M.Sc. Leonie Freise

Wissenschaftliche Mitarbeiterin

Telefon: +49 561 804-6066
E-Mail: leonie.freise[at]uni-kassel[dot]de

Standort: Pfannkuchstraße 1
34121 Kassel

Raum: ITeG, 1250, 1. Etage

Sprechstunde

Mi, 13:00-14:00 Anmeldung per E-Mail erforderlich. Weitere Termine nach Vereinbarung.

Lebenslauf

Ausbildung

(10/2019 – 03/2022) Studium in Wirtschaft, Psychologie & Management (Master of Science) an der Universität Kassel.

Thema der Masterarbeit: Sustainability Transformations at Higher Education Institutions“.

(10/2015 – 03/2019) Studium der Psychologie (Bachelor of Science) an der Universität Trier mit dem Schwerpunkt Wirtschaftspsychologie.

Thema der Bachelorarbeit: „The Ability to Switch Off: What Facilitates and Influences Psychological Detachment“.

Arbeitserfahrung

(08/2021 – 04/2022) Studentische Hilfskraft in der Wirtschaftsinformatik an der Universität Kassel, Kassel.

(02/2021 – 08/2021) Werkstudentin & OKR Master in der Organisationsentwicklung am Fraunhofer Institut IEE, Kassel.

(09/2020 – 01/2021 Praktikum in der Menschenrechtsberatung bei Löning – Human Rights & Responsible Business, Berlin

(12/2019 – 08/2020) Studentische Hilfskraft in der strategischen Personalentwicklung und Organisationskultur an der Universität Kassel, Kassel.

(04/2019 – 10/2019) Praktikum & Werkstudententätigkeit im Leadership Consulting bei PricewaterhouseCoopers Frankfurt am Main.

(10/2018 – 01/2019) Praktikum im Recruiting bei Emma, Frankfurt am Main.

Forschungsinteressen

Digitalisierung der Arbeit
Future Work
Digital Detox

Publikationen

2025[ to top ]

Freise, L. R.; Bruhin, O.; Ritz, E.; Li, M. M.; & Leimeister, J. M. (2025): Code and Craft: How Generative AI Tools Facilitate Job Crafting in Software Development. In: 58th Hawaii International Conference on System Sciences (HICSS). Hawaii, USA.
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@inproceedings{ls_leimeister, abstract = {The rapid evolution of the software development industry challenges developers to manage their diverse tasks effectively. Traditional assistant tools in software development often fall short of supporting developers efficiently. This paper explores how generative artificial intelligence (GAI) tools, such as Github Copilot or ChatGPT, facilitate job crafting—a process where employees reshape their jobs to meet evolving demands. By integrating GAI tools into workflows, software developers can focus more on creative problem-solving, enhancing job satisfaction, and fostering a more innovative work environment. This study investigates how GAI tools influence task, cognitive, and relational job crafting behaviors among software developers, examining its implications for professional growth and adaptability within the industry. The paper provides insights into the transformative impacts of GAI tools on software development job crafting practices, emphasizing their role in enabling developers to redefine their job functions.}, address = {Hawaii, USA}, author = {Freise, Leonie Rebecca and Bruhin, Olivia and Ritz, Eva and Li, Mahei Manhai and Leimeister, Jan Marco}, booktitle = {58th Hawaii International Conference on System Sciences (HICSS)}, keywords = {itegpub}, title = {Code and Craft: How Generative AI Tools Facilitate Job Crafting in Software Development}, year = 2025 }
%0 Conference Paper %1 ls_leimeister %A Freise, Leonie Rebecca %A Bruhin, Olivia %A Ritz, Eva %A Li, Mahei Manhai %A Leimeister, Jan Marco %B 58th Hawaii International Conference on System Sciences (HICSS) %C Hawaii, USA %D 2025 %T Code and Craft: How Generative AI Tools Facilitate Job Crafting in Software Development %X The rapid evolution of the software development industry challenges developers to manage their diverse tasks effectively. Traditional assistant tools in software development often fall short of supporting developers efficiently. This paper explores how generative artificial intelligence (GAI) tools, such as Github Copilot or ChatGPT, facilitate job crafting—a process where employees reshape their jobs to meet evolving demands. By integrating GAI tools into workflows, software developers can focus more on creative problem-solving, enhancing job satisfaction, and fostering a more innovative work environment. This study investigates how GAI tools influence task, cognitive, and relational job crafting behaviors among software developers, examining its implications for professional growth and adaptability within the industry. The paper provides insights into the transformative impacts of GAI tools on software development job crafting practices, emphasizing their role in enabling developers to redefine their job functions.

2024[ to top ]

Ritz, E.; Freise, L.; Elshan, E.; Rietsche, R.; & Bretschneider, U. (2024): What to Learn Next? Designing Personalized Learning Paths for Re-&Upskilling in Organizations. In: Hawaii International Conference on System Sciences (HICSS). Waikiki, Hawaii, USA.
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@inproceedings{ls_leimeister, abstract = {The fast-paced acceleration of digitalization requires extensive re-&upskilling, impacting a significant proportion of jobs worldwide. Technology-mediated learning platforms have become instrumental in addressing these efforts, as they can analyze platform data to provide personalized learning journeys. Such personalization is expected to increase employees’ empowerment, job satisfaction, and learning outcomes. However, the challenge lies in efficiently deploying these opportunities using novel technologies, prompting questions about the design and analysis of generating personalized learning paths in organizational learning. We, therefore, analyze and classify recent research on personalized learning paths into four major concepts (learning context, data, interface, and adaptation) with ten dimensions and 34 characteristics. Six expert interviews validate the taxonomy’s use and outline three exemplary use cases, undermining its feasibility. Information Systems researchers can use our taxonomy to develop theoretical models to study the effectiveness of personalized learning paths in intra-organizational re-&upskilling.}, address = {Waikiki, Hawaii, USA}, author = {Ritz, Eva and Freise, Leonie and Elshan, Edona and Rietsche, Roman and Bretschneider, Ulrich}, booktitle = {Hawaii International Conference on System Sciences (HICSS)}, keywords = {itegpub}, title = {What to Learn Next? Designing Personalized Learning Paths for Re-&Upskilling in Organizations}, year = 2024 }
%0 Conference Paper %1 ls_leimeister %A Ritz, Eva %A Freise, Leonie %A Elshan, Edona %A Rietsche, Roman %A Bretschneider, Ulrich %B Hawaii International Conference on System Sciences (HICSS) %C Waikiki, Hawaii, USA %D 2024 %T What to Learn Next? Designing Personalized Learning Paths for Re-&Upskilling in Organizations %U https://pubs.wi-kassel.de/wp-content/uploads/2024/01/JML_959.pdf %X The fast-paced acceleration of digitalization requires extensive re-&upskilling, impacting a significant proportion of jobs worldwide. Technology-mediated learning platforms have become instrumental in addressing these efforts, as they can analyze platform data to provide personalized learning journeys. Such personalization is expected to increase employees’ empowerment, job satisfaction, and learning outcomes. However, the challenge lies in efficiently deploying these opportunities using novel technologies, prompting questions about the design and analysis of generating personalized learning paths in organizational learning. We, therefore, analyze and classify recent research on personalized learning paths into four major concepts (learning context, data, interface, and adaptation) with ten dimensions and 34 characteristics. Six expert interviews validate the taxonomy’s use and outline three exemplary use cases, undermining its feasibility. Information Systems researchers can use our taxonomy to develop theoretical models to study the effectiveness of personalized learning paths in intra-organizational re-&upskilling.
Ritz, E.; Freise, L.; & Li, M. (2024): Offloading to Digital Minds: How Generative AI Can Help to Craft Jobs. In: Proceedings NeuroIS Retreat 2024.
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@incollection{ls_leimeister, abstract = {In the era of ChatGPT and other generative AI tools, white-collar workers are given tremendous potential to simplify everyday tasks. Within vocational psychology, this phenomenon is known as job crafting. We conduct an electroencephalography-based mixed-factorial experiment to explore the underlying mechanisms of how and why the use of generative AI tools can lead to job crafting. Relying on cognitive load theory and resource demand theory, we measure the effects of ChatGPT use and prompt engineering guidance in strategic thinking tasks. We hypothesize that individuals who use ChatGPT without and with prompting examples rely on cognitive offloading to avoid cognitive effort, affecting resource demands. An initial evaluation of our experiment task design provides promising results. We plan our experiment with participants who are familiar with executive assistant tasks. Our expected results contribute to the ongoing discussion of ICT-enabled job crafting and provide empirical-driven explanations of AI-enabled job crafting mechanisms.}, author = {Ritz, Eva and Freise, Leonie and Li, Mahei}, booktitle = {Proceedings NeuroIS Retreat 2024}, keywords = {itegpub}, title = {Offloading to Digital Minds: How Generative AI Can Help to Craft Jobs}, year = 2024 }
%0 Book Section %1 ls_leimeister %A Ritz, Eva %A Freise, Leonie %A Li, Mahei %B Proceedings NeuroIS Retreat 2024 %D 2024 %T Offloading to Digital Minds: How Generative AI Can Help to Craft Jobs %U http://pubs.wi-kassel.de/wp-content/uploads/2024/06/JML_972.pdf %X In the era of ChatGPT and other generative AI tools, white-collar workers are given tremendous potential to simplify everyday tasks. Within vocational psychology, this phenomenon is known as job crafting. We conduct an electroencephalography-based mixed-factorial experiment to explore the underlying mechanisms of how and why the use of generative AI tools can lead to job crafting. Relying on cognitive load theory and resource demand theory, we measure the effects of ChatGPT use and prompt engineering guidance in strategic thinking tasks. We hypothesize that individuals who use ChatGPT without and with prompting examples rely on cognitive offloading to avoid cognitive effort, affecting resource demands. An initial evaluation of our experiment task design provides promising results. We plan our experiment with participants who are familiar with executive assistant tasks. Our expected results contribute to the ongoing discussion of ICT-enabled job crafting and provide empirical-driven explanations of AI-enabled job crafting mechanisms.
Ritz, E.; Mühlheim, J.; Freise, L. R.; & Li, M. M. (2024): Prompting for Perks: Enhancing Generative AI-Enabled Job Crafting in Knowledge Work. In: Australasian Conference on Information Systems (ACIS). Canberra, Australia.
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@inproceedings{ls_leimeister, abstract = {The increasing use of Generative AI (GAI) has captivated industries seeking to enhance productivity, particularly among white-collar workers. Drawing upon job crafting theory from occupational psychology, prior research suggests that GAI applications can also enhance employee well-being by modifying their work environment for self-perceived benefits. However, the conditions facilitating job crafting behaviours in this context remain underexplored. This study posits that prompt engineering can promote job crafting behaviour. To explore this, we conducted a between-subjects online experiment, manipulating a prompt support intervention through worked examples. Additionally, we examined the moderating role of participants' AI literacy in influencing the effectiveness of the prompt intervention. A pre-test with 42 participants indicated that prompt support can increase GAI-enabled job crafting, but only for those with high AI literacy. The findings underscore the importance of AI literacy and prompt engineering in optimising job crafting behaviour, advocating for organisational training programs to support these skills.}, address = {Canberra, Australia}, author = {Ritz, Eva and Mühlheim, Joël and Freise, Leonie Rebecca and Li, Mahei Manhei}, booktitle = {Australasian Conference on Information Systems (ACIS)}, keywords = {AI_Literacy}, title = {Prompting for Perks: Enhancing Generative AI-Enabled Job Crafting in Knowledge Work}, year = 2024 }
%0 Conference Paper %1 ls_leimeister %A Ritz, Eva %A Mühlheim, Joël %A Freise, Leonie Rebecca %A Li, Mahei Manhei %B Australasian Conference on Information Systems (ACIS) %C Canberra, Australia %D 2024 %T Prompting for Perks: Enhancing Generative AI-Enabled Job Crafting in Knowledge Work %X The increasing use of Generative AI (GAI) has captivated industries seeking to enhance productivity, particularly among white-collar workers. Drawing upon job crafting theory from occupational psychology, prior research suggests that GAI applications can also enhance employee well-being by modifying their work environment for self-perceived benefits. However, the conditions facilitating job crafting behaviours in this context remain underexplored. This study posits that prompt engineering can promote job crafting behaviour. To explore this, we conducted a between-subjects online experiment, manipulating a prompt support intervention through worked examples. Additionally, we examined the moderating role of participants' AI literacy in influencing the effectiveness of the prompt intervention. A pre-test with 42 participants indicated that prompt support can increase GAI-enabled job crafting, but only for those with high AI literacy. The findings underscore the importance of AI literacy and prompt engineering in optimising job crafting behaviour, advocating for organisational training programs to support these skills.
Freise, L. R.; Bretschneider, U.; & Oeste-Reiss, S. (2024): Skills in Flux – Challenges in AI-based Skills Management and Skills Profiles. In: 19. Internationale Tagung der Wirtschaftsinformatik (Wi24). Würzburg, Germany.
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@inproceedings{ls_leimeister, abstract = {The changing world of work, driven by automation and digital tech-nologies, requires a workforce that continuously adapts its skills in order to be competitive and employable. This dynamic environment has fueled the demand for advanced skills management, with artificial intelligence (AI) playing a critical role in measuring and supporting individual skills development. This paper looks at AI-based competency profiles as a strategic tool for talent acquisition, reten-tion, and development and highlights their potential challenges. Using semi-structured interviews with experts from HR, education, and industry, we explore the multiple challenges of AI-based skills management from a theoretical, con-ceptual, and practical perspective. Our findings reveal complex problems at the individual, team, organizational, and systemic levels that form a basis for the de-velopment of effective AI-based skills management strategies. This research highlights the importance of using AI to foster an adaptable and skilled workforce that meets both current needs and future challenges.}, address = {Würzburg, Germany}, author = {Freise, Leonie Rebecca and Bretschneider, Ulrich and Oeste-Reiss, Sarah}, booktitle = {19. Internationale Tagung der Wirtschaftsinformatik (Wi24)}, keywords = {itegpub}, title = {Skills in Flux – Challenges in AI-based Skills Management and Skills Profiles}, year = 2024 }
%0 Conference Paper %1 ls_leimeister %A Freise, Leonie Rebecca %A Bretschneider, Ulrich %A Oeste-Reiss, Sarah %B 19. Internationale Tagung der Wirtschaftsinformatik (Wi24) %C Würzburg, Germany %D 2024 %T Skills in Flux – Challenges in AI-based Skills Management and Skills Profiles %U http://pubs.wi-kassel.de/wp-content/uploads/2024/09/JMl_976.pdf %X The changing world of work, driven by automation and digital tech-nologies, requires a workforce that continuously adapts its skills in order to be competitive and employable. This dynamic environment has fueled the demand for advanced skills management, with artificial intelligence (AI) playing a critical role in measuring and supporting individual skills development. This paper looks at AI-based competency profiles as a strategic tool for talent acquisition, reten-tion, and development and highlights their potential challenges. Using semi-structured interviews with experts from HR, education, and industry, we explore the multiple challenges of AI-based skills management from a theoretical, con-ceptual, and practical perspective. Our findings reveal complex problems at the individual, team, organizational, and systemic levels that form a basis for the de-velopment of effective AI-based skills management strategies. This research highlights the importance of using AI to foster an adaptable and skilled workforce that meets both current needs and future challenges.
Freise, L. R.; & Bretschneider, U. (2024): Completing the Skills Puzzle: Developing a Skills Profile Data Model. In: 19. Internationale Tagung der Wirtschaftsinformatik (Wi24). Würzburg, Germany.
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@inproceedings{ls_leimeister, abstract = {In today’s working world, driven by technological progress, there is a growing need to adapt and update skills to remain competitive. Employers need qualified employees, and employees want to develop their job-related skills, so skills profiles are becoming more prevalent. These profiles comprise skills that individuals bring to their jobs and develop over employment. When used effectively, they offer benefits in attracting, retaining, and developing talent, as well as in staffing and performance management. This paper proposes a data model for such profiles. Drawing upon a systematic literature review and interviews with employees, we derived the critical aspects of a skill profile data model. We further demonstrate the complexity and the need for a structured approach to include a bottom-up perspective. This research contributes to the theoretical understanding of skills profile data models by including the employee perspectives. It further provides insights for organizations to develop a skilled workforce.}, address = {Würzburg, Germany}, author = {Freise, Leonie Rebecca and Bretschneider, Ulrich}, booktitle = {19. Internationale Tagung der Wirtschaftsinformatik (Wi24)}, keywords = {itegpub}, title = {Completing the Skills Puzzle: Developing a Skills Profile Data Model}, year = 2024 }
%0 Conference Paper %1 ls_leimeister %A Freise, Leonie Rebecca %A Bretschneider, Ulrich %B 19. Internationale Tagung der Wirtschaftsinformatik (Wi24) %C Würzburg, Germany %D 2024 %T Completing the Skills Puzzle: Developing a Skills Profile Data Model %U http://pubs.wi-kassel.de/wp-content/uploads/2024/09/JML_977.pdf %X In today’s working world, driven by technological progress, there is a growing need to adapt and update skills to remain competitive. Employers need qualified employees, and employees want to develop their job-related skills, so skills profiles are becoming more prevalent. These profiles comprise skills that individuals bring to their jobs and develop over employment. When used effectively, they offer benefits in attracting, retaining, and developing talent, as well as in staffing and performance management. This paper proposes a data model for such profiles. Drawing upon a systematic literature review and interviews with employees, we derived the critical aspects of a skill profile data model. We further demonstrate the complexity and the need for a structured approach to include a bottom-up perspective. This research contributes to the theoretical understanding of skills profile data models by including the employee perspectives. It further provides insights for organizations to develop a skilled workforce.

2023[ to top ]

Freise, L. R.; & Bretschneider, U. (2023): Automized Assessment for Professional Skills – A Systematic Literature Review and Future Research Avenues. In: Internationale Tagung Wirtschaftsinformatik (WI). Paderborn, Germany.
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@inproceedings{ls_leimeister, abstract = {Globalization, technological progress, and demographic trends increasingly influence our labor markets. With changing labor markets and increasing digitalization, new competencies of workers are needed to meet demands. However, as a first step to developing these new skills, knowledge about the existing skills and their status quo is necessary. Here, automated skill assessment offers a crucial added value, as it can create a reliable and objective database. Based on a systematic investigation, our analysis shows, in four different areas, how skills and competencies in the automated assessment are (1) defined, (2) included as an element of analysis, (3) methodically recorded and processed, (4) which data source is used. In doing so, we offer insights into existing approaches to automated assessment of professional skills. We contribute to a better under-standing of the design of automated skill assessment methods and provide perspectives on future research directions.}, address = {Paderborn, Germany}, author = {Freise, Leonie Rebecca and Bretschneider, Ulrich}, booktitle = {Internationale Tagung Wirtschaftsinformatik (WI)}, keywords = {itegpub}, title = {Automized Assessment for Professional Skills – A Systematic Literature Review and Future Research Avenues}, year = 2023 }
%0 Conference Paper %1 ls_leimeister %A Freise, Leonie Rebecca %A Bretschneider, Ulrich %B Internationale Tagung Wirtschaftsinformatik (WI) %C Paderborn, Germany %D 2023 %T Automized Assessment for Professional Skills – A Systematic Literature Review and Future Research Avenues %U https://pubs.wi-kassel.de/wp-content/uploads/2023/09/JML_948.pdf %X Globalization, technological progress, and demographic trends increasingly influence our labor markets. With changing labor markets and increasing digitalization, new competencies of workers are needed to meet demands. However, as a first step to developing these new skills, knowledge about the existing skills and their status quo is necessary. Here, automated skill assessment offers a crucial added value, as it can create a reliable and objective database. Based on a systematic investigation, our analysis shows, in four different areas, how skills and competencies in the automated assessment are (1) defined, (2) included as an element of analysis, (3) methodically recorded and processed, (4) which data source is used. In doing so, we offer insights into existing approaches to automated assessment of professional skills. We contribute to a better under-standing of the design of automated skill assessment methods and provide perspectives on future research directions.
Freise, L. R.; & Hupe, A. (2023): Transferring Digital Twin Technology on Employee Skills: A Framework to Support Human Resources. In: Academy of Management Annual Meeting (AOM). Boston, Massachusetts, USA.
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@inproceedings{ls_leimeister, abstract = {Skill assessment has become increasingly important in recent years. The shortage of skilled workers has demonstrated the need to identify suitable candidates for jobs and to develop existing employees. However, human resources processes rely on resumes, references, or job certifications to assess their employees’ skills. A few years ago, the concept of a digital twin was introduced, which is a digital replica of a physical entity. While using blockchain, the digital twin technology offers tremendous potential for transfer to other contexts. In the context of these considerations, we present a framework that allows the technology of the digital twin to be combined with that of skill assessment to create an enhanced skill profile. With a job market signaling perspective, we integrate knowledge about skills, clarify the opportunities of assessment, and develop a framework for a digital skill twin. In doing so, we argue that the multi-source and multi-method approach of such a digital skill twin leads to increased validity, reliability, and standardization. We thereby contribute to theory and practice by developing a new framework that offers employees to know their strengths and development potential and organizations to assess their employees’ skills.}, address = {Boston, Massachusetts, USA}, author = {Freise, Leonie Rebecca and Hupe, Anna}, booktitle = {Academy of Management Annual Meeting (AOM)}, keywords = {itegpub}, title = {Transferring Digital Twin Technology on Employee Skills: A Framework to Support Human Resources}, year = 2023 }
%0 Conference Paper %1 ls_leimeister %A Freise, Leonie Rebecca %A Hupe, Anna %B Academy of Management Annual Meeting (AOM) %C Boston, Massachusetts, USA %D 2023 %T Transferring Digital Twin Technology on Employee Skills: A Framework to Support Human Resources %X Skill assessment has become increasingly important in recent years. The shortage of skilled workers has demonstrated the need to identify suitable candidates for jobs and to develop existing employees. However, human resources processes rely on resumes, references, or job certifications to assess their employees’ skills. A few years ago, the concept of a digital twin was introduced, which is a digital replica of a physical entity. While using blockchain, the digital twin technology offers tremendous potential for transfer to other contexts. In the context of these considerations, we present a framework that allows the technology of the digital twin to be combined with that of skill assessment to create an enhanced skill profile. With a job market signaling perspective, we integrate knowledge about skills, clarify the opportunities of assessment, and develop a framework for a digital skill twin. In doing so, we argue that the multi-source and multi-method approach of such a digital skill twin leads to increased validity, reliability, and standardization. We thereby contribute to theory and practice by developing a new framework that offers employees to know their strengths and development potential and organizations to assess their employees’ skills.

M.Sc. Leonie Freise

Wissenschaftliche Mitarbeiterin

Le­bens­lauf

Publikationen

Lebenslauf