Naslov
STUDENT RETENTION USING ADVANCED LEARNING VALIDATION SOFTWARE TOOL AND EDUCATIONAL DATA MINING: A CASE STUDY

Autori
Mutka, Alan ; Zivkovic, Fatima ; Breka, Mislav ; Zagar, Martin

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
INTED2023 Proceedings / - : International Academy of Technology, Education and Development (IATED), 2023, 8492-8496

Skup
INTED 2023

Mjesto i datum
Valencia, Španjolska, 06.03.2023. - 08.03.2023

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
Learning validation, synchronous assessment, academic integrity, data mining, retention, higher education.

Sažetak
The main objective of higher education is to provide quality education to students. An approach to achieving the highest quality of education is by discovering a model for prediction and prevention regarding the variables affecting the retention rates of students. Student retention is a crucial educational measurement metric, as retention rates accumulate as students re-enroll from one academic year to the next. Institutions obtain retention if it provides appropriate support and teaching methods among the various practices to prevent student deferment. This paper examines the validated learning metrics acquired using AssessMe, an advanced software solution, in the Programming I and II courses at the Rochester Institute of Technology in Croatia and presents a predictive model for student retention management. Given new records of incoming students, the predictive model can produce an accurate prediction identifying students who require additional support. Moreover, the software tool aids in facilitating students' personal development.

Izvorni jezik
Engleski

Znanstvena područja
Računarstvo

POVEZANOST RADA