Our new research report, Learner Personas: The Human in the Experience, takes us back into design territory. Using personas – archetypes of “typical” learners – in making design decisions is hardly a new idea. But it has had its problems: reliance on belief rather than data, the risk of stereotyping and bias, difficulty with validity, and the real danger of missing issues with things like accessibility. And the process of developing personas can be cumbersome and time consuming. But the age of data is helping to change that.
Learner Personas: First, find the facts
While instructional designers have probably always worked from some notion of their target audience in terms of personalities and beliefs, the idea of more intentional development and use grew out of ideas from both marketing and Universal Design (UX). They can be a useful tool for learner analysis and consequent design of learning experiences and, as I discuss at more length in the report, this helps to address a gap I have found in much of the research I’ve reported on these past few years. That’s designers working from assumption and stakeholder and SME-provided “facts” about learners that may be more fictional than real. (My own favorite, from years ago in state government: The SME from the Safety office who said with great confidence, “Blind people will never need this training.” The target audience included our school for the blind, staffed by faculty who were blind.) As I’ve written elsewhere we’ve found that designers sometimes don’t know how or where to find more data, even from places like the LMS, and perhaps don’t know how to use the data they do find.
Learner Personas: Still relevant?
The report attempts to answer a couple of questions: What are the whats, whys, hows, and good practices for developing and using learner personas? And in the age of analytics, Big Data, and AI, are they still relevant? To this latter question authors say yes, for a variety of reasons. Preeminent personas researcher, the University of Vaasa’s (Finland) Joni Salminen (et al.) offers ways advances with data solve some of the historical problems with creating personas:
- Use of analytics speeds up the process of data gathering from months previously required by ethnographies and surveys.
- The ability to infer behavioral data (such as video viewing habits) rather than gather self-reported information provides information less susceptible to bias.
- Data can be drawn from the whole user base, eliminating the issue of representativeness of the sample; they say: “Using online analytics data potentially solves the trade-off of relying on either qualitatively rich but non-verifiable data or using numbers that are accurate but lose the immersion of another human being” (p.55).
Available data help overcome the “file drawer effect” of personas remaining static once they are developed.
Additionally, advances in data help minimize the subjectivity of prediction, which an algorithm can manage as a numerical problem.
For a nice overview of the ways designers in even small organizations can make better use of technology and data to inform development and use of personas, see Danielle Wallace’s recent article Transform Training with AI-Powered Learner Personas.
Learner Personas: A powerful addition to the designer’s toolkit
Learner personas can be a powerful addition to the designer’s toolkit. Viewing them as data-based tools supported with data analytics, machine learning algorithms and generative AI can extend our ability to enact skillful work. For more on what the research says, along with recommendations for practice, real-world cases, and suggestions for additional reading please see The Learning Guild’s July 2024 research report Learner Personas: The Human in the Experience.
Reference:
Salminen, J., Jansen, B. J., An, J., Kwak, H., & Jung, S. G. (2018). Are personas done? Evaluating their usefulness in the age of digital analytics. Persona Studies, 4(2), 47-65.