AktivGrid

Overview

Drawing organic molecules shouldn't feel like fighting with software. Yet for chemistry students, that's exactly what traditional digital tools felt like: restrictive, assessment-focused, and disconnected from how chemists actually think about molecular structures.

AktivGrid reimagined molecule drawing as a learning experience rather than an evaluation tool. As the sole designer, I built an interactive system that enables students to visualize and construct resonance structures, chair conformations, Newman projections, Fischer diagrams, lone pairs, and curved-arrow mechanisms, all with real-time feedback that helps them learn from their mistakes rather than just marking them wrong.

The result was a U.S. Patent (#12,347,531 B2) and a tool adopted by over 5,000 institutions in General and Organic Chemistry courses.

The Problem

Traditional digital chemistry tools had a fundamental disconnect. They were built for assessment, testing whether students could produce the correct answer, rather than for learning. This created several critical problems:

Students Preferred Paper Over Digital

In user interviews with curriculum designers and chemistry professors, I heard the same story repeatedly: students would rather sketch on paper than use existing digital tools. The software felt restrictive and didn't support nuanced learning concepts like resonance structures, curved arrow mechanisms, chair conformations, and conformational analysis.

No Room for Mistakes

Existing tools marked answers as simply right or wrong, with little guidance on why an answer was incorrect or how to improve. This binary feedback model doesn't align with how students actually learn chemistry: through experimentation, hypothesis testing, and iterative refinement.

Disconnected from Chemical Thinking

The tools didn't reflect how chemists actually think about and teach molecules. They focused on input mechanics rather than chemical concepts. Students needed to understand formal charges, octet rules, electron movement, and structural relationships, but the tools provided no support for developing this understanding.

Expensive and Inaccessible

The few available alternatives were prohibitively expensive, costing over $1,500 per license. Even worse, they were desktop-only applications with no online version, forcing instructors to manually collect and review files via email. This created significant workflow friction and made remote learning nearly impossible. The cost barrier meant many institutions couldn't provide these tools to students at all, widening educational inequity.

User interviews revealed students preferred sketching on paper due to restrictive digital tools

Design Process

As the sole designer, I managed the complete product lifecycle from research through implementation. The process was deeply collaborative with chemistry professors and curriculum designers who helped me understand the pedagogical requirements.

1. Research & Understanding

I started by immersing myself in how organic chemistry is taught and learned:

• Observed chemistry lectures: Watched how professors draw structures on whiteboards and explain mechanisms
• Student interviews: Understood pain points with existing tools and preferences for paper-based work
• Competitive analysis: Evaluated existing molecule drawing software (ChemDraw, MarvinSketch, etc.) to identify gaps
• Textbook study: Analyzed how chemistry concepts are visually represented in educational materials

2. Interaction Design Foundations

I developed visual interaction systems for the fundamental building blocks:

• Atoms and bonds: How to place, connect, and modify atomic structures intuitively
• Charges and electrons: Visual representations for formal charges, lone pairs, and radical electrons
• Stereochemistry: Wedge and dash notation for 3D spatial relationships
• Arrows and mechanisms: Tools for showing electron movement and reaction pathways

3. Iteration & Prototyping

Through multiple design cycles, I tested different approaches:

• Contextual sidebar vs. floating toolbar: Tested different UI patterns to minimize cognitive load
• Tap-to-place vs. drag interactions: Evaluated what felt most natural for mobile and desktop
• Grid-based vs. free-form: Explored constraints that guide without restricting
• Feedback timing: Determined when to show validation messages (immediate vs. on-demand)

4. Engineering Collaboration

I created interactive prototypes in Figma and worked closely with the engineering team to implement the validation logic. This required understanding the chemical rules well enough to specify edge cases and error states clearly.

Three-year iterative design process from research to patented product

Technical Innovation

The patent-worthy innovation in AktivGrid wasn't just the interface. It was the underlying chemical intelligence system that validates structures and provides meaningful feedback.

Structure Validation Engine

The system analyzes molecular structures using chemical rules to identify errors:

• Carbon chain validation: Detects incorrect bonding patterns and missing carbons
• Functional group recognition: Identifies missing or misplaced chemical groups
• Valency checking: Ensures atoms have correct number of bonds
• Stereochemistry analysis: Validates 3D spatial arrangements

Multi-Step Synthesis Grading

For complex mechanism problems, the system evaluates each step independently:

• Reagent validation: Checks if reagents are appropriate for each step
• Product evaluation: Verifies intermediate and final products
• Mechanism accuracy: Validates electron movement arrows
• Partial credit: Awards points for correct portions even if final answer is wrong

Mistake-Driven Learning

Rather than just flagging errors, the system provides guidance that helps students understand why something is wrong and how to fix it. This key pedagogical innovation made the patent possible.

Design Principles

Several core principles guided every design decision in AktivGrid:

1. Learning Over Assessment

Every feature was evaluated through the lens of "does this help students learn?" rather than "does this help us grade students?" This meant prioritizing real-time feedback, partial credit, and multiple solution paths over binary right/wrong evaluation.

2. Mistake-Driven Discovery

Mistakes are learning opportunities, not failures. The system was designed to make chemistry logic visible. When students drew an invalid structure, they could see exactly why it violated chemical rules and experiment with corrections.

3. Reflect How Chemists Think

The interface needed to mirror how chemists actually work with molecular structures by thinking in terms of functional groups, electron movement, and structural relationships rather than just positioning atoms on a grid.

4. Mobile-First, Not Mobile-Adapted

Rather than building for desktop and adapting to mobile, I designed for touch interaction first. This meant larger tap targets, gesture-based controls, and simplified toolbars that worked with thumbs, not just cursors.

5. Deep Subject Matter Collaboration

I couldn't design an effective chemistry tool without understanding chemistry. I worked closely with professors and curriculum designers throughout the process, learning not just what to build but why certain pedagogical approaches work.

Technologies & Tools