Revealed: the best and worst attended lectures

Credit: The Saint
Credit: The Saint

“Dealing in Darkness: An Anatomy of Realism in International Relations” (IR4541) is the University’s worst attended module with just 20 per cent average attendance (two out of 10 enrolled students) according to data obtained by The Saint through Freedom of Information request.

The data, which was collected by staff employed by the University during week 3 of semester two last year, recorded student attendance at lectures throughout the week.

Though some modules failed to attract high attendance, the overall numbers are not all damning. 34 modules show 100 per cent attendance and five subjects have an average attendance of over 90 per cent.

The best attended subject across sub-honours and honours is Mediaeval History, where a substantial 92.8 per cent of students turned up to their lectures. Also on the roll of honour are Greek (92 per cent), Film Studies (91.8 per cent), Modern History (90.1 per cent) and Modern Language Grammar (90 per cent). At the opposite end of the scale, Sustainable Development failed to develop sustainable attendance, with just 47.8 per cent average attendance. Interdisciplinary modules also fared poorly, with less than one in two students attending at 49.6 per cent. Linguistics (58 per cent), Music (60.1 per cent) and English (62.8 per cent) round off the bottom five.

Other modules that failed to attract students included MT4537 (Spatial Processes), where there was plenty of space in the lecture theatre at 36.4 per cent attendance, four out of 11 enrolled students. MN2002 (Management and Analysis) failed to manage their attendance rates, with only 42.1 per cent – 62 of 148 – students turning up to class.

Credit: The Saint
Credit: The Saint

The popular first year Sustainable Development module SD1003 (Towards Alternative Futures) had students contemplating alternative futures to spending time in lectures, with 38.6 per cent of 180 students turning up. Meanwhile, Computer Science students had concurrent plans as they opted to avoid CS4204 (Concurrency and Multi-Core Architectures), with a 42.9 per cent attendance rate; 3 out of 7 students.

EN3164 (Self and Society in the English Novel) also failed to entice its students to make it to lectures with 23.8 per cent attendance, or five out of 21 students in attendance. Another English module which showed poor attendance was EN4418 (American Poetry since 1950) which saw only 35.7 per cent, five out of 14, students attend.

Language modules are also amongst the worse attended, with 33.3 per cent of students (six out of 18) attending IT1014 Italian Histories and 41.7 per cent (eight out of 18) attending FR4160 (From One War to Another: French Politics, Culture and Society 1914–1945).

Aggregating the subjects within their respective faculties reveals conclusions that may challenge perceived wisdom. It is the Arts faculty which has the higher average attendance of the two largest faculties, with just under four in five students (79.9 per cent) showing up to their lectures. Science subjects trail by 5.2 per cent, with 74.7 per cent. Medicine students require urgent treatment before they can top the table, with the worst faculty attendance rate of 68.4 per cent. However, the poor attendance of medical students can largely be attributed to smaller class sizes. This may make the percentage of students in attendance seem smaller than that of a larger class.

Disclaimer: Class sizes should be taken into consideration when looking at these results. All modules (mostly senior honours) where classes have been combined have been excluded, as lecture attendance figures show more students attending than are enrolled on the module. This may well apply to some of the modules displaying high attendance less than or equal to 100 per cent, however the data obtained by The Saint made it impossible to distinguish where this is the case. Where Arts and Science averages have been calculated, all departments have been weighted equally, no matter the number of students or modules on offer.

For a full list of attendance at every module, see the data here.


  1. I think a better measure for medical students would be how many attend or watch the lecture later. I know a number of people who don’t attend lectures but instead watch them later on our Lecture Echo system. The likelihood that 31.6% of students don’t watch the lectures at all is 0, as failing to do this would almost certainly result in failing the course!

  2. Well not too hard to understand when modern languages grammar lectures are compulsory. Take that away and I guarantee you the graph will be different lol

  3. Why is medieval history listed as ‘med’ (for medicine) in the faculty column rather than as ‘arts’? My module from last year, second semester isn’t even listed. This faulty and limited data (one week’s worth, when arts honours students only go to one class per week) doesn’t reflect anything about module impact or lecturer teaching expertise. And to what end is The Saint publishing this data? To shame lecturers? Students? Once again, The Saint has resorted to sensationalist journalism that undoes the hard work of class reps and academic reps. Disappointing.

  4. What is the point of this article? Are you attempting to shame individual lecturers by claiming their modules are poorly attended and extrapolating to say that their teaching is bad? In which case, this is an ill-conceived article in very poor taste. I was actually in one of the modules you listed as particularly bad and can safely say that it was regularly well attended and well taught. I think it is absolutely ridiculous to base an entire school’s attendance on one week of classes.

    In my experience poor attendance of lectures is rarely due to poor teaching, and more to do with lazy student attitudes. This kind of journalism is unhelpful and non-constructive, especially when academic reps work hard with staff to try and tackle these issues.

  5. Your, by subject and by faculty, analysis is dodgy at best. I have done some analysis myself to help rectify a couple of its issues. I can send you the file if you want.

    By averaging over modules you create a huge bias in favour of subjects which have many small, well attended, honours modules (Medieval and Modern History) and few large sub-honours modules or even none at all. A better way to do that particular analysis would be to total the number of students enrolled on modules for that subject and do the same for those that attend and take that percentage.

    When I did this I found that there were 22 points between our estimates of attendance at social anthropology lectures (you 84% – me 62%) and 11 points between our estimates of attendance at medieval history lectures (you 93% – me 82%).

    Your headline about medicine students ceases to be an outlier. You had in most cases overestimated attendance but your analysis for medicine was largely free of bias due to their course structure. However their figure of 68% attendance becomes distinctly average. SD, Social Anthropology, Management, Italian, English, Economics and Computer Science all now post lower scores. While most subjects have scores between the high 60s and low 80s.

    The biggest positive outliers were Film Studies (87%) and Greek (92%). Although an element of this was having few modules with small class sizes.

    Although this new analysis rectifies some of the issues your analysis has it does not fix other biases which result from the different course structures in each subject. For instance compulsory classes. Large numbers of students whose degrees aren’t in that subject taking it for a doss at sub-honours. The small number of students being in certain subjects full stop. The fact the data was collected over a period of just one week. Not running sub-honours modules. The recording of lectures by certain departments.

    You are comparing apples and pears in any attempt to analyse these data and I advise that you don’t try. Its not informative and I fail to see the benefit in bashing certain lecturers or subjects publicly. I thought module evaluation forms were good enough feedback.

    You also have no evidence of causality of poor lecturing or student laziness being behind these statistics and I am sure there are many other factors which could be looked at. e.g. The proximity of students lectures to each other in both time and space. Possibly students who have left their homes already or are near to their next class when they leave their first are more likely to go to their next.

    Finally I ask that if in future The Saint feels the need to write a piece that relies on statistics you ask someone with more statistical training to do the analysis for The Saint.

    • I provided a little bit of help with the statistical analysis and provided several suggestions for this article, some of which were taken on board. (Unfortunately, I was not available to do much more than look over an earlier draft of the article.) Part of the issue is that the Saint is relying on FOI data. This data included only the module number, module enrollment and average attendance over the evaluation period. This limits the possible analysis. What I was able to do was take into account module enrollment size, which is what led to a few of the caveats at the end of the article.
      Another issue is that can be quite difficult to write with statistics for the general public. For instance, I suggested that they include the 95% confidence intervals along with the averages, in order to take into account some of the very issues you mentioned. Unfortunately, many readers do not know what these are and what they mean, and it makes for dry reading.


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