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Solution Probability Model and Fairness Evaluation This in-session prediction model seeks to predict the users’ performance on the Orthografietrainer.net platform. The target variable is binary and predicts if the user will do the following sentence correctly or not. For fairness evaluations the best models (MLP and DTE), and the worst model (SVM) are considered. A random state is not set, thus, results might differ marginally. A detailed description of the solution probability model and the fairness evaluation can be found here: tba
Adaptive Learning, Learning Analytics
Adaptive Learning, Learning Analytics
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
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| downloads | 7 |

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