Discussion: A teaching dataset on student communting and attendance. The data for this discussion came from an online survey completed by 180 students at one university over the course of a week in March. Of the 60 students who in that week traveled long distances (over 45 minutes each way), 35% of them reported that in the previous month they had on occasion missed a morning class. Of the 120 students who in that week traveled short distances (less than 45 minutes each way), 20% reported that in the previous month they had on occasion missed a morning class. The travel time and the attendance for each of the students were self-reported and so were subject to a number of potential problems. No attempt was made to correlate the students’ reported travel times with transport data, or their reported attendance with records of attendance.

There is a noticeable difference in the two percentages. However, this does not necessarily mean that long commutes have a negative effect on attendance. In fact, it is more likely that a variety of factors could explain why some students are able to attend classes and others are not. These factors could include students’ employment, caring responsibilities, disabilities, as well as the design of the university timetable and the availability of online materials to support study. It is also possible that occasional long commutes are perceived by students as typical and therefore reported in the survey. Furthermore, it is well known that people are prone to remembering absent days more than normal ones, therefore the way in which students have responded to the survey may not be accurate.

The method of recruitment to the study also has to be considered. Links to the online survey were distributed to two student mailing lists, and all students who were members of these lists were encouraged to participate in the study. Thus, it is likely that students who have experienced problems with their commutes are overrepresented in the sample of participants. On the other hand, students who are under the greatest time pressure may be less likely to participate in the online study. In this sense, the number of participants is not in itself sufficient to justify the assumption that the sample of participants is representative of all students at the university, let alone of students at other universities.

A more suitable investigation would include a sample of students from all departments, and collect data on a number of background variables. He or she could then track the attendance of students over a longer period, comparing the morning timetables and questioning why students choose certain lessons over others. The survey can provide starting points for further investigations and for everyday discussions about morning timetables. However, the results should not be used to predict the degree of improvement in attendance if every journey was to be less than 45 minutes. This would require evidence that is not provided by the current data.