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- Creators: Computer Science and Engineering Program
Description
Engineers have a strong influence on everyday lives, ranging from electronics and trains to chemicals and organs [1]. However, in the United States, there is a large knowledge gap in the roles of engineers, especially in K-12 students [2] [3]. The National Academy of Engineering (NAE) recognizes the current problems in engineering, such as the dominance of white males in the field and the amount of education needed to become a successful engineer [4]. Therefore, the NAE encourages that the current engineering community begin to expose the younger generations to the real foundation of engineering: problem-solving [4]. The objective of this thesis is to minimize the knowledge gap by assessing the current perception of engineering amongst middle school and high school students and improving it through engaging and interactive presentations and activities that build upon the students’ problem-solving abilities.
The project was aimed towards middle school and high school students, as this is the estimated level where they learn biology and chemistry—key subject material in biomedical engineering. The high school students were given presentations and activities related to biomedical engineering. Additionally, within classrooms, posters were presented to middle school students. The content of the posters were students of the biomedical engineering program at ASU, coming from different ethnic backgrounds to try and evoke within the middle school students a sense of their own identity as a biomedical engineer. To evaluate the impact these materials had on the students, a survey was distributed before the students’ exposure to the materials and after that assesses the students’ understanding of engineering at two different time points. A statistical analysis was conducted with Microsoft Excel to assess the influence of the activity and/or presentation on the students’ understanding of engineering.
The project was aimed towards middle school and high school students, as this is the estimated level where they learn biology and chemistry—key subject material in biomedical engineering. The high school students were given presentations and activities related to biomedical engineering. Additionally, within classrooms, posters were presented to middle school students. The content of the posters were students of the biomedical engineering program at ASU, coming from different ethnic backgrounds to try and evoke within the middle school students a sense of their own identity as a biomedical engineer. To evaluate the impact these materials had on the students, a survey was distributed before the students’ exposure to the materials and after that assesses the students’ understanding of engineering at two different time points. A statistical analysis was conducted with Microsoft Excel to assess the influence of the activity and/or presentation on the students’ understanding of engineering.
ContributorsLlave, Alison Rose (Author) / Ganesh, Tirupalavanam (Thesis director) / Parker, Hope (Committee member) / Harrington Bioengineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
Big Data Network Analysis of Genetic Variation and Gene Expression in Individuals with Breast Cancer
Description
The advent of big data analytics tools and frameworks has allowed for a plethora of new approaches to research and analysis, making data sets that were previously too large or complex more accessible and providing methods to collect, store, and investigate non-traditional data. These tools are starting to be applied in more creative ways, and are being used to improve upon traditional computation methods through distributed computing. Statistical analysis of expression quantitative trait loci (eQTL) data has classically been performed using the open source tool PLINK - which runs on high performance computing (HPC) systems. However, progress has been made in running the statistical analysis in the ecosystem of the big data framework Hadoop, resulting in decreased run time, reduced storage footprint, reduced job micromanagement and increased data accessibility. Now that the data can be more readily manipulated, analyzed and accessed, there are opportunities to use the modularity and power of Hadoop to further process the data. This project focuses on adding a component to the data pipeline that will perform graph analysis on the data. This will provide more insight into the relation between various genetic differences in individuals with breast cancer, and the resulting variation - if any - in gene expression. Further, the investigation will look to see if there is anything to be garnered from a perspective shift; applying tools used in classical networking contexts (such as the Internet) to genetically derived networks.
ContributorsRandall, Jacob Christopher (Author) / Buetow, Kenneth (Thesis director) / Meuth, Ryan (Committee member) / Almalih, Sara (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description
With the recent rise in opioid overdose and death1<br/><br/>, chronic opioid therapy (COT) programs using<br/>Center of Disease Control (CDC) guidelines have been implemented across the United States8<br/>.<br/>Primary care clinicians at Mayo Clinic initiated a COT program in September of 2017, during the<br/>use of Cerner Electronic Health Record (EHR) system. Study metrics included provider<br/>satisfaction and perceptions regarding opioid prescription. Mayo Clinic transitioned its EHR<br/>system from Cerner to Epic in October 2018. This study aims to understand if provider perceptions<br/>about COT changed after the EHR transition and the reasons underlying those perceptions.
ContributorsPonnapalli, Sravya (Author) / Murcko, Anita (Thesis director) / Wallace, Mark (Committee member) / College of Health Solutions (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05