| 72378 |
Creator |
c9d52ef4a11ad1277436a89c20d0a5d4 |
| 72378 |
Creator |
a9a97ac58a1dd64befd06ad78f505793 |
| 72378 |
Creator |
b6986f808e4858b950e798c2d78784de |
| 72378 |
Creator |
53ef08d464d2da571ab07b90e5a01815 |
| 72378 |
Creator |
ce6380dbaaf961bb95b31b9b1cf9d808 |
| 72378 |
Date |
2020 |
| 72378 |
Is Part Of |
repository |
| 72378 |
Is Part Of |
p19297750 |
| 72378 |
abstract |
Despite the potential of Predictive Learning Analytics (PLAs) to identify
students at risk of failing their studies, research demonstrating effective
application of PLAs to higher education is relatively limited. The aims of this study
are 1) to identify whether and how PLAs can inform the design of motivational interventions
and 2) to capture the impact of those interventions on student retention at the Open
University UK. A predictive model — the Student Probabilities Model (SPM) — was used
to predict the likelihood of a student remaining in a course at the next milestone
and eventually completing it. Undergraduate students (N=630) with a low probability
of completing their studies were randomly allocated into the control (n=312) and intervention
groups (n=318), and contacted by the university Student Support Teams (SSTs) using
a set of motivational interventions such as text, phone, and email. The results of
the randomized control trial showed statistically significant better student retention
outcomes for the intervention group, with the proposed intervention deemed
effective in facilitating course completion. The intervention also improved the
administration of student support at scale and low cost. |
| 72378 |
authorList |
authors |
| 72378 |
issue |
2 |
| 72378 |
status |
peerReviewed |
| 72378 |
uri |
http://data.open.ac.uk/oro/document/1223254 |
| 72378 |
uri |
http://data.open.ac.uk/oro/document/1224583 |
| 72378 |
uri |
http://data.open.ac.uk/oro/document/1224584 |
| 72378 |
uri |
http://data.open.ac.uk/oro/document/1224585 |
| 72378 |
uri |
http://data.open.ac.uk/oro/document/1224586 |
| 72378 |
uri |
http://data.open.ac.uk/oro/document/1224595 |
| 72378 |
uri |
http://data.open.ac.uk/oro/document/1240864 |
| 72378 |
volume |
7 |
| 72378 |
type |
AcademicArticle |
| 72378 |
type |
Article |
| 72378 |
label |
Herodotou, Christothea ; Naydenova, Galina ; Boroowa, Avinash ; Gilmour, Alison and
Rienties, Bart (2020). How Can Predictive Learning Analytics and Motivational Interventions
Increase Student Retention and Enhance Administrative Support in Distance Education?
Journal of Learning Analytics, 7(2) pp. 72–83. |
| 72378 |
Title |
How Can Predictive Learning Analytics and Motivational Interventions Increase Student
Retention and Enhance Administrative Support in Distance Education? |
| 72378 |
in dataset |
oro |