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    PreSS#, A Web-Based Educational System to Predict Programming Performance


    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

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    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:

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