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141 results on '"Lemke, Claudia"'

1. Accounting and Statistical Analyses for Sustainable Development

Author

Lemke, Claudia

Subjects
Environmental Economics, Sustainability, Sustainable Development Goals (SDGs), Composite indicators, Multilevel perspective, Principal component analysis, Information theory, Open Access, bic Book Industry Communication::K Economics, finance, business & management::KC Economics::KCN Environmental economics
Abstract

In this Open Access publication Claudia Lemke develops a comprehensive Multi-Level Sustainable Development Index (MLSDI) that is applicable to micro, meso, and macro objects by conducting methodological and empirical research. Multi-level comparability is crucial because the Sustainable Development Goals (SDGs) at macro level can only be achieved if micro and meso objects contribute. The author shows that a novel information-theoretic algorithm outperforms established multivariate statistical weighting methods such as the principal component analysis (PCA). Overcoming further methodological shortcomings of previous sustainable development indices, the MLSDI avoids misled managerial and political decision making.

Published
2021
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12. Discussion and conclusion

Author

Lemke, Claudia, Weber, Gregor, Series Editor, Bodemann, Markus, Series Editor, Schmidpeter, René, Series Editor, and Lemke, Claudia

Published
2021
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14. Methodology

Author

Lemke, Claudia, Weber, Gregor, Series Editor, Bodemann, Markus, Series Editor, Schmidpeter, René, Series Editor, and Lemke, Claudia

Published
2021
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15. Empirical findings

Author

Lemke, Claudia, Weber, Gregor, Series Editor, Bodemann, Markus, Series Editor, Schmidpeter, René, Series Editor, and Lemke, Claudia

Published
2021
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16. Introduction

Author

Lemke, Claudia, Weber, Gregor, Series Editor, Bodemann, Markus, Series Editor, Schmidpeter, René, Series Editor, and Lemke, Claudia

Published
2021
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47. Exploring the Student Perspective: Assessing Technology Readiness and Acceptance for Adopting Large Language Models in Higher Education.

Author

Lemke, Claudia, Kirchner, Kathrin, Anandarajah, Liadan, and Herfurth, Florian N.

Subjects
TECHNOLOGY assessment, HIGHER education, COMPUTER science education, LANGUAGE models
Abstract

These discussions range from banning these technologies for learning and teaching in HE to guided study support. This study avoids taking up these multifarious and partly controversial debates. Instead, we show how students perceive using AI-based tools for automated text generation for their studies. Drawing on a synthesis of two theories: the 'Technology Readiness Index' (TRI) and 'Technology Acceptance Model' (TAM). The model is validated based on survey data collected among undergraduate first-semester students (N=111) of a computer science-related study programme in Germany in winter 2022/23. The students had to evaluate their relationship to that new technology focusing on their readiness for technology adoption and acceptance. By analysing the collected data with a partial least squares model, we find that the optimism toward the new technology positively influences technology acceptance, while discomfort with the technology negatively influences perceived ease of use. The paper concludes with recommendations for action for adopting LLMs in HE. A proper investment in building AI skills in academic teaching plays a valuable role in fostering the students' positive attitude and innovativeness towards this new technology. Additionally, there is a need for more education about the risks and challenges of using this technology to reduce the impact of factors such as discomfort on ease of use. This requires a factual discourse, away from the current hype-induced exaggerated and hyperbolic statements, for instance, in developing formal guidance for universities. [ABSTRACT FROM AUTHOR]

Published
2023
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