2018 EDSIGCON Proceedings - Abstract Presentation
Using Contextual Semantic Search to Gather Actionable Insights for Curriculum Development: A Research Proposal
Diane Igoche
Robert Morris University
Abstract
According to IBM, jobs requiring data science skills will see a 28 percent by the year 2020. However, there is a skill-gap for this highly compensated, interdisciplinary field. In response to this gap, colleges and universities have begun to develop graduate programs to train individuals with an interest in Data Science and its related fields. The typical Data Science graduate program has enrollments from students with a Computing, Mathematics, Engineering, and Natural Science background.
Bootcamps have also presented an opportunity for aggressive, shorter timed training to bridge this skill gap, by training interested individuals in core Data Science concepts and applications. A survey of the top Data Science Bootcamps show that entrants must possess at least a Bachelor’s Degree. These Bootcamps provide an attractive opportunity for college graduates who find their career potential restricted by their already acquired degree (Waguespack, Babb & Yates, 2018). Bootcamps like Data Incubator have been successful in preparing and placing participants in Data Science related positions globally. However, employers still favor individuals with graduate degrees in the applicable Data Science fields (Thayer & Ko, 2017). Although Bootcamps provide a fast-tracked means to beginning a career in Data Science, people are still opting for graduate degrees as a means to upgrade skills and knowledge, and change career directions (Seibel, 2018). Graduate programs can learn from the structure of Bootcamp programs while taking advantage of the resources and structure of a graduate program (online or on-ground); a review of the literature shows that there is a need to study the Data Science Bootcamp structure and its applicability to the Data Science graduate program. This study seeks to highlight how colleges and universities can develop programs that will prepare graduates to enter the job market as effective Data Scientists.
This research study is using Sentiment Analytics to web mine data from Bootcamp attendees on their opinions of the Bootcamp preparation in relation to their ability to perform as Data Scientists. Contextual Semantic Search (CSS) will be used to gather web-based data from Data Science Bootcamp attendees (past and present) to determine the areas of improvement that can be applied to Data Science graduate programs in the area of curriculum, and continuous development. Sentiment Analysis is a text classification tool that analyses data and classifies the sentiment of the messages into positive, negative or neutral category. Deriving actionable insights from the data requires the use of an intelligent algorithm like CSS (Ruas & Grosky, 2017). Contextual Semantic Search will also be used to identify the needs of employers, to inform the preparation of Data Science graduate students prior to graduation.
Finally, the research study will add to the body of knowledge on the use of Sentiment Analytics in curriculum development in higher education?
The research study can influence the curriculum of Data Science/Data Analytics graduate programs in colleges and universities nationwide. The data will also be useful to institutions that are considering creating Master’s Degree programs in Data Science, Machine Learning or closely related fields.
Ruas, T., & Grosky, W. (2017, November). Keyword Extraction Through Contextual Semantic Analysis of Documents. In Proceedings of the 9th International Conference on Management of Digital EcoSystems (pp. 150-156). ACM.
Seibel, S. (2018, February). Social Motivators and Inhibitors for Women Entering Software Engineering through Coding Bootcamps vs. Computer Science Bachelor's Degrees. In Proceedings of the 49th ACM Technical Symposium on Computer Science Education (pp. 274-274). ACM.
Thayer, K., & Ko, A. J. (2017, August). Barriers faced by coding bootcamp students. In Proceedings of the 2017 ACM Conference on International Computing Education Research(pp. 245-253). ACM.
Waguespack, L., Babb, J. S., Yates, D. (2018). Triangulating Coding Bootcamps in IS Education: Bootleg Education or Disruptive Innovation?. Information Systems Education Journal, 16(6) pp 48-58. http://isedj.org/2018-16/ ISSN: 1545-679X
Recommended Citation: Igoche, D., (2018). Using Contextual Semantic Search to Gather Actionable Insights for Curriculum Development: A Research Proposal. Proceedings of the EDSIG Conference, (2018) n.4796, Norfolk, Virginia