Project Overview

After successfully launching the AI-Driven Course Creation project, we encountered a new challenge: many clients inquired about Eduqat’s assignment feature and how it could be enhanced. This prompted us to explore the integration of AI into our Assignment system. Our goal was to simplify the process for educators—helping them create assignments more efficiently, generate grading rubrics seamlessly, and leverage AI-powered assessment to evaluate thousands of submissions instantly. By automating these aspects, we aim to reduce manual workload and enhance the overall learning experience.

Problem Statement

Despite the growing adoption of digital learning platforms, educators and institutions still face significant challenges in managing student assignments effectively:

• 1. Time-Consuming Assignment Creation: Educators spend substantial time structuring assignments and defining grading criteria. Many lack the tools to streamline this process, leading to inefficiencies.
• 2. Inconsistent and Subjective Grading: Manual grading is often subjective and inconsistent, especially when multiple educators are involved. This inconsistency affects fairness and student learning outcomes.
• 3. Scalability Issues: Large-scale courses struggle with grading assignments promptly. Reviewing thousands of submissions manually is impractical, delaying feedback and hindering student progress.
• 4. Limited AI-Driven Insights: Traditional grading systems lack intelligent analytics that could provide deeper insights into student performance and learning patterns.

Solutions Offered

To address these challenges, we designed the AI-Powered Assignment System, which streamlines assignment creation, evaluation, and feedback with intelligent automation:

• 1. AI-Generated Assignments & Rubrics: Educators can quickly generate well-structured assignments and grading rubrics with AI assistance, reducing the time spent on manual creation.
• 2. Automated AI Grading: The system can evaluate thousands of submissions in real time, providing objective, consistent, and transparent grading based on predefined rubrics.
• 3. Scalable and Adaptive Feedback: AI not only grades assignments but also offers personalized feedback, helping students understand their strengths and areas for improvement.AI not only grades assignments but also offers personalized feedback, helping students understand their strengths and areas for improvement.

Objectives

The goal of this project is to empower educators and institutions by streamlining the assignment creation, evaluation, and feedback process through AI-driven automation. By integrating intelligent grading, rubric generation, and personalized feedback, the system reduces manual workload while ensuring accuracy, consistency, and scalability.

With an intuitive user interface and smart automation tools, educators can effortlessly design assignments, generate structured grading criteria, and assess thousands of submissions in real-time. This not only enhances efficiency but also improves learning outcomes by providing students with instant, data-driven feedback. Ultimately, the AI-Powered Assignment System enables a more effective, fair, and engaging assessment experience for both educators and learners.

Roles & Responsibilities

As a Product Designer, I played a key role in shaping the AI Smart Assignment System, covering both UX and UI design aspects. I began by conducting in-depth research on AI integration in assignment workflows, exploring its feasibility, opportunities, and limitations within edtech. This involved understanding AI’s role in automated grading, rubric generation, and personalized feedback, while also identifying potential challenges such as bias in AI assessments, scalability issues, and regulatory considerations.

To ensure alignment with user needs, I synthesized insights from multiple stakeholder meetings with Eduqat’s C-level team, gathering direct feedback from clients on their frustrations and expectations. From these discussions, I identified critical pain points, mapped AI workflows based on stakeholder assumptions, and refined the solution to ensure both technical viability and educator usability.

Competitor benchmarking was another key part of my role, where I analyzed how leading edtech platforms implemented AI-driven assignment tools. This research helped uncover industry best practices, feature logic, and usability gaps that informed our design strategy.

With these insights, I developed user flows, wireframes, and initial UI designs, ensuring a seamless experience for educators. My work laid the foundation for the AI-powered assignment creation, grading automation, and scalable feedback system, before the final UI refinements were handed off to the dedicated UI Designer.

Uncharted Teritory

After multiple discussions with stakeholders about the logic behind AI Smart Assignment, my team and I uncovered a key insight about AI Smart Assignment that the true challenge isn’t just about automation, but at its core, this feature is about helping educators spend less time creating assignments and making grading at scale more efficient and insightful. However, as we explored further, we discovered that the problem space was much broader than anticipated many aspects remained undefined, and the expected output needed clearer mapping to truly address these challenges. As a product designer, I found myself asking:

"What role do I play in solving this? What kind of solution can I define?"

In trying to break down the problem, several concerns surfaced:

With so many uncharted questions, our team dived deeper into discussions to establish the boundaries and capabilities AI should have in this Smart Assignment feature. Through this process, we defined key feature logic:

This process of understanding how AI can help with assignments has been both challenging and exciting. As I design the interface, my main goal is to make sure educators feel supported, not replaced. AI isn’t just about automation, it’s about enhancing the learning experience in a way that keeps the human touch at the center.

Source: www.aiprm.com/ai-in-education-statistics

Comparative Feature Analysis

To build a competitive and innovative course creation platform, I conducted a competitor benchmarking analysis on the following platforms: Thinkific, Kajabi, Teachable, Mini Course Generator, and Learnworld. The goal was to compare key features and identify opportunities where Eduqat can stand out.

For the competitor benchmarking, I analyzed five key aspects to gain insights into how Eduqat can stand out in the market. These included total active users to understand the market reach and adoption of each platform, Pro plan pricing to compare subscription costs and position Eduqat competitively, AI course creation to evaluate how AI is being used to streamline the course development process, AI assignment or assessment to check if AI is being utilized for automating student evaluations and giving a feedback, and also AI quiz creation to analyze how AI is assisting in generating quizzes and interactive content. This comprehensive analysis provided valuable insights to guide Eduqat’s feature development and competitive strategy.

Google Classroom

Learnworld

Lorem ipsum dolor

Key Takeaways From Benchmarking

After analyzing Thinkific, Kajabi, Teachable, Mini Course, and Learnworlds, here’s what I found:

Business Goal Insights for Eduqat Based on the Research Data

Based on my research, Eduqat’s AI-driven course creation should align with the following business goals:

2 Ideate

Brainstorming With Team

After gathering insights from research, the next crucial step is to present the findings to the internal team. My team and I will always open a meeting discussion using Zoom, Slack or Lark, this step will help us to determine the scope of AI implementation in course creation. In the end of discussion, we prioritize the most impactful features while aligning with development feasibility. Additionally, we will identify the key user needs when interacting with the AI-powered course creation tool.

Features Mapping Using Eisenhower Matrix

Previous Next

Let's 👋 Work Together Let's 👋 Work Together

Let's 👋 Work Together Let's 👋 Work Together