Discrepancies between normative, expected and observed student workload reveal curriculum structure inconsistencies

Background: Student workload is considered from three view-points: normative (8 hours/day, 5 days/week, 20 weeks/semester equals 800h/semester); expected (the planned by the teacher workload the average student should devote to get an average pass examination mark 7.5 out of 10, pass cut-point 5); observed (the actual workload students devote to pass the exams). Do they coincide? Methods: A questionnaire was administered to all Ioannina medical students during both 2011 semesters to report the hours they devoted in lectures, laboratories, clinic-attachments, homework, self-study, and examinations for the examined courses. All teachers were asked to report the corresponding hours they have planned their courses for the average student. Results: Of the 284 student questionnaires collected, 277 were valid. Of the 109 courses offered, 50 till now reported corresponding expected hours. Compared to 800h normative semester, first semester students reported 481h (60%), third 771 ( 96%), fifth 666 (83%), seventh 591 (74%), ninth 1217 (152%), eleventh or twelfth 1322 (165%). Giving some course examples, Biostatistics expected workload was 92h (~4ECTS, as officially allocated), while passed students reported average mark 7.0 by 56.2h workload (~2ECTS). Pharmacology expected 213h (~8.5ECTS >7 officially allocated), while passed students reported average mark 8.0 by 187.5h (~7.5ECTS). Robotic surgery (elective) expected workload was 95h (~4ECTS >>1 officially allocated), while passed students reported average mark 8.8 by 17.2h (<1ECTS). Discussion: Teachers and students had no previous experience on this kind of survey and they might have been quite confused. Non-representative student sampling and recall bias are the main limitations. Conclusion: However, tactile numbers are now available, revealing great deviations between normative, expected, observed, and allocated working hours, that seem to be beyond these limitations. Since student workload discrepancies reflect curriculum structure inconsistencies, the solving of the latter will decrease the former. Take-home-message: Quantifying expected and observed student workload gives a great opportunity to restructure our whole curriculum.


Saturday, 7 April, 2012 - 11:45 to 13:00