Tools
Tools
Groves, Timothy, Allison, Jordan 
ORCID: https://orcid.org/0000-0001-8513-4646 and El Masri, Omar ORCID: https://orcid.org/0000-0003-0554-590X
(2026)
AI-Assisted Analysis of PowerPoint Slides: A Methodological Approach to Decolonising Business Education.
Journal of Educational Computing Research.
doi:10.1177/07356331261468611
(In Press)
Preview |
Text
16419 Groves, T. et al. (2026) AI-Assisted Analysis of PowerPoint Slides - A Methodological Approach to Decolonising Business Education.pdf - Accepted Version Available under License Creative Commons Attribution Non-commercial No Derivatives 4.0. Download (3MB) | Preview |
Abstract
Despite growing calls to challenge epistemic inequalities within business education, there remains a lack of systematic and scalable approaches for identifying coloniality within routine curricular artefacts. This study addresses this gap by asking: How can a reproducible AI-assisted workflow be developed to identify and audit colonial markers within MBA PowerPoint lecture slides? This ‘Systems and Tools’ article adopts a sequential three-phase research design. First, a Colonial Markers Framework was developed through iterative expert review, AI-assisted analysis, and comparative thematic synthesis of MBA teaching materials from two programmes within a UK university. This process resulted in seven colonial markers relating to language and terminology, inclusivity and representation, capitalist and economic focus, Eurocentrism and Western dominance, epistemological dominance and knowledge production, historical context and oversight, and case study and example bias. Second, the framework was implemented within an exploratory Langflow-based workflow to assess the feasibility of automated colonial marker detection. While the approach demonstrated promising alignment with expert interpretations, technical limitations relating to document processing, citation accuracy, and workflow stability constrained its effectiveness. Third, insights from this exploratory phase informed the development of a more robust LangChain-Python workflow incorporating optical character recognition, automated reporting, structured data generation, and enhanced reproducibility. Findings demonstrate substantial convergence between AI-generated and expert-identified colonial markers, suggesting that AI can support the systematic auditing of teaching materials when guided by a human-developed analytical framework. Exploratory evaluation with MBA programme leads further indicated that the resulting outputs were interpretable, accessible, and useful as prompts for reflective curriculum review.
| Item Type: | Article |
|---|---|
| Article Type: | Article |
| Uncontrolled Keywords: | Decolonising the curriculum; Decolonising business education; Decolonising PowerPoint presentations; Colonial markers; Artificial intelligence; AI |
| Subjects: | Q Science > Q Science (General) Q Science > Q Science (General) > Q336 Artificial intelligence Q Science > QA Mathematics > QA76 Computer software |
| Divisions: | Schools and Research Institutes > School of Business, Computing and Social Sciences |
| Depositing User: | Kamila Niekoraniec |
| Date Deposited: | 08 Jul 2026 12:09 |
| Last Modified: | 12 Jul 2026 09:30 |
| URI: | https://eprints.glos.ac.uk/id/eprint/16419 |
University Staff: Request a correction | Repository Editors: Update this record
