Thesis Title
Bounded inference in sequences: theory and evidence from news judgements

Research Description

Fletcher’s research focuses on how the order and diversity of online information shape attention, judgement, and belief revision when time and computation are limited. Focusing on news and political content, he studies how item ordering can yield the most learning for the least effort, and how these effects interact with the diverse prior beliefs people bring to decisions.

He uses large‑scale online experiments to manipulate sequence features—including misleading and emotionally provocative items—and measures when people shift from intuitive, cue‑driven judgements to focused deliberation, and how beliefs change as a result. To explain these shifts, Fletcher develops formal computational models of decision‑making and tests how adaptive placement of corrections and explanations can be timed to interrupt habitual responding and encourage more informed decisions for the public good.

Supervisors
Dr Damiano Spina, RMIT University
Dr Lauren Saling, RMIT University