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1. Undergraduate Student Concerns in Introductory STEM Courses: What They Are, How They Change, and What Influences Them

   https://doi.org/10.1007/s41979-020-00031-1  

   Meaders, Clara L. ; Lane, A. Kelly ; Morozov, Anya I. ; Shuman, J. Kenny ; Toth, Emma S. ; Stains, Marilyne ; Stetzer, MacKenzie R. ; Vinson, Erin ; Couch, Brian A. ; Smith, Michelle K. ( April 2020 , Journal for STEM Education Research)

   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.
2. Investing in Instructors: Creating Intelligent Feedback Loops in Large Foundational Courses for Undergraduate Engineeringg

   Grohs, J.R. ; Knight, D.B. ; Soledad, M.M. ; Case, S.W. ; Murzi, H.G. ; Smith, N. ( June 2018 , ASEE Annual Conference proceedings)

   The drive to encourage young people to pursue degrees and careers in engineering has led to an increase in student populations in engineering programs. For some institutions, such as large public research institutions, this has led to large class sizes for courses that are commonly taken across multiple programs. While this decision is reasonable from an operational and resource management perspective, research on large classes have shown that students suffer decreased engagement, motivation and achievement. Instructors, on the other hand, report having difficulty establishing rapport with their students and a growing inability to monitor students’ learning gains and provide quality individualized feedback. To address these issues, our project draws from Lattuca and Stark’s Academic Plan model, which incorporates a thorough consideration of factors influencing curricular activities that can be applied at the course, program, and institutional levels, and assumes that instructors are key actors in curriculum development and revision. We aim to revitalize feedback loops to help instructors and departments continuously improve. Recognizing that we must understand both individual and systems level perspectives, we prioritize regular engagement between faculty and institutional support structures to collaboratively identify problems and systematically establish continuous improvement. In the first phase of this NSF IUSEmore »Institutional Transformation project, we focus on specifically prompting and studying the experiences of 8 instructors of foundational engineering courses usually taught in large class sizes across 4 different departments at a large public research institution. We collected qualitative data (semi-structured interviews, reflective journals, course-related documents) and quantitative data (student surveys and institution-provided transcript data) to answer research questions (e.g., what data do faculty teaching large foundational undergraduate engineering courses identify as being useful so that they may enhance students’ experiences and outcomes within the classes that they teach and across students’ multiple large classes?) at the intersection of learning analytics and faculty change. The data was used as a baseline to further refine data collection protocols, identify data that faculty consider meaningful and useful for managing large foundational engineering courses, and consider ways of productively leveraging institutional data to improve the learning experience in these courses. Data collection for the first phase is ongoing and will continue through the Spring 2018 semester. Findings for this paper will include high-level insights from Fall interviews with instructors as well as data visualizations created from the population-level data characterizing student performance in the foundational courses within the context of pre-college characteristics (e.g., SAT scores) and/or other academic outcomes (e.g., major switching within or out of engineer, degree attainment).« less
3. Impacts Resulting from a Large-Scale First-Year Engineering and Computer Science Program on Students’ Successful Persistence Toward Degree Completion

   Ragusa, Gisele ; Allen, Emily L. ; Menezes, Gustavo B. ( June 2020 , ASEE Annual Conference Proceedings 2020)

   There is a critical need for more students with engineering and computer science majors to enter into, persist in, and graduate from four-year postsecondary institutions. Increasing the diversity of the workforce by inclusive practices in engineering and science is also a profound identified need. According to national statistics, the largest groups of underrepresented minority students in engineering and science attend U.S. public higher education institutions. Most often, a large proportion of these students come to colleges and universities with unique challenges and needs, and are more likely to be first in their family to attend college. In response to these needs, engineering education researchers and practitioners have developed, implemented and assessed interventions to provide support and help students succeed in college, particularly in their first year. These interventions typically target relatively small cohorts of students and can be managed by a small number of faculty and staff. In this paper, we report on “work in progress” research in a large-scale, first-year engineering and computer science intervention program at a public, comprehensive university using multivariate comparative statistical approaches. Large-scale intervention programs are especially relevant to minority serving institutions that prepare growing numbers of students who are first in their family tomore »attend college and who are also under-resourced, financially. These students most often encounter academic difficulties and come to higher education with challenging experiences and backgrounds. Our studied first-year intervention program, first piloted in 2015, is now in its 5th year of implementation. Its intervention components include: (a) first-year block schedules, (b) project-based introductory engineering and computer science courses, (c) an introduction to mechanics course, which provides students with the foundation needed to succeed in a traditional physics sequence, and (d) peer-led supplemental instruction workshops for calculus, physics and chemistry courses. This intervention study responds to three research questions: (1) What role does the first-year intervention’s components play in students’ persistence in engineering and computer science majors across undergraduate program years? (2) What role do particular pedagogical and cocurricular support structures play in students’ successes? And (3) What role do various student socio-demographic and experiential factors play in the effectiveness of first-year interventions? To address these research questions and therefore determine the formative impact of the firstyear engineering and computer science program on which we are conducting research, we have collected diverse student data including grade point averages, concept inventory scores, and data from a multi-dimensional questionnaire that measures students’ use of support practices across their four to five years in their degree program, and diverse background information necessary to determine the impact of such factors on students’ persistence to degree. Background data includes students’ experiences prior to enrolling in college, their socio-demographic characteristics, and their college social capital throughout their higher education experience. For this research, we compared students who were enrolled in the first-year intervention program to those who were not enrolled in the first-year intervention. We have engaged in cross-sectional 2 data collection from students’ freshman through senior years and employed multivariate statistical analytical techniques on the collected student data. Results of these analyses were interesting and diverse. Generally, in terms of backgrounds, our research indicates that students’ parental education is positively related to their success in engineering and computer science across program years. Likewise, longitudinally (across program years), students’ college social capital predicted their academic success and persistence to degree. With regard to the study’s comparative research of the first-year intervention, our results indicate that students who were enrolled in the first-year intervention program as freshmen continued to use more support practices to assist them in academic success across their degree matriculation compared to students who were not in the first-year program. This suggests that the students continued to recognize the value of such supports as a consequence of having supports required as first-year students. In terms of students’ understanding of scientific or engineering-focused concepts, we found significant impact resulting from student support practices that were academically focused. We also found that enrolling in the first-year intervention was a significant predictor of the time that students spent preparing for classes and ultimately their grade point average, especially in STEM subjects across students’ years in college. In summary, we found that the studied first-year intervention program has longitudinal, positive impacts on students’ success as they navigate through their undergraduate experiences toward engineering and computer science degrees.« less
4. Exploring the Evolution of Engineering Students™ Feelings of Inclusion in Their College and the Broader Scientific Community

   Melissa Lynn Morris, University of ; Joseph Dygert, West Virginia ; Robin A.M Hensel, West Virginia ( July 2021 , 2021 ASEE Virtual Annual Conference Content Access, Virtual Conference)

   This complete research paper discusses how students’ feelings of inclusion change throughout their undergraduate career. Student responses acquired through focus groups and one-on-one interviews were examined to determine how included the students felt in their engineering college and also the broader scientific community. A small group of non-calculus ready engineering students enrolled in a large land grant institution in the Mid-Atlantic region consented to participate in the study. The student cohort participated in an NSF S-STEM funded program aimed at fostering a sense of inclusion in engineering by implementing a curriculum focused on cohort formation, career exploration, and professional development. The AcES, consisting of a weeklong pre-fall bridge experience, two common courses, and a variety of co-curricular activities, has been operating for eight years. Students who receive S-STEM funded scholarships participate in three focus groups and two one-on-one interviews each semester throughout their undergraduate studies. Student responses from the one-on-one interviews and focus groups conducted from 2017-2020 were examined with qualitative coding methods. Questions examined in this work include: 1) Did the engineering in history course help make you feel like you belong in engineering at WVU and that you are included in engineering at WVU?, 2) Do you feelmore »part of the group when working on projects in your engineering courses?, 3) Do you consider yourself a member of the scientific and engineering community here at WVU? Why or why not, and 4) Do you consider yourself a member of the broader scientific and engineering community? During the exploratory coding phase three codes were established to represent the degree of inclusion felt by students: Edge of Inclusion, Slight Inclusion, and Feelings of Inclusion. Edge of Inclusion was characterized by student responses such as “almost there but not totally”, “just starting to be”, and “no, well maybe a bit” while student responses such as “yes, but only a little” and “in some classes or situations” were recognized as Slight Inclusion. Examples of student responses such as “yes, I do feel part of it”, “absolutely, since I’ve…”, and “I would consider myself part of . . .” were classified with the code Feelings of Inclusion. Since the sample size was limited by scholarship funding, statistically significant results weren’t obtainable, but clear themes emerged that can be used to influence engineering curricula and serve as justification for an expanded study. Participating in an internship emerged as a major contributor to students feeling included in the broader scientific community. Interestingly, a decrease in the average degree of inclusion occurred after the students’ first semester, prior to increasing in later semesters. It is hypothesized that the emphasis on cohort formation, career exploration, and planned co-curricular activities during the first semester in the AcES program bolstered the initial feelings of inclusion. A student’s feeling of inclusion is known to be a contributing factor in retention. The findings of this research indicate that internships should not only be strongly encouraged, but university resources should be invested in helping students be prepared for, apply to, and obtain internships. The researchers suggest the study be expanded beyond the AcES program to examine a broader sample and greater number of students.« less
5. Results of an Intro to Mechanics Course Designed to Support Student Success in Physics I and Foundational Engineering Courses

   Menezes, Gustavo B. ; Nerenberg, Paul S. ; Li, Ni ; Allen, Emily L. ( June 2020 , ASEE Annual Conference Proceedings)

   This complete evidence-based practice paper discusses the strategies and results of an introduction to mechanics course, designed to prepare students for introductory-level physics and other fundamental courses in engineering, such as statics, strength of materials, and dynamics. The course was developed to address historically high failure (DFW) rates in the physics courses and is part of a set of interventions implemented to support student success in a college of engineering and computer science. The course focuses on providing in-depth understanding of Newton’s Laws of motion, free-body diagrams, and linear and projectile motion. Because it focuses on a limited number of competencies, it is possible to spend more time on inquiry-based activities and in-class discussions. The course framework was designed considering the Ebbinghaus’ Forgetting Curve, to provide students with learning opportunities in 6-day cycles: (i) day 1: a pre-class learning activity (reading or video) and a quiz; (ii) day 2: in-class Kahoot low-stakes quiz with discussion, a short lecture with embedded time for problem-solving and discussion, and in-class activities (labs, group projects); (iii) day 4: homework due two days after the class; (iv) day 6: homework self-reflection (autopsy based on provided solutions) two days after homework is due. The assessment ofmore »course performance is based on the well-characterized force concept inventory (FCI) exam that is administered before the intro to mechanics course and both before and after the Physics I course; and on student performance (grades) in Physics and Statics courses. Results from the FCI pre-test show that students who took the introduction to mechanics course (treatment group) started the physics course with a much better understanding of force concepts than other students in the course. The FCI post-test shows better normalized gain for the treatment group, compared to other students, which is also aligned with student performance in the course. Additionally, student performance is significantly better in statics, with 25% DWF rate compared to 50% for the other students. In summary, the framework of the course, which focuses on providing students with in-depth understanding of force concepts, has led to better learning and performance in Physics I, but importantly it has also helped students achieve better performance in the Statics course, the first fundamental course in civil and mechanical engineering programs.« less