BusyBody: Counsellor Meeting - Student Emotional Wellness

Nov 3, 2025 by SLV Team 58 views

Hey guys! We're diving deep into the emotional wellness of students with our BusyBody project, and our first stakeholder meeting with a counsellor is super important. This meeting will help us validate our problem statement and ensure we're on the right track with our Mood Mate project. Let's get into the details!

Purpose

The main goal of this meeting is to sit down with a counsellor (or someone from student affairs or psychology) to really nail down the problem statement around student emotional wellness. We want to make sure we're addressing the real issues students face and that our Mood Mate app is a relevant and helpful solution.

Meeting Details

Here’s the lowdown on the meeting:

Proposed Date/Time: November 5, 2025 (We'll confirm this ASAP!)
Venue/Platform: We're thinking either face-to-face, Google Meet, or even a quick WhatsApp call – whatever works best for the counsellor.
Team Attending: @hfzdnshah, @oldpistol, and @badz20 will be there to represent the BusyBody team.
Stakeholder: We'll be meeting with a counsellor or someone from Student Affairs. We'll fill in the exact name and role after the meeting.

Agenda

We've got a clear plan for what we want to discuss:

Present the Idea: We'll introduce Mood Mate as an AI friend that's designed to listen and provide supportive replies. Think of it as a virtual buddy for students.
Ask About Current Issues: We really want to hear from the counsellor about the challenges students are currently facing. Things like stress, loneliness, and even just venting online. What are the big concerns they're seeing?
Confidentiality and Data Sensitivity: This is huge. We need to understand the ethical and privacy considerations around handling student data. How can we ensure everything is secure and confidential?
"Flagged User" Feature: We're thinking about including a feature that would flag users who might need extra support. Is this something the counsellor would find helpful? What are the potential downsides?
Feedback on Tone/Language: Getting the tone right is crucial. We'll ask for feedback on the kind of language Mood Mate uses in its replies. We want it to be supportive and encouraging, not clinical or off-putting.

Deep Dive on the Agenda Items

Let's break down each agenda item a bit further to make sure we're all on the same page:

Presenting Mood Mate: When we introduce Mood Mate, we need to emphasize its potential to provide accessible and immediate support to students. We should highlight how it can act as a first point of contact for students who might be hesitant to seek help from traditional sources. It’s crucial to explain the AI aspect in a way that's easy to understand, focusing on its ability to offer personalized responses based on the student's input. This presentation should be concise and engaging, leaving plenty of room for discussion and feedback.
Understanding Current Issues: This is where the counsellor's expertise really comes into play. We need to ask open-ended questions that encourage them to share their insights on the prevalent issues affecting student well-being. What are the common stressors? What kind of support are students actively seeking? Are there any emerging trends or challenges that we should be aware of? Understanding the specific issues will help us tailor Mood Mate to address the most pressing needs.
Confidentiality and Data Sensitivity: We need to have a thorough discussion about data privacy and ethical considerations. How should student data be stored and protected? What kind of consent is required? Are there any legal or institutional guidelines we need to adhere to? We need to demonstrate that we're taking these issues seriously and that we're committed to maintaining the highest standards of data security and privacy.
Exploring the "Flagged User" Feature: This feature could be a game-changer in terms of providing timely support to students in distress. However, it also raises some important ethical questions. How do we ensure that the flagging mechanism is accurate and reliable? What kind of protocols should be in place for responding to flagged users? How do we avoid creating a system that stigmatizes or unfairly targets certain students? We need to carefully weigh the potential benefits against the potential risks.
Refining Tone and Language: The way Mood Mate communicates is critical to its success. We want to create a tone that's empathetic, supportive, and non-judgmental. We need to avoid using language that's too clinical, patronizing, or dismissive. We should ask the counsellor for specific examples of language that would resonate with students and language that would be off-putting. This feedback will help us fine-tune the AI's responses and ensure that it's providing truly helpful and supportive interactions.

Documentation Required

After the meeting wraps up, we need to add a comment to this issue with the following info:

Date & Time (Actual): When did the meeting actually happen?
Stakeholder Name/Role: Who did we meet with, and what's their position?
3–5 Bullet Points of Feedback: Key takeaways from the discussion.
Any Risks or Cautions Mentioned: Did the counsellor raise any red flags or potential issues?

Linkage

What we learn in this meeting will directly impact:

Requirement Analysis (Mood Mate): This will help us define exactly what Mood Mate needs to do.
UML (actor: Counsellor/Admin): We'll use this to map out how counsellors and admins will interact with the system.

Project

BusyBody

Expanding on the Impact of the Meeting

To really drive home the importance of this meeting, let's explore how the findings will shape our project:

Requirement Analysis: The insights we gain from the counsellor will be instrumental in defining the functional and non-functional requirements of Mood Mate. For example, if the counsellor emphasizes the importance of anonymity, we'll need to ensure that the app provides a way for students to interact without revealing their identity. If they highlight the need for resources on specific topics like anxiety or depression, we'll need to incorporate relevant information and links into the app. This meeting will help us create a comprehensive and user-centered set of requirements.
UML Diagram: The Unified Modeling Language (UML) diagram will visually represent how different actors (in this case, counsellors and administrators) interact with the Mood Mate system. By understanding the counsellor's role and responsibilities, we can accurately depict their interactions with the app. For example, if the "flagged user" feature is implemented, the UML diagram will show how counsellors receive notifications, access user information, and provide support. This diagram will serve as a blueprint for the app's design and development.

Addressing Potential Risks and Cautions

It's also important to anticipate potential risks and challenges that might arise during the meeting. Here are a few things to keep in mind:

Confidentiality Concerns: The counsellor might be hesitant to share sensitive information about students due to privacy concerns. We need to reassure them that we understand and respect these concerns and that we're committed to protecting student data.
Skepticism About AI: The counsellor might be skeptical about the ability of AI to provide genuine support to students. We need to address these concerns by explaining the limitations of Mood Mate and emphasizing that it's intended to supplement, not replace, human interaction.
Ethical Dilemmas: The "flagged user" feature could raise ethical dilemmas if it's not implemented carefully. We need to be prepared to discuss these dilemmas and demonstrate that we're committed to using this feature responsibly and ethically.

By proactively addressing these potential risks and cautions, we can ensure that the meeting is productive and that we build a strong working relationship with the counsellor.

Let's make this meeting count, guys! This is a huge step in making Mood Mate a real, helpful tool for students. Good luck team!