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Effectiveness of Instructional Techniques to Create Retainable Quantitative Skills. Kathy Baughman Assistant Professor of Accounting Wei-Chung Wang Assistant Professor of Economics. Overview. Review of Study Motivation of the Study
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Effectiveness of Instructional Techniques to Create Retainable Quantitative Skills Kathy Baughman Assistant Professor of Accounting Wei-Chung Wang Assistant Professor of Economics
Overview • Review of Study • Motivation of the Study • Quantitative Requirements in the Business Curriculum at Juniata College • Current Experiment Design and Progress • Discussion on Challenges and Next Steps 2
Quantitative Requirements for Business POEs • Calculus I or Quantitative Business Analysis (QBA) • QBA had been considered by students as a course designed for students that have less aptitude in math • For certain POEs we require or recommend students to take more math courses (i.e. Accounting, Economics, Finance) • Self-selection problem 3
QBA • Algebra based, 200-level course • Course contents • Module 1: Review of Math and Descriptive Stats • Module 2-4: Taxes, Insurance, Payrolls, Distribution of Profit and Loss, Discounts, Markups and Markdowns, Interest, Present and Maturity Value • No calculator policy, techniques demonstrated for efficiency • In-class practice problems, homework assignments • Speed and accuracy • Course reputation 4
Managerial Accounting • 200-level require course for all business POEs • Course with heavy use of numbers • QBA first then MA or the other way around • Some students take calculus instead of QBA • Memo writing requirements • Anecdotal evidence showed students with QBA experience perform better in MA and other courses 3
Video • Shark Tank 4
Research Questions • Does changing the instructional technique help students retain numerical sense? • Does the improved skill transfer to other quantitative courses in the curriculum? • Does the change in instruction cause any change in student perception of their math abilities? 5
Feedback from Last Presentation • Mathematical Ability vs. Numerical Sense • Estimation vs. Accuracy • Self-reported Attitude Assessment • Control Group 6
Challenges • Lack of longitudinal data • Interpretate speed vs. accuracy • Estimation is or is not numerical sense • Differentiate between numerical sense and reading comprehension 8
Next Steps • Enriching the study with external data (SAT , GPA etc.) • Pre-post test comparison 10
Questions? 15