Research

MY Research areas

Educational data mining

We employ state-of-the-art methods in data mining, machine learning, and natural language processing to analyze large-scale data from different educational settings (e.g., digital assessments). Our goal is to extract meaningful information from complex educational data and turn it into actionable insights.

learning analytics

We harness student data from various sources (e.g., trace data from learning management systems) to identify important factors associated with learning. Our goal is to design and implement effective learning analytics systems that inform personalized learning applications in all stages of education.

psychometrics

We analyze data from educational and psychological assessments and make inferences about the quality of the measurement process. Our goal is to identify and resolve psychometric issues (e.g., bias, careless responding, and wording effects) that threaten the validity and reliability of assessments.

CURRENT AND PAST PROJECTS

My projects aim to address research questions concerning how humans learn and demonstrate their learning in a variety of areas, such as academic achievement, social-emotional learning, and psychological latent constructs. As an educational researcher embracing pragmatism, I put a stronger emphasis on actionable knowledge and research practicality to solve critical problems related to the learning process. I collaborate with school authorities, educational organizations, and industrial partners on research projects focusing on different levels of education.

Further details about my current/past projects and research collaborations can be accessed using the following links:

Note to prospective students: I am currently accepting new students (M.Ed. or Ph.D.) for my research group. I am particularly interested in students who are interested in educational data mining, learning analytics, and artificial intelligence applications in education. Depending on the availability of research funding, I provide research assistantship (RA) support for students in my research group. Also, I help my students find internships (e.g., Mitacs) through my collaborations with industry partners. Before submitting an application for the MEDS program, I strongly encourage prospective students to review my current projects, publications, and presentations to determine fit.

CURRENT MEMBERS OF BULUT Research Group

Graduate students play a crucial role in my research program as all of my projects always involve graduate students that I either supervise or co-supervise. In my research group, senior students work closely with new students on a wide range of research projects. My goal is to train excellent students who can be valuable assets to the workforce, while we collectively cultivate diversity, inclusion, and equity within a collaborative learning environment.

Elisabetta Mazzullo

M.Ed. Student, Measurement, Evaluation, and Data Science

Elisabetta is interested in test development, computational psychometrics, and the application of artificial intelligence (AI) technologies to educational assessments.

Daniel Jerez Garcia

M.Ed. Student, Measurement, Evaluation, and Data Science

Daniel is interested in analyzing large collections of data from educational settings to address important educational and psychological questions.

Tarid Wongvorachan

Ph.D. Student, Measurement, Evaluation, and Data Science

Tarid is interested in the application of AI (i.e., educational data mining, learning analytics, and natural language processing) to educational measurement research.

Joyce Liu

M.Ed. Student, Measurement, Evaluation, and Data Science

Joyce is interested in computational psychometrics applications, both in low-stakes and high-stakes assessments, to gain deeper insight into students’ learning and competencies.

Ashley Clelland

M.Ed. Student, Measurement, Evaluation, and Data Science

Ashley is interested in applied measurement, data science, and evaluation in the context of public health and education, especially psychometric instrument development and data literacy assessment.

Kevin Vo

M.Ed. Student, Measurement, Evaluation, and Data Science

Kevin is interested in utilizing data science, particularly machine learning and educational data mining, to enrich our understanding of important educational and psychological variables.

Bin Tan

M.Ed. Student, Measurement, Evaluation, and Data Science

Bin is interested in applying the methods and techniques in artificial intelligence and data science to modeling educational and psychological constructs (e.g., well-being).