EVOKE DisruptAI Project
EVOKE DisruptAI Project
A simplified recruiting chatbot for students and hiring managers.
Vanessa Seto : UI Designer
Daisy Agrawal : Front-End Developer
Katie Zhan : Back-End Developer
Jiaqi Song : Software Developer
Students are always looking for opportunities to practice job interviews, whether it be technical or soft skill interviews. The goal with this project is essentially to make the interview and recruiting process easier for both students and employers. As a group of four university students in co-op programs, my team wanted to impact the student community - specifically with improving the interview process.
When it comes to job interviews, young students often don't get enough practice for interviews, and feel unconfident due to their lack of experience with interviews. Students need accurate and professional feedback to prepare for their interviews, and it is uncommon for employers to give suggestions for improvement after interviews.
"How might we provide an interactive tool for students to practice job interviews?"
The solution for this problem comes in two forms: the student side and the employer side. AthenaAI Student is an AI chatbot used by students to practice interviews with a realistic and accurate experience, while also receiving descriptive feedback and a mark. AthenaAI Employer simplifies the candidate recruiting process for employers by having candidates can be sorted through a custom AI interview chatbot. This AI solution saves the company time and money while also helping employers hire, grow, and retain top talent.
From research, ideation, wire-framing, designing, to prototyping, here's the process I lead my team through.
We conducted 5 user interviews with various students of different academic backgrounds. We discovered pain points and experiences within the recruiting process that needed improvement. It was found that students wanted more opportunities to practice interviews, in order to feel more confident and well prepared for the real deal. Here are some insights that my team gained from the research.
- Large volume of applicants - The current interview process is inefficient for employers when there are a large pool of candidates for only a few positions
- Not enough opportunities for interview prep - Students often don't get enough accurate and professional practice for interviews
- The need for professional feedback - Employers often do not bother giving suggestions for improvement after interviews
- Improvement & Growth - Students don't know how to improve interview responses
Ideation & Wireframes
With the results from the user interviews and with product goals in mind, we brainstormed ideas and a feature list in order to understand how our product would function. We came up with the idea of a chatbot that can be used for students to practice interviews, while also receiving descriptive feedback and a mark. We also ideated with the consideration of the other end of things - the recruiters.
Wireframing allowed for us to work through the logic of hour our content should flow, and helped to lay the groundwork for the overall experience. The following are the initial wireframes for AthenaAI.
In order to design for both types of primary users for the app, we had to consider both ends of AthenaAI. From the student side, there is an interview practice feature, which generate automatic interviews, and there is an employer interview that gets sent to the company interviewing. From the employer side, they create an interview or select a pre-made interview template to send and receive results.
Intended to be as minimal and user friendly as possible, the style of this design places emphasis on crucial information such as interview results and chatbot responses. The following screens display the digital and voice chatbot features, as well as the interview results page for when a user finishes an interview. Finally, there is a learn more page for users to explore different features of the app.
LANGAUGES & TOOLS USED
/ HTML & CSS
/ Sketch (UI Design)
/ Azure Text Analytics
/ Mozilla Speech Recognition
VOICE RECOGNITION FEATURE
Using the Mozilla Speech Recognition API, speech is received through the device's microphone, and a word or phrase is successfully recognized. The phrase is returned as a text string then is outputted to the web application's front-end. This is a sample of a speech answer and how the speech recognition API detects words being spoken.
1. If given minimal instruction on a certain task, how would you proceed?
2. What are the two things that are most important to you in a job?
In the future, my team and I are aiming to implement this with companies who frequently hire co-op students from the University of Waterloo. AthenaAI would become a common tool in the recruiting process for University of Waterloo students to improve interview skills, and for hiring managers to more efficiently recruit from the university. Further development for the future of this project include:
- More in-depth answer analysis
- Other means of communicating answers (Facebook Messenger Chat, AR, VR ..)
- Virtual meetings with AthenaAI