Work | Ciro Annunziata

Ciro Annunziata

UX Researcher

I explore how people learn, stay motivated, and grow in confidence.

I help teams turn insights into thoughtful product decisions.

Portfolio Highlights

A person sits at a white desk working on a laptop, resting their chin on one hand while using the trackpad with the other. A smartphone and a glass sit nearby, with indoor plants and soft lighting in the background, creating a calm, focused workspace.

Defining the Aha Moment in the Era of AI

A multi-phase research programme investigating when learners recognise value in AI-powered language learning — and why strong aha moments don’t always translate into Premium intent.

1
Led a four-phase programme combining usability testing, interviews, and surveys across Free and Premium users
2
Found that AI features trigger strong aha moments, but limited discoverability and clarifying framing reduce impact
3
Shaped Premium messaging, tier differentiation, and roadmap priorities for AI and vocabulary review iteration in H1 2026

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Understanding How Learners Use Community Exercises at Scale

A large-scale behavioural analysis of Community exercise submissions, examining how learners actually use social learning features — and why many fail to deliver meaningful learning without clearer structure, guidance, and placement.

1
Analysed 160k+ Community submissions across English and Spanish to uncover real usage patterns
2
Identified distinct learner behaviours revealing misalignment between task design and learner expectations
3
Informed clearer guidelines for when and how Community exercises should be introduced to support meaningful learning

A person wearing glasses studies at a small table, writing notes in a notebook placed on top of an open book. A tablet displaying highlighted text and a black mug sit nearby by a window with sheer curtains, creating a quiet, focused study atmosphere.

Understanding Learner Motivation Over Time

A 4-week diary study exploring how adult language learners stay motivated, build habits, and experience AI-supported learning in everyday life.

1
Led a longitudinal diary study with 26 learners (A1–C1), combining in-context self-reports and product analytics
2
Identified strong intrinsic motivation alongside a clear mid-journey dip, revealing key moments for product intervention
3
Informed AI feature expansion and prioritisation across Q3–Q4 2025

A person sits at a table reviewing printed documents and writing notes with a pen. A laptop, calculator, glasses, and a drink are arranged nearby, with plants in the background, suggesting a focused work or study moment in a bright, calm setting.

Measuring Learning Impact at Scale

A large-scale efficacy study translating independent learning outcome data into actionable product insights, helping ground AI and Premium strategy in evidence rather than assumptions.

1
Led internal research synthesis and product interpretation of a six-language efficacy study conducted with an external research team
2
Analysed learning outcomes across 1.200+ users using pre/post testing, study time, and feature usage data
3
Informed evidence-based product strategy around AI features, Live Lessons, and Premium positioning

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When AI Promises Learning — and Learners Expect Proof

A mixed-methods study evaluating whether AI-powered mistake review delivers meaningful learning and how trust, relevance, and visible progress shape perceived value.

1
Led end-to-end research combining moderated user testing and a large-scale global survey
2
Found that generic feedback and limited transparency erode trust, with learners expecting review of their own mistakes
3
Informed the redesign of Mistake Repair and review features toward more personalised, adaptive feedback

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