{
  "id": "enwiki-001323291895",
  "slug": "bayesian-knowledge-tracing",
  "title": "Bayesian knowledge tracing",
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  "lead": "Bayesian knowledge tracing is an algorithm used in many intelligent tutoring systems to model each learner's mastery of the knowledge being tutored. It models student knowledge in a hidden Markov model as a latent variable, updated by observing the correctness of each student's interaction in which they apply the skill in question. BKT assumes that student knowledge is represented as a set of binary variables, one per skill, where the skill is either mastered by the student or not. Observations in BKT are also binary: a student gets a problem/step either right or wrong. Intelligent tutoring systems often use BKT for mastery learning and problem sequencing. In its most common implementation, BKT has only skill-specific parameters.",
  "body": "Bayesian knowledge tracing is an algorithm used in many intelligent tutoring systems to model each learner's mastery of the knowledge being tutored. It models student knowledge in a hidden Markov model as a latent variable, updated by observing the correctness of each student's interaction in which they apply the skill in question. BKT assumes that student knowledge is represented as a set of binary variables, one per skill, where the skill is either mastered by the student or not. Observations in BKT are also binary: a student gets a problem/step either right or wrong. Intelligent tutoring systems often use BKT for mastery learning and problem sequencing. In its most common implementation, BKT has only skill-specific parameters. p(L_1)^k_u=p(L_0)^k Equation (b): p(L_t \\mid \\text{obs}=\\text{correct})^k_u=\\frac{p(L_t)^k_u\\cdot(1-p(S)^k)}{p(L_t)^k_u\\cdot(1-p(S)^k)+(1-p(L_t)^k_u)\\cdot p(G)^k} Equation (c): p(L_t\\mid \\text{obs}= \\text{wrong})^k_u=\\frac{p(L_t)^k_u\\cdot p(S)^k}{p(L_t)^k_u\\cdot p(S)^k+(1-p(L_t)^k_u) \\cdot (1-p(G)^k)} Equation (d): p(L_{t+1})^k_u=p(L_t\\mid \\text{obs})^k_u+(1-p(L_t\\mid \\text{obs})^k_u)\\cdot p(T)^k Equation (e): p(C_{t+1})^k_u=p(L_{t+1})^k_u\\cdot(1-p(S)^k)+(1-p(L_{t+1})^k_u)\\cdot p(G)^k ==See also== Computerized adaptive testing Item response theory Knowledge space theory Latent growth modeling ==References== ==Further reading==",
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  "license": "CC BY-SA 4.0",
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    "title": "Bayesian knowledge tracing",
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      {
        "family": "Anticloud FZ LLE",
        "literal": "Anticloud FZ LLE"
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    "publisher": "Anticloud FZ LLE",
    "publisher-place": "Dubai, United Arab Emirates",
    "URL": "https://encyclopegia.org/a/bayesian-knowledge-tracing",
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      "date-parts": [
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          2026,
          11,
          14
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