The Carnegie Mellon University, as a leader in education technology, provides tools and methods for CMU and the educational community in general thanks to rigorous expertise in research and learning science. Last year, the University launched a new seed subsidy program to help teachers undertake the research and development of generative education tools.
The selection of this year's laureates includes three projects led by teachers intended to support the efforts that develop, unfold and test new generative AI tools to improve teaching and learning. The initiative funded by the CMU and the donors allows up to $ 150,000 in support of each new research project with the potential to improve educational methods and results.
Help students demonstrate control of subjects
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Paulo Carvalho(Opens in a new window)The main researcher of this subsidy is a deputy professor at Carnegie Mellon Human computers Institute(Opens in a new window). Carvalho examines how generative AI can stimulate students' commitment while allowing teachers to provide more personalized support.
The search for Carvalho explores how AI can revolutionize learning by creating committing environments, first and only practice. Using data analysis and computer modeling, he studies the models of the learning, motivation and interest of students to develop specific models that improve educational experiences.
Work alongside Fellow Postdoctoral HCII Michael Asher(Opens in a new window)Carvalho seeks to use the price to develop a master's based on master's based on master's dearction tool, which will provide personalized comments on open issues. The objective is to encourage more in -depth treatment among students, rather than limiting control tests to multiple choice questions, which tend to cause minimal effort.
Creation of a framework for significant feedback
John Stamper(Opens in a new window) is an associate professor in Human-Computer Interaction Institute. He is also the technical director of learning Datashop(Opens in a new window)The largest reference data reference of transactional educational data, visualization tools and analysis tools for researchers in learning sciences.
As a recipient of seed subsidies, Stamper will focus on the development of a framework for the design of feedback prompts based on LLM guided by the principles of the learning sciences.
The project, which uses an existing library called Langchain to allow the API to access a large number of LLM, will also seek to integrate the frame into existing platforms (for example, Carnegie Mellon Open learning initiative(Opens in a new window)) and provide educators with tools to create comments focused on LLM for educational and research purposes – for example, allowing education researchers and instructors to test the types of feedback work best in parameters.
Create immersive and adaptive learning experiences
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Param Vir Singh(Opens in a new window) is dean partner for research and the professor of commercial and marketing technologies of Carnegie Bosch Tepper business school(Opens in a new window). His research is generally focused on the intersection of the economy, automatic learning and AI, and the development of algorithms that deal with economic inequality, algorithmic biases and societal impacts of AI.
The project team of this prize includes the economics teacher Laurence Ales(Opens in a new window)Associate teaching professor of economics and director of assessment and success of apprenticeship John Gasper(Opens in a new window)And the project engineer Ai Bambi Brewer. Together, they will use the AI ​​to build an interactive case analysis tool which allows students to explore a scenario that takes place dynamically in response to their decisions, instead of following a single static story.
The declared objective is to provide learners with an immersive and adaptive learning experience that reflects the complexity of the real world. The research and implementation of the project will start within the Tepper school, with long -term potential for use in other political and human sciences.
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