become self-motivated learners who can make the bestuse of the resources that are available at the college and their transfer institution.STARSS ElementsExcept for the transfer scholarship, the amount of each scholarship is determined by the numberof courses that a student enrolls during the academic year. Awards are made in four tiers: • Tier 1: $4,000 for two consecutive semesters enrolled in two transfer level STEM courses each semester during one academic year. • Tier 2: $5,000 for two consecutive semesters enrolled in three transfer level STEM courses in one semester and two during the other semester of one academic year. • Tier 3: $6,000 for two consecutive semesters enrolled in three transfer level STEM courses
inpre-engineering do not complete their degree2,3. To improve engineering learning effectiveness, alaboratory experience is highly beneficial; it reinforces the material comprehension,complements the theory, and provides an active, interactive learning. However, issues such ashigh cost and high credit-hour engineering curricula have resulted in elimination of many of theengineering teaching laboratories, especially at the sophomore level. Our project goal was toimprove student success rate by providing them a set of virtual experiments that we develop toadequately simulate the physical laboratory.Guiding Principles in Developing the Virtual Laboratory: 1. The virtual laboratory modules must mimic reality and the learning experience in the
constituencies.Both of these general areas of activity represent works-in-progress. In the former we areinvestigating formulations of concepts and possible learning and assessment activities andcollecting data on their effectiveness. We identify three objectives of Hands-On instruction, 1) toapply instrumentation to make measurements of physical quantities, 2) to identify limitations ofmodels to predict of real-world behavior, and 3) to develop an experimental approach tocharacterize and explain the world. We have consulted with experts to develop a list of common Page 26.360.2misconceptions students display in laboratory instruction. A unique feature in
, Hispanic American, Native American Indian, Alaskan Native, Native Hawaiian, andNative Pacific Islander faculty. These inequities limit opportunities for individuals and hinder theinnovation and inclusivity of STEM fields.Such barriers are deeply rooted in structural inequities, including “epistemic exclusion”—themarginalization of scholarship and scholars that challenge disciplinary norms or focus on equityand inclusion [1], [2]. Hiring and evaluation processes often emphasize narrow productivitymetrics, such as publication counts, grant funding, and citation indices, which privilege dominantgroups and discourage bold, innovative research [3], [4]. These practices reinforce institutionalbiases and reduce opportunities for all scholars to thrive in
a model for ongoingtechnical support.IntroductionThe broader goals of this project have been to enhance program evaluation within and acrossNSF-funded ERCs (and other large, STEM-focused research centers) by: 1) expandingdissemination and providing validity testing of a collaborative evaluation survey, 2) developing acomplementary set of qualitative tools (e.g., interview, focus group, observation protocols, etc.),3) facilitating an evaluator’s toolbox to guide and support center evaluation leads, and 4)providing updated information to available resources (e.g., drafting new content for the NSFEngineering Research Centers’ Best Practice Manual). Over the duration of the grant, this workhas been completed while aligning with each of the four
, management, andpreservation. Proficiency in one or more of these areas in conjunction with domain knowledgewithin a core STEM discipline is rapidly becoming a key need for education and workforcedevelopment. To meet the need for STEM professionals with proficiency in data science, theNSF-sponsored DIFUSE project at Dartmouth has focused on integrating data science intoSTEM disciplines to enhance undergraduate student learning and preparation for the STEMworkforce. The interdisciplinary approach, described in [1], develops data science modules foruse in the classroom in introductory STEM and social science courses ranging from psychologyand environmental studies to astronomy and engineering; to date, we have developed anddisseminated over 20 such
financial, academic, and social barriers faced by low-income,academically talented students, the program emphasizes pathways into and through STEMdisciplines such as computer science, mathematics, and physics. The initiative is dedicated tosupporting underrepresented groups, including women, minorities, and first-generation collegestudents, with the goal of increasing retention, graduation rates, and career readiness. Thispartnership creates a comprehensive pipeline from MCC and TCC to CCSU, blending academicpreparation, social integration, and professional development into a holistic support system forstudent success [1, 2].Program Goals and ObjectivesThe CSMP program was developed to address critical challenges in STEM education,particularly for
institution’s College of Engineering.Background and MotivationMiddle and upper-level engineering courses are vital for students to master specializedknowledge and skills necessary for their chosen fields. Despite their importance, research onteaching methods in these courses has been limited [1]. These courses are recognized asparticularly challenging and require innovative teaching strategies to enhance student learning[2]. This project, funded by NSF (DUE2215989) addresses these gaps by exploring effectiveinstructional practices and fostering a sustainable community of practice to disseminate thesemethods across engineering departments.The project’s motivation stems from the need to align instructional practices with student-centered teaching which
teachers must find ways to expose studentsto engineering in ways that are accessible and age-appropriate. In order to attract more studentsto engineering as a field of study and career path, it is important to offer outreach programs thatare both educational and inspirational. [1], [2], [5] The activity discussed in this paper introducesstudents to fundamental engineering concepts through the design, implementation andoptimization of a smart nightlight. The activity is designed to be customizable for students ingrades 4 through 12 and further tailored to the learning skills and available time of theparticipating groups. Furthermore, the activity emphasizes hands-on learning while integratingengineering principles such as the engineering design
interactions among group members. IntroductionEngineering education strives to transform the field of engineering by integrating research andpractice. These efforts often involve groups of individuals from fields such as engineering,engineering education, sociology, and psychology and from different roles within a university(e.g., faculty, administration, student support staff) [1], [2], [3]. Each of these group membersbring their own approaches to the generation, expression, and application of knowledge. Thesedifferences in thinking are key to the success of engineering education; however, they can createtensions that prevent many groups from achieving their core goals. These tensions are oftenassociated
of covariance (ANCOVA) wasperformed to investigate the difference in students’ cognitive empathy between the two groups,with pre-test empathy scores as the covariate.Results Experimental group exhibited an average post-test score of 5.09 with a standard deviationof 1.23 with a noticeable improvement from their pre-test mean score of 4.60 with a standarddeviation of 1.18. The control group showed a lower post-test average of 4.26 with a standarddeviation of 1.38, while decreased from their pre-test average of 4.37 with a standard deviation of1.14. The ANCOVA result underscored the evidence of improved student empathy as the groupdifferences in post-test cognitive empathy scores were statistically significant, with an F(1, 40) =39.80, p
enough to meet the demand of firms competing in the globaleconomy19-25. All learning modules developed in these five years of work are available free to all USAengineering educational institutions on http://sites.google.com/site/finiteelementlearning/home.Initially, we developed FE learning modules in six engineering areas: (1) structural analysis, (2)mechanical vibrations, (3) computational fluid dynamics, (4) heat transfer, (5) electromagnetics,and (6) biometrics. To evaluate these "Proof of Concept" modules, they were integrated intoexisting courses in the corresponding subject areas. Faculty and students initially assessed theireffectiveness at three higher educational institutions. We included student demographic data,learning style
Page 26.11.2indicated that it was inappropriate to leave out one of the five most common disciplines, and thelatter because its enrollments and pathways are sufficiently interrelated with those of MechanicalEngineering students that studying some outcomes require the consideration of both disciplines.Major activitiesSince September 1, 2013, the project team has been productive working together well andmaking progress on all planned tasks from the proposal. We are publishing in other disciplinaryvenues as we build on our success in being recognized for the best paper in the IEEETransactions on Education in 20111 for the first of our disciplinary studies and with the BettyVetter Award for Research from the Women in Engineering ProActive Network
Department of Labor, the job outlook is on the rise and willcontinue to expand for at least the short- to medium-term future [1]. To respond to the industry Page 26.549.3needs for FPGA design skills, universities are updating their curriculum with courses inhardware description languages and programmable logic design. Although most traditionalelectrical and computer engineering programs have updated their curriculum to include topics inhardware description language and programmable logic design (FPGA/CPLD), only 19.5 % of 4-year and 16.5 % of 2-year electrical and computer engineering technology programs at USacademic institutions currently have a
from2011-2013, their results showed improvement in the students’ knowledge of the additivemanufacturing processes. In the 2012-2014 study, the Missouri University program evaluatedstudents with a survey before and after the program, along with weekly presentation evaluations.The Missouri study obtained qualitative data through interviews with the participants prior to andafter completion of the REU program. It was also stated that the program seemed to improveyear after year and succeeded in increasing the students’ awareness of additive manufacturing.10Research QuestionsThe research questions that we had in this study were: 1. Does the REU program contribute to increasing students’ understanding/perception of the systems medicine field
iterative implement-evaluate development cycles, it is expectedthat faculty will emergently adopt RBIS that meet their course design goals and objectives suchas increased student learning, motivation, and retention.The purpose of this paper is to (1) describe our initial experiences with creating the CoPs andwith attempting to change the teaching culture to be one of collaborative joint ownership withinCoPs, (2) describe the groups of instructors who are successfully forming CoPs and discuss thecharacteristics of effective and ineffective CoPs, based on observation data, and (3) describe thedifferent RBIS that have been implemented, and the fidelity and success of implementation thus
spaceconsisting of five categories of description of students’ ways of experiencing their transitionfrom pre-college engineering programs and activities to a first-year engineering classroom.These results, described in the following section, provide a theoretical framework that is Page 26.1141.2currently guiding the development of a quantitative instrument to understand students’transitions to first-year engineering on a larger scale across multiple institutions.Qualitative ResultsFigure 1 shows the outcome space illustrating the relationships between the five ways ofexperiencing the transition from pre-college to first-year engineering. In order of
. in Bioengineering and Ph.D. in Engineer- ing and Science Education from Clemson University. c American Society for Engineering Education, 2016 CAREER: Informing Instructional Practice through the Study of Students’ Future Time Perspectives Lisa Benson1, Catherine McGough1, Justine Chasmar1 and Adam Kirn2 1 Department of Engineering and Science Education, Clemson University 2 Colleges of Engineering and Education, University of Nevada - RenoAbstractThis research seeks to help educators understand factors that contribute to engineering students’motivation and the relationship between those factors and their problem
identify three objectives of Hands-Oninstruction, 1) to apply instrumentation to make measurements of physical quantities, 2)to identify limitations of models to predict of real-world behavior, and 3) to develop anexperimental approach to characterize and explain the world. We have consulted withexperts to develop a list of common misconceptions students display in laboratoryinstruction. A unique feature in testing Hands-On concepts is that laboratory skills areinextricably tied to analytical concepts and therefore both analytical and hands-onconcepts have to be tested in order to distinguish the root cause of themisunderstanding. Based on these common misconceptions, test questions are beingdeveloped and data are being collected on their
or leaveengineering altogether before they have taken even one engineering course. Students with fewerhigh school educational opportunities, such as students of color, disabled students, or lowsocioeconomic status students, in particular, are thwarted by the calculus sequence 1. Many aredoomed before they even begin, since the timing of engineering courses assumes that all studentsare entering college “calculus ready”.Given the barriers that the calculus sequence poses to engineering retention, we must criticallyexamine the rationale of faculty for requiring the calculus sequence. Why do engineering facultyrequire these courses? What do engineering faculty hope that their students will gain from thecalculus sequence? During the authors
make-up of pulse-waves (relative to Fourier analysis), and demonstrate knowledge of the effects of transmission line filtering and pulse distortion. k. Use engineering applications software for electrical/electronics network and systems analysis and simulation.Figure 1 shows ratings for each of these competencies. The numbers indicate the percentage ofindustry participants who indicated that the competency is either important or very important forpersonnel who maintain automated manufacturing systems to have. Competencies: Electrical and Electronic Components and Systems j. Use spectral analysis techniques to determine the make
took four years to grow to its full size. We have recently submitted a new S-STEM proposal that, if funded, will initiate a design and development project that will include quantitative and qualitative assessment of the achievement of the programs ultimate goals, which include shifting the demographics of graduates at our institution and observing continued employment of CS/M Scholars in their field.1 Program Description1.1 RecruitmentWith the aid of staff in the Office of Admissions, we invite high-achievingfemale applicants with leadership potential to submit a short application. Indeciding whom to invite, we consider several broad measures of academic andpersonal achievement and don’t require that applicants
conflict resolution, and (ii) reflected on ways inwhich their teams are already successfully fostering a psychologically safe environment.To support an environment in which individuals could more freely share stories and experiencesof their own RED teams, during this group workshop, individuals were placed in small workinggroups composed of members from different RED teams. The workshop was divided into 4activities: 1. Individuals completed a vetted seven-question, seven category Likert survey (Edmondson, 1999) to quantify current levels of participants’ experiences of psychological safety on their teams; 2. Small groups participated in reflective and role-playing activities to practice speaking and interacting in ways that
guidelines.This rubric, detailed in the appendix and earlier papers [1], is a work in progress, addressingsystemic issues that have persisted for centuries.The importance of such collaborations is echoed in recent National Academies reports. The 2019report Minority Serving Institutions: America’s Underutilized Resource for Strengthening theSTEM Workforce [2] highlights MSIs' critical role in diversifying the STEM workforce. The2023 report Advancing Antiracism, Diversity, Equity, and Inclusion in STEMM Organizations:Beyond Broadening Participation [3] underscores the need for sustainable partnerships betweenMSIs and PWIs, recommending PWIs draw inspiration from MSIs’ culturally responsivepractices. A January 2024 dissemination event by the National
currently a doctoral student at Wright State University in the School of Professional Psychology.Ansley Lynn Shamblin, West Virginia University Ansley Lynn Shamblin is an undergraduate student in Sociology at West Virginia University. She participated in the Research Apprenticeship Program (RAP) at West Virginia University. ©American Society for Engineering Education, 2025 Progress of an NSF BCSER Grant: Effective Strategies to Recruit Underserved Students to Engineering Bridge and Success ProgramsAbstractThis project is funded by the National Science Foundation EDU Core Research: BuildingCapacity in STEM Education Research (ECR: BCSER) program. The BCSER grant is twofold:(1) to build the
either a two-day intensive training, or could bebroken up into two weeks of six smaller training sessions (modules). Each module willconsist of 1) presentation materials mapping learning objectives and the relatededucational theories, 2) peer mentor created case scenario videos, and 3) an activelearning activity that practices theories and case study topics from the module.This short format is intended to be delivered at the beginning of each course semester,when students have returned to campus, in time for certification of new peer mentors, oras a refresher for returning peer mentors to be prepared to serve in the first-yearmakerspace classroom the same semester.Results and ReflectionsThe results of the portion of the research project
the mountains “join” up). After mapping out the mountain, we can then lookto see if, for example, trees on different mountains have any systematic differences, such as theirgenus, average height, longevity, etc. The analogy of studying the location of trees on themountain is represented schematically in Figure 1 as a companion to the illustrative exampledescribed in this paragraph.Figure 1: Schematic representation of the illustrative example of use Topological Data Analysis. Here elevation profiles of mountains are examine to understand the different tree populations found in different elevation zones.In this same way, we use the Mapper algorithm to search the quantitative student response datafor patterns in the
Circuit Tutor system hasnow been used by over 2300 students in 54 class sections at eight different colleges anduniversities, with generally very favorable ratings.1. IntroductionLinear circuit analysis is a foundational topic for electrical engineering students and frequentlycomprises the exposure to electrical topics for non-electrical engineers. Optimizing studentsuccess in this course is therefore of critical importance. The development of a computer-basedtutoring system based on the idea of step-based tutoring has therefore been undertaken, whereeach individual step in a student’s work on a problem is accepted and evaluated for correctnessbefore they proceed to the next step of the solution. Such a system requires the creation ofspecial
National Science Foundation (NSF) funded grants: Designing Teaching: Scaling up the SIMPLE Design Framework for Interactive Teaching Development and a research initiation grant: Student-directed differ- entiated learning in college-level engineering education. Her research centers on facilitating and studying her role in faculty development self-study collaboratives. c American Society for Engineering Education, 2016 SIMPLE Design Framework for Teaching Development Across STEMIntroductionExtensive research has shown the benefits of interactive teaching for student learning andretention 1. However, significant barriers exist to broadening the use of interactivetechniques in college classrooms, particularly
contextualizationThe four courses were contextualized in a hypothetical remodeling project of a small, singlefamily residence. This scenario was chosen because it is familiar to students, it is a realisticapplication of class principles, and it lends itself well to integrating material from differentcourses. An overview of the house is shown in Figure 1. Students analyzed two houseremodeling improvements in this project: installation of an air conditioning (AC) unit on theroof, and removal of an exterior wall to open up access to the yard. These two tasks are shown inFigure 2. In what follows, a chronological account is given of the exercises in the class related tothe project.Figure 1: Single family residence used in the remodeling project. Architectural