no code implementations • 28 Apr 2024 • Atharva Naik, Jessica Ruhan Yin, Anusha Kamath, Qianou Ma, Sherry Tongshuang Wu, Charles Murray, Christopher Bogart, Majd Sakr, Carolyn P. Rose
An advantage of Large Language Models (LLMs) is their contextualization capability - providing different responses based on student inputs like solution strategy or prior discussion, to potentially better engage students than standard feedback.
no code implementations • 5 Dec 2023 • Jacob Doughty, Zipiao Wan, Anishka Bompelli, Jubahed Qayum, Taozhi Wang, Juran Zhang, Yujia Zheng, Aidan Doyle, Pragnya Sridhar, Arav Agarwal, Christopher Bogart, Eric Keylor, Can Kultur, Jaromir Savelka, Majd Sakr
While there is a growing body of research in computing education on utilizing large language models (LLMs) in generation and engagement with coding exercises, the use of LLMs for generating programming MCQs has not been extensively explored.
no code implementations • 30 Jun 2023 • Pragnya Sridhar, Aidan Doyle, Arav Agarwal, Christopher Bogart, Jaromir Savelka, Majd Sakr
We evaluated 127 LOs that were automatically generated based on a carefully crafted prompt (detailed guidelines on high-quality LOs authoring) submitted to GPT-4 for conceptual modules and projects of an AI Practitioner course.
no code implementations • 16 Mar 2023 • Jaromir Savelka, Arav Agarwal, Christopher Bogart, YiFan Song, Majd Sakr
We evaluated the capability of generative pre-trained transformers (GPT), to pass assessments in introductory and intermediate Python programming courses at the postsecondary level.
no code implementations • 9 Mar 2023 • Jaromir Savelka, Arav Agarwal, Christopher Bogart, Majd Sakr
While questions requiring to fill-in a blank in the code or completing a natural language statement about the snippet are handled rather successfully, MCQs that require analysis and/or reasoning about the code (e. g., what is true/false about the snippet, or what is its output) appear to be the most challenging.
no code implementations • 25 Jan 2022 • Margaret Burnett, Martin Erwig, Abrar Fallatah, Christopher Bogart, Anita Sarma
HCI researchers' and practitioners' awareness of intersectionality has been expanding, producing knowledge, recommendations, and prototypes for supporting intersectional populations.
no code implementations • WS 2017 • Shrimai Prabhumoye, Samridhi Choudhary, Evangelia Spiliopoulou, Christopher Bogart, Carolyn Penstein Rose, Alan W. black
There has been a long standing interest in understanding `Social Influence' both in Social Sciences and in Computational Linguistics.