Case Study 2022
CollegeKnowledge

Overview đź‘‹

Problem

Low-income, first-generation, and underrepresented minorities make up the lowest percentage of individuals often faces various obstacles such as classism, lack of resources and informational support when pursing higher education.

Solution

We designed CollegeKnowledge, a platform that allows our user to organize their graduate school application process better and connect with mentors who could assist them along the way. It enables users to better navigate their graduate school applictaions, get insights from people with similar background thus to address the demographic disparity in higher education.

My Role

Lead UX Designer, UX Researcher

Timeline

August 2022 - December 2022

Time Members

Druti Naik

Sydney Lodge

Tools

Figma, Miro, Google drive

populated Programs

When users first use this platform, they will go through an onboarding process. They will indicate information about themselves such as their areas of interest and identity to match with potential mentors and get program list based on their interests.

School Management

On this page, users can manage the program they wanted to apply. A timeline that has been automatically generated depending on their desired admission cycle. They can choose the programs they want to be displayed on the timeline by checking the checkbox. Additionally, the users can expand and collapse the checklist as they want.

Approachable mentors

On the school detail page, there is a list of potential mentors. The list consists of potential mentors ranked from “best matched” to “third matched”. Beyond “third matched” mentors will not have a tag displaying their rank but will still be displayed in a hierarchy of likeness to the user. By clicking message button, it will take the user to the message page where the user can message and book a meeting with potential mentors.

Categorized Reviews

There are reviews for the specific program from current students and alumni of that program. The reviews are on specific factors such as community, diversity, funding support, and rigor. When a user hits the arrow on any of these, the factor will expand and you will be able to see more reviews on that specific factor. These reviews are anonymous.

Our Approach

01   Define
02  Research
03  DESIGN
04  Evaluate
understanding space
Survey
Concept Sketch
Task-Based User testing
defining project goal
semi-structured interview
Wireframe
Expert Evaluation
secondary research
competitive analysis
User Feedback
Feedback Review
project timeline
Persona
Interactive Prototype
proposed methods
Empathy Map

My Contribution

During the research phase, I was in charge of competitive analysis. I also contributed to preliminary research, construct survey and interview questions, and interviewed potential users.
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As the lead designer in the team, I first facilitated a brainstorming session to engage everyone in generating innovative ideas. After that, I created sketches and storyboards to convey our design ideas visually. I am also in charge of deciding on the core functionality and main user flow. I then designed the user interface for creating avatars and exercise processes using Figma.

During the evaluation phase, I moderated user testing, made interactive prototypes, and walked the users through during the session.

Research 🪄

pre-existing programs and products

There are many pre-existing programs and products that are designated for minorities in higher education or can be used to find graduate school related information on it. However, they are either highly selective or takes up a lot of time to gather and search for userful information . We analyzed these programs and platforms to get a better understanding of the gap between the current products and user needs.

Survey & Interview

We conducted interviews and distrbuted separate surveys for undergraduate students and graduate students. Our goal was to collect information from participants that would capture their experiences with the overall graduate school application process before, during, and after the process itself.

Affinity Mapping

We synthesized all the data gathered from our surveys and interviews and organized them based on their affinities, to find patterns and common themes. We used our top findings to inform design decisions and derive design implications from.

Prospective students consistently wished to have more insights about a program from the current students/alumni of that program.

They wish to get first-hand information on the curriculum and program so they could get a better understanding and decide if it is the right program for them.

Community expectations influence an individual’s decision to pursue graduate school.

These communities expectations were often discussed in the semi-structured interviews, with many participants stating that the expectations heavily influenced their decision, whether they ultimately went against or aligned with these expectations.

Underrepresented students look for role models with similar backgrounds.

Whether they were successful or not, participants often thought it was important for them to see and interact with these role models rather than people in the same positions with whom they had less in common.

During the application process, people seek support and advice from a variety of people.

Most of the people in our user group especially those who are first-generation students find it hard to rely on academic/ professional advice from their parents. They seek support from people such as their professors, faculty members, alumni, and friends.

Design 🪄

Ideation

When kicking off the design phase for this project, we identified and established two distinct design concepts that would be unified by interface and voice prototyping. These two design concepts address the core issues minorities faces when applying for graduate school. We got together as a team to brainstorm ideas on whiteboards and came up with low fidelity sketches for the screens of each design concept.

Concept Feedback

We conducted a concept feedback session with 3 participants of our target users using paper sketches. We guided them through each concept and askd users thought-provoking questions about their initial impressions, considerations, and interpretations of the sketch concepts.

concept 1

MentorChat

MentorChat was generally perceived positively by all participants during the feedback sessions. Participants loved the idea of connecting to and speaking to mentors with similar backgrounds and aspirations. We heard positive feedback about the fact that our concept was program specific as all of our participants had reached out to current students or alumni of a more general university who were able to give them limited or not practical advice.

concept 2

Rate my Grad School

Rate My Grad School was generally perceived positively during our feedback sessions, but less so than MentorChat. Participants liked certain features of this sketch and said they would be useful, but only for a short period of time for each user. Once past the exploratory part of the graduate school application process, participants said that they would not use this often.

Wireframe

After collecting responses from our participants in the concept feedback session, we compiled all the information we got about each design concept. We focused on recurring themes that were mentioned in the session. We developed wireframes based on the concept of MentorChat and combines some of the desired features from Rate My Grad School.
Based on our findings from the sketches, our group decided to incorporate the following features:

●  Onboarding
●  Populated programs
●  Search program
●  Mentor match
●.  Review Repository
●  Direct messaging
●  Scheduling a meeting
●  Timeline & checklist

Wireframe Feedback

We printed out the wireframes we designed and conducted think-aloud task-based user testing. During these feedback sessions, our team wished to gather information about participants’ overall impressions, whether we had addressed their expressed needs and wants, and feedback about specific features and intervention capabilities. We also wished to understand what they expected and wanted in these screens’ flow.

Feedback & Improvement

After the feedback sessions were complete, we compiled a list of findings based on comments, questions, and user suggestions about the platform. Users generally had positive feedback about our wireframes and expressed that our intervention would adequately address non-systemic issues of equity and diversity.

A platform that provides reviews from current students and alumni and rankings for various graduate school programs in the United States.

A platform that provides reviews from current students and alumni and rankings for various graduate school programs in the United States.

Prototype 🔶

High-Fidelity Design

After reiterate the wireframe based on feedbackas we received from the feedback session,

Onboarding

Allowing users to select their needs and identities to find the programs and mentors better suited for them.

Users either states they are a prospective graduate student or a current graduate student/alumnus, thus determining whether they are qualified to be a mentee or mentor.

Users can choose whether they are low-income, first-generation, or an underrepresented minority race or ethnicity and also indicates where they need help with

Users can select their areas of interest to generate the recommended programs.

Users need to enter what admission cycle they are applying for so the system can generate a timeline for referenece.

A list of programs will be automatically generated based on the areas of interest that they indicated, as well as what the user has already added to their favorites.

School & Meeting Management

Providing a timeline for users better manage their selected programs and a schedule for meetings they have with mentors

Users can add new programs and see the programs that they have selected. They can also see a timeline that has been automatically generated depending on their desired admission cycle.

Display the schedule of meetings that have been set up by the prospective graduate student, as well as all of the mentors they have previously met or are planning to meet.

Chat with Mentors

Match with mentors based on users' interests and identities. Allow users to chat with mentors and schedule 1:1 meetings for more in-depth conversations.

Beneath the school details is a list of potential mentors. This list consists of potential mentors ranked from “best matched” to “third matched”.

When a user first messaging a potential mentor, it has a suggested message displayed based on the information they entered.

The schedule feature is enabled after the mentor replies to their message which will allow users to see their mentor’s availability and schedule a meeting.

school reviews

Provide categorized, in-depth reviews based on different aspects of programs so users can find information on the specific aspect they care about.

There are reviews for the specific program from current students and alumni of that program. The reviews are on specific factors such as community, diversity, funding support, and rigor.

When a user hits the arrow on any of these, the factor will expand and you will be able to see more reviews on that specific factor.

Evaluation & iteration đź“ť

Evaulation

We conducted user testing of our final prototype with five protential users and expert evaluations with four experts. We were interested in understanding how users navigated the platform, what users valued the most as well as getting recommendations from the experts.

User testing

These user tests consisted of three phases: the think-aloud free-explore phase, the think-aloud task-completion phase, and an open-ended interview phase. 3 task-based tests were conducted in-person and 2 were conducted remotely.

●  Walk through the onboarding process

●  Find a mentor and how you would schedule a call with them.

●  Add programs to your program list?
   How would you delete?

●  Select programs from your program list to be displayed in your timeline? Deselect?

●  Check your profile page and make edits?

Expert evaluation

Expert evaluation consists two parts: an cognitive walkthrough and an heuristic evaluation. The evaluation was adapted from Neilson Norman’s Usability Heuristics for User Interface Designs. We developed questions that were specific to our project and asked the experts to rate them on a scale from 1-5 (1= strongly disagree; 5=strongly agree).

●  Does the user understand how to initiate the task?

●  Is the next step noticeable by the user?

●  Does the next step match user expectation?

●  Does the user know about the progress made?

●  Is the user able to complete this task?

Findings from evaluation

onboarding process

Users are confused about what will happen when clicking on the checkbox “use this to match me with a mentor”

Users are confused about the program list shown right after the onboarding process

homepage and meeting

Users are confused about the relationship between the program list and timeline and the checkbox

Users want to have more information about the upcoming meeting instead of the meeting history

Program detail page

Users are confused about the “students” list and not sure they are mentors

Users want to see more information regarding every review such as posted date, upvote counts

Reflection đź’­

Diversity of research methods lead to rich insights and new perspectives, which contributes a great deal to the design process.

Research and design are extremely reiterative and the work is never truly finished