As a literature graduate student in the late 1990s, I participated in a baffling seminar discussion on Lacanian semiotics. I didn’t get it, but an amazing tutorial video from EPIC 2016 prompted me to take another look at the power of visual and verbal cultural analysis.
During the workshop, we leaned basics tasks of semiotic analysis, including:
- Exploring gaps between intended meaning and experienced meaning
- Analyzing cultural assets to create codes
- Analyzing tensions to create semiotic squares
- Using a residual-dominent-emergent framework to analyze codes
- Field work to collect data to inform semiotic analysis
Culture Map of Mobile Learning
Since the workshop, I have been using what I learned to develop a semiotic map of residual, dominant, and emergent codes for mobile learning.
To develop this map, I conducted a visual analysis of many images on Google Images related to mobile learning. I used mobile learning and other broad key terms like “augmented reality” and “virtual reality” and “robots”. I explored a range of geographic markets as well. It was far from a scientific sample, but it was fun.
I used Pinterest to gather the images and Mural as a platform to group and cluster the images.
10 Mobile Learning Codes
- Learn Alone Together (Residual)
- Access the World From Anywhere (Residual)
- Gather Around a Screen (Residual)
- Augment how You Live (Dominant)
- Simulate a Situation (Dominant)
- Augment your Experience of Here (Dominant)
- Try Immersive Learning (Emergent)
- Wear Your Learning (Emergent)
- Integrate Learning into Yourself (Emergent)
- Interact with Robots (Emergent)
4 Mobile Learning Spaces
I created the culture map by iteratively positioning the codes on semiotic squares constructed using cultural tensions that emerged through exploring the visual data. These tensions included:
- Familiar / Unfamiliar
- Augment / Integrate
- Create / Consume
- Ready at Hand / Present to Hand
- Private / Public
From playing with the coded and tensions, I developed the following four quadrants on my semiotic square:
- Become a Cyborg (Unfamiliar / Private)
- Engage with the Machines (Unfamiliar / Public)
- Use the Data (Familiar / Private)
- Mediate Together (Familiar /Public)
This thought experiment has been a fun way to apply my learning. Since doing the initial semiotic exploration, a couple of additional ideas occurred to me:
- Semiotics aimed at settings has great potential as a tool for analyzing learning settings. I am intrigued by Bonnie Shapiro’s work on analyzing sustainability in learning settings. Laura Oswald‘s case studies on analyzing retailscapes with semiotics points to the potential for using semiotics to analyze learning settings (e.g. programs and learning spaces) in comparison to competitive and aspirational programs.
- Where do emergent products like smart speakers, particularly niche products like the Amazon Echo Look, fit on within the frame of mobile learning. They are likely somewhere between dominant and emergent because they are still relatively unfamiliar and sit somewhere on the boundary between public or private?
- What might happen if I took an explicitly critical frame and asked how these products vary on their representation of domestication vs. liberation. Most images promise a dream of endless open knowledge, and most images represent scenes of social control (students being disciplined by lessons in formal learning settings or people being domesticated by new technological forms). I recognize my initial sample had scant examples of mobile learning in the context of non-formal learning settings beyond the cliched coffee shop or non-spaces of everyday life (e.g commuting).
The workshop has prompted me to start reading more in the domain of semiotic marketing analysis and qualitative marketing analysis. I have been diving into the work of Laura Oswald, The Handbook of Qualitative Marketing Research, and Tim Stock‘s culture mapping.
If you are interesting in applying semiotics to analyze a learning setting, I would love to hear from you.