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Writing Intensive Engaged Learning Business Analytics Class

This presentation discusses the implementation and impact of a writing-intensive and engaged learning approach in a business analytics class at Loyola University Chicago. It highlights the use of analytics techniques, case studies, team projects, and symposium presentations as part of the learning experience. Student feedback and sample projects are also shared.

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Writing Intensive Engaged Learning Business Analytics Class

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  1. Writing IntensiveEngaged Learning Business Analytics Class Mary Malliaris Loyola University Chicago Presentation for SEDSI 2017

  2. Student & Class Levels Student: junior/senior level Type of Class: • Counts toward IS major • Not required (one of a number of electives), • All students would have had Statistics and Intro to Information Systems • Class is capped at 24

  3. Why Writing Intensive/Engaged Learning? • Employers are asking for more communication skills (oral and written), • All students at Loyola are required to take at least two writing intensive classes; one must be in their major. • The University has a requirement that all students complete at least one engaged learning class.

  4. Major class requirements • Analytics techniques (we used IBM’s SPSS Modeler) • Read case & write response each week • 2 short presentations in class about cases • Team research project • Symposium presentation

  5. Team Project • A practical learning experience in developing and delivering a research project in data mining & analytics. • Students had to decide on a problem, describe their data collection and manipulation, analysis process, and the potential benefits of expected findings

  6. The Final Project Write-up Included • Question that was driving the analysis • Data selection, origin and manipulation • Technique(s) used for the analysis and why • Results from the technique • The answer or action for the initial problem addressed • Discussion of how they would judge the effect of their solution if implemented

  7. Weekly Template: Monday • Analytics technique and practice (class in the lab) • For example: Association Analysis, Cluster Analysis, Decision Trees, Neural Networks, Logistic Regression, Support Vector Machines

  8. Weekly Template: Wednesday • Case paper using Monday’s technique • Each week: All students wrote a short criticism of the paper, as though they were a journal editor, focusing on both the strong and the weak points in the analysis and writing. • These were due before class on Wednesday.

  9. Weekly Template: Wednesday • One person was designated as lead presenter and one as lead critic. Each gave a short overview in class. • The lead presenter: presentation of the research story and results; emphasis on the best of the writing style • The lead critic: the weak points with emphasis on the worst parts of the writing, research, and results. • After these, the class was opened for discussion of the paper overall and we talked about each section’s good and bad points.

  10. Weekly Template: Friday • Team assignment day for work on their project • Identify problem • Collect data, clean, join, modify • Collect references • Write paper parts (abstract, introduction, literature review, data and model, results, conclusion, recommendation for future research) • To discourage “free riders”, assignment was due before class (individual) and after class (team)

  11. Example papers:

  12. Example papers:

  13. Sample Student Projects: • A Neural Network Analysis of U.S. Voter Turnout Rates • Entrepreneurship and Business Success in Chicago • Association Analysis of Age, Race and Gender in Unemployment Rates across the United States • Crime in the Windy City: A Loyola Student’s Guide to Off‐Campus Crime

  14. Student Responses • Enjoyed being able to criticize other’s work • Felt more empowered • Liked working on a problem that had direct implications in the world • Thought they were more connected to Loyola after symposium presentation

  15. Questions? QUESTIONS?

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