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Purdue Education with AI Research Lab

Welcome to the Purdue University AI in Education Research Lab, led by the visionary Dr. Emily Xander. Our lab is at the forefront of integrating artificial intelligence into educational frameworks, developing innovative AI-driven tools that revolutionize how students learn and educators teach.

Our mission is to bridge the gap between cutting-edge AI research and practical educational applications, fostering an environment where innovation thrives and educational barriers are dismantled. Dedicated to advancing the integration of AI in educational settings, we focus on enhancing learning outcomes, personalizing student experiences, and optimizing educational processes.

We believe in the power of AI to make education more effective and inclusive, ensuring every student has the opportunity to succeed. Join us as we explore the future of education and unlock new possibilities for learners everywhere.

Key Projects

Adaptive Learning Platform

Adaptive Learning Platform

An AI-driven system that customizes course content based on individual student performance and preferences.

Intelligent Tutoring System

Intelligent Tutoring System

A personalized tutoring system that uses AI to provide tailored learning experiences.

EduData Insights

EduData Insights

A data analytics tool for educational institutions to enhance student success.

NLP Essay Grader

NLP Essay Grader

An AI-powered tool for automated essay grading and feedback.

Research Focus Areas

AI-Powered Personalized learning

    Development of adaptive learning platforms that tailor educational content to individual student needs and learning styles.
    Research on intelligent tutoring systems that provide real-time feedback and support to learners.

Educational Data Mining

    Analyzing large datasets from educational institutions to uncover patterns and insights that can inform instructional strategies and policy decisions.
    Predictive analytics to identify at-risk students and suggest interventions.

Natural Language Processing in Education

    Creating AI tools for automated essay scoring, feedback generation, and language learning assistance.
    Development of conversational agents that can interact with students and answer their questions.

AI Ethics in Education

    Investigating the ethical implications of AI deployment in educational contexts.
    Ensuring fairness, transparency, and accountability in AI systems used in education.

Gamification and Immersive Learning

    Designing AI-driven educational games that make learning engaging and interactive.
    Research on virtual and augmented reality applications in education.

Dr. Emily Xander

128 Memorial Mall Dr., West Lafayette, IN 47907 Room 201

Work Phone: (765) - 498 - X686

Work Email: emilyxander@purdue.edu

Dr. Emily Xander's early career was marked by significant contributions to general AI research, including advanced machine learning algorithms and natural language processing. Over time, her interests and expertise evolved towards applying AI to education, where she has become a leading figure in developing AI-driven tools and systems that enhance learning experiences.

Education

  • Ph.D. in Artificial Intelligence: Massachusetts Institute of Technology (MIT), 2010
    • Dissertation: "Adaptive Learning Systems: Bridging AI and Educational Theory"
  • M.S. in Computer Science: Stanford University, 2005
    • Thesis: "Natural Language Processing for Educational Applications"
  • B.S. in Computer Science and Cognitive Science: University of California, Berkeley, 2003
    • Honors Thesis: "The Role of AI in Personalized Learning Environments"

Professional Experience

  • Associate Professor: Stanford University, Department of Computer Science (2015-2023)
  • Senior Research Scientist: Google AI (2012-2015)
  • Postdoctoral Fellow: Harvard University, Graduate School of Education (2010-2012)

Professional Memberships

  • Association for the Advancement of Artificial Intelligence (AAAI)
  • International Society for Artificial Intelligence in Education (IAIED)
  • IEEE Computer Society

Selected Publications

  • Xander, E. (2020). "AI-Powered Adaptive Learning: A New Era in Education." Journal of Educational Technology, 35(4), 567-589.
  • Xander, E., & Smith, J. (2018). "Natural Language Processing in Education: Challenges and Opportunities." AI in Education Journal, 29(3), 456-478.
  • Xander, E. (2014). "Advanced Machine Learning Algorithms for Language Processing." Journal of Artificial Intelligence Research, 28(1), 98-120.
  • Xander, E. (2011). "Building Robust Language Models." International Journal of Computational Linguistics, 25(3), 334-357.