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dc.contributor.authorIsom, Aaron F.
dc.date.accessioned2019-05-06T17:08:45Z
dc.date.available2019-05-06T17:08:45Z
dc.date.issued2019-04
dc.identifier.urihttp://hdl.handle.net/1853/61026
dc.descriptionThis paper was created as part of CS6460 Educational Technology at Georgia Tech.en_US
dc.description.abstractThis work involved a comparative analysis of randomly selected Data Science Massive Open Online Courses (MOOCs) and master’s degree programs in investigating how effectively interdisciplinary curricula approaches were being utilized in the course design. It also involved a second study, in the form of a qualitative survey, that asked students to share their perspective, satisfaction, and sentiment from MOOC experiences. These findings were combined, analyzed and utilized to support the foundation of the proposed case-based learning methodology. This approach provides a more real-world and project simulated approach that challenges students to solve problems analytically which is seen as a more effective framework for delivering data science offerings.en_US
dc.language.isoen_USen_US
dc.publisherGeorgia Institute of Technologyen_US
dc.subjectArtificial intelligenceen_US
dc.subjectCase-based learningen_US
dc.subjectData scienceen_US
dc.subjectEthicsen_US
dc.subjectMachine learningen_US
dc.subjectMOOCen_US
dc.subjectSentiment analysisen_US
dc.titleEstablishing a Data Science 101 Pedagogy: Reimagining the MOOC Learning Experience Through a Case-Based Learning Methodologyen_US
dc.typePaperen_US
dc.contributor.corporatenameGeorgia Institute of Technology. College of Computingen_US
dc.contributor.corporatenameGeorgia Institute of Technology. School of Computer Scienceen_US


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