1. Success against the Odds
Carol Calvert, Juliet Coleman, Rachel Hilliam Linda Brown

2. Summary The initial thinking
Can we help other students by learning messages from students who have succeeded, despite it looking unlikely that they would ?
The actual project
Qualitative and quantative approach with individual discussions , led by Al’s, with ten students on a level 1 Maths module and a level 2 Science module. “Top tips” shared with new intake of students
The strong theme was a “can do” attitude and the “spin offs”
Module team OU live introduction sessions
An additional joint study calendar
Early start from July on a J presentation

3. The initial thinking
The University has at least two models in use that in some sense aim to predict the probability that a student will “succeed”. The accuracy of those models is frequently expressed in terms of “do students predicted to succeed actually do so?”. But what if you considered it the other way around?
The aim of this project was to identify why some students succeeded even though the models predicted a relatively high likelihood of failure. The intention was to request students’ views as to why they felt they had succeeded, identify any common themes and use these common themes to inform and help future students.
Trying to access student views, given why we were asking those students, led to a conclusion that this had to take a semi structured interview approach with ALs who knew the modules concerned. The role of any quantative analysis was to support the main qualitative approach

4. The actual project (1 of 2)
Funding for the AL aspect of the work – eSTEem bid
Agreement from SRPP and HR ethics groups;
Recruitment of module chairs and identification of AL’s
Initial discussions with AL’s to establish framework, agree contact letters
Identification of students to be involved
Contact with students
Second phase of discussion with AL’s to review contact and discussions and look for emerging themes
Remaining contacts and write up and extraction of “top tips “ to pass onto new intakes
Addition of information on why the students had been identified by the model as having a low predicted probability of success
Final review of interviews and extraction of common themes

5. The actual project (2 of 2)
Predicted probabilities of success were generated after the first fee liability point. This effectively means that students were committed to the module. Students on the 2014J cohorts were selected on the basis that the predicted probability of passing the module was less than The selection of the October 2015 cohort students was similar but based on the probabilities that the student would still be enrolled on the module at the final fee liability point which was at the end of April In this case students were selected if the probability of still being present was less than 0.75 and they actually were still present.
This process generated a sample, for 2014J, of 49 for MU123 and for 2015J a sample of 58. The Science module, S207, in 2014 generated a sample of size 33,with a sample of 28 generated for S217 in 2015.
The student identifiers were checked by IET to ensure the students had not been involved in several surveys recently; or had asked not to be included in surveys; or should not be contacted for other reasons. This led to the removal of a very small number of students for each sample.

6. Student comments
Start early! Join a Facebook group. Pair up with a study buddy.
Don’t be afraid to try different ways of learning to see what works; Preserve with studies; You need a break sometimes
The module is doable as it takes you step-by-step through the concepts; If returning to study, don’t be too hard on yourself; Enjoy the module.
Be prepared to put in the work and you’ll enjoy it.
Don’t look too far ahead, just go through step-by-step; Stick to good Methodology; take a business-like approach.
Don’t be scared or threatened by it at the beginning, it is not as bad as it looks!

7. The strong themes and “spin offs”
The “Can do “ attitude – a very consistent theme
– The students interviewed had a very strong “can do” attitude and implied they just kept trying different things. So it seemed important to ensure students had a very good chance of knowing what different possibilities were on offer via the OU. We now have Module team introductions – run as pilot for M140 for 16J and all three level 1 entry modules ran in 17B. Plans are to do so and extend for 17J. The intention to show the range of materials the student can call upon. It is specific to the module but does not cover specific contents of module
- Growth mind-sets: An area to develop!
Get organised – In addition to the above sessions- which have a strong focus on the module study calendar we have added a Joint study calendar MST124 &M140 and run tutorials to coincide with that joint planner
Get ahead if you can - M140 early start programme – eSTEeM funded to offer an early start to registered students on M140 for 17J. It will be tutor supported and conclude when the main tutor allocation occurs in mid September

8. Further details Carol.calvert@open.ac.uk And some details on the model
Carol.Calvert (2014) "Developing a model and applications for probabilities of student success: a case study of predictive analytics" Open learning Vol 29,No2,
Interim write up
And growth mindsets
Dweck,C. RSA ANIMATE: How To Help Every Child Fulfil Their Potential
and at

9. Questions