Overview

Logan & Friends is an educational technology platform created to support teachers, instructional coaches, administrators, students, and parents through a centralized instructional coaching ecosystem.

The project focused on simplifying classroom observations, improving feedback workflows, and providing actionable teaching insights through AI-powered analytics and role-based dashboards.

Problem

Educational institutions often rely on fragmented systems for teacher evaluations, classroom observations, and instructional coaching. Existing solutions lacked workflow clarity, accessibility, and actionable insights, creating friction for educators and administrators.

Key Challenges

• Delayed and inconsistent instructional feedback

• Disconnected classroom observation systems

• Limited visibility into student engagement

• Complex reporting and analytics workflows

• Administrative overload for teachers and coaches

• Lack of collaboration across stakeholders

Objective

Design an AI-powered instructional coaching platform that:

• Simplifies teacher evaluation workflows

• Improves classroom engagement visibility

• Supports data-driven instructional decisions

• Enhances collaboration among educators

• Delivers accessible and scalable user experiences

Research Process

To better understand the educational ecosystem, we conducted a mixed-method UX research process combining qualitative and quantitative methods.

Research Methods

• Competitor Analysis

• Secondary Research

• Stakeholder Interviews

• Surveys

• Journey Mapping

• User Flows

• Persona Development

• Usability Testing

Stakeholders

• Teachers

• Instructional Coaches

• Administrators

• Students

• Parents

Competitor Analysis

We analyzed platforms including:

• ClassDojo

• Panorama Education

• Observe4Success

• Schoolytics

• LessonUp

Key Findings

• Most tools focused heavily on analytics but lacked usability

• Classroom observation workflows were often complex

• Existing systems lacked centralized instructional support

• Real-time actionable feedback was limited

• Accessibility and onboarding experiences were inconsistent

Opportunity Identified

Create a unified platform that balances analytics, usability, accessibility, and collaborative instructional coaching.

Secondary Research

We reviewed educational and UX research papers focused on:

• AI-assisted instructional coaching

• Classroom engagement systems

• Data-driven educational decision making

• Accessibility in educational technology

• Teacher evaluation frameworks

Major Insights

• Teachers preferred actionable insights over raw analytics

• Multi-source feedback improved instructional quality

• Accessibility increased platform adoption and trust

• Simplified workflows reduced educator burnout

• Transparent AI systems improved user confidence

User Interviews & Surveys

We conducted interviews and surveys with educators and stakeholders to identify workflow pain points and user expectations.

Teachers Needed

• Faster feedback loops

• Simplified classroom analytics

• Better student participation visibility

• Reduced administrative effort

Instructional Coaches Needed

• Structured observation workflows

• Easier documentation systems

• Progress tracking visibility

Administrators Needed

• Centralized reporting systems

• Consistent evaluation frameworks

• Data-backed instructional decisions

9. Personas

We developed personas representing the platform’s primary stakeholders.

Teacher Persona

Focused on improving classroom engagement while minimizing administrative complexity.

Instructional Coach Persona

Needed efficient observation workflows and collaborative feedback systems.

Administrator Persona

Required centralized visibility into instructional performance and classroom trends.

The personas helped prioritize platform features, dashboard structures, and workflow organization.

10. Journey Mapping

Journey maps helped identify friction points across instructional coaching and classroom evaluation workflows.

Key Pain Points

• Manual evaluation processes

• Delayed instructional feedback

• Inconsistent classroom observations

• Information overload in reporting systems

• Limited collaboration between educators and administrators

These findings guided the redesign of the coaching and analytics experience.

11. Information Architecture

The platform architecture was redesigned around role-specific experiences to simplify navigation and reduce cognitive overload.

Core Platform Areas

• Teacher Dashboard

• Admin Dashboard

• Coaching Workflow

• Classroom Analytics

• Feedback & Reporting System

Outcome

The new structure improved workflow clarity and task efficiency across stakeholder groups.

12. Ideation & Wireframing

We explored multiple dashboard layouts, analytics systems, and coaching workflows through iterative design exploration.

Process

• Low-fidelity wireframes

• User flow diagrams

• Mid-fidelity concepts

• Dashboard explorations

• High-fidelity prototypes

Continuous feedback loops helped refine usability and simplify navigation patterns.

13. High-Fidelity Design

The final interface emphasized clarity, accessibility, and actionable data visualization.

Key Features

• AI-powered instructional insights

• Multi-role dashboards

• Classroom engagement tracking

• Observation and coaching workflows

• Responsive and accessible layouts

The design system prioritized consistency, readability, and reduced cognitive load.

14. Usability Testing

Usability evaluations were conducted with teachers, administrators, and instructional coaches to validate workflow clarity and dashboard usability.

Testing Goals

• Evaluate navigation efficiency

• Validate dashboard comprehension

• Identify workflow friction

• Test accessibility and readability

Key Findings

Users appreciated:

• Simplified navigation

• Clear visual hierarchy

• Structured coaching workflows

• Actionable data presentation

Iterations Made

• Reduced information overload

• Improved onboarding guidance

• Simplified dashboard layouts

• Enhanced accessibility support

15. Final Solution

The final product delivered a centralized instructional coaching ecosystem designed to improve teaching effectiveness through AI-assisted insights and collaborative educational workflows.

Final Deliverables

✅ AI-powered instructional feedback
✅ Classroom engagement analytics
✅ Multi-role educational dashboards
✅ Streamlined coaching workflows
✅ Accessible and responsive design system
✅ Data-driven decision support tools

16. Impact

UX Impact

• Simplified coaching and evaluation workflows

• Improved instructional visibility

• Reduced navigation complexity

• Enhanced accessibility and usability

Product Impact

• Unified disconnected educational workflows

• Improved collaboration between stakeholders

• Created scalable foundations for AI-driven educational support

17. Key Learnings

Designing for Multiple Stakeholders

Balancing the needs of teachers, coaches, administrators, students, and parents required continuous prioritization and systems thinking.

Simplicity Improves Adoption

Users preferred actionable and simplified insights over complex analytics-heavy systems.

Accessibility Matters Early

Inclusive and accessible educational systems directly improve usability and trust.

AI Requires Transparency

Users responded positively when AI recommendations felt understandable, explainable, and supportive rather than intrusive.

18. Reflection

This project strengthened my ability to:

• Conduct end-to-end UX research

• Translate research into product strategy

• Design complex multi-user systems

• Facilitate usability testing

• Create accessible and data-driven digital experiences

The experience deepened my understanding of designing responsible AI-powered educational products that balance analytics, usability, and human-centered design.