Knowledge tracing refers to the problem of estimating each student’s knowledge component/skill mastery level from their past responses to questions in educational applications. One direct benefit knowledge tracing methods provide is the ability to predict each student’s performance on the future questions. However, one key limitation of most existing knowledge tracing methods is that they treat student responses to questions as binary-valued, i.e., whether the responses are correct or incorrect. Response correctness analysis/prediction is easy to navigate but loses important information, especially for open-ended questions: the exact student responses can potentially provide much more information about their knowledge states than only respo...
The use of Bayesian Knowledge Tracing (BKT) models in predicting student learning and mastery, espec...
Massive Open Online Courses (MOOCs) provide an effective learning platform with various high-quality...
Knowledge tracing, which is used to predict students’ performance based on their previous practices,...
Knowledge tracing refers to the problem of estimating each student's knowledge component/skill maste...
Knowledge tracing (KT) models are a popular approach for predicting students' future performance at ...
Intelligent Tutoring Systems have become critically important in future learning environments. Knowl...
Abstract. Traditionally, the assessment and learning science commu-nities rely on different paradigm...
Knowledge tracing (KT) is a crucial technique to predict students’ future performance by observing t...
Large-scale data about learners’ behavior are being generated at high speed on various online learni...
Knowledge Tracing (KT) aims to predict students’ future performances based on their former exercises...
High-quality education is one of the keys to achieving a more sustainable world. In contrast to trad...
Various kinds of e-learning systems, such as Massively Open Online Courses and intelligent tu-toring...
Knowledge tracing (KT) is an essential task in online education, which dynamically assesses students...
Knowledge tracing is one of the major focus of modern artificial intelligence (AI) enabled intellige...
Paaßen B, Jensen J, Hammer B. Execution Traces as a Powerful Data Representation for Intelligent Tut...
The use of Bayesian Knowledge Tracing (BKT) models in predicting student learning and mastery, espec...
Massive Open Online Courses (MOOCs) provide an effective learning platform with various high-quality...
Knowledge tracing, which is used to predict students’ performance based on their previous practices,...
Knowledge tracing refers to the problem of estimating each student's knowledge component/skill maste...
Knowledge tracing (KT) models are a popular approach for predicting students' future performance at ...
Intelligent Tutoring Systems have become critically important in future learning environments. Knowl...
Abstract. Traditionally, the assessment and learning science commu-nities rely on different paradigm...
Knowledge tracing (KT) is a crucial technique to predict students’ future performance by observing t...
Large-scale data about learners’ behavior are being generated at high speed on various online learni...
Knowledge Tracing (KT) aims to predict students’ future performances based on their former exercises...
High-quality education is one of the keys to achieving a more sustainable world. In contrast to trad...
Various kinds of e-learning systems, such as Massively Open Online Courses and intelligent tu-toring...
Knowledge tracing (KT) is an essential task in online education, which dynamically assesses students...
Knowledge tracing is one of the major focus of modern artificial intelligence (AI) enabled intellige...
Paaßen B, Jensen J, Hammer B. Execution Traces as a Powerful Data Representation for Intelligent Tut...
The use of Bayesian Knowledge Tracing (BKT) models in predicting student learning and mastery, espec...
Massive Open Online Courses (MOOCs) provide an effective learning platform with various high-quality...
Knowledge tracing, which is used to predict students’ performance based on their previous practices,...