ERIC Number: EJ1414122
Record Type: Journal
Publication Date: 2024
Pages: 8
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-1055-3096
EISSN: EISSN-2574-3872
Teaching Tip: Using Text Analytics AI Insights in Microsoft Power BI Desktop to Score Sentiments, Extract Key Phrases, and Discover Unstructured Data Patterns
Chang Liu; Charles Downing
Journal of Information Systems Education, v35 n1 p48-55 2024
This teaching tip describes using Microsoft Power BI Desktop in a class to analyze unstructured data from an exit survey of prior students from a Master of Science in Management Information Systems program. Results from a short survey administered to these students showed that the students, using the no-code Power BI, were able to accomplish their text analytics tasks in a shorter period, and with less overall effort, as compared to using traditional code-rich text analytics methods. The process is described in detail as to how the students, new to unstructured data analysis, can uncover these results. This process can be replicated by other instructors teaching text analytics.
Descriptors: Graduate Students, Program Effectiveness, Information Science, Management Information Systems, Information Management, Artificial Intelligence, Computer Software, Data Analysis, Data Collection, Business, Program Improvement
Journal of Information Systems Education. e-mail: editor@jise.org; Web site: http://www.jise.org
Publication Type: Journal Articles; Reports - Research; Tests/Questionnaires
Education Level: Higher Education; Postsecondary Education
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Grant or Contract Numbers: N/A