‘Clumsy’ Methodology for Wicked Educator Management: A Predictive Tool to Uncover Blindspots from Conflicting Teaching Preferences

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Authors: Renjie Zheng, Tze-Hin Jawn Lim, Lishan Xue
Cited by: 0

Abstract

Module Leaders can appreciate that beyond managing students, a key ‘wicked’ problem is the challenge of managing the diverse teaching preferences of the faculty team. In our university-wide design innovation module, we uncovered a deeper wicked problem: conflicting teaching preferences amongst our team of full-time and adjunct faculty - leading to blind spots where module policies are misaligned with some of their teaching preferences. As such, we ask, how might we deploy or adapt existing frameworks or methodologies to help us pre-emptively uncover blind spots caused by conflicting teaching preferences, so that we can create consistency across classes, and minimize gaps in students’ learning outcomes? This study first investigated a data set of educator’s qualitative feedback through the analytical lenses of Mary Douglas's Grid-Group Typology. The results showed a framework that can shed light on the nature of their conflicting preferences and how ‘elegant’ (non-pluralistic) module policy blind spots lead to gaps in teaching outcomes. This study then investigated how this framework can be adapted to become a predictive tool to help module leaders uncover potential blind spots in their modules. The results showed a methodology that module leaders can deploy to uncover blind spots in both existing modules (through guided investigation of existing preferences data), and new modules (through guided reflection), so that they can implement ‘clumsy’ (non-elegant) policies to address conflicting teaching preferences before the next/new module starts. This paper concludes with an open invitation to collaborate on studies to test this ‘Clumsy’ Methodology in other educational contexts.

Fields of Study & Subjects

Evaluation of Teaching Practices Management and Marketing Education Higher Education Practises and Engagement

Publication details

Journal / source
Singapore Institute of Technology
Publication date
10 February 2026
Language
EN