Guiding Educational Designers in partnership with Gen AI

An autoethnographic approach

Abstract

The journey to becoming an Educational Designer (ED) can be daunting – creating many feelings, the most popular of those being imposter syndrome (Pingo et al., 2024). These feelings, although mostly not validated, create subjective hindrances to participating in and contributing to the field (Sage & Sankey, 2021).

This poster explores a partnership with Generative Artificial Intelligence (GenAI) as a way to provide a scaffold for anyone new to the field. To do this, one of the author’s own journey to becoming an ED is used as an example to create a blueprint of how to navigate new terrain. By partnering with GenAI (i.e., ChatGPT), the authors use an emic lens to survey a journey through three distinct eras (Beals et al., 2020). These eras evolved from the intersection of professional, personal and environmental influences and captures a newcomers’ introduction to the field situated in the professional space of higher education.

The narrated data captured via subjective reflections of lived experiences, are transcribed and then partnered with ChatGPT to be thematically analysed. The authors then engage an etic lens to objectively use media (e.g., newspapers, magazines, videos, etc.) to illustrate the journey using the themes to gain more meaning towards personal agency for the profession (Méndez, 2013). 

This autoethnography creates great insight into how a newcomer can uniquely and individually create a self-serving map to increase a sense of belonging by partnering with a non-human intelligence tool. Using ChatGPT reduces the feelings of being judged – the feelings associated with imposter syndrome - yet creating a path that may not be seen without such an intervention.

By leveraging human-influenced algorithms almost like a mentor, GenAI can identify patterns and themes in the narratives that might be overlooked by human analysis – a symbiosis of autoethnography and GenAI (McNally et al., 2022).

Adopting autoethnography as a method to navigate professional, social and cultural terrains, via an emic and etic lens of lived experiences, personal vignettes and introspection provide the qualitative inputs to be examined and interpreted (Beals et al., 2020; Méndez, 2013). The second step in this research involves the use of GenAI as a tool for analysing and interpreting this self-reflective data (Boulus-Rødje et al., 2024). This research strategy holds relevance for educational designers and the wider community of third-space professionals, particularly those who may be new to the field or navigating a career transition. It will demonstrate the potential of GenAI as a tool for interpreting and applying autoethnographic data in a practical, actionable way.

The insights generated could inform the development of GenAI-driven tools and resources that support educational designers to develop their professional identity. By highlighting the value of transferable skills and experiences through a resulting blueprint, the mapping of the imposter-syndrome-like feelings among third space professionals could be mitigated. This will allow for transformations of self-perceptions to aid in the recognition of one’s unique contributions to confidently engage with the profession and the field.