Abejide Ade-Ibijola

How to cite: Van Lill, D & Ade-Ibijola, A 2026, ‘Sustainable community empowerment through coding and digital innovation’, in N Meyer, C Schachtebeck & M Venter (eds.), Sustainability and local economic development: Pathways to resilience and growth, Centre for Local Economic Development: Topics in Local Development Series, vol. 6, AOSIS Books, Cape Town, pp. 223–248.

Amid increasing global sustainability emphasis, there have been calls for universities to integrate sustainability into teaching curricula. Specifically, accounting disciplines are expected to groom and produce sustainability-conscious graduates, owing to accountants’ recognition as key players in advancing sustainable practice. Yet traditional accounting continued to struggle with integrating sustainability education, leaving students and graduates ill-equipped with the necessary skills to address sustainability challenges in the workplace. Using an AI-powered personalized pedagogical chatbot tool, this study introduces undergraduate accounting students to sustainability accounting concepts. Thereafter, we examined the chatbot’s effectiveness in enhancing sustainability accounting education to foster sustainability-conscious accountants. Guided by constructivist and human capital theories, the study employed a single-group pre-test/post-test pre-experimental design and survey instrument to gather perception-based data from 203 students at Kwara State University in Nigeria. Findings revealed a low baseline knowledge about sustainability accounting prior to chatbot intervention and a significant improvement in student performance post-intervention, indicating the chatbot was instrumental in fostering sustainability knowledge. Additionally, confirmation that the tool fosters active learning, knowledge and skills development, and enhanced employability value. This study contributes to sustainability accounting education and aligns with Sustainable Development Goals (SDGs) 4 (quality education), 9 (industry, innovation, and infrastructure), and 17 (partnerships for the goals). The study lends credence to aligning digital transformation with sustainability literacy, offering a transformative solution to the challenges of sustainability practice in the realm of accounting education in an emerging context. It has implications for higher institutions, government, education regulators, ministries, and professional bodies.

Arguably, the role of a postgraduate supervisor is aligned to support the student to think critically and be able to write academically, but not necessarily as a “proofreader” for checking spelling, grammar, or syntax inconsistencies. This process can be realised as an AI-based tool providing near–real-time automated feedback to students, whilst reducing academic workload pressures. This paper proposes a formal (referring to rules) based proofreading process for information extraction, recognition, and correction of meaningful text chunks, images or figures, and tables (referred to as document tokens) from research proposals. The ultimate objective is custom-fit automated generation of feedback across multiple sections of submitted research proposals for a large number of authors. To this effect, an AI-driven tool was developed to support the proofreading of research proposals by delivering timely, automated feedback at scale, named RX Autoproofreader. The tool’s test on eighty (80) publicly available research documents analysed for constituent parts recognition and proofreading in an algorithm programmed in a c# Visual Studio environment, which ran in 182 min, produced an average accuracy of 68%. During the test, the tool extracted and proofread a total of 14,231 document pages into meaningful items of title, author, supervisor, research date, aim, objectives, figures, tables, paragraphs, lists, headings, and page numbers. The recognition and extraction of unstructured texts into meaningful items is a document understanding task necessary for proofreading and feedback generation. It aims to complement existing spell and grammar tools for proofreading academic manuscripts.