140 citations · 563 across the 18 of their papers we have counts for
18 papers
Personalized Assessments from Personal Artifacts
Yufan Zhang, Jaromir Savelka, Seth Copen Goldstein +1
The rapid development and popularization of AI-enabled coding agents have meant software engineering students and professionals cannot be assumed to understand their own code, whic…
Prompt Coach: An Empirical Evaluation of an Agentic Tutor for Learning Prompt Engineering in Software Development
Rohit Mehra, Kapil Singi, Vikrant Kaulgud +5
Prompt engineering has emerged as a critical yet undertaught skill for software developers, one that traditional learning approaches are ill-equipped to support given its evolving,…
AI Literacy Assessment Revisited: A Task-Oriented Approach Aligned with Real-world Occupations
Christopher Bogart, Aparna Warrier, Arav Agarwal +6
As artificial intelligence (AI) systems become ubiquitous in professional contexts, there is an urgent need to equip workers, often with backgrounds outside of STEM, with the skill…
PlantD: Performance, Latency ANalysis, and Testing for Data Pipelines -- An Open Source Measurement, Testing, and Simulation Framework
Christopher Bogart, Rajeev Chhajer, Baljit Singh +2
As the volume of data available from sensor-enabled devices such as vehicles expands, it is increasingly hard for companies to make informed decisions about the cost of capturing,…
AI Technicians: Developing Rapid Occupational Training Methods for a Competitive AI Workforce
Jaromir Savelka, Can Kultur, Arav Agarwal +4
The accelerating pace of developments in Artificial Intelligence~(AI) and the increasing role that technology plays in society necessitates substantial changes in the structure of…
Generating Situated Reflection Triggers about Alternative Solution Paths: A Case Study of Generative AI for Computer-Supported Collaborative Learning
Atharva Naik, Jessica Ruhan Yin, Anusha Kamath +6
An advantage of Large Language Models (LLMs) is their contextualization capability - providing different responses based on student inputs like solution strategy or prior discussio…
Understanding the Role of Temperature in Diverse Question Generation by GPT-4
Arav Agarwal, Karthik Mittal, Aidan Doyle +5
We conduct a preliminary study of the effect of GPT's temperature parameter on the diversity of GPT4-generated questions. We find that using higher temperature values leads to sign…
Accelerated Cloud for Artificial Intelligence (ACAI)
Dachi Chen, Weitian Ding, Chen Liang +3
Training an effective Machine learning (ML) model is an iterative process that requires effort in multiple dimensions. Vertically, a single pipeline typically includes an initial E…
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…
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…
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…
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…
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…
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…
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,…
Comparing Example-Based Collaborative Reflection to Problem Solving Practice for Learning during Team-Based Software Engineering Projects
Sreecharan Sankaranarayanan, Siddharth Reddy Kandimalla, Christopher Bogart +5
Contributing to the literature on aptitude-treatment interactions between worked examples and problem-solving, this paper addresses differential learning from the two approaches wh…
Expressing Ethnicity through Behaviors of a Robot Character
Maxim Makatchev, Reid Simmons, Majd Sakr +1
Achieving homophily, or association based on similarity, between a human user and a robot holds a promise of improved perception and task performance. However, no previous studies…
A Cross-cultural Corpus of Annotated Verbal and Nonverbal Behaviors in Receptionist Encounters
Maxim Makatchev, Reid Simmons, Majd Sakr
We present the first annotated corpus of nonverbal behaviors in receptionist interactions, and the first nonverbal corpus (excluding the original video and audio data) of service e…