back to home button
Logan & Friends
An AI-powered instructional coaching tool designed to deliver real-time, personalized feedback and assist educators with professional development, enhancing traditional coaching with seamless AI integration.
ROLE
Founding Product Designer
DURATION
Sep 2023 - April 2024
8 Months
TOOLS
chatgptchatgpt
Logan & Friends is an ed-tech company focused on empowering teachers with innovative tools to support with professional development. They aim to combine traditional instructional coaching with technology to help K-12 educators adapt to the evolving needs of the classroom.
The product is a game-changing tool designed to elevate instructional coaching by integrating AI. It addresses the limitations of traditional coaching methods and provides educators with real-time, personalized feedback, helping them continuously refine their pedagogical practices and improve teaching techniques seamlessly.
Context
What is instructional coaching?
Instructional coaching is a process where experienced coaches observe teachers in the classroom and offer feedback to help them improve. It’s meant to support teachers in refining their methods and boosting student outcomes, but the traditional approach comes with challenges.
Traditional coaching with in-person observation and feedback sessions.
Creates an environment of distress for teachers and students.
Limited observation time, thus the observation may lack accuracy and depth.
Coaching sessions are infrequent to drive real improvement.
Feedback comes too late, losing its impact.
Inadequate progress tracking.
State of instructional coaching
Instructional coaching is crucial for teachers’ professional growth, but it isn’t widely accessible. Despite its proven benefits, only a small portion of K-12 schools offer structured coaching, leaving the majority of teachers without the guidance they need.
source: Sage Journals
Without coaching, teachers miss valuable opportunities to improve their practice.
The lack of coaching creates disparities in how teachers develop professionally.
When teachers aren’t supported, student learning suffers.
Problem Statement
How can we optimize instructional coaching and teachers' professional development to increase efficiency?
Vision
Our North Star design
Our North Star guides us in addressing the shortcomings of traditional instructional coaching by envisioning a solution that truly empowers educators.
We believe that by making professional development more meaningful, every teacher will have the resources they need to thrive.
AI-driven coaching to provide personalized support that adapts to each teacher’s needs.
Reduce stress and anxiety to eliminate the pressure of in-person evaluations.
Continuous growth to offer actionable insights for ongoing professional development.
Empower educators to enable teachers to focus on teaching and inspiring students.
process
Embracing chaos in research
Our process was anything but linear. We embraced a non-linear journey, diving into competitive analysis, user research and literature review parellelly. Each piece of research informed the others, giving us a holistic view of the problem.
This approach helped us refine our understanding of the product requirements while staying open to new insights.
The goal was simple: create a solution that truly addresses the needs of educators, guided by evidence at every step.
How different research methods came together to define the problem and guide our solution.
User Research
Who are the key stakeholders?
In our research, we focused primarily on teachers and instructional coaches. These two groups are at the core of instructional coaching, directly benefiting from improved support systems.
While we acknowledge the important role that school leaders play in the coaching process, they were not included in this initial phase of our research.
The illustration depicts our primary, secondary, and tertiary users.
School leaders and customers/buyers were not included in this phase of the research.
What did they say?
We interviewed 6 instructional coaches and 5 teachers, gathering insights from 11 users. The focus of these interviews was to understand traditional coaching practices—how they happen, what the process looks like, what users like about it, and where the pain points lie.
Through these conversations, several recurring themes emerged, revealing the core challenges in instructional coaching.
Teachers and Coaches quotes that stood out to us, highlighting their key experiences and challenges.
Design Hypothesis
Bridging the gap with AI
The hypothesis centered on leveraging AI’s ability to analyze classroom interactions, provide timely, data-driven support, and reduce the overwhelming aspects of traditional coaching—ultimately enhancing both teacher growth and student outcomes.
AI analyzes classroom recordings and provides direct feedback to teachers.
Human coaches may feel that their role is being replaced by AI.
AI might not understand the emotional or situational context that human coaches can.
AI lacks empathy.
AI lacks personal touch.
Teachers may not trust the AI.
Addresses the issue of limited human coaching resources.
System can be scaled to support a large number of teachers.
Immediate feedback after uploading lessons.
Consistent and regular feedback.
Receive feedback at any time and from any location.
Augmenting AI with human coach
To tackle the limitations of an AI-only approach, we envisioned a solution where human coaches work alongside AI. This combined approach harnesses AI’s data capabilities while bringing in the empathy, context, and personal understanding that only a human can provide, leading to a more effective and supportive coaching experience for teachers.
Introducing human coach involvement in collaboration with AI.
Will the teachers be comfortable with recording their classes?
Will the teachers use and trust AI involevement?
Will the AI analysis be accurate?
Reduces the workload of human coach while keeping them in the loop.
Human coaches provide empathy and situational context.
Balanced and comprehensive feedback with AI analysis and human coach's validation.
Teachers trust and feel comfortable with the process with human involvement.
Secondary research supporting our hypothesis
We validated our design hypothesis through secondary research. The focus was on understanding how AI integration in instructional coaching could enhance teacher development.
91%
Accuracy with AI chat-bots
Reflecting the reliability of AI in educational support scenarios.
80%
Accuracy in results when compared to human experts
AI’s potential to match professional expertise.
45%
Cost reduction adopting AI
Institutions that adopted AI reported significant cost reduction
Sources: AI in Education Statistics 2023;
Artificial Intelligence in Education. 2023 Survey Insights
Evaluating technical feasibility
To ensure our design hypothesis was both effective and feasible, we needed to address technical uncertainties regarding AI integration, specifically around providing personalized feedback to teachers.
This exploration was crucial to transition from an abstract design hypothesis to a solution grounded in a solid technological foundation.
We did online research and talked to AI subject matter experts, leading to these solutions:
Teachers use lapel mic to capture high quality and accurate data.
Train AI to pick up different accents using a diverse set of data.
Acoustic feature extraction—analyse voice for meaningful data.
Voice and sentiment analysis—gauging emotional context in feedback.
Use NLP to generate personalised feedback.
Voices from the field
We surveyed 30+ educators to understand their openness to AI in instructional coaching
67%
Teachers are willing to use AI tools for feedback
75%
Teachers feel comfortable being recorded during lessons
Product requirements
Defining the essentials
With a clear vision of how the product should function, we moved on to defining the key features. Based on insights from user and competitive analysis, these product requirements focus on effective teacher support, ease of use, and fostering meaningful growth.
Flexible recording options—record and upload lessons without hassle.
Uploading of supporting documents, URLs, and notes to provide complete context for coaching.
Targeted and personalised feedback.
Let teachers collaborate with other teachers and coaches.
Foster relationship building between the AI product and teachers.
Ensure AI works as a teacher’s ally—supportive companion.
Visual progress tracking with always-accessible rubrics.
Professional development resources—training modules and video demonstrations.
Ideation
From ideas to practical solutions
After defining core requirements, we moved into ideation, transforming concepts into practical solutions.
To ensure the effectiveness of our solution, we defined clear roles for each stakeholder involved.
Key Discovery
School leaders can range from principals to district administrators overseeing multiple schools, varying by public or private institutions.
Framework for stakeholders' collaboration.
challenge
Some schools may opt out of implementing the product on school level, leaving educators without essential coaching support.
Accessibility for all educators
What if a school or district chooses not to implement the platform on a large scale? This question led us to explore alternative solutions to ensure individual teachers could still benefit from the product, regardless of institutional buy-in.
Individual subscriptions allowing teachers to independently access the AI platform for personalized support.
Enterprise plans for schools and districts allowing for institution-wide access to all teachers under purview.
Scalable enterprise plans for schools and districts—similar to Microsoft and Google Workspace.
Leaders can manage access for all educators under their purview.
Administrative monitoring for teacher progress.
Teachers can get individual software subscriptions.
Access to all features, resources and AI feedback.
Allows for personal growth without relying on school-wide decision.
Wireframes
Defining the essentials
With a clear vision of how the product should function, we moved on to defining the key features. Based on insights from user and competitive analysis, these product requirements focus on effective teacher support, ease of use, and fostering meaningful growth.
A popup allowing teachers to schedule a recording session now or later.
A confirmation popup for scheduling lesson recordings with editable details.
A table view listing generated reports with filters for name, subject, and performance.
A report summary screen showing overall performance, domain-wise scores, and written feedback.
A feedback screen with an audio waveform and timestamped suggestions linked to domains.
A feedback timeline view with AI chat assistant providing contextual suggestions.
A detailed performance breakdown by domains and subdomains with color-coded scoring.
Design Work in Progress
This one’s still brewing.
Thanks for peeking behind the curtain.
next project
IU x Accessibility