Application of Knowledge Graphs with the Theory of Planned Behaviour to Assess Learners’ Willingness to Pursue Sustainability Education

Aim/Purpose The paper aims to identify opportunities within the Bachelor of Business (BBus) degree of RMIT for learners to gain sustainable and ethical knowledge. Background The paper explores how students are offered sustainable and ethical courses related to the BBus programme, particularly the courses in social impact. The paper seamlessly integrates the knowledge graph with the theory of planned behaviour to graphically present the relationships between learners’ attitudes, subjective norms, perceived behavioural control, and sustainability education choices. Methodology The paper adopts illustrative and case study approaches to describe the opportunities provided to learners to gain sustainable and ethical knowledge through the Social Impact major of the BBus degree. It shows a descriptive analysis of the list of courses offered for the award of the BBus of RMIT. The data used in this paper are collected from existing students’ records of RMIT and presented in tables and chart format. Contribution The paper steps beyond the traditional survey-based Theory of Planned Behaviour studies by incorporating structured and unstructured data sources for more robust analysis. The paper provides a framework that can be adapted to various educational contexts and sustainability domains, contributing to broader research on educational behavior modeling. Findings Bachelor of Business graduates of RMIT are identified to offer at least one Social Impact unit to enhance their sustainable and ethical knowledge. Attitudes influenced the willingness of students to acquire sustainability knowledge. Future Research The next part of this research will address the second and third research questions and integrate the knowledge graph with the theory of planned behaviour to offer dynamic models to predict learners’ willingness. This approach would provide actionable insights for targeted interventions.