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

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.
- [ BibTeX ]
- [ EndNote ]
- [ URL ]
@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.

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.
- [ BibTeX ]
- [ EndNote ]
- [ URL ]
@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.
- [ BibTeX ]
- [ EndNote ]
@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