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Use of Mastery Software in the Undergraduate OM Course

Use of Mastery Software in the Undergraduate OM Course. Peter J. Billington Colorado State University – Pueblo. Undergraduate OM Course. Junior Level Required of all Business students Blend of quantitative and qualitative Tools and techniques, e.g. Project management, waiting lines

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Use of Mastery Software in the Undergraduate OM Course

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  1. Use of Mastery Software in the Undergraduate OM Course Peter J. Billington Colorado State University – Pueblo

  2. Undergraduate OM Course • Junior Level • Required of all Business students • Blend of quantitative and qualitative • Tools and techniques, e.g. • Project management, waiting lines • MRP, inventory, SPC, learning curves • Statistics as a pre-requisite

  3. Mastery Software • Quant Systems’ Adventures in Operations Management • Modules for a number of topics • Demo mode – shows how it works • Practice mode – student can practice • Certify mode

  4. Certify Mode • Student has ~ 10 problems with some subsections, varies each module • Read question, calculate answer, submit answer. • If correct, moves to next question. • If incorrect, indicates a “strike” and gives correct answer • Cannot correct the submitted answer

  5. Certify continued • 3 “strikes” and you’re out. • Must start over. • If answer all questions with fewer than 3 strikes, student certifies. • Gets a certification number and prints out certification sheet. • Submits this to professor.

  6. AiOM in the OM course • 10 modules assigned in semester • 10% of course grade • “All of nothing” - Must certify in all modules to receive the 10%, otherwise zero % • Started with required submission before corresponding exam • If student missed first, they gave up

  7. AiOM in the course - continued • Changed to: submit any time before end of semester, but strongly urged to submit before exam. • Some students certified before exam. • Some did not. • Positive student comments on course evaluation. • Ah ha – “Maybe I should find out if they are affecting test scores!”

  8. Collecting Data • After each exam, noted if student had completed corresponding AiOM. • 138 students • 636 exams • Normalized each exam average to 100

  9. Results • “Yes” means student did certify AiOM module before exam. • “No” means student did not. • Significance tests have not yet been performed on the data.

  10. Results

  11. Analysis • Were the exam results and % completed before exam related to • Grade in pre-requisite statistics course? • GPA of student? • Other factors?

  12. Related to Stats Grade

  13. Related to GPA

  14. Average Exam Grade

  15. Average Exam Grade

  16. Conclusions • Certifying appears to improve grades. • Makes little difference to top students. • Makes a large difference for other students. • GPA better predictor than stats grade.

  17. Next • Add this semester’s 60 students and 300 exams. • Significance tests. • Break out by difficulty of test material? • Is difference in MRP test greater than for learning curve test? • Other factors to consider? • For a student that did not complete all on time, did it make a difference? • End the experiment! Require for all!

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