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Timetables, Attendance and Academic Achievement in Higher Education

Author

Listed:
  • Delavande, Adeline

    (University of Technology, Sydney)

  • Del Bono, Emilia

    (ISER, University of Essex)

  • Holford, Angus J.

    (University of Essex)

  • Williams, Kevin

    (University of Utah)

Abstract

We identify the impacts of a student's timetable on their attendance, study time and academic achievement using administrative and survey data from a public UK university across a broad range of degree programmes using quasi-random assignment of students to their timetables. Timetable measures include back-to-back classes, single-class days, time-of-day, day-of-instruction and long hours. We observe hourly attendance decisions. Findings indicate that student attendance at the event level is highly dependent on the timetable structure. Single-class days reduce attendance and back-to-back classes raise it. We are able to show that students compensate for marginal non-attendance at some events with increased attendance at other events on the same module, or among more conscientious students, with increased study time. Net of all behavioural responses to the timetable, these features have little impact on academic attainment.

Suggested Citation

  • Delavande, Adeline & Del Bono, Emilia & Holford, Angus J. & Williams, Kevin, 2025. "Timetables, Attendance and Academic Achievement in Higher Education," IZA Discussion Papers 17979, Institute of Labor Economics (IZA).
  • Handle: RePEc:iza:izadps:dp17979
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    References listed on IDEAS

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    JEL classification:

    • I23 - Health, Education, and Welfare - - Education - - - Higher Education; Research Institutions
    • I24 - Health, Education, and Welfare - - Education - - - Education and Inequality
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior

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