Autumn 2007
ISSN 1477-1241

Why do Foundation Year Students Fail to Attend their Classes?

A model of the poor attendee.

Background

The University Foundation Year (UFY) was designed for students from a variety of academic, experiential and social backgrounds. It prepares students with a vocation in a particular discipline, but who do not have the necessary requirements for direct entry onto a degree programme, for progression to a linked degree at Manchester Metropolitan University.

Attendance monitoring forms an important part of the UFY’s Student Success Strategy. It provides a measure of student motivation and engagement and is an excellent indicator of future success – entry qualifications are irrelevant at this level (Figure 1).

Figure 1: Effect of attendance on success

A register is submitted to the UFY office for each unit each week and the data entered onto a central database. This database allows us to review attendance in a number of ways to facilitate both programme management and identification of at-risk students: by unit, by student and by percentage non-attendance.

Intervention takes the form of letters and/or interviews depending upon the actual level of attendance. The protocol followed has been modified over the years as a result of evaluation of its effectiveness against cost in terms of academic staff time. Evaluation has demonstrated a measurable improvement in overall student success rates and an improvement in attendance amongst those students with the poorest attendance.


Aims of Attendance Research Project

  • To investigate the underlying reasons for poor attendance.
  • To identify any pre-determined risk factors which could be used to inform student support strategies.

 

Methodology - Target Groups

It was decided that as well as collecting data on the whole student cohort, several specific groups identified as part of the normal attendance monitoring process would also be targeted for further analysis:

  • Whole UFY student cohort as of October 2005 (677 students)
  • Students with 15-35% attendance on 14/11/05 (87 students)
  • Students with less than 15% attendance on 14/11/05 (40 students)

In addition students were grouped by age at entry and whether or not they lived at home.

 

Methodology - Data Collection

Data were collected from both primary and secondary sources as follows:

1. Questionnaires

These were adapted for each target group to identify factors affecting attendance and the degree of self-awareness students had regarding their true level of attendance. They included:

  • a whole student cohort questionnaire, completed in the core unit in October 2005. A total of 246 responses were obtained, representing 36% of the cohort.
  • an attendance interview questionnaire, completed in interviews with students exhibiting 15 – 35% attendance. This questionnaire contained sections to be completed by both students and interviewers. Thirty five responses were obtained, representing 50% of interview attendees.
  • a very low attendee questionnaire which was sent to the home address of students with less than 15% attendance. None were returned.

2. Programme management databases

These were used to:

  • analyse cohort registration data to identify any link between age of student and levels of attendance
  • analyse cohort registration data to investigate whether local students commuting to University from home are more or less likely to attend than non-local ones living in student accommodation
  • analyse Guidance Manage emails relating to low attendance
  • compile results of attendance monitoring exercise to identify effectiveness of current intervention activities.

All questionnaires were completed anonymously and none of the data collected for analysis allowed for identification of individual students.

 

Results

The results of these analyses are shown below.

1. Does age affect attendance?

Two thirds of UFY students in this study were under 20 and came to MMU straight from secondary or further education (Figure 2a). However, if we exclude the over 30’s, almost identical proportions of each age group fell into the 35 to 50% and 15 to 35% attendance categories (Figure 2b) indicating that attendance was not simply a matter of maturity. Interestingly the students exhibiting the worst levels of attendance were actually in the 20 to 23 year old group. In the under 20 group, 68% had an attendance record of at least 50%, however this age group also represents the students most likely to withdraw from or suspend their studies (16%).

Figure 2a                               Figure 2b

Does living at / away from home make a difference to attendance?

The UFY student cohort had an almost 50:50 split of students who had moved to Manchester to study and those who were local and commuted in on a daily basis. There was no significant difference in attendance levels (or indeed withdrawals or suspensions) (Figure 3).

Figure 3: Effect of residency on attendance

How does paid employment affect attendance?

The need for work has often been postulated as having a major impact on student attendance. Students were asked whether they were in employment, the hours they worked, whether it had impacted upon their studies, and if not in employment whether they were looking for paid work.

Of the 102 students in employment who provided information on working hours, the majority worked between 10 and 20 hours per week. Just under half (45%) felt that working had had an impact on their studies.

Figure 4 compares the responses from the cohort as a whole with that of students interviewed as a result of poor attendance. Contrary to expectations students with poor attendance levels were less likely to have, or be looking for, employment than the rest of the cohort. It is more than likely therefore that it is not employment as such which is preventing attendance but that the factors affecting a student’s ability or motivation to attend classes also affect their ability or motivation to work.

Figure 4: Does work affect attendance?

Is attendance affected by students’ levels of motivation and confidence?

Student engagement with their programme of study is strongly affected by their level of motivation. Their decision to enrol on a UFY may have been influenced by many factors – not all of them positive. For example approximately half of the cohort is recruited during Clearing – many of these students therefore have come to UFY having failed to achieve the grades for entry needed for their original choice.

As motivation is difficult to quantify students were asked whether their motivation to study had changed since starting their courses (Figure 5a). Most declared they were either as motivated or more so since starting their course. Interestingly the interviewed students (those with 15-35% attendance) were the most positive – either they were expressing views they thought their interviewers wished to hear or being identified as not attending and being called for interview had reignited their motivation to be on the course.

Figure 5a: Change in motivation

UFY students are often characterised by their low levels of self esteem and confidence to succeed. Both of these factors can directly impact on their level of engagement. However there were no significant differences exhibited by students called for interview because of low attendance and that of the whole cohort (Figure 5b). However these levels of confidence were not shared by the interviewers - 72% of interviewees were confident they would pass, interviewers were only confident that 46% would. In fact only 34% of these students did actually pass.

Figure 5b: Confidence to suceed

Why do students come to University?

We asked the two groups to rank from a list of 12 the top three reasons they had decided to come to University. These rankings have been combined and expressed as an overall percentage of all the combined returns in Figure 6. For both groups the same four categories came top although there was variation between the groups in their rank order. The control group placed most importance on career prospects with this coming top of the individual (42% put it first) and combined rankings. Interest in the subject came second.

Figure 6: Why did students come to University?

Only 26% of the poor attendees interviewed ranked career prospects first, instead 65% put interest in the subject as the main reason. For many UFY students less than half of their programme is in subjects with direct links to their degrees with the remainder being in supporting skills-based units and electives. Perhaps students who are at University to further their career prospects are more likely to take the long term view of the value of such studies than those whose primary reason for being at University is simply to study a subject they enjoy.

What reasons do the students give for not attending?

The two groups (plus interviewers) were asked to rank the top three reasons from a list of 16 why they did not attend classes. Again these rankings were combined (Figure 7). In the general cohort there were two top ranking categories – “family obligations” and “laziness” (16% each) However when rankings are combined “illness” comes out top (14%), “family obligations” falls to 4% overall but “laziness” remains high at 12%. “Time of lecture” was the third most common reason (10%) when combined and fourth most common as a primary reason. Interestingly “employment” came third as a primary reason (9%) but second to bottom (2%) when rankings are combined.

Figure 7: Reasons given by students for not attending

In the low attendees group there was little variance in the students’ and interviewers’ opinions about the reasons for non-attendance with the exception of “laziness”. Most stated “family obligation” as the primary reason for not attending with “illness” coming second. “Time management” was the main second rank reason and “laziness” third.


How do the students think attendance can be improved?

Question 8 of the questionnaire completed by the whole cohort asked students to name one thing which the University could change to improve attendance. Responses were then collated into different categories (Figure 8). Interestingly, despite these areas not being identified as being in the top three ranked reasons for non-attendance, half of the suggestions related to changes in the times of lectures and the syllabus. This is probably because they recognise that the main reasons for non-attendance fall outside of the influence of the University or UFY.

Figure 8: One change to improve attendance

A quarter of students suggested that a change in the time of lectures would improve their attendance, with 23% wanting to have no early morning lectures or wanting more afternoon lectures. Efficient space utility of teaching rooms reduces the scope for much change here.

A further 25% wanted changes in the syllabus. As mentioned earlier, less than half the programme of study for many UFY students is in subjects with direct links to their degrees. Students often fail to see the value of some of this supporting study.

The next most popular category of suggestion was to avoid timetable gaps, with 13% of students saying this would improve attendance. Centralised timetabling and an intelligent use of timetabling packages would certainly be of assistance here.

Conclusions and Recommendations

There is a clear link between attendance and attainment thus an understanding of the issues affecting attendance can potentially indicate areas upon which to focus resources and further research. Although this study was carried out on Foundation Year students its findings will also undoubtedly apply to most first year cohorts across the University.

The factors identified as affecting attendance are summarised below:

  • The group exhibiting the worst levels of attendance were in the 20-23 age group.
  • Whether a student lived at or away from the parental home made no difference to levels of attendance.
  • Students with poor attendance levels were less likely to have, or be looking for, paid employment than the rest of the cohort. However there were no discernable differences in motivation and confidence levels as measured by this study in the two groups.
  • Students with good levels of attendance were more likely to have decided to come to University to further their future career prospects than poor attendees. Poor attendees were more likely to have come to University because of interest in the subject alone.
  • Many of the primary reasons for poor attendance were outside of the immediate control of the University (for example family obligations, illness). Poor attendees were more likely to present with domestic obligations, illness and financial worries that prevented them from attending.

It is our hypothesis that the cause of many of the factors we have detailed that characterise the poor attendee is poor time management. Poor attendees struggle to combine paid employment with their studies and when difficulties present they are less capable of juggling their responsibilities.

We would therefore propose that the University routinely put measures in place to help these students cope better and regain a more productive study/life balance. These measures include:

  • Early identification of at-risk students by attendance monitoring.
  • Recognition of specific risk factors from intervention / progression interviews.
  • Referral to specialist staff where appropriate.
  • Courses to include greater focus on providing time management skills and career planning.
  • “Intelligent timetabling” – avoid timetable gaps, condense provision to three or four days per week.

About the Authors

Nicola Hughes and Pauline Hearn
Department of Combined Honours and Foundation

e-mail: n.t.hughes@mmu.ac.uk
e-mail: p.hearn@mmu.ac.uk

Annabel Latham
Department of Computing and Mathematics Studies

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