Abstract:

During this presentation I will showcase aspects of an eLearning collection that I curated over three years. The collection houses best practices. I will also reflect on the project’s goals and process. As learning technologist at a university of technology in South Africa, I investigated how I could remain a step ahead and help grow eLearning practices without distracting teaching staff who juggle large classes, overloaded timetables, curriculum renewal and research projects.

There is a proportion of educators who feel they have insufficient exposure and this impacts on their confidence. On the other hand, some continue to innovate under trying circumstances. I searched for ways to enable sharing, recognition and modelling.

Over three annual cycles, combining methodologies such as design thinking, auto-ethnography and poetic inquiry, I developed {engage > make > cast > rate}. This is an adaptation and extension of the Stanford d.school’s {empathise > define > ideate > prototype > test}.

Rating the work showed the following benefits, among others:
ENGAGE: Restricting my work to a tablet and phone taught me to grasp cloud concepts and mobile ecologies. Becoming guerilla technologist and technology ethnographer, I understood users’ frustrations, challenges and dreams. I learnt about writing engaging stories.
MAKE: I made an eLearning collection to promote a spectrum of solutions to a range of educational problems. These nuances don’t show up in analytics. I learnt the craft of curating open educational resources.
CAST: By promoting practitioners’ work through asynchronous, synchronous and face-to-face modes, they became aware of each other’s work. Sharing occurred across disciplines, campuses and continents. The eLearning collection is available for posterity. Casting / promoting fits into the communities of practice and “working out loud” ethos.

The paper is embedded in epistemologies of hope and imagination. The investigation generated thick data, then I employed auto-reflexivity as method of analysis to share tips, obstacles and design criteria. At times poetic analysis is used to gain insight into auto-ethnographic observations -- a student’s voice about the digital divide and my own observations on academic life in the mobile age here at a South African university of technology.

Keywords:

e-learning professional development, learning technology, design thinking, auto-ethnography, poetry.