Andrew Katz
Biographic Data
| ID | 4219480 |
|---|---|
| NAME | Andrew Katz |
| GIVEN NAMES | Andrew |
| FAMILY NAME | Katz |
| SIGNATURE | KATZ A |
| AFFILIATIONS | Virginia Tech |
| ORCID | 0000-0002-3554-9015 |
| VERIFIED | Yes |
| TOTAL WORKS | 7 |
| TOTAL CITATIONS | 5 |
| WORKS AS AUTHOR | 7 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 1988 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 2 |
Understanding health systems thinking in medical education
BACKGROUND: Health systems science (HSS) education is an increasingly important component of undergraduate medical education. Despite curricular advances, the ways in which clinicians implement health systems science knowledge in everyday clinical practice, health systems thinking, remains understudied. A better understanding of how clinicians engage in health systems thinking to address everyday problems in clinical contexts is needed. METHODS: …
Thematic analysis with open-source generative AI and machine learning
This work aims to answer one central question: to what extent can open-source generative text models be used in a workflow to approximate steps in thematic analysis in social science research? To answer this question, we present the Generative AI-enabled Theme Organization and Structuring (GATOS) workflow, which uses open-source machine learning techniques, natural language processing tools, and generative text models to facilitate aspects of the…
Advancing qualitative analysis in professional disaster and risk communication
Leveraging Generative Text Models and Natural Language Processing to Perform Traditional Thematic Data Analysis
We explore the possibility of using natural language processing (NLP) and generative artificial intelligence (GAI) to streamline the process of thematic analysis (TA) for qualitative research. We followed traditional TA phases to demonstrate areas of alignment and discordance between (a) steps one might take with NLP and GAI and (b) traditional thematic analysis. Using a case study, we illustrate the application of this workflow to a real-world d…
Using Generative Text Models to Create Qualitative Codebooks for Student Evaluations of Teaching
Feedback is a critical aspect of improvement. Unfortunately, when there is a lot of feedback from multiple sources, it can be difficult to distill the information into actionable insights. Consider student evaluations of teaching (SETs), which are important sources of feedback for educators. These evaluations can provide instructors with insights into what worked and did not during a semester. A collection of SETs can also be useful to administra…
Predicting engineering students’ desire to address climate change in their careers
More engineering students are needed to address climate change in their careers. These students are necessary because engineering includes designing and building machines, structures, and components that contribute large portions of society’s carbon emissions. We surveyed a national sample of undergraduate engineering students (n = 4605) in their last semester of college about their desire to address climate change in their careers and the factor…
A New Transliteration of Hebrew into Standard Characters
EKTB is a new transliteration scheme for Hebrew based on the historical development of the alphabet. Latin characters are identified by the early Hebrew letters from which they developed. Nineteen Hebrew letters find natural representatives among the Latin characters. The three others are assigned arbitrarily. EKTB treats the Latin characters as graphic variants of the Hebrew letters and permits Hebrew to be used with standard equipment while mai…
Using Generative Text Models to Create Qualitative Codebooks for Student Evaluations of Teaching
Feedback is a critical aspect of improvement. Unfortunately, when there is a lot of feedback from multiple sources, it can be difficult to distill the information into actionable insights. Consider student evaluations of teaching (SETs), which are important sources of feedback for educators. These evaluations can provide instructors with insights into what worked and did not during a semester. A collection of SETs can also be useful to administra…
Leveraging Generative Text Models and Natural Language Processing to Perform Traditional Thematic Data Analysis
We explore the possibility of using natural language processing (NLP) and generative artificial intelligence (GAI) to streamline the process of thematic analysis (TA) for qualitative research. We followed traditional TA phases to demonstrate areas of alignment and discordance between (a) steps one might take with NLP and GAI and (b) traditional thematic analysis. Using a case study, we illustrate the application of this workflow to a real-world d…
A New Transliteration of Hebrew into Standard Characters
EKTB is a new transliteration scheme for Hebrew based on the historical development of the alphabet. Latin characters are identified by the early Hebrew letters from which they developed. Nineteen Hebrew letters find natural representatives among the Latin characters. The three others are assigned arbitrarily. EKTB treats the Latin characters as graphic variants of the Hebrew letters and permits Hebrew to be used with standard equipment while mai…
Predicting engineering students’ desire to address climate change in their careers
More engineering students are needed to address climate change in their careers. These students are necessary because engineering includes designing and building machines, structures, and components that contribute large portions of society’s carbon emissions. We surveyed a national sample of undergraduate engineering students (n = 4605) in their last semester of college about their desire to address climate change in their careers and the factor…
Using Generative Text Models to Create Qualitative Codebooks for Student Evaluations of Teaching
Feedback is a critical aspect of improvement. Unfortunately, when there is a lot of feedback from multiple sources, it can be difficult to distill the information into actionable insights. Consider student evaluations of teaching (SETs), which are important sources of feedback for educators. These evaluations can provide instructors with insights into what worked and did not during a semester. A collection of SETs can also be useful to administra…
Advancing qualitative analysis in professional disaster and risk communication
Leveraging Generative Text Models and Natural Language Processing to Perform Traditional Thematic Data Analysis
We explore the possibility of using natural language processing (NLP) and generative artificial intelligence (GAI) to streamline the process of thematic analysis (TA) for qualitative research. We followed traditional TA phases to demonstrate areas of alignment and discordance between (a) steps one might take with NLP and GAI and (b) traditional thematic analysis. Using a case study, we illustrate the application of this workflow to a real-world d…
Understanding health systems thinking in medical education
BACKGROUND: Health systems science (HSS) education is an increasingly important component of undergraduate medical education. Despite curricular advances, the ways in which clinicians implement health systems science knowledge in everyday clinical practice, health systems thinking, remains understudied. A better understanding of how clinicians engage in health systems thinking to address everyday problems in clinical contexts is needed. METHODS: …
Thematic analysis with open-source generative AI and machine learning
This work aims to answer one central question: to what extent can open-source generative text models be used in a workflow to approximate steps in thematic analysis in social science research? To answer this question, we present the Generative AI-enabled Theme Organization and Structuring (GATOS) workflow, which uses open-source machine learning techniques, natural language processing tools, and generative text models to facilitate aspects of the…
Generative grammar (4 works) · Computer Science (3 works) · Generative model (3 works) · Artificial Intelligence (2 works) · Codebook (2 works) · Computational and Text Analysis Methods (2 works) · Linguistics (2 works) · Natural language processing (2 works) · Psychology (2 works) · Qualitative research (2 works)