DocumentCode :
3563184
Title :
An extensible online environment for teaching data science concepts through gamification
Author :
Anderson, Paul E. ; Turner, Clayton ; Dierksheide, Jacob ; McCauley, Renee
Author_Institution :
Dept. of Comput. Sci., Coll. of Charleston, Charleston, SC, USA
fYear :
2014
Firstpage :
1
Lastpage :
8
Abstract :
Learn2Mine is a cloud-based environment developed to support the teaching of data science. This paper discusses the architecture of Learn2Mine, the research that guided its development, and the pilot implementation and formative assessment of its use in teaching data science. Learn2Mine was pilot-tested in Fall 2013 in an introductory data science source. At the end of the term, a survey of students concerning their experiences with the environment was conducted. Quantitative analysis of survey data showed that student opinion about the usefulness of the tool for learning course content was positive. Through open-ended comments, students provided constructive feedback on how the system might be improved. To collect expert opinion on both the didactic and usability aspects of the Learn2Mine system, a number of experts were enlisted to try the system. Experts responded to a survey regarding criteria typically expected of instructional software, such as system usability and flexibility, as well as accuracy and organization of content. Overall, the responses from experts were extremely positive. A plan for further development of the system, based on these results, is presented along with information on the developers´ plans for making the environment available for use at other institutions.
Keywords :
Big Data; cloud computing; computer aided instruction; data analysis; data mining; educational courses; teaching; Learn2Mine; cloud-based environment; course content learning; data science teaching; extensible online environment; gamification; Computer architecture; Data mining; Education; Programming profession; Usability; Data mining; big data; computer science; data science; interdisciplinary; machine learning; statistics; tools;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Frontiers in Education Conference (FIE), 2014 IEEE
Type :
conf
DOI :
10.1109/FIE.2014.7044205
Filename :
7044205
Link To Document :
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