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Architectural Inefficiencies and Educational Outcomes in STEM

Explore the potential benefits of removing the common pacing requirement on the production of scientists, technologists, mathematicians, and engineers. Simulate different education architectures to analyze the impact on student learning and progress.

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Architectural Inefficiencies and Educational Outcomes in STEM

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  1. Architectural Inefficiencies and Educational Outcomes in STEM Dan Sturtevant Massachusetts Institute of Technology Engineering Systems Division dan.sturtevant@sloan.mit.edu

  2. Question • Christensen, Horn, & Johnson assert that a technology enabled transformation will occur in education in the next ten years. • Such a transformation could change the very character of how the educational function is performed. • One potential benefit could be the elimination of the “common pace requirement” within classrooms. What are the potential benefits of removing the common pacing requirement on societal production of scientists, technologists, mathematicians, and engineers?

  3. Simulate one cohort of students under different education architectures

  4. Movement through the pipeline • Give each between 0 and 1 ‘unit’ of knowledge • Every year (repeat until graduation): • Move students up one grade. • Assign students to the appropriate schools based on geographic district. • Assign students to a classroom within that school. • Administrators set expectations and teachers adapt to skills of students they have in the class. • Teaching and learning for one year. Goal is to gain 1 unit of knowledge per year. After 16 years, one may hope that each student will contain 16 additional units of knowledge.

  5. Schools and Classrooms

  6. Test impact of:Pace setting policiesVariation in student and teacher abilityStudent tracking policies

  7. Rules for setting class Start Point (SP):

  8. Rules for setting variation in student ability and teacher quality:

  9. Rules for assigning students to classrooms:

  10. Rules for imposing learning penalty to student based on pacing requirement:

  11. Six Simulation Tests SP = FloatingNoIndividualVariationRandomAssignmentPacingPenaltyOn SP = FloatingTeacherAndStudentVariationRandomAssignmentPacingPenaltyOn SP = FixedTeacherAndStudentVariationRandomAssignmentPacingPenaltyOn SP = HalfFixedFloatTeacherAndStudentVariationTrackedAssignmentPacingPenaltyOn SP = FloatTeacherAndStudentVariationTrackedAssignmentPacingPenaltyOn TeacherAndStudentVariationRandomAssignmentPacingPenaltyOff

  12. Results

  13. Simulation 1 SP = FloatingNoIndividualVariationRandomAssignmentPacingPenaltyOn

  14. Simulation 1 SP = FloatingNoIndividualVariationRandomAssignmentPacingPenaltyOn

  15. Simulation 1 SP = FloatingNoIndividualVariationRandomAssignmentPacingPenaltyOn

  16. Simulation 2 SP = FloatingTeacherAndStudentVariationRandomAssignmentPacingPenaltyOn

  17. Simulation 2 SP = FloatingTeacherAndStudentVariationRandomAssignmentPacingPenaltyOn

  18. Simulation 2 SP = FloatingTeacherAndStudentVariationRandomAssignmentPacingPenaltyOn

  19. Simulation 3 SP = FixedTeacherAndStudentVariationRandomAssignmentPacingPenaltyOn

  20. Simulation 3 SP = FixedTeacherAndStudentVariationRandomAssignmentPacingPenaltyOn

  21. Simulation 4 SP = HalfFixedFloatTeacherAndStudentVariationTrackedAssignmentPacingPenaltyOn

  22. Simulation 5 SP = FloatTeacherAndStudentVariationTrackedAssignmentPacingPenaltyOn

  23. Simulation 5 SP = FloatTeacherAndStudentVariationTrackedAssignmentPacingPenaltyOn

  24. Simulation 6 TeacherAndStudentVariationRandomAssignment PacingPenaltyOff

  25. NAEP Scores 2005 Mathematics 4th 200 220 239 258 273 8th 231 255 280 304 324 Reading 4th 171 196 221 244 263 8th 216 240 265 286 305 12th 235 262 288 313 333 Percentiles 10th 25th 50th 75th 90th

  26. NAEP Scores 2005 Mathematics 4th 200 220 239 258 273 8th 231 255 280 304 324 Reading 4th 171 196 221 244 263 8th 216 240 265 286 305 12th 235 262 288 313 333 Percentiles 10th 25th 50th 75th 90th

  27. Final Thoughts • Lots of attention in education research is placed on relating individual attributes (student ability, teacher quality, socioeconomic status) to social outcomes. • Increased focus on system architecture and the way structure leads to behaviormight provide insights of significant value. • Technology enabled education represents a fundamental change (from cellular to network centric)in the very nature of the education system. • Simulation modeling can be used to explore potential benefits and costs of alternative architectures in a risk free environment.

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