The document summarizes a pilot project that tested using a pre-arrival induction task through the university's student dashboard. The task involved students answering 6 questions before arriving on campus. The pilot found that students who completed the task had higher engagement with the dashboard, better progression to the second year, and higher average grades. It is an effective early predictor of students who may need additional support. The document recommends more fully integrating the task into course activities and providing follow-up interventions for at-risk students identified through the task.

1. Piloting of a pre-induction/induction activity through the
NTU Student Dashboard
Ed Foster, Rebecca Siddle
ABLE Project 2015-1-BE-EPPKA3-PI-FORWARD
STELA Project: 562167-EPP-1-2015-1-BE-EPPKA3-PI-FORWARD

2. Our Study
• Pre-arrival induction task
• 6 questions located in the NTU Student Dashboard
• Technical pilot
• Designed to:
• Make information available for future referral/ discussion
• Contextualize other data in the Dashboard (help relationship-building)
• Introduce students to the Dashboard
• Analysis of whether it could work as an early warning that
students might need further support?
• This session will:
• Outline our pilot
• Test the hypothesis whether or not it would work as an early warning

3. NTU Pre-induction Trial (2016)
Aspiration
Raising
Pre entry
&
Admission
Initial
Induction
First
year
Moving
through
the
course
Employ
-ment
Higher Education Funding Council Student Life Cycle Model (2001)
• All students at NTU are required to
complete a task prior to arriving on
campus
• Developed originally from Keenan
(2008)
• Essentially, only different because
completed in Dashboard
• Five 1st year courses took part (n=967
students, 307 completed)
• Computing
• Law
• History
• Environmental Science
• Youth Studies
• We will concentrate on results from
computing (n=322, 182 completed)

4. Diagnosing Student ‘Risk’
• Student
Background
• SE background
• Entry qualifications
• Issues
• Genuine gaps
• Blanket approach
• Risks stereotyping
• Student
Engagement
• Attendance
• Learning Analytics
• Issues
• Strong
personalized
predictor
• Institutional
infrastructure
• Academic
Outcomes
• Assessments
• Issues
• Often too late
• Formative/
diagnostic
assessment not
‘real’

5. Core Dashboard Process
Student
data
Engagement
with learning
Engagement
score,
Risk alerts
Referrals
Notes,
Sense
checking,
Referrals
Static/
manual
information
Algorithmic
engagement
data
Attendance
E-resources
Card swipes
VLE log ins
Dropbox
submissions
Library loans
!

6. The Task
Questions
1. What are you most looking forward to about
becoming an NTU student?
2. What are you most looking forward to about
starting your course?
3. How much do you think learning at University
is going to be different to your previous
studies?
4. Do you have any concerns about starting
University?
• If so, what are they?
• Based on how you normally overcome difficulties, how
do you plan to deal with these concerns?
5. What have you most enjoyed about your
previous studies?
6. There are many opportunities to make the
most of your time at University. What would
you like to achieve by the end of the year?
Pre-arrival
Complete the questions in own
time prior to arriving on campus
Stages
Initial induction
Discuss questions in groups as
part of timetabled induction
activity
First Year
Used in tutorial conversations
Reference point for tutors
Self-reflection point for students

7. Looking After Our Students

8. Students’ Answers
Major themes
similar to previous
studies
Fewer students
answered the
question about
anticipating
problems

9. Staff Feedback
• Computing
• Well integrated into the induction, activity led by student mentors
• Created second opportunity to complete the task in class during
induction week
• Limited follow up during tutorials
• Social Sciences
• Mainly used during mid-term review meetings
• Useful/ interesting, but concern that the students who needed it
most didn’t complete the task
• Environmental Sciences
• Deemed as a useful aide memoir for tutorial discussion, but
insufficient time to use properly

10. Research Methodology
• We were interested to compare the relationship between participating
in the activity or not with:
• Average engagement measured by the Dashboard
• Progression to second year
• Average grades
• However, completion rates varied between 8% and 67%
• We therefore focused on two large courses with good rates of
participation & will report on the computing courses today
• Any questions answered counted as participation
• We didn’t set a threshold for quality of responses

11. Interactions with the Student Dashboard
Took part in
activity?
Count of
students
% of students
Total number of
Dashboard log-ins
Average of number of
Dashboard log-ins
No 62 26% 2,157 35
Yes 173 74% 8,056 47
Grand Total 235 100% 10,213 43
New, first year undergraduates
(higher completion rate)

12. Student Engagement
(measured by NTU Student Dashboard)
13% 19%
71%
90%

13. Student Progression
32%
69%
15%
8%
21%
9%
32%
15%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
No Yes
%ofstudents
Student Progression (split by whether or not
students participated in the induction activity)
Progressing Progressing following referral Repeating Not Progressing
47%
77%

14. Grade Point Average
Mean
64.1
Mean
59.0
45%
65%
0%
20%
40%
60%
80%
100%
No Yes
%ofstudentswithGPA60+
“Good degree” equivalence

15. Student Background
• Background does appear to influence the likelihood of
answering the questions
• Male/ female students answered in very similar proportions
• Disabled students were more likely to answer
• However the following groups were less likely to complete the
questions
• Widening participation (poorer background)
• BTEC qualifications
• Overseas/ EU
• BME*
* = largest gap

16. Discussion
• Did the activity change student behaviour?
• We don’t believe so
• Similar findings to previous study into library support – engaged students
do better
• Realistically, these would have to be spectacularly good questions
• Was it well integrated into the courses?
• Not as well as we’d have liked
• Problem with a central team carrying out pilots in schools/faculties
• Need much greater time to work with course teams
• Does it work as a predictor?
• Yes, in this case study there is a strong association between completing
the task, engagement and success
• Engagement is a strong predictor of success

17. Recommendations
• This is an effective predictor of students who would benefit from
early interventions
• It could be well integrated into student/ staff Dashboards, but could also
stand alone if you don’t have the capacity/ interest
• As with all early warnings, ‘what next?’ becomes the crucial
question
• Tutorials
• Centralised specialist support
• Student mentors
• Self help resources

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