group project
Nextstep career service
NextStep is a career service located at University of Melbourne. It is aimed at helping students enhance career readiness through targeted support in skills development and professional networking.
Project Background
The University of Melbourne Student Union, backed by grants from the University and State Government, aims to improve student experience, career success, and wellbeing. Our team is hired as a service design consultancy and tasked to propose a career service that enhances equity and inclusion, particularly for students with disabilities.
Project duration
April 2024– June 2024
Objectives and Goal
Help students build their career readiness, find part time work, connect with mentors and identify other opportunities for careers guidance or support:
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To boost students' confidence in job-ready skills.
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To provide social and emotional support through peer interactions.
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To create a platform for students to collaborate on self-initiated projects.
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To offer accessible and immediate career guidance via an AI-driven chatbot.
My role
User research, User Journey creation, Chatbot Design and Report composing, Project formatting and Proofreading
tool
Figma, Miro, Google Doc, Voiceflow, Procreate
Understanding challenges
Several key challenges emerged during the project:
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Scope Management: Initially, we considered addressing multiple themes including soft skills, emotional support, professional connections, and internship opportunities. We realized that covering all these areas would dilute our focus and decided to concentrate on boosting job-ready skills and social support.
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Mentor Involvement: Integrating a mentoring mechanism effectively involves sourcing, recruiting, and verifying mentors, which requires further research and resource allocation​.
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Technical Implementation and Support: Developing and maintaining tools like an AI-driven career coach chatbot that supports various accessibility needs and integrates seamlessly with other services poses technical and operational challenges​.
Research
Aiming to validate how our proposed service suits the user needs and interests, and (b) refine NextStep’s service processes, we came up with the following research questions:
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What are users’ needs relating to career readiness? If they have used the current career-ready service provided by Unimelb, what do they like and dislike about it? And how can NextStep fill the gap?
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Are users interested in using our service? Why (Why not)?
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Which part of our service needs further improvement and in what way?
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Desktop walkthroughs were conducted with two groups of peer students (around 10 participants) during tutorials to evaluate our service process. We used Lego prototypes representing the student-led project hub and one-to-one skill swap or job agent consultation sessions.
Feedback analysis
To understand users' expectations and concerns, we conducted semi-structured Zoom interviews with two University of Melbourne students . Participants were shown photos of Lego prototypes and early storyboards while we described our service components. The qualitative data were analyzed by the group using the feedback grid, where all members revisit the transcriptions and organize post-its into themed categories.
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Pair Practicing: Users appreciated the emphasis on practicing over teaching and expressed a preference for skill practice sessions that were directly relevant to their career aspirations.
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Project Hub: There was strong interest in collaborating on projects, though concerns were raised about project scope, team dynamics, and commercialization. The decision was made to focus on educational projects and ensure clear team information.
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Mentoring: The integration of a mentoring system was well-received, with students valuing the opportunity to receive expert feedback on their career skills.
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Physical Touchpoints: Feedback highlighted the need for accessible workspaces that cater to both individual and group work. The service will address accessibility with trained staff, hearing loop systems, sign language interpreters, ramps, and other features to support various disabilities.
Feedback impact
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The feedback led to significant design refinements, particularly in focusing on practical skill development and ensuring accessibility.
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The project provided a structured yet flexible platform for students to gain hands-on experience, enhancing their career readiness.
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The mentoring system bridged the gap between theoretical knowledge and practical application, offering personalized guidance to students.
Storyboards
functionality
functionality
User journey map
Key wireframes
conversational design
Iteration 1
The first iteration of the chatbot saw it take form within a single block of functionality. Initially, all interactions were managed within this single block, but it soon became clear that this approach was too simplistic and inflexible.
The image on the left shows this iteration, where interactions with the chatbot were limited to single user journeys, preventing the user from exploring different services after completing one user flow.
Iteration 2
In the second iteration, we clarified the scope of the chatbot by removing the confusing clubs and associations feature and enhancing the "Becoming a Mentor" feature. We also expanded the career advisor functionality, allowing users to choose their consultation method, whether remote or in-person. This version integrated variables to track different user requests and process them more efficiently, improving the overall user experience.
Iteration 3
The third iteration focused on cleaning up the flows to allow users to return to where they left off after signing up, enhancing the experience for both new and returning users.
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We added functionalities that specifically benefited returning users, such as Airtable API calls to check on Pair Practice session bookings and Project Hub details. By mapping Airtable filterByFormula calls to equivalent Voiceflow variables, we ensured efficient presentation of information, improving the overall functionality of the chatbot. This iteration
included the presentation of a venue map for accessibility purposes, making the chatbot more inclusive.
evaluation and feedback
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Based on feedback regarding the returning users sections, we implemented additional error-catching mechanisms to check if student numbers were valid (did not contain letters). We also allowed users to backtrack to previous conversation options if they accidentally triggered returning user options.
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To further enhance robustness, we iterated on the implementation of errorcatching, ensuring API callsregistered accurately and did not return misleading success statuses. We added additional AI set and response features related to the Project Hub, allowing users to create sample project proposals by inputting keywords.
Chatbot interaction prototyping
reflections
Areas for achievement
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User-Centered Design: Engaging users throughout the design process ensured the final product was aligned with their needs. This approach allowed for the development of solutions that were highly relevant and effective in addressing the specific challenges faced by students.
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Collaborative Learning: The Pair Practicing program effectively promoted peer-to-peer learning and support. This initiative fostered a collaborative environment where students could build confidence and enhance their skills through mutual support and practice.
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AI Integration: The Career Coach Chatbot provided accessible, immediate support, significantly enhancing user engagement.
areas for improvement
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Interface Design: Further refinements are needed to make the Project Hub interface more intuitive. User feedback indicated that while the functionality was beneficial, the user experience could be enhanced through a more user-friendly design.
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Scalability: Ensuring the platform can scale effectively to accommodate more users and sessions remains a challenge. As user adoption grows, it's critical to maintain performance and reliability to support a larger user base.
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Feedback Incorporation: Continuous user feedback loops should be maintained to iteratively improve the service. Regularly gathering and integrating user feedback will help to identify areas for enhancement and ensure the platform evolves in line with user needs.