McGraw Hill Teaching Style Assessment

I designed the assessment interface and personalized results experiences, collaborated with the content writer on the question flow, developed the scoring implementation, and built the experience within Ion.

My responsibilities included creating the interactive question flow, implementing the scoring logic, designing the results page layouts, mapping each possible outcome to the correct experience, and thoroughly testing the assessment to ensure every response combination produced an accurate result.

Teachers may have a strong understanding of how they teach, but they may not use the same terminology organizations use to describe instructional approaches. Asking educators to identify their own teaching style—or navigate a large collection of resources without guidance—created unnecessary complexity.

The goal was to create a more approachable way for teachers to understand their instructional preferences while helping McGraw Hill connect educators with resources that aligned with their classroom approach.

The experience was built around McGraw Hill's existing teaching style framework, which positioned instructional approaches along a spectrum ranging from more lecture-based instruction (Guided Exploration) to more hands-on approaches (Activity-Based Learning).

Rather than requiring teachers to self-identify their teaching style, the assessment used a series of preference-based questions to uncover patterns in their responses. Each answer contributed to a scoring model that placed users into one of five teaching style categories. The scoring logic remained completely invisible to users. Teachers did not need to understand how their result was calculated—the complexity was handled behind the scenes so they could focus on answering questions and receiving a personalized recommendation.

Each result page translated the recommendation into an approachable experience using McGraw Hill's branded character system. The pages explained the user's teaching style, provided relevant educational resources, offered downloadable materials, and guided users toward additional McGraw Hill resources.

A major part of the project involved ensuring that the assessment logic worked reliably across every possible user path.

I implemented the scoring model within Ion and tested the experience to ensure responses consistently mapped to the correct teaching style category. The assessment included five possible outcomes, each with its own personalized results experience.

I also partnered with the content writer to review the structure and wording of the questions. Because responses were collected through a Strongly Agree to Strongly Disagree format, we considered how question phrasing could unintentionally favor one teaching style over another. The goal was to create a more balanced assessment experience that allowed users' responses—not the wording of individual questions—to determine their result.

The final experience provided educators with a more guided way to discover relevant McGraw Hill resources based on their teaching preferences.

Instead of asking teachers to navigate a broad collection of products and determine what might work for their classroom, the assessment created a personalized entry point based on their responses.

The project demonstrated how thoughtful experience design and technical implementation can transform a complex recommendation framework into a simple, approachable digital experience.