Knowledge Tracing
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.
Rekodi ya chanzo
Nukuu zimehamishwa kwa uhalisi kutoka kwa rekodi ya chanzo cha mbinu. Hakuna uthibitisho wa kiwango cha dai unaodokezwa kutoka kwao.
Madai yaliyotunzwa
Madai yamehifadhiwa katika daftari la ushahidi, kila moja ikiwa na tathmini yake.
Mwonekano huu haubuni tathmini ya dai wakati daftari haina yoyote.
Mbinu zinazohusiana
Zilizotengenezwa kutoka kwa grafu ya mbinu na kuonyeshwa kama uhusiano uliopendekezwa na mashine — hakuna dai la ushahidi linalodokezwa.