Learning and teaching fully online is a challenging task as it requires maximum engagement with fellow students and the course convenor to create a sense of online community among distance learners.
Project Description:
Learning and teaching fully online is a challenging task as it requires maximum engagement with fellow students and the course convenor to create a sense of online community among distance learners. The growing number of enrolments to cyber security postgraduate programs (125% increase since 2016) brings yet another layer of challenges for course convenors in fostering students' collaborative learning in the online Moodle environment. This project aims to research on how to maximize student engagement online, develop a novel Machine Learning (ML) based approach to predict the students' final grades and evaluate this approach by incorporating various inputs which are collected during students' collaboration in the online platform.
Description of Work:
Literature review.
Design of surveys, and statistical analysis of survey data.
Design of interview protocols and interviewing, qualitative and/or quantitative analysis of interview data.
Conduct the data analysis correlation and verification using ML techniques.
Thus, ML and AI skills are essential for this project.
Contact:
Elena Sitnikova e.sitnikova@unsw.edu.au
School of Engineering & IT