The Customer
Named one of the top childcare franchises in the United States, Goddard Schools is a vast network of schools serving over 90,000 students. The quality of their teaching is a top priority. To honor their educators, they have an annual “Teacher of the Year” award program, where faculty and parents can nominate outstanding teachers in their Goddard communities. Previously, this process involved collecting and manually evaluating thousands of feedback submissions across different regions. The feedback ranged from written essays to video submissions, all evaluated on a specific grading criterion.
The Opportunity
The evaluation process had historically been quite time-consuming as it relied on a third-party vendor manually reviewing over seven thousand submissions. From those thousands, Goddard was given the top 48 options and from there narrowed it down to their “Teacher of the Year.”
This approach took several weeks given the very nature of the varied submissions and the different criteria required to score with.
Goddard wanted a solution that would help automate and standardize the evaluation process, ensuring a faster, more objective and scalable approach to selecting their “Teacher of the Year.”
This was an opportunity for dbSeer to help provide guidance and ensure these objectives would be met.
The Solutions
At dbSeer we believe that technology is intended to serve you and help bring you closer to your impact. We use cutting-edge technologies to help you get to that goal.
We decided to do just that with Goddard. dbSeer is a proud and we were able to use the extensive capabilities offered by AWS to help empower the educators in the Goddard Schools- finding the “Teacher of the Year” in the process.
Goddard provided dbSeer the data with thousands of essay responses and video recordings. The recordings were transcribed using AWS Transcribe, and all the responses were processed using AWS Glue. They were then stored in an AWS Aurora database for ease of access.
The transcriptions were fed into Anthropic’s Claude Sonnet Large Language Model (LLM) designed by dbSeer using AWS Bedrock. The LLM used the grading criteria to sift through and provide scoring in a consistent and unbiased way. Empowering the AI with these AWS and Anthropic capabilities helped eliminate the judgment variability that naturally occurs between different human evaluators, ensuring more consistent and fair assessment. This helped provide an approachable and less overwhelming process for Goddard to choose their “Teacher of the Year.”
The Results
By leveraging the power of AWS, Anthropic and next-gen technology, we transformed Goddard Schools’ Teacher of the Year selection process.
We were able to turn a weeks-long evaluation process to one that can be completed within hours. The AWS-empowered process allows for subjective scoring, offering a level playing field for the grading.
The storing of data also now offers previously untapped potentials for the information they received. The data is now structured and stored for future reporting, which can help Goddard analyze future trends if they choose to. This allows opportunities for better reporting and year-over-year comparisons, further empowering their educators.
Goddard Schools emphasized the impact on their process: “Partnering with dbSeer to utilize GenAI and LLM technology for our ‘Teacher of the Year’ award has been a game changer. The solution resulted in a significant reduction of the time and resources needed to process nominations—from weeks to just hours. The ability to train the model to align with our criteria ensured a consistent and improved scoring process. dbSeer was an exceptional partner, taking the time to deeply understand our needs and delivering a solution that exceeded expectations.” ~Danika Brown, Director, Brand Marketing & Creative Services
Let data drive your impact. Connect with dbSeer today to empower your employees with faster, fairer solutions—just like Goddard did.
