ABSTRACT
This NSF-IUSE exploration and design project began in fall 2018 and features cross-disciplinary collaboration between engineering, math, and psychology faculty to develop learning activities with hands-on models and manipulatives. We are exploring how best to design these activities to support learners' development of conceptual understanding and representational competence in integral calculus and engineering statics, two foundational courses for most engineering majors. A second goal is to leverage the model-based activities to scaffold spatial skills development in the context of traditional course content. As widely reported in the literature, well-developed spatial abilities correlate with student success and persistence in many STEM majors. We provided calculus students in selected intervention sections taught by four instructors at three different community colleges with take-home model kits that they could reference for a series of asynchronous learning activities. Students in these sections completed the Purdue Spatial Visualization Test: Rotations (PSVT:R) in the first and last weeks of their course. We also administered the assessment in multiple control sections (no manipulatives) taught by the same faculty. This paper analyzes results from fall 2020 through fall 2021 to see if there is any difference between control and intervention sections for the courses as a whole and for demographic subgroups including female-identifying students and historically-underserved students of color. All courses were asynchronous online modality in the context of the COVID-19 pandemic. We find that students in intervention sections of calculus made slightly larger gains on the PSVT:R, but this result is not statistically significant as a whole or for any of the demographic subgroups considered. We also analyzed final course grades for differences between control and intervention sections and found no differences. We found no significant effect of the presence of the model-based activities leading to increased PSVT:R gains or improved course grades. We would not extend this conclusion to face-to-face implementation, however, due primarily to the compromises made to adapt the curriculum from in-person group learning to asynchronous individual work and inconsistent engagement of the online students with the modeling activities. © American Society for Engineering Education, 2022.
ABSTRACT
The coronavirus crisis disrupted business survivability. Measures, like going concern opinion and bankruptcy predictors, depend on past trends extending into the future. With black swan events, past trends do not extend into the future. We propose two new metrics. The "Going Concern Survivability Index" (GCSI) is the maximum percentage revenue loss that a business can endure as a going concern. The "One Month Resilience Index" (OMRI) is the effect on the net income from the loss of the revenue for its most successful month. While OMRI is straightforward, calculating GCSI requires real options and process mining. The emerging technology of process mining and artificial intelligence are needed to capture the dynamic process by which management will juggle cash flows, sources of funds, and payment of liabilities as revenue falls. This paper is an instance of action design science research, and we discuss the steps to put our artifact into practice.
ABSTRACT
OBJECTIVE: To report the clinical characteristics and transmission rate of coronavirus disease 2019 (COVID-19) in a community inpatient long-term care psychiatric rehabilitation facility designed for persons with serious mental illness to provide insight into transmission and symptom patterns and emerging testing protocols, as well as medical complications and prognosis. METHODS: This study examined a cohort of 54 residents of a long-term care psychiatric rehabilitation program from March to April 2020. Baseline demographics, clinical diagnoses, and vital signs were examined to look for statistical differences between positive versus negative severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) groups. During the early phase of the pandemic, the facility closely followed the local shelter-in-place order (starting March 19, 2020) and symptom-based testing. RESULTS: Of the residents, the primary psychiatric diagnoses were schizoaffective disorder: 28 (51.9%), schizophrenia: 21 (38.9%), bipolar I disorder: 3 (5.5%), and unspecified psychotic disorder: 2 (3.7%). Forty (74%) of 54 residents tested positive for SARS-COV-2, with a doubling time of 3.9 days. There were no statistical differences between the positive SARS-COV-2 versus negative groups for age or race/ethnicity. Psychiatric and medical conditions were not significantly associated with contracting SARS-COV-2, with the exception of obesity (n = 17 [43%] positive vs n = 12 [86%] negative, P = .01). Medical monitoring of vital signs and symptoms did not lead to earlier detection. All of the residents completely recovered, with the last resident no longer showing any symptoms 24 days from the index case. CONCLUSION: Research is needed to determine optimal strategies for long-term care mental health settings that incorporate frequent testing and personal protective equipment use to prevent rapid transmission of SARS-COV-2.