Abstract

Content personalization or tailoring content as per the needs of users has been a focus of technical communicators’ work since a very long time. Recently, algorithms have helped trace users’ characteristics such as devices they use, platforms they work on, local language spoken, etc. to personalize content through strategies like responsive content, automatic translation and so on. AI tools have extended algorithmic capabilities for personalization, but at the same time increased the randomness of personalized content. That is, algorithms produce different results for the same user at different times or different results for different users at the same time with the same prompt thus shifting the agency of both rhetors (or content creators) and the audience (or content users). While conventional technical communication pedagogy has focused on writing for users, and more recently on writing for algorithms which serve the users, today it is crucial to understand how technologies like AI impact knowledge consumption processes from a user experience perspective? And how can we teach content personalization and adaptive techniques in the increasingly digital spaces of audience interactions? These questions motivated our research. To follow the roles of algorithms and technical communicators closely, we analyzed three different case studies where algorithms are responsible for a high level of personalization beyond the decisions made by technical communicators. Our findings suggest that we must teach students to investigate concepts such as user personas in UX for understanding audiences, several methods of decision-making for content assets, and rhetorical ecology for a holistic view of content production to dissemination.

Journal
Computers and Composition
Published
2026-03-01
DOI
10.1016/j.compcom.2025.102973
CompPile
Open Access
OA PDF Hybrid
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Citation Context

Cited by in this index (1)

  1. Computers and Composition

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