Skip to content
Gaia Cecchi
IT

All work

Academic case study A02

PATH

An AI chatbot that helps students choose their university path with the Designing Your Life method

Period
2022–2024 — MSc coursework
Context
Academic concept for the University of Siena's orientation service
Role
Co-creator and designer: concept, user research, conversation design, Wizard-of-Oz prototype
Programme
MSc coursework — Digital Communication / Communication Design / Cognitive Sciences
Team
Two-designer team
15,3%
of Italian graduates struggle to choose a path
6,6%
drop out in the first university year
24/7
free guidance, on the university site

Problem

15,3%
of graduates struggle choosing their university path

Source: Rapporto Almalaurea 2020

6,6%
first-year dropout rate, plus 8,7% switching course or university

Source: Rapporto Almalaurea 2020

~40%
after the final exam still undecided between university and work

Source: Rapporto Ansa 2018

Choosing what comes after high school is a decision most students face with little structured support. Traditional orientation is episodic — an open day, a brochure — while the uncertainty is continuous.

Target user

Andrea

19 — recent graduate

Profile
Uncertain about which faculty fits him; browses the university site without a clear direction.
Goal
Understand which degree course matches his aspirations.

Corinna

24 — student in crisis

Profile
Considering dropping out of her current studies.
Goal
Figure out whether to change route before abandoning altogether.

Francesco

34 — professional

Profile
Works, but wants to specialize further.
Goal
Find the right course to grow in his field.

Marianna

25 — evaluating options

Profile
Weighing different scenarios for her next step.
Goal
Compare the possible versions of her future self.

My role

I co-created PATH in a two-designer team: from the benchmark of the department's existing TutorBot to persona and journey mapping, the storyboard, the question-tree dataset, and the Wizard-of-Oz testing sessions.

Process

The core idea: embed Bill Burnett and Dave Evans' “Designing Your Life” framework into a conversational agent. The chatbot guides students through reframing — imagining three possible versions of themselves — before matching aspirations to actual courses and career paths. We benchmarked the DISPOC TutorBot, whose dataset covered a single department, to design a cross-department, always-available alternative.

User journey — Andrea, 19: choosing a faculty
  1. 01 · Trigger

    Actions
    Fresh out of high school and uncertain, Andrea finds the PATH icon on the university site and reads the welcome message.
    Pain point
    At first glance the PATH icon may not make clear what it refers to.
  2. 02 · Phase 1

    Actions
    He starts chatting; the first questions aim to understand his situation.
    Pain point
    Initial distrust — the user may tire of preliminary questions.
    Opportunity
    A friendly, neutral tone keeps the user from walking away this early.
  3. 03 · Phase 2

    Actions
    As the chatbot requests, he imagines three possible versions of himself and describes them in chat.
    Pain point
    The unconventional approach (Burnett's model) takes time and trust.
    Opportunity
    Pair the request with a short explanation of the method behind it.
  4. 04 · Phase 3

    Actions
    PATH returns a map of alternatives and advice on approaching each profession.
  5. 05 · Goal

    Actions
    Andrea finds a fitting degree course — in another city — and thanks to PATH doesn't waste time evaluating it.
    Opportunity
    Deploy PATH across all Italian university sites, linked to share course data.
Hand-drawn storyboard: the Designing Your Life flow applied to the UniSi site
Storyboard of the onboarding conversation — reframing applied to the university site

Key decisions

  • Position PATH as a ChatGPT-based plug-in embedded in the university site, not a separate app to install.
  • Friendly, neutral conversation style — guidance without judgment, so undecided users aren't pushed away.
  • Explicitly explain the Burnett method in-chat: unconventional models need transparency to earn trust.
  • Structure the dataset as a question tree (ALGHO platform) spanning courses and career outcomes across departments.

Final result

We validated the conversation design with a Wizard-of-Oz prototype — real dialogues with users playing out the personas' scenarios — plus a Balsamiq wireframe showing PATH embedded in the UniSi site.

Wizard-of-Oz prototype: PATH's welcome message in a real chat with a user
Wizard-of-Oz session — PATH introduces itself as a free 24/7 guidance chat
PATH concept: the chatbot on a phone with what it is, what it does, and how
The final concept sheet

What I learned

  • In conversational products, tone is architecture: a friendly, neutral style is what keeps uncertain users in the funnel.
  • Unconventional methods must be explained, not just applied — users grant trust when they understand the model working on them.