Tailor GenAI chatbot onboarding, training, and support to identified adoption personas¶

Strategy · All strategies
Evidence · 2 claims (2 for) · 2 studies (2 associational), q2 · 1 of 2 report an effect size · 2 claims rest on one study

Description¶

The article recommends that institutions use persona profiles as the basis for differentiated implementation of GenAI tools rather than one-size-fits-all deployment. It states that the persona profiles "provide actionable guidance for tailoring chatbot onboarding, training and support to specific user needs", and urges universities to "go beyond one-size-fits-all implementations and embrace a more nuanced, evidence-based strategy for human-centered AI integration". The strategy operationalizes the persona framework for institutional deployment decisions.

Design Implications¶

Context¶

Requirements¶

• Requires institutions to first identify their own user personas using perceptual and contextual data before designing support

Constraints¶

• The article frames this as groundwork; it presents the personas from one dataset of 192 respondents and does not report testing tailored interventions

Target Learners¶

• higher education students
• higher education educators

Target Learning Goals¶

• effective and inclusive adoption of GenAI chatbots in higher education

Affordances¶

• Persona Centered Genai Adoption Framework

Claims¶

• Cluster analysis identifies four tentative moral response profiles: Comfortable Adopters, Guilty Non-Users, Cautious Users, and Morally Distressed Avoiders [+W]
• A four-cluster solution is optimal for segmenting higher education users' GenAI chatbot adoption perceptions [+W]

Related Strategies¶

• Tailor institutional GenAI training to teachers' prior GenAI use experience
• Provide differentiated scaffolding matched to teachers' behavioral-cognitive profiles when supporting multi-agent AI workflow design
• Typology-differentiated AI adoption policy interventions for education systems
• Deployment priorities for classroom AI feedback tools: latency ceiling, adaptive onboarding, and verifier transparency

Examples¶

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Key Sources¶

• Afef Saihi and Vian Ahmed. (2026). Uncovering adoption personas for generative AI in higher education: a clustering-based segmentation approach. International Journal of Educational Technology in Higher Education. https://doi.org/10.1186/s41239-026-00583-z