Exploring student non-completion in higher education using electronic footprint analysis

1. Exploring student non-completion in higher education using electronic footprint analysis Dr John Buglear Nottingham Business School This work was supported by funding from the Staff and Educational Development Association (SEDA)

2. ‘The Origin of the Thesis’ • Retention matters but institutional retention data is unreliable • Why students leave is related to when they leave • Virtual learning environments are an intrinsic part of the modern undergraduate experience • From an academic management perspective tracking electronic engagement is more robust than physical registers of attendance • Electronic engagement data is an information resource capability for developing retention strategies

3. The studyBuilding on pilot research of business students (Buglear, 2009) • Final electronic engagement of first year undergraduates leaving their course in 2008/9 by type of leaver • The final electronic engagement by each leaver, the last login • The last visit to the university electronic environment as a registered user • Why first years? • Most students who leave prematurely do so in their first year • Defining types of leaver • Notifiers; the ‘decided’, those giving formal notification of their departure, recorded as e.g. ‘Transferred to other institution’, ‘Gone into employment’, ‘Other withdrawn’. • Non-notifiers; the ‘drifters’, those giving no such notification, recorded as e.g. ‘Written off after lapse of time’, ‘Dormant’. ‘Academic failure’ is included in this category as the last logins preceded the examination period.

4. The case study • Nottingham Trent University (NTU), UK • Student population of approximately 25,000 in 2008/9 • In 2008/9 nine schools located on three campuses

5. Results • Total last logins to May 2009 = 435 • 217 last logins in the first half year (October to January) • 228 last logins in the second half year (February to May) • Notifiers = 257 (59.1%) • Non-notifiers = 178 (40.9%)

6. Last logins over time

7. Last logins over time by notificationYes = notification of departure No = no notification of departure

8. Last logins by school and notificationTotalYes = notified departures from the school Total No = departures from the school not notified

9. First half year: 71/217 last logins were non-notifiers (32.7%)Second half year: 108/218 were non-notifiers (49.5%)Test for difference in proportions = 0, P-Value=0.000Difference is significant

10. Animal, Rural and Environmental SciencesDifference in proportions is not significant(Fisher’s exact test P = 1.000)

11. Architecture, Design and the Built Environment Difference in proportions is significant at 5%(Fisher’s exact test P = 0.016)

12. Art and DesignDifference in proportions is significant at 10%(Fisher’s exact test P = 0.098)

13. Arts and HumanitiesDifference in proportions is not significant (Fisher’s exact test P = 0.747)

14. Education Difference in proportions is not significant (Fisher’s exact test P = 0.384)

15. Nottingham Business SchoolDifference in proportions is not significant (Fisher’s exact test P = 0.286)

16. Nottingham Law SchoolDifference in proportions is not significant (Fisher’s exact test P = 1.000)

17. Science and TechnologyDifference in proportions is significant at 10%(Fisher’s exact test P = 0.099)

18. Social SciencesDifference in proportions is not significant (Fisher’s exact test P = 0.282)

19. Discussion • Financial aspect • Approximately 180 first year students drifted out of NTU programmes in 2008/9. • Consequent loss of tuition fee revenue ≈ £2m. • Pedagogical aspects • first-semester decisions to exit […] are most aptly characterised as driven by external factors’ (Peel et al., 2004) • ‘second semester [leavers] seemed more disillusioned and unhappy, […] expressing feelings of loneliness, isolation, and lack of recognition’, feeling that ‘lecturers were “never there” or “always regard failure with disdain” or “never gave me the help I needed” ’ (Peel et al., 2004)

20. Discussion • The Fitzgibbon and Prior (2003) timeline model • ‘Zone 1: enrolment, induction and the first two weeks of teaching’, • ‘Zone 2: late enrolment, late induction and early weeks of teaching’, • ‘Zone 3: middle to end of teaching period, first/second assessments’, • ‘Zone 4: final assessment period, revision and examination or assessment’ • Zone 3 is when ‘students who have poorly established […] study habits, really come under pressure’ and ‘students […] receive feedback from their first assignment [;] constructive feedback and reassurance is […] crucial’ • Yet by this stage ‘staff assume students have settled […] but this is frequently not the case [,] students are still seeking significant levels of contact with their tutors for a whole range of issues’

21. DiscussionRetention strategies • The Beatty-Guenter four-stage retention strategies model (1994) • Sorting students ‘into meaningful subsets […] to create strata that can be matched with appropriate targeted retention strategies’ • Supporting, ‘making it more likely that they will be able to maintain their status as students’ • Connecting, ‘bonding between a student and the institution’ • Transforming ‘students from uncommitted to committed, from uninvolved to involved, from passive to active, or from failure threatened to achievement motivated’ • How did we do? • Sorting – partially applied e.g. international students • Supporting – Welcome weeks, induction • Connecting and Transforming – assumed to be intrinsic

22. Conclusions • A significantly greater proportion of second half year leavers than first half year leavers didn’t tell us they were going • Considerable variation between schools • The majority, 60% of last logins before the examination period were by students who told us they were going, the ‘decided’ • The notification suggests some form of dialogue about their departure • The remaining 40% were by the ‘drifters’. • The lack of notification suggests an absence of dialogue about their departure • The extent of non-notified departure is the scope for pay-off from Zone 3 Connecting and Transforming strategies • Not the whole retention picture, but another perspective of it

23. References • Beatty-Guenter, P. (1994) Sorting, supporting, connecting, and transforming: Retention strategies at community colleges. Community College Journal of Research and Practice, 18, 113-129. • Buglear, J. (2009) Logging in and dropping out: exploring student non-completion in higher education using electronic footprint analysis. Journal of Further and Higher Education, 33, 381-393 • Fitzgibbon, K and Prior, J. (2003) Student expectations and university interventions – a timeline to aid undergraduate student retention[online]. BEST Conference: Creativity and Innovation in Academic Practice, Brighton, 9-11 April 2003. • Peel, M., Powell, S., and Tracey, M. (2004) Student Perspectives on Temporary and Permanent Exit from University: A Case Study from Monash University. Journal of Higher Education Policy and Management 26 (2), 239-249.