Publikationen in Zusammenarbeit mit Forschern von Weizmann Institute of Science (11)

2024

  1. A General Purpose Anomaly-Based Method for Detecting Cheaters in Online Courses

    IEEE Transactions on Learning Technologies, Vol. 17, pp. 1-11

2023

  1. The effects of assessment design on academic dishonesty, learner engagement, and certification rates in MOOCs

    Journal of Computer Assisted Learning, Vol. 39, Núm. 1, pp. 141-153

2022

  1. Evaluating a learning analytics dashboard to detect dishonest behaviours: A case study in small private online courses with academic recognition

    Journal of Computer Assisted Learning, Vol. 38, Núm. 6, pp. 1574-1588

  2. Trustworthy remote assessments: A typology of pedagogical and technological strategies

    Journal of Computer Assisted Learning, Vol. 38, Núm. 6, pp. 1507-1520

2021

  1. ASL expression in ALDH1A1+ neurons in the substantia nigra metabolically contributes to neurodegenerative phenotype

    Human Genetics, Vol. 140, Núm. 10, pp. 1471-1485

2020

  1. Assessment that matters: Balancing reliability and learner-centered pedagogy in MOOC assessment

    ACM International Conference Proceeding Series

2019

  1. Are MOOC Learning Analytics Results Trustworthy? With Fake Learners, They Might Not Be!

    International Journal of Artificial Intelligence in Education, Vol. 29, Núm. 4, pp. 484-506

  2. Correction to: Picomolar concentrations of oligomeric alpha-synuclein sensitizes TLR4 to play an initiating role in Parkinson’s disease pathogenesis (Acta Neuropathologica, (2019), 137, 1, (103-120), 10.1007/s00401-018-1907-y)

    Acta Neuropathologica

  3. Picomolar concentrations of oligomeric alpha-synuclein sensitizes TLR4 to play an initiating role in Parkinson’s disease pathogenesis

    Acta Neuropathologica, Vol. 137, Núm. 1, pp. 103-120

  4. Towards a general purpose anomaly detection method to identify cheaters in massive open online courses

    EDM 2019 - Proceedings of the 12th International Conference on Educational Data Mining

2018

  1. Evaluating the Robustness of Learning Analytics Results Against Fake Learners

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)