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20232025
most citedThrilled by Your Progress! Large Language Models (GPT-4) No Longer Struggle to Pass Assessments in Higher Education Programming Courses

140 citations · 527 across the 13 of their papers we have counts for

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8 papers · 1 filter

cs.CY2023★ 118 cited

A Comparative Study of AI-Generated (GPT-4) and Human-crafted MCQs in Programming Education

Jacob Doughty, Zipiao Wan, Anishka Bompelli +12

There is a constant need for educators to develop and maintain effective up-to-date assessments. While there is a growing body of research in computing education on utilizing large…

cs.CY2023★ 1 cited

From GPT-3 to GPT-4: On the Evolving Efficacy of LLMs to Answer Multiple-choice Questions for Programming Classes in Higher Education

Jaromir Savelka, Arav Agarwal, Christopher Bogart +1

We explore the evolving efficacy of three generative pre-trained transformer (GPT) models in generating answers for multiple-choice questions (MCQ) from introductory and intermedia…

cs.AI2023★ 29 cited

Harnessing LLMs in Curricular Design: Using GPT-4 to Support Authoring of Learning Objectives

Pragnya Sridhar, Aidan Doyle, Arav Agarwal +3

We evaluated the capability of a generative pre-trained transformer (GPT-4) to automatically generate high-quality learning objectives (LOs) in the context of a practically oriente…

cs.LG2023★ 1 cited

MultiZoo & MultiBench: A Standardized Toolkit for Multimodal Deep Learning

Paul Pu Liang, Yiwei Lyu, Xiang Fan +4

Learning multimodal representations involves integrating information from multiple heterogeneous sources of data. In order to accelerate progress towards understudied modalities an…

cs.CL2023★ 108 cited

Can GPT-4 Support Analysis of Textual Data in Tasks Requiring Highly Specialized Domain Expertise?

Jaromir Savelka, Kevin D. Ashley, Morgan A Gray +2

We evaluated the capability of generative pre-trained transformers~(GPT-4) in analysis of textual data in tasks that require highly specialized domain expertise. Specifically, we f…

cs.CY2023★ 140 cited

Thrilled by Your Progress! Large Language Models (GPT-4) No Longer Struggle to Pass Assessments in Higher Education Programming Courses

Jaromir Savelka, Arav Agarwal, Marshall An +2

This paper studies recent developments in large language models' (LLM) abilities to pass assessments in introductory and intermediate Python programming courses at the postsecondar…

cs.AI2023★ 108 cited

Can Generative Pre-trained Transformers (GPT) Pass Assessments in Higher Education Programming Courses?

Jaromir Savelka, Arav Agarwal, Christopher Bogart +2

We evaluated the capability of generative pre-trained transformers (GPT), to pass assessments in introductory and intermediate Python programming courses at the postsecondary level…

cs.CL2023★ 4 cited

Large Language Models (GPT) Struggle to Answer Multiple-Choice Questions about Code

Jaromir Savelka, Arav Agarwal, Christopher Bogart +1

We analyzed effectiveness of three generative pre-trained transformer (GPT) models in answering multiple-choice question (MCQ) assessments, often involving short snippets of code,…