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Over the past year we continued, under support from the NSF Division of Undergraduate Education, to emphasize implementation of Low-Cost Desktop Learning Modules LCDLMs for fluid mechanics, heat transfer and biomedical applications. Here we present implementation data from concept tests and surveys, details on new designs and insights gained. Through these activities our team progressed beyond original expectations that were outlined in our original set of NSF-sponsored objectives. We analyzed data from several institutions added from the south central and mid-eastern portions of the US through a combined University of ***-L** and -P** training hub conducted in a virtual mode held in September 2020 with regional communications spearheaded by respective faculty from these institutions. Much of the data analyzed results from support through a 2020 NSF supplement where we engaged in a study to compare direct hands-on implementations of LCDLMs to virtual synchronous and asynchronous implementations augmented with short conceptual videos, a tact necessary because of COVID-19 in-person restrictions. Surprisingly, both in-person and virtual modes show similar conceptual gains. A publication is being developed with intent for submission to the International Journal of Engineering Education where we compare the virtual and in-person modes of instruction. We added a few moremore »institutions through a northeastern training hub held in August 2021 with faculty from the University of *** managing regional communications; again, this hub was held virtually given uncertainty about the lifting of COVID-19 related restrictions. Regarding new LCDLMs we added a shell and tube heat exchanger and fabricated a large number for distribution and implementation and began analyzing conceptual gains and survey results. We prototyped a new evaporative cooler and continue to develop new broader impact units to demonstrate stenosis in an artery and blood cell separations and began implementing them in the classroom. Regarding LCDLM publications a paper was published in Chemical Engineering Education on a study where we compare heat transfer data for the miniature double pipe heat exchanger to predictions based on correlations for industrial scale heat exchangers and included classroom assessment data.« less

Although there is extensive literature documenting hands-on learning experiences in engineering classrooms, there is a lack of consensus regarding how student learning during these activities compares to learning during online video demonstrations. Further, little work has been done to directly compare student learning for similarly-designed hands-on learning experiences focused on different engineering subjects. As the use of hands-on activities in engineering continues to grow, understanding how to optimize student learning during these activities is critical. To address this, we collected conceptual assessment data from 763 students at 15 four-year institutions. Students completed activities with one of two highly visual low-cost desktop learning modules (LCDLMs), one focused on fluid mechanics and the other on heat transfer principles, using two different implementation formats: either hands-on or video demonstration. Conceptual assessment results showed that assessment scores significantly increased after all LCDLM activities and that gains were statistically similar for hands-on and video demonstrations, suggesting both implementation formats support an impactful student learning experience. However, a significant difference was observed in effectiveness based on the type of LCDLM used. Score increases of 31.2% and 24% were recorded on our post-activity assessment for hands-on and virtual implementations of the fluid mechanics LCDLM compared to pre-activitymore »assessment scores, respectively, while significantly smaller 8.2% and 9.2% increases were observed for hands-on and virtual implementations of the heat transfer LCDLM. In this paper, we consider existing literature to ascertain the reasons for similar effectiveness of hands-on and video demonstrations and for the differing effectiveness of the fluid mechanics and heat transfer LCDLMs. We discuss the practical implications of our findings with respect to designing hands-on or video demonstration activities.« less

Our team has developed Low-Cost Desktop Learning Modules (LCDLMS) as tools to study transport phenomena aimed at providing hands-on learning experiences. With an implementation design embedded in the community of inquiry framework, we disseminate units to professors across the country and train them on how to facilitate teacher presence in the classroom with the LC-DLMs. Professors are briefed on how create a homogenous learning environment for students based on best-practices using the LC-DLMs. By collecting student cognitive gain data using pre/posttests before and after students encounter the LC-DLMs, we aim to isolate the variable of the professor on the implementation with LC-DLMs. Because of the onset of COVID-19, we have modalities for both hands-on and virtual implementation data. An ANOVA whereby modality was grouped and professor effect was the independent variable had significance on the score difference in pre/posttest scores (p<0.0001) and on posttest score only (p=0.0004). When we divide out modality between hands-on and virtual, an ANOVA with an Ftest using modality as the independent variable and professor effect as the nesting variable also show significance on the score difference between pre and posttests (p-value=0.0236 for handson, and p-value=0.0004 for virtual) and on the posttest score only (p-value=0.0314 formore »hands-on, and p-value<0.0001 for virtual). These results indicate that in all modalities professor had an effect on student cognitive gains with respect to differences in pre/posttest score and posttest score only. Future will focus on qualitative analysis of features of classrooms yield high cognitive gains in undergraduate engineering students.« less

Hands-on experiments using the Low-Cost Desktop Learning Modules (LCDLMs) have been implemented in dozens of classrooms to supplement student learning of heat transfer and fluid mechanics concepts with students of varying prior knowledge. The prior knowledge of students who encounter these LCDLMs in the classroom may impact the degree to which students learn from these interactive pedagogies. This paper reports on the differences in student cognitive learning between groups with low and high prior knowledge of the concepts that are tested. Student conceptual test results for venturi, hydraulic loss, and double pipe heat exchanger LCDLMs are analyzed by grouping the student data into two bins based on pre-test score, one for students scoring below 50% and another for those scoring above and comparing the improvement from pretest to posttest between the two groups. The analysis includes data from all implementations of each LCDLM for the 2020-2021 school year. Results from each of the three LCDLMs were analyzed separately to compare student performance on different fluid mechanics or heat exchanger concepts. Then, the overall pre- and posttest scores for all three LCDLMs were analyzed to examine how this interactive pedagogy impacts cognitive gains. Results showed statistically significant differences in improvement betweenmore »low prior knowledge groups and high prior knowledge groups. Additional findings showed statistically significant results suggesting that the gaps in performance between low prior knowledge and high prior knowledge groups on pre-tests for the LCDLMs were decreased on the posttest. Findings showed that students with lower prior knowledge show a greater overall improvement in cognitive gains than those with higher prior knowledge on all three low-cost desktop learning modules.« less

Currently, substantial efforts are underway to improve the engagement and retention of engineering and computer science (E/CS) students in their academic programs. Student participation in specific activities known as High Impact Educational Practices (HIP) has been shown to improve student outcomes across a variety of degree fields. Thus, we suggest that understanding how and why E/CS students, especially those from historically underrepresented groups, participate in HIP is vital for supporting efforts aimed at improving E/CS student engagement and retention. The aim of the current study is to examine the participation of E/CS undergraduates enrolled at two western land-grant institutions (both institutions are predominantly white; one is an emerging Hispanic-serving institution) across five HIEP (i.e., global learning and study aboard internships, learning communities, service and community-based learning, and undergraduate research) that are offered outside of required E/CS curricula and are widely documented in the research literature. As part of a larger study, researchers developed an online questionnaire to explore student HIP participation and then surveyed E/CS students (n = 576) across both land-grant institutions. Subsequently, researchers will use survey results to inform the development of focus groups interview protocols. Focus group interviews will be conducted with purposefully selected E/CS students whomore »participated in the survey. Combined survey and focus group data will then be analyzed to more deeply understand why and how E/CS students participate in the HIP at their university. This research paper reports on the frequency distribution analysis of the survey data generated with E/CS undergraduates enrolled at one of the two land grant institutions. The combined sample included E/CS undergraduates from the following demographic groups: female (34 %), Asian (10 %), Black or African American (2%), Hispanic or Latinx (6%), Native American or Alaskan Native (1%), Native Hawaiian or Other Pacific Islander (1%), White (81 %), and multiracial (4 %). Results show that most (38%) E/CS students reported participating in internships, while study abroad programs garnered the smallest level of E/CS student participation (5%) across all five HIP. Internships were found most likely to engage diverse students: Female (42%), Hispanic or Latinx (24%), Multiracial (44%), Asian (31%), First-generation (29%), and nontraditional students—other than those categorized as highly nontraditional—all reported participating in internships more than any other HIP. Notable differences in participation across E/CS and demographic groups were found for other HIPs. Results further revealed that 43% of respondents did not participate in any extracurricular HIP and only 19% participated in two or more HIP. Insights derived from the survey and used to inform ongoing quantitative and qualitative analyses are discussed. Keywords: community-based learning, high impact educational practices, HIP, internships learning communities, service learning, study aboard, undergraduate research« less

Despite efforts to attract and retain more students in engineering and computer science — particularly women and students from underrepresented groups — diversity within these educational programs and the technical workforce remains stubbornly low. Research shows that undergraduate retention, persistence, and success in college is affected by several factors, including sense of belonging, task value, positive student-faculty interactions, school connectedness, and student engagement [1], [2]. Kuh [1] found that improvement in persistence, performance, and graduation for students in college were correlated to students’ level of participation in particular activities known as high impact educational practices (HIEP). HIEP include, among others, culminating experiences, learning communities, service learning, study abroad, and undergraduate research; Kuh [1] concluded that these activities may be effective at promoting overall student success. Kuh [1] and others [3] further hypothesized that participation in HIEP may especially benefit students from non-majority groups. Whether and how engineering and computer science students benefit from participating in HIEP and whether students from non-majority groups have access to HIEP activities, however, remain as questions to investigate. In this project, we examine engineering and computer science student participation in HIEP at two public land grant institutions. In this study, we seek to understand howmore »and why students participate in HIEP and how participation affects their persistence and success in engineering and computer science majors. Set within the rural, public land grant university context, this study conceptualizes diversity in a broad sense and includes women, members of underrepresented racial and ethnic groups, first generation college students, adult learners, and nontraditional student as groups contributing to the diversity of academic programs and the technical workforce.« less

Providing students with authentic software development experiences is essential to preparing them for careers in industry. To that end, many undergraduate courses include a team-based software development experience in which each team works on a different software project. This raises significant challenges for assessing student work and measuring the impact of pedagogical interventions: What do we measure and how, when each team is working on a different project? To address this question, we present a collection of metrics developed using the Goal-Question-Metric framework from the empirical software engineering literature, and an empirical study in which we applied those metrics to assess 23 team software projects involving 94 students at three institutions. Study results suggest that these metrics, which gauge commit, issue, and overall product quality, are sensitive to differences in the quality of teams' processes and products. This work contributes a new metric-based approach to evaluating key aspects of software development processes and products in a wide variety of computing courses.

A large portion of the cost of any software lies in the time spent by developers in understanding a program’s source code before any changes can be undertaken. Measuring program comprehension is not a trivial task. In fact, different studies use self-reported and various psycho-physiological measures as proxies. In this research, we propose a methodology using functional Near Infrared Spectroscopy (fNIRS) and eye tracking devices as an objective measure of program comprehension that allows researchers to conduct studies in environments close to real world settings, at identifier level of granularity. We validate our methodology and apply it to study the impact of lexical, structural, and readability issues on developers’ cognitive load during bug localization tasks. Our study involves 25 undergraduate and graduate students and 21 metrics. Results show that the existence of lexical inconsistencies in the source code significantly increases the cognitive load experienced by participants not only on identifiers involved in the inconsistencies but also throughout the entire code snippet. We did not find statistical evidence that structural inconsistencies increase the average cognitive load that participants experience, however, both types of inconsistencies result in lower performance in terms of time and success rate. Finally, we observe that self-reported taskmore »difficulty, cognitive load, and fixation duration do not correlate and appear to be measuring different aspects of task difficulty.« less

It has been well documented that a large portion of the cost of any software lies in the time spent by developers in understanding a program’s source code before any changes can be undertaken. One of the main contributors to software comprehension, by subsequent developers or by the authors themselves, has to do with the quality of the lexicon, (i.e., the identifiers and comments) that is used by developers to embed domain concepts and to communicate with their teammates. In fact, previous research shows that there is a positive correlation between the quality of identifiers and the quality of a software project. Results suggest that poor quality lexicon impairs program comprehension and consequently increases the effort that developers must spend to maintain the software. However, we do not yet know or have any empirical evidence, of the relationship between the quality of the lexicon and the cognitive load that developers experience when trying to understand a piece of software. Given the associated costs, there is a critical need to empirically characterize the impact of the quality of the lexicon on developers’ ability to comprehend a program. In this study, we explore the effect of poor source code lexicon and readabilitymore »on developers’ cognitive load as measured by a cutting-edge and minimally invasive functional brain imaging technique called functional Near Infrared Spectroscopy (fNIRS). Additionally, while developers perform software comprehension tasks, we map cognitive load data to source code identifiers using an eye tracking device. Our results show that the presence of linguistic antipatterns in source code significantly increases the developers’ cognitive load.« less