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| Knowledge Tracing× | LSTM× | Rasch-Modell× | |
|---|---|---|---|
| Fachgebiet≠ | Bildungsanalytik | Deep Learning | Psychometrie |
| Familie≠ | Machine learning | Machine learning | Latent structure |
| Entstehungsjahr≠ | 1994 | 1997 | 1960 |
| Urheber≠ | Albert Corbett & John Anderson | Hochreiter, S. & Schmidhuber, J. | Georg Rasch |
| Typ≠ | Probabilistic student modeling | Recurrent neural network (gated memory cell) | Item Response Theory / Latent trait model |
| Wegweisende Quelle≠ | Corbett, A. T., & Anderson, J. R. (1994). Knowledge tracing: Modeling the acquisition of procedural knowledge. User Modeling and User-Adapted Interaction, 4(4), 253–278. DOI ↗ | Hochreiter, S. & Schmidhuber, J. (1997). Long Short-Term Memory. Neural Computation, 9(8), 1735–1780. DOI ↗ | Rasch, G. (1960). Probabilistic Models for Some Intelligence and Attainment Tests. Danish Institute for Educational Research, Copenhagen. link ↗ |
| Aliasnamen | BKT, Bayesian Knowledge Tracing, Deep Knowledge Tracing, Bilgi İzleme | LSTM (Uzun Kısa Dönem Bellek Ağı), long short-term memory, LSTM network, recurrent neural network with memory cells | 1PL IRT, one-parameter logistic model, Rasch Modeli — 1PL IRT, 1PL model |
| Verwandt≠ | 3 | 5 | 6 |
| Zusammenfassung≠ | Knowledge Tracing (KT) is a student-modeling technique that estimates, at each moment in time, the probability that a learner has mastered a target knowledge component. Introduced by Corbett and Anderson in 1994, the classical Bayesian Knowledge Tracing (BKT) model treats skill acquisition as a two-state Hidden Markov Model driven by four interpretable parameters: prior knowledge, learning rate, slip, and guess. Deep variants (DKT, DKVMN, AKT) later replaced HMMs with recurrent and transformer architectures. | LSTM (Long Short-Term Memory) is a recurrent neural network architecture, introduced by Sepp Hochreiter and Jürgen Schmidhuber in 1997, that can learn long-term dependencies in sequential data and is widely used for time-series and sequence prediction. It keeps an internal memory that lets information persist across many time steps. | The Rasch model, introduced by Georg Rasch in 1960, is the simplest member of the Item Response Theory (IRT) family. It assigns a single difficulty parameter to each test item and places both item difficulties and person abilities on the same logit scale, enabling direct, sample-independent comparison of items and persons. |
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