Quille, Keith and Bergin, Susan and Mooney, Aidan
(2015)
PreSS#, A Web-Based Educational System to Predict Programming
Performance.
International Journal of Computer Science and Software Engineering (IJCSSE), 4 (7).
pp. 178-189.
ISSN 2409-4285
Abstract
PreSS# (Predict Student Success #) is a web based educational
system developed during the academic year 2013/14. This paper
describes the design and development, highlighting the
methodologies and architecture of the system. The system builds
upon the findings of a previous study undertaken by Bergin [1],
who successfully developed a semi-automated computational
model named PreSS that could predict a student’s academic
performance in programming with an accuracy of over 80% after
only 4-6 teaching hours. PreSS used a paper based data collection
method and the analysis of the collected data required manual
data entry thus making PreSS administratively heavy. PreSS# is a
system that accurately replicates the performance of PreSS with
95% confidence (P (value) = 1.0 and a T (value) = 0.0), is fully
functional and can compute predictions in real time with crossbrowser
(mobile and desktop) compatibility. PreSS# is scalable,
secure and robust allowing it to be employed across different
institutions, ultimately leading to an increase in progression rates
by identifying both struggling and gifted (students in danger of
becoming disengaged) students earlier than had been previously
feasible.
| Item Type: |
Article
|
| Additional Information: |
This work is licensed under a Creative Commons Attribution 3.0 Unported License. |
| Keywords: |
Web Based Application; Education; Learning;
Prediction; performance; |
| Academic Unit: |
Faculty of Science and Engineering > Computer Science |
| Item ID: |
6503 |
| Depositing User: |
Aidan Mooney
|
| Date Deposited: |
02 Nov 2015 16:54 |
| Journal or Publication Title: |
International Journal of Computer Science and Software Engineering (IJCSSE) |
| Refereed: |
Yes |
| URI: |
|
| Use Licence: |
This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available
here |
Repository Staff Only(login required)
 |
Item control page |
Downloads per month over past year
Origin of downloads
Altmetric
Altmetric