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 between 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.
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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 F- test 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 hands- on, and p-value=0.0004 for virtual) and on the posttest score only (p-value=0.0314 for 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.more » « less
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As this NSF LCDLM dissemination, development, and assessment project matures going into our fourth year of support we are moving forward in parallel on several fronts. We are developing and testing an injection-molded shell-and-tube heat exchanger for heat transfer concepts, an evaporative cooler to expand to another industrial-based heat exchange system, and a bead separation module to demonstrate principles of fluid mechanics in blood cell separations applications. We are also comparing experimental data for our miniaturized hydraulic loss and venturi meter LCDLMs to predicted values based on standard industrial correlations. As we develop these new learning components, we are assessing differential gains based on gender and ethnicity, as well as how students learn with existing LCDLMs in a virtual mode with online videos compared to an in-person hands-on mode of instruction.more » « less
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Abstract Aim Anthropogenic noise pollution (ANP) is a globally invasive phenomenon impacting natural systems, but most research has occurred at local scales with few species. We investigated continental‐scale breeding season associations with ANP for 322 bird species to test whether small‐scale predictions related to breeding habitat, migratory behaviour, body mass and vocal traits are consistent at broad spatial extents for an extensive group of species.
Location Conterminous USA.
Time period 2004–2011.
Major taxa studied North American breeding birds.
Methods We calculated, for each species, the association between the breeding season and ANP, using spatially explicit estimates of ANP from the National Park Service and weekly estimates of probabilities of occurrence based on observations from the eBird citizen‐science database. We evaluated how the association of the breeding season for each species with ANP was related to expectations based on size, migratory behaviour and breeding habitat. For a subset of species, we used vocal trait data for song duration, pitch and complexity to evaluate hypotheses from the birdsong literature related to habitat complexity and sensitivity to ANP.
Results Species that breed predominantly in anthropogenic environments were associated with twice the level of ANP (~7.4 dB) as species breeding in forested habitats (~3.2 dB). However, we did not find evidence to suggest that birds with higher‐pitched songs are more likely to be found in areas with higher levels of ANP. Residents and migratory species did not differ in associations with ANP, but songs were less complex among forest‐breeding species than non‐forest‐breeding species and increased in complexity with increasing ANP.
Main conclusions Anthropogenic noise pollution is an important factor associated with breeding distributions of bird species in North America. Vocal traits could be useful to understand factors that affect sensitivity to ANP and to predict the potential impact of ANP, although future studies should aim to understand how and why patterns differ across spatial scales.
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