Data from Students' Use of Generative AI in Innovation Education Programs at CERN IdeaSquare

Mikko Sairanen; Jimmy Poulaillon; Lauri Valtonen; Giulia Gaddi; Catarina Batista; Ole Werner; Matteo Balocco; Andrea Bruno; Diego Canova Tandaypan; Ángel Costa-Perales; Jacopo Dardini; Ngo Hung Dung; Anastasiia Korovina; Fernando Palma Fanjul; Eduard Puga Creus; Filomena Scirocco; Adrián Toledo Martínez; Javier Pérez Trujillo

doi:10.23726/cij.2025.1799

Data from Students' Use of Generative AI in Innovation Education Programs at CERN IdeaSquare

Mikko Sairanen^*
, Jimmy Poulaillon
, Lauri Valtonen
, Giulia Gaddi
, Catarina Batista
, Ole Werner
, Matteo Balocco
, Andrea Bruno
, Diego Canova Tandaypan
, Ángel Costa-Perales
, Jacopo Dardini
, Ngo Hung Dung
, Anastasiia Korovina
, Fernando Palma Fanjul
, Eduard Puga Creus
, Filomena Scirocco
, Adrián Toledo Martínez
, Javier Pérez Trujillo

^*Corresponding author for this work

CERN
ESADE Business School
Universitá di Bologna
Polytechnic University of Valencia
Universidad del Bío-Bío
BarcelonaTech

Research output: Contribution to journal › Article › Scientific › peer-review

1 Citation (Scopus)

5 Downloads (Pure)

Abstract

This article presents a dataset comprising Master-level students’ prompts and discussions with generative artificial intelligence (AI) as part of a challenge-based innovation problem-solving process. Openly accessible through Zenodo (https://doi.org/10.5281/zenodo.17857679), the data consists of 466 pages of students’ conversations with generative AI tools and a 28-page extract comprising only the prompts. The data was collected through a survey for students participating in week-long intense innovation education programs at CERN IdeaSquare throughout 2024. The data can be used to advance practice and theory regarding the use of generative AI in problem solving and innovation education. Scholars are encouraged to use the data in various forms of analysis, including thematic, content, and narrative analysis. The data can also complement other similar datasets in larger studies to examine the effects of different pedagogical approaches, student profiles, or problem-solving situations on the use of generative AI.

Original language	English
Pages (from-to)	53-56
Number of pages	4
Journal	CERN IdeaSquare Journal of Experimental Innovation
Volume	9
Issue number	3
DOIs	https://doi.org/10.23726/cij.2025.1799
Publication status	Published - 2025
MoE publication type	A1 Journal article-refereed

Keywords

Generative AI
innovation education
prompt

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Cite this

Sairanen, M., Poulaillon, J., Valtonen, L., Gaddi, G., Batista, C., Werner, O., Balocco, M., Bruno, A., Tandaypan, D. C., Costa-Perales, Á., Dardini, J., Dung, N. H., Korovina, A., Fanjul, F. P., Creus, E. P., Scirocco, F., Martínez, A. T., & Trujillo, J. P. (2025). Data from Students' Use of Generative AI in Innovation Education Programs at CERN IdeaSquare. CERN IdeaSquare Journal of Experimental Innovation, 9(3), 53-56. https://doi.org/10.23726/cij.2025.1799

@article{04ddefb056fd4eb080cdc65a8f439acf,

title = "Data from Students' Use of Generative AI in Innovation Education Programs at CERN IdeaSquare",

abstract = "This article presents a dataset comprising Master-level students{\textquoteright} prompts and discussions with generative artificial intelligence (AI) as part of a challenge-based innovation problem-solving process. Openly accessible through Zenodo (https://doi.org/10.5281/zenodo.17857679), the data consists of 466 pages of students{\textquoteright} conversations with generative AI tools and a 28-page extract comprising only the prompts. The data was collected through a survey for students participating in week-long intense innovation education programs at CERN IdeaSquare throughout 2024. The data can be used to advance practice and theory regarding the use of generative AI in problem solving and innovation education. Scholars are encouraged to use the data in various forms of analysis, including thematic, content, and narrative analysis. The data can also complement other similar datasets in larger studies to examine the effects of different pedagogical approaches, student profiles, or problem-solving situations on the use of generative AI.",

keywords = "Generative AI, innovation education, prompt",

author = "Mikko Sairanen and Jimmy Poulaillon and Lauri Valtonen and Giulia Gaddi and Catarina Batista and Ole Werner and Matteo Balocco and Andrea Bruno and Tandaypan, \{Diego Canova\} and {\'A}ngel Costa-Perales and Jacopo Dardini and Dung, \{Ngo Hung\} and Anastasiia Korovina and Fanjul, \{Fernando Palma\} and Creus, \{Eduard Puga\} and Filomena Scirocco and Mart{\'i}nez, \{Adri{\'a}n Toledo\} and Trujillo, \{Javier P{\'e}rez\}",

note = "Publisher Copyright: {\textcopyright} The author/s, 2025.",

year = "2025",

doi = "10.23726/cij.2025.1799",

language = "English",

volume = "9",

pages = "53--56",

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Sairanen, M, Poulaillon, J, Valtonen, L, Gaddi, G, Batista, C, Werner, O, Balocco, M, Bruno, A, Tandaypan, DC, Costa-Perales, Á, Dardini, J, Dung, NH, Korovina, A, Fanjul, FP, Creus, EP, Scirocco, F, Martínez, AT & Trujillo, JP 2025, 'Data from Students' Use of Generative AI in Innovation Education Programs at CERN IdeaSquare', CERN IdeaSquare Journal of Experimental Innovation, vol. 9, no. 3, pp. 53-56. https://doi.org/10.23726/cij.2025.1799

TY - JOUR

T1 - Data from Students' Use of Generative AI in Innovation Education Programs at CERN IdeaSquare

AU - Sairanen, Mikko

AU - Poulaillon, Jimmy

AU - Valtonen, Lauri

AU - Gaddi, Giulia

AU - Batista, Catarina

AU - Werner, Ole

AU - Balocco, Matteo

AU - Bruno, Andrea

AU - Tandaypan, Diego Canova

AU - Costa-Perales, Ángel

AU - Dardini, Jacopo

AU - Dung, Ngo Hung

AU - Korovina, Anastasiia

AU - Fanjul, Fernando Palma

AU - Creus, Eduard Puga

AU - Scirocco, Filomena

AU - Martínez, Adrián Toledo

AU - Trujillo, Javier Pérez

PY - 2025

Y1 - 2025

N2 - This article presents a dataset comprising Master-level students’ prompts and discussions with generative artificial intelligence (AI) as part of a challenge-based innovation problem-solving process. Openly accessible through Zenodo (https://doi.org/10.5281/zenodo.17857679), the data consists of 466 pages of students’ conversations with generative AI tools and a 28-page extract comprising only the prompts. The data was collected through a survey for students participating in week-long intense innovation education programs at CERN IdeaSquare throughout 2024. The data can be used to advance practice and theory regarding the use of generative AI in problem solving and innovation education. Scholars are encouraged to use the data in various forms of analysis, including thematic, content, and narrative analysis. The data can also complement other similar datasets in larger studies to examine the effects of different pedagogical approaches, student profiles, or problem-solving situations on the use of generative AI.

AB - This article presents a dataset comprising Master-level students’ prompts and discussions with generative artificial intelligence (AI) as part of a challenge-based innovation problem-solving process. Openly accessible through Zenodo (https://doi.org/10.5281/zenodo.17857679), the data consists of 466 pages of students’ conversations with generative AI tools and a 28-page extract comprising only the prompts. The data was collected through a survey for students participating in week-long intense innovation education programs at CERN IdeaSquare throughout 2024. The data can be used to advance practice and theory regarding the use of generative AI in problem solving and innovation education. Scholars are encouraged to use the data in various forms of analysis, including thematic, content, and narrative analysis. The data can also complement other similar datasets in larger studies to examine the effects of different pedagogical approaches, student profiles, or problem-solving situations on the use of generative AI.

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KW - innovation education

KW - prompt

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DO - 10.23726/cij.2025.1799

M3 - Article

AN - SCOPUS:105033720958

SN - 2413-9505

VL - 9

SP - 53

EP - 56

JO - CERN IdeaSquare Journal of Experimental Innovation

JF - CERN IdeaSquare Journal of Experimental Innovation

IS - 3

ER -

Data from Students' Use of Generative AI in Innovation Education Programs at CERN IdeaSquare

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Keywords

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