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Formative Assessment as Learning: Establishing Key Performance indicators for Online Instruction
No full textA mixed methods data collection methodology was used.In an action research mixed-methods project, the authors designed doctoral-level online courses with the explicit intent of using student feedback to improve the curricula, and this study demonstrates that incorporating those assessments seemed to markedly improve enrollees' ratings of course-design elements and their mastery of the subject matter
Smart Materials and Soft Robotic; How They Mimic Nature
No full textThe observation method was used for the data collection methodology.Despite the traditional robots, soft robots do not have heavy and expensive parts such as motors, instead they are made of more advanced materials. The natural complexity of smart materials is exploited to provide delicate movements that we need in variety of applications. In this study, Ionic polymer-metal nanocomposite as an electro-active smart material is used to build a ring-like robot
Ground-level ice nucleating particle abundance on the North Slope of Alaska during Fall-Winter 2021
No full textAtmospheric ice-nucleating particles (INPs) are an important subset of aerosol
particles that promote the heterogeneous formation of ice crystals under ice
supersaturated conditions. In the Arctic, INPs contribute to partitioning between ice and
liquid water in mixed-phase clouds, influencing their albedo and climate forcing.
Furthermore, because INPs can catalyze precipitation and function as cloud-destroying
agents, the increase in INPs may result in accelerated positive radiative feedback.
However, the abundance and source of Arctic INPs are not yet well understood. This
study examined how profound atmospheric dynamics and extreme meteorological
conditions coinciding with low-pressure systems introduce INP anomalies on the North
Slope of Alaska (NSA). A Portable Ice Nucleation Experiment (PINE) chamber, which
simulates adiabatic expansion cooling, was used to monitor, and measure INP abundance
with ≈12-min time resolution at Barrow Atmospheric Baseline Observatory (71.32° N,
156.61° W). The INP abundance is reported as a function of freezing temperature
between the approximate -15 °C and -30 °C range and collected in November-December
2021. The offline measurements of the same period are found using the West Texas
Cryogenic Refrigerator Applied to Freezing Test (WT-CRAFT) at temperatures between
0 °C and -25 °C. Measured INP concentrations at overlapping temperatures of both
instruments are then compared. Besides the discussion of general INP abundance in the
NSA region, the influence of atmospheric low-pressure systems, as well as geopotential
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height anomalies, on the ground-based INP abundance (averaged for 6-hour) is discussed
in this work. The influence of heating on multi-seasonal INP abundance is also discussed.
A potential linkage was observed between INP concentration and the newly developed
climate index Aleutian Low Beaufort Sea Anticyclone (ALBSA). Finally, the current
international protocols for ambient aerosols, as well as further need in the international
legitimate framework for the aerosol-cloud-climate interactions, are investigated and
discussed
The Lived Experience of Nursing Students Caring for COVID-19 Patients
No full textThe data collection methodology was qualitative interviews.Abstract Background: As the wave of COVID-19 pandemic hit the world, schools and students were affected in many ways. Schools had to migrate courses to an online or hybrid platform while students had to adapt their learning to take care of COVID-19 patients in the clinical setting. Purpose: Caring for COVID-19 patients in the hospital setting provided the students with big challenges, and it became essential for faculty members to understand the students' feelings and obstacles as the semester continued. Methods: Utilizing a phenomenological framework, a qualitative descriptive study was performed to determine the lived experience of student nurses caring for COVID-19 patients. Results: Four main themes emerged from the study, which included 1. Importance of a support system, 2. Moral distress, 3. Enhancement of clinical skills, and 4. Significance of therapeutic communication. Conclusions: Based on the themes, four recommendations were identified to help students and faculty, which included 1. The value of simulation, 2. Development of a support system, 3. Collaborative preceptorship, and 4. Preparation for a new era
Community College Faculty Roles in Shared Governance
Get PDFPurpose:
The central purpose of this study was to examine the level of faculty authority
in institutional decision making in practice at community colleges in Texas. Additionally,
levels of faculty authority in community colleges were compared to that of faculty in
universities in the United States. Finally, levels of faculty authority were examined for
patterns relating to institutional characteristics. Research Method: This quantitative
study extended the 2021 American Association of University Professors Shared
G overnance survey to include community colleges in Texas using the same survey
instrument. Percentages of responses by decision making areas were calculated for
comparison. Observation Oriented Modeling was used to identify patterns relating to
faculty auth ority in universities or community college institutional characteristics.
Findings: The findings indicated that the highest levels of faculty authority in the
academic areas related to grade assignments, teaching assignments, and faculty searches.
The lowe st levels of faculty authority were discovered in areas related to provost
selection, building, budgets, salary policies, and undergraduate admissions policies.
Levels of faculty authority in community colleges were found to be most similar to
university f aculty in administrative decisions overall and the most divergent in academic
decision making. Findings indicated a moderate relationship between institutional size
and faculty authority, with smaller community colleges reporting higher levels of faculty
a uthority than larger schools. Conclusion: Results of this study provide a relative
benchmark for statewide faculty authority that is beneficial for individual college
comparison and future studies
Water Availability Sources for Land Value Prediction Using Machine Learning Methods
Get PDFGeolocated data was sourced from the Water Information Management and Analysis System (WIMAS, 2015) & the Kansas Department of Revenue (KDR, 2021). Land sale prices (adjusted for inflation, ref= 2020 dollars) were obtained from 2,000 dryland and irrigated land sale transactions (2012 to 2021). Water data and crop sources was recovered from 2,497 individual wells in GMD4 from 2005 to 2015. Prior to modeling, the two georeferenced databases were merged on the basis of Euclidean, and curvature-corrected (haversine), nearest distance analysis.Accurately predicting land values requires a solid understanding of geographical, economic, and management factors affecting water availability in a given region. To this end, most parcel valuation studies utilize hedonic regression - or some of its variants- to model final land prices as the aggregation of all of the intrinsic and market-driven characteristics affecting the land-unit. However, the prediction capabilities of hedonic pricing models are limited when fitted to datasets of increasing complexity across time and space, especially those derived from merging multiple layers of information. In this paper, we used a land valuation dataset, comprising originally 65,000 sale-transaction records paired to 160 possible geographical, socioeconomic, and agricultural features to evaluate three alternatives of penalty-based regression (LASSO, Ridge, and Elastic-Net), and two ensemble learning methods (Random Forest, and, Gradient Boosting Regression). It is expected that the learning algorithms evaluated increase land-price prediction accuracy relative to conventional hedonic pricing models. Also, this project will evaluate the generalization capabilities of the algorithms evaluated in terms of error sources derived from bias (BIAS) and variance (VAR) in the predictions. Future work is expected to assess also local stationarity as well as potential sources of dependence between observations in our dataset
The Lived Experience of a Nursing Course Failure
Get PDFThe data collection methodology was qualitative interviews.Abstract Background: Nursing remains one of the fastest growing occupations according to the Bureau of Labor Statistics (2022). Factors contributing to the ongoing nursing shortage including too few nursing faculty, limited clinical space, and sluggish growth in nursing program enrollment/capacity (AACN, 2020). Although most nursing programs are under pressure to accept as many qualified applicants as possible, as recently as 2019, U.S. nursing programs reported turning away over 80,000 qualified applicants due to insufficient space (AACN). Because each spot in the program is valuable - the ability to help all students from admission through to graduation is critical. Purpose: The purpose of this study was to identify the lived experience of students who had failed a nursing course. The information gathered from this group of students will enable nursing faculty to develop methods to help prevent this with future students. Methods: This qualitative descriptive study utilized a phenomenological framework to determine the lived experience of baccalaureate nursing students who failed a nursing course. Semi-structured interviews were conducted during the summer and fall of 2021. Results: There are much literature that report the challenges of nursing school and maintaining a balance between life and studies - however, our findings show that students still need help with this. The findings of this study revealed four themes. These included: academic challenges faced by the students, life issues encountered while in the program, issues with testing, and finally, having to handle the aftermath and consequences of a course failure. Conclusion: Early identification of students at-risk of a nursing course failure and implementation of success strategies may decrease the event of nursing course failure
RESOURCE DEPLETION AND MANAGEMENT IN RURAL ECONOMIES: GROUNDWATER IN TWO TEXAS WATERSHEDS
No full textThe Palo Duro and Double Mountain Fork Regions of Texas include counties that cover sub-basins of the Ogallala Aquifer. These regions rely on the Ogallala Aquifer for water. As concern grows over the diminishing availability of groundwater, policies such as caps on water use are put in place to conserve water. These policies raise concerns over their impacts on employment, markets, the welfare of different income groups, and impacts across political boundaries.
This study analyzed policy impacts in the Palo Duro and Double Mountain Fork Regions in Texas. A computable general equilibrium model (CGE) was developed to assess impacts on the economy by combining economic theory with real economic data. Data were collected for water use, land (including agricultural land use and production), and Impact Analysis for Planning (IMPLAN) sectors. These data were compiled into a social accounting matrix (SAM) to represent the flow of economic transactions in each of the two regions and balanced using the RAS procedure. The General Algebraic Modeling System (GAMS) was used to compile the data and create the CGE model. Land and water were added to the model as factors of production.
Importantly, a CGE model of this kind has never been incorporated into water policy analysis for this area in Texas. Rather, most studies have only utilized a modified IMPLAN model to measure direct, indirect, and induced impacts of economic output, value-added, and employment within a regional economy. The CGE model makes it
possible to further evaluate factors such as employment impacts, price impacts, and other economy-wide implications of various policy scenarios.
Comparisons were made between the impacts of different policy scenarios within the two regions. The scenarios analyzed included a baseline scenario without any policy implementation along with projected saturated thickness depletion after 50 years, a water reduction policy scenario, a land reduction scenario, and technology advancement scenario. The results of the study indicate that the projected saturated thickness depletion scenario with the land reduction policy scenario had the biggest impact on the overall economy in both the Palo Duro and Double Mountain Fork regions. In the Palo Duro Region, the projected saturated thickness scenario with the water reduction scenario mitigates some of the negative changes to GDP through policy, while the projected saturated thickness depletion scenario with the technology change scenario mitigates some of the negative changes in the Double Mountain Fork region. There is need for future research as these scenarios do not account for the negative impacts to producers such as costs and loss of production.
This information is useful for policymakers to base their decisions on in order to keep the regional economy viable while saving water. In addition, the creation of the foundational CGE modeling procedure will be beneficial in evaluating alternative scenarios in the future as water levels and political dynamics in the region change over time. This study had several limitations including how detailed the model could be. Future research should focus on nested production functions and combining this model with other economic models to improve the abilities of this model