Using Biometrics to Understand AI-Assisted Coding Performance and its Perception - a Registered Report

Nadja  Brix Koch; Theis  Helth Stensgaard; Paolo Tell; Paolo Burelli; Guillaume Andrea Desaphy; Alberto Antonio Romano; Nicole Novielli; Fabio Cefalato

doi:10.31219/osf.io/mex39_v2

Using Biometrics to Understand AI-Assisted Coding Performance and its Perception - a Registered Report

Nadja Brix Koch
, Theis Helth Stensgaard
, Paolo Tell
, Paolo Burelli
, Guillaume Andrea Desaphy
, Alberto Antonio Romano
, Nicole Novielli
, Fabio Cefalato

University of Bari

Research output: Contribution to conference - NOT published in proceeding or journal › Paper › Research › peer-review

Abstract

This paper presents the Stage 1 protocol for a confirmatory study investigating how biometric measurements can reveal cognitive differences in software development with and without AI assistance. We outline the theoretical foundation, specific hypotheses, detailed methodology, and planned analyses that will be conducted to address our research questions. Our study aims to identify and understand the neurophysiological correlates of the cognitive processes involved in AI-assisted programming and how these relate to measurable performance outcomes and developer perceptions.

Original language	English
Publication date	2025
Number of pages	10
DOIs	https://doi.org/10.31219/osf.io/mex39_v2
Publication status	Published - 2025
Event	International Symposium on Empirical Software Engineering and Measurement - Honululu, United States Duration: 28 Sept 2025 → 3 Dec 2025 Conference number: 19th https://conf.researchr.org/home/esem-2025

Symposium

Symposium	International Symposium on Empirical Software Engineering and Measurement
Number	19th
Country/Territory	United States
City	Honululu
Period	28/09/2025 → 03/12/2025
Internet address	https://conf.researchr.org/home/esem-2025

Keywords

AI
ChatGPT
Cognitive load
GenAI
Registered report

Access to Document

10.31219/osf.io/mex39_v2Licence: CC BY

ESEM_25_Registered_Report (1)Submitted manuscript, 560 KB

Cite this

Brix Koch, N., Helth Stensgaard, T., Tell, P., Burelli, P., Desaphy, G. A., Romano, A. A., Novielli, N., & Cefalato, F. (2025). Using Biometrics to Understand AI-Assisted Coding Performance and its Perception - a Registered Report. Paper presented at International Symposium on Empirical Software Engineering and Measurement, Honululu, Hawaii, United States. https://doi.org/10.31219/osf.io/mex39_v2

@conference{e08ba990f0e44a449cd34257b670553f,

title = "Using Biometrics to Understand AI-Assisted Coding Performance and its Perception - a Registered Report",

abstract = "This paper presents the Stage 1 protocol for a confirmatory study investigating how biometric measurements can reveal cognitive differences in software development with and without AI assistance. We outline the theoretical foundation, specific hypotheses, detailed methodology, and planned analyses that will be conducted to address our research questions. Our study aims to identify and understand the neurophysiological correlates of the cognitive processes involved in AI-assisted programming and how these relate to measurable performance outcomes and developer perceptions.",

keywords = "AI, ChatGPT, Cognitive load, GenAI, Registered report",

author = "\{Brix Koch\}, Nadja and \{Helth Stensgaard\}, Theis and Paolo Tell and Paolo Burelli and Desaphy, \{Guillaume Andrea\} and Romano, \{Alberto Antonio\} and Nicole Novielli and Fabio Cefalato",

year = "2025",

doi = "10.31219/osf.io/mex39\_v2",

language = "English",

note = " International Symposium on Empirical Software Engineering and Measurement, ESEM 2025 ; Conference date: 28-09-2025 Through 03-12-2025",

url = "https://conf.researchr.org/home/esem-2025",

}

Brix Koch, N, Helth Stensgaard, T, Tell, P , Burelli, P, Desaphy, GA, Romano, AA, Novielli, N & Cefalato, F 2025, 'Using Biometrics to Understand AI-Assisted Coding Performance and its Perception - a Registered Report', Paper presented at International Symposium on Empirical Software Engineering and Measurement, Honululu, United States, 28/09/2025 - 03/12/2025. https://doi.org/10.31219/osf.io/mex39_v2

Using Biometrics to Understand AI-Assisted Coding Performance and its Perception - a Registered Report. / Brix Koch, Nadja ; Helth Stensgaard, Theis ; Tell, Paolo et al.
2025. Paper presented at International Symposium on Empirical Software Engineering and Measurement, Honululu, Hawaii, United States.

Research output: Contribution to conference - NOT published in proceeding or journal › Paper › Research › peer-review

TY - CONF

T1 - Using Biometrics to Understand AI-Assisted Coding Performance and its Perception - a Registered Report

AU - Brix Koch, Nadja

AU - Helth Stensgaard, Theis

AU - Tell, Paolo

AU - Burelli, Paolo

AU - Desaphy, Guillaume Andrea

AU - Romano, Alberto Antonio

AU - Novielli, Nicole

AU - Cefalato, Fabio

N1 - Conference code: 19th

PY - 2025

Y1 - 2025

N2 - This paper presents the Stage 1 protocol for a confirmatory study investigating how biometric measurements can reveal cognitive differences in software development with and without AI assistance. We outline the theoretical foundation, specific hypotheses, detailed methodology, and planned analyses that will be conducted to address our research questions. Our study aims to identify and understand the neurophysiological correlates of the cognitive processes involved in AI-assisted programming and how these relate to measurable performance outcomes and developer perceptions.

AB - This paper presents the Stage 1 protocol for a confirmatory study investigating how biometric measurements can reveal cognitive differences in software development with and without AI assistance. We outline the theoretical foundation, specific hypotheses, detailed methodology, and planned analyses that will be conducted to address our research questions. Our study aims to identify and understand the neurophysiological correlates of the cognitive processes involved in AI-assisted programming and how these relate to measurable performance outcomes and developer perceptions.

KW - AI

KW - ChatGPT

KW - Cognitive load

KW - GenAI

KW - Registered report

U2 - 10.31219/osf.io/mex39_v2

DO - 10.31219/osf.io/mex39_v2

M3 - Paper

T2 - International Symposium on Empirical Software Engineering and Measurement

Y2 - 28 September 2025 through 3 December 2025

ER -

Using Biometrics to Understand AI-Assisted Coding Performance and its Perception - a Registered Report

Abstract

Symposium

Keywords

Access to Document

Fingerprint

Cite this