My research leverages unique data sources and advanced AI and machine learning methods to enhance higher education pathways. Key initiatives include the development of sophisticated recommender systems that have significantly improved the college selection process for international and graduate students. These efforts involved utilizing extensive datasets from the TOEFL test and a graduate school matching service to provide personalized educational recommendations. This work included complex tasks such as data collection, cleaning, and analysis, which were crucial in understanding student preferences and decision-making.

The impact of these initiatives is documented in our publication in the International Journal of Artificial Intelligence in Education (Tenison, McCulla, and Ling, 2023), which highlights our advancements in personalizing education solutions and introduces innovative methods for context-aware recommendations.

Beyond technical achievements, my role also encompasses leadership and strategic initiatives at ETS. I have spearheaded projects to address the challenges of bias in AI, enhancing our commitment to equitable educational technology. My leadership extends to cross-functional collaboration with teams and technology partners, ensuring that our projects not only meet but exceed industry standards. This advocacy for ethical AI implementation has been recognized in my presentations at major conferences, such as AIED 2023, and through consultations across departments at ETS. I have contributed to establishing frameworks that ensure our AI solutions uphold the highest ethical standards, reinforcing ETS's leadership in educational technology.

Tenison, C., Ober, T. & Phelps, G. (2025). Predicting Success: Joint Modeling of Retake Behaviors in Teacher Licensure Assessment. Paper accepted for presentation at the Annual Meeting of the National Council on Measurement in Education,Denver, CO. (Author preprint)