Literatur
Специальные | А | Б | В | Г | Д | Е | Ё | Ж | З | И | К | Л | М | Н | О | П | Р | С | Т | У | Ф | Х | Ц | Ч | Ш | Щ | Э | Ю | Я | Все
A |
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Akçapınar et al., 2019Akçapınar, G., Hasnine, M. N., Majumdar, R., Flanagan, B., & Ogata, H. (2019). Developing an early-warning system for spotting at-risk students by using eBook interaction logs. Smart Learning Environments, 6(1), 4. https://doi.org/10.1186/s40561-019-0083-4 | ||
Aulck et al., 2019Aulck, L., Nambi, D., Velagapudi, N., Blumenstock, J., & West, J. (2019). Mining University Registrar Records to Predict First-Year Undergraduate Attrition. In C. F. Lynch, A. Merceron, & R. Nkambou (Hrsg.), Proceedings of The 12th International Conference on Educational Data Mining (EDM 2019) (S. 9–18). Université du Québec à Montréal. https://educationaldatamining.org/edm2019/proceedings/ | ||
B |
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Baker et al., 2015Baker, R. S., Lindrum, D., Lindrum, M. J., & Perkowski, D. (2015). Analyzing Early At-Risk Factors in Higher Education E-Learning Courses. International Conference on Educational Data Mining (EDM), Madrid. https://eric.ed.gov/?id=ED560553 | ||
Bañeres et al., 2020Bañeres, D., Rodríguez, M. E., Guerrero-Roldán, A. E., & Karadeniz, A. (2020). An Early Warning System to Detect At-Risk Students in Online Higher Education. Applied Sciences, 10(13), Article 13. https://doi.org/10.3390/app10134427 | ||
Barbour & Plough, 2009Barbour, M., & Plough, C. (2009). Social Networking in Cyberschooling: Helping to Make Online Learning Less Isolating. TechTrends, 53(4), 56–60. https://doi.org/10.1007/s11528-009-0307-5 | ||
Berens et al., 2019Berens, J., Schneider, K., Gortz, S., Oster, S., & Burghoff, J. (2019). Early Detection of Students at Risk—Predicting Student Dropouts Using Administrative Student Data from German Universities and Machine Learning Methods. Journal of Educational Data Mining, 11(3), 1–41. https://doi.org/10.5281/zenodo.3594771 | ||
Bildungsbericht 2024Autor:innengruppe Bildungsberichterstattung (Hrsg.). (2024). Bildung in Deutschland 2024: Ein indikatorengestützter Bericht mit einer Analyse zu beruflicher Bildung. wbv Media. https://doi.org/10.3278/6001820iw | ||
C |
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Corrin & de Barba, 2015Corrin, L., & de Barba, P. (2015). How do students interpret feedback delivered via dashboards? Proceedings of the Fifth International Conference on Learning Analytics And Knowledge, 430–431. https://doi.org/10.1145/2723576.2723662 | ||
D |
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de Quincey et al., 2019de Quincey, E., Briggs, C., Kyriacou, T., & Waller, R. (2019). Student Centred Design of a Learning Analytics System. Proceedings of the 9th International Conference on Learning Analytics & Knowledge, 353–362. https://doi.org/10.1145/3303772.3303793 | ||
Diaz, 2002Diaz, D. P. (2002). Online Drop Rates Revisited. The Technology Source, May/June 2002. http://www.technologysource.org/article/online_drop_rates-revisited/ | ||