Project FA15h: Geographic perspectives on building a big data analytics workforce

Project FA15h: Geographic perspectives on building a big data analytics workforce

Researcher: Eun-Kyeong Kim

Semester for work to be done: Fall 2015

Position type: Big data analytics; geographic education

Application deadline: 5:00 p.m. on Tuesday, Sept. 1, 2015

Application URL: http://www.geog.psu.edu/uroc-apply

Project description

I am seeking one or two undergraduate students to assist with a NSF-funded research project on “Building a Big Data Analytics Workforce in iSchools” (http://www.nsf.gov/awardsearch/showAward?AWD_ID=1525601&HistoricalAwards...) that I am involved in as a graduate researcher. Recognizing the need of big data analytics skills to analyze a massive and complex data set, this project aims to develop innovative learning modules based on both group-based and contextualized learning methods to build a big data analytics workforce in iSchools. In this project, we develop different types of learning modules (digital storytelling about big data, security analysis in the cloud, and big data mining) and teaching methods/materials. As big data with geo-location information are becoming prevalent, geographic perspectives are valuable to develop such learning modules and teaching methods. Potential tasks of undergraduate assistants in this project are: 1) Reviewing different types of learning modules for big data analytics and existing course materials regarding big data analytics (online/offline courses); 2) Develop innovative learning modules and teaching methods. For undergraduate assistants who are interested in big data analytics and geographic education, this project will be a great opportunity to learn basic concepts of big data analytics and how to teach them with my helps; depending on assistants' interest, they can experience big data analytics skills including R, Python, database, visualization, and so on.

Desired qualifications

Candidates must be willing to learn basics of big data analytics and develop learning modules from a geographic perspective with help from mentor. Candidates who have background knowledge in data analysis, database, and programming languages including R and Python are preferred; however, other candidates will be considered as well. Candidates must be willing to contribute 40–120 total hours of work toward the project over the semester, resulting in 1–3 credit hours applied to the transcript. There is no monetary stipend attached to this assistantship, although the experiences gained in this work will be immediately valuable when applying for graduate school or full-time employment.

 

To apply

Prospective candidates should submit application to http://www.geog.psu.edu/uroc-apply by 5:00 p.m. on Tuesday, September 1, 2015.

A complete application must include:


1. All required fields of online form: http://www.geog.psu.edu/uroc-apply

2. A one-page cover letter identifying the position for which you're applying and stating your interest in conducting research, your academic preparation, the skills you hope to gain from this experience, and contact information of two references.

  • Upload a PDF document named as follows: FirstinitialLastname_letterMMYY.pdf (e.g. jvender_letter1114.pdf)

3. A resume

  • Upload a PDF document named as follows: FirstinitialLastname_resumeMMYY.pdf (e.g. jvender_resume1114.pdf)
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