This study examined the relationships between attendance, online engagement, and assessment outcomes in undergraduate students across multiple universities. The study found that continuous assessment was the most predictive of outcomes for new entrants, while online activity was most predictive for repeating students. For new entrants, online activity had a larger effect size than physical attendance. The study noted that non-attendance is a symptom and that identifying underlying individual issues is essential to allow for early intervention.

1. Examining the relationships between attendance, online
engagement and assessment outcomes in undergraduates; an
observational prospective, multicentre study.
Jane Holland*, Eric Clarke*, Morag Monro , Evelyn Kelleher , Mark Glynn 
*RCSI Dublin, DCU Dublin
Funded by 3U Partnership
N-STEP Strand 1 Initiative

2. Non-attendance:
 Correlates with poor performance (1)
 Non-anglophones(2)
 Understanding & conceptualisation(3)
 Identifying individual cause is essential (4,5)
Monitoring:
 Time-consuming & potential for recording errors
 Software / biometrics –cost considerations
 Reports & logs
Background & Literature
1. Massingham, 2006
2. Gatherer, 1998
3. Sharma, 2005
4. Dobkin, 2007
5. Rodgers, 2002
Funded by 3U Partnership
N-STEP Strand 1 Initiative

3. o Ethical approval obtained
 RCSI - REC848
o Data collection
Methods
Funded by 3U Partnership
N-STEP Strand 1 Initiative

4. Physical
attendance
Online
activity
Continuous
assessment
Summative
examination
NM
New entrants (n=329) 8 24 2.9% 63.5 %
Repeat (n=29) 7 14 2.3% 54.4 %
AS
New entrants (n=329) 12 25 2.9% 66.3 %
Repeat (n=29) 8 15 2.3% 55.8 %
Results – Descriptive statistics (1)
Funded by 3U Partnership
N-STEP Strand 1 Initiative
JC-NM
0 10 20 30 40 50 60 70 80 90
<20
21-24
25
New JC1 Repeating JC1

5. Results – Descriptive statistics (2)
Funded by 3U Partnership
N-STEP Strand 1 Initiative
Physical
attendance
Online
activity
Continuous
assessment
Summative
examination
NM
New entrants (n=329) 8 24 2.9% 63.5 %
Repeat (n=29) 7 14 2.3% 54.4 %
AS
New entrants (n=329) 12 25 2.9% 66.3 %
Repeat (n=29) 8 15 2.3% 55.8 %
*
* p< 0.005
Mann-Whitney U
JC-AS
0 10 20 30 40 50 60 70
<20
21-25
26
New JC1 Repeating JC1

6. Physical
attendance
Online activity
Continuous
assessment
NM
New entrants R2 < 0.1 R2 < 0.1 R2 = 0.54
Repeat No correlation No correlation R2 = 0.22
AS
New entrants R2 < 0.1 R2 = 0.12 R2 = 0.58
Repeat R2 = 0.17 R2 = 0.21 R2 = 0.15
Results – Regression analysis
Basic assumptions confirmed
Tests for tolerance & VIF- no evidence of multicollinearity
*? Late arrival due to appeals
*
Funded by 3U Partnership
N-STEP Strand 1 Initiative

7. CA
NM AS
Funded by 3U Partnership
N-STEP Strand 1 Initiative

8.  New entrants
o Continuous assessment most predictive
o Online activity – larger effect size than physical attendance
 Repeat students
o Outliers - High risk
o Online activity most predictive
Summary of results
Funded by 3U Partnership
N-STEP Strand 1 Initiative
Caveats & Conclusions...
Caveat – correlation does not equal causation
Non-attendance is a symptom – individual diagnosis & management of
underlying issues is essential...
Developing a screening program for early identification allows early
intervention

9. 1. Massingham P, Herrington T. Does attendance matter? An examination of student
attitudes, participation, performance and attendance. Journal of university teaching
& learning practice. 2006;3(2):3.
2. Gatherer, D., & Manning, F. C. (1998). Correlation of examination performance with
lecture attendance: a comparative study of first-year biological sciences
undergraduates. Biochemical Education, 26(2), 121-123.
3. Sharma, M. D., Mendez, A., & O’Byrne, J. W. (2005). The relationship between
attendance in student‐centred physics tutorials and performance in university
examinations. International Journal of Science Education, 27(11), 1375-1389.
4. Dobkin C, Gil R, Marion J. Causes and consequences of skipping class in college:
Mimeo, UC Santa Cruz 2007.
5. Rodgers JR. Encouraging tutorial attendance at university did not improve
performance. Australian Economic Papers. 2002;41(3):255-66.
References
Funded by 3U Partnership
N-STEP Strand 1 Initiative