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Enkelejda Kasneci

Biographic Data

ID2773335
NAMEEnkelejda Kasneci
GIVEN NAMESEnkelejda
FAMILY NAMEKasneci
SIGNATUREKASNECI E
AFFILIATIONSTechnical University of Munich
ORCID0000-0003-3146-4484
VERIFIEDYes
TOTAL WORKS4
TOTAL CITATIONS1
AUTHOR COUNT4
EDITOR COUNT0
FIRST PUBLICATION YEAR2021
LATEST PUBLICATION YEAR2026
H-INDEX1
  • Validating automated assessments of teaching effectiveness using multimodal data

    Open Access•Tim Fütterer, Ruikun Hou et al.•ARTICLE•Learning and Instruction•2026

    For enhancing student learning in classrooms, high-quality teaching is essential. Research highlighted core dimensions of effective teaching, including classroom management, student support, and cognitive activation. However, traditional methods of assessing teaching effectiveness dimensions (e.g., student surveys) have limitations, including rating biases and resource intensiveness. To overcome these challenges, we explored machine learning (ML)…

  • Temporal dynamics of meta-awareness of mind wandering during lecture viewing: Implications for learning and automated assessment using machine learning

    Babette Bühler, Efe Bozkir et al.•ARTICLE•Journal of Educational Psychology•2025

  • ChatGPT for good? On opportunities and challenges of large language models for education

    Open Access•Enkelejda Kasneci, Kathrin Sessler et al.•ARTICLE•Learning and Individual Differences•2023

  • Expertise Classification of Soccer Goalkeepers in Highly Dynamic Decision Tasks: A Deep Learning Approach for Temporal and Spatial Feature Recognition of Fixation Image Patch Sequences

    Open Access•Benedikt Hosp, Florian Schultz et al.•ARTICLE•Frontiers in Sports and Active…•2021•Cited by: 1•References: 36

    The focus of expertise research moves constantly forward and includes cognitive factors, such as visual information perception and processing. In highly dynamic tasks, such as decision making in sports, these factors become more important to build a foundation for diagnostic systems and adaptive learning environments. Although most recent research focuses on behavioral features, the underlying cognitive mechanisms have been poorly understood, mai…

  • Expertise Classification of Soccer Goalkeepers in Highly Dynamic Decision Tasks: A Deep Learning Approach for Temporal and Spatial Feature Recognition of Fixation Image Patch Sequences

    Open Access•Benedikt Hosp, Florian Schultz et al.•ARTICLE•Frontiers in Sports and Active…•2021•Cited by: 1•References: 36

    The focus of expertise research moves constantly forward and includes cognitive factors, such as visual information perception and processing. In highly dynamic tasks, such as decision making in sports, these factors become more important to build a foundation for diagnostic systems and adaptive learning environments. Although most recent research focuses on behavioral features, the underlying cognitive mechanisms have been poorly understood, mai…

  • Expertise Classification of Soccer Goalkeepers in Highly Dynamic Decision Tasks: A Deep Learning Approach for Temporal and Spatial Feature Recognition of Fixation Image Patch Sequences

    Open Access•Benedikt Hosp, Florian Schultz et al.•ARTICLE•Frontiers in Sports and Active…•2021•Cited by: 1•References: 36

    The focus of expertise research moves constantly forward and includes cognitive factors, such as visual information perception and processing. In highly dynamic tasks, such as decision making in sports, these factors become more important to build a foundation for diagnostic systems and adaptive learning environments. Although most recent research focuses on behavioral features, the underlying cognitive mechanisms have been poorly understood, mai…

  • ChatGPT for good? On opportunities and challenges of large language models for education

    Open Access•Enkelejda Kasneci, Kathrin Sessler et al.•ARTICLE•Learning and Individual Differences•2023

  • Temporal dynamics of meta-awareness of mind wandering during lecture viewing: Implications for learning and automated assessment using machine learning

    Babette Bühler, Efe Bozkir et al.•ARTICLE•Journal of Educational Psychology•2025

  • Validating automated assessments of teaching effectiveness using multimodal data

    Open Access•Tim Fütterer, Ruikun Hou et al.•ARTICLE•Learning and Instruction•2026

    For enhancing student learning in classrooms, high-quality teaching is essential. Research highlighted core dimensions of effective teaching, including classroom management, student support, and cognitive activation. However, traditional methods of assessing teaching effectiveness dimensions (e.g., student surveys) have limitations, including rating biases and resource intensiveness. To overcome these challenges, we explored machine learning (ML)…

Cognition (3 works) · Psychology (3 works) · Computer Science (2 works) · Online Learning and Analytics (2 works) · Pedagogy (2 works) · Artificial Intelligence (1 works) · Artificial Intelligence in Healthcare and Education (1 works) · Cognitive psychology (1 works) · Cognitive science (1 works) · Curriculum (1 works)

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