationalized in related settings, a systematic classification of how undergraduate STEM students perceive trustworthiness in their instructors remains to be developed. Moreover, previous operationalizations impose a structure that often includes distinct domains, such as cognitive and affective trust, that have yet to be empirically tested in the undergraduate STEM context. MethodsTo address this gap, we engage in a multi-step qualitative approach to unify existing definitions of trust from the literature and analyze structured interviews with 57 students enrolled in undergraduate STEM classes who were asked to describe a trusted instructor. Through thematic analysis, we propose that characteristics of a trustworthy instructor can be classified into three domains. We then assess the validity of the three-domain model both qualitatively and quantitatively. First, we examine student responses to determine how traits from different domains are mentioned together. Second, we use a process-model approach to instrument design that leverages our qualitative interview codebook to develop a survey that measures student trust. We performed an exploratory factor analysis on survey responses to quantitatively test the construct validity of our proposed three-domain trust model. Results and discussionWe identified 28 instructor traits that students perceived as trustworthy, categorized into cognitive, affective, and relational domains. Within student responses, we found that there was a high degree of interconnectedness between traits in the cognitive and relational domains. When we assessed the construct validity of the three-factor model using survey responses, we found that a three-factor model did not adequately capture the underlying latent structure. Our findings align with recent calls to both closely examine long-held assumptions of trust dimensionality and to develop context-specific trust measurements. The work presented here can inform the development of a reliable measure of student trust within undergraduate STEM student environments and ultimately improve our understanding of how instructors can best leverage the effectiveness of EBTs for positive student learning outcomes.more » « less
