Bayesian Knowledge Tracing for Navigation through Marzano’s Taxonomy
In this paper we propose a theoretical model of an ITS (Intelligent Tutoring Systems) capable of improving and updating computer-aided navigation based on Bloom’s taxonomy. For this we use the Bayesian Knowledge Tracing algorithm, performing an adaptive control of the navigation among different leve...
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Universidad Internacional de La Rioja (UNIR)
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doaj-f1423e67b44240f39214bb29ceca500b2021-05-31T11:28:40ZengUniversidad Internacional de La Rioja (UNIR)International Journal of Interactive Multimedia and Artificial Intelligence1989-16601989-16602021-05-016623423910.9781/ijimai.2021.05.006ijimai.2021.05.006Bayesian Knowledge Tracing for Navigation through Marzano’s TaxonomyFrancisco Cervantes-PérezJoaquin Navarro-PeralesAna L. Franzoni-VelázquezLuis ValentínIn this paper we propose a theoretical model of an ITS (Intelligent Tutoring Systems) capable of improving and updating computer-aided navigation based on Bloom’s taxonomy. For this we use the Bayesian Knowledge Tracing algorithm, performing an adaptive control of the navigation among different levels of cognition in online courses. These levels are defined by a taxonomy of educational objectives with a hierarchical order in terms of the control that some processes have over others, called Marzano’s Taxonomy, that takes into account the metacognitive system, responsible for the creation of goals as well as strategies to fulfill them. The main improvements of this proposal are: 1) An adaptive transition between individual assessment questions determined by levels of cognition. 2) A student model based on the initial response of a group of learners which is then adjusted to the ability of each learner. 3) The promotion of metacognitive skills such as goal setting and self-monitoring through the estimation of attempts required to pass the levels. One level of Marzano's taxonomy was left in the hands of the human teacher, clarifying that a differentiation must be made between the tasks in which an ITS can be an important aid and in which it would be more difficult.https://www.ijimai.org/journal/bibcite/reference/2950bayesian knowledge tracingbloom’s taxonomycomputer-assisted instructionintelligent tutoring systemsmarzano's taxonomy |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Francisco Cervantes-Pérez Joaquin Navarro-Perales Ana L. Franzoni-Velázquez Luis Valentín |
spellingShingle |
Francisco Cervantes-Pérez Joaquin Navarro-Perales Ana L. Franzoni-Velázquez Luis Valentín Bayesian Knowledge Tracing for Navigation through Marzano’s Taxonomy International Journal of Interactive Multimedia and Artificial Intelligence bayesian knowledge tracing bloom’s taxonomy computer-assisted instruction intelligent tutoring systems marzano's taxonomy |
author_facet |
Francisco Cervantes-Pérez Joaquin Navarro-Perales Ana L. Franzoni-Velázquez Luis Valentín |
author_sort |
Francisco Cervantes-Pérez |
title |
Bayesian Knowledge Tracing for Navigation through Marzano’s Taxonomy |
title_short |
Bayesian Knowledge Tracing for Navigation through Marzano’s Taxonomy |
title_full |
Bayesian Knowledge Tracing for Navigation through Marzano’s Taxonomy |
title_fullStr |
Bayesian Knowledge Tracing for Navigation through Marzano’s Taxonomy |
title_full_unstemmed |
Bayesian Knowledge Tracing for Navigation through Marzano’s Taxonomy |
title_sort |
bayesian knowledge tracing for navigation through marzano’s taxonomy |
publisher |
Universidad Internacional de La Rioja (UNIR) |
series |
International Journal of Interactive Multimedia and Artificial Intelligence |
issn |
1989-1660 1989-1660 |
publishDate |
2021-05-01 |
description |
In this paper we propose a theoretical model of an ITS (Intelligent Tutoring Systems) capable of improving and updating computer-aided navigation based on Bloom’s taxonomy. For this we use the Bayesian Knowledge Tracing algorithm, performing an adaptive control of the navigation among different levels of cognition in online courses. These levels are defined by a taxonomy of educational objectives with a hierarchical order in terms of the control that some processes have over others, called Marzano’s Taxonomy, that takes into account the metacognitive system, responsible for the creation of goals as well as strategies to fulfill them. The main improvements of this proposal are: 1) An adaptive transition between individual assessment questions determined by levels of cognition. 2) A student model based on the initial response of a group of learners which is then adjusted to the ability of each learner. 3) The promotion of metacognitive skills such as goal setting and self-monitoring through the estimation of attempts required to pass the levels. One level of Marzano's taxonomy was left in the hands of the human teacher, clarifying that a differentiation must be made between the tasks in which an ITS can be an important aid and in which it would be more difficult. |
topic |
bayesian knowledge tracing bloom’s taxonomy computer-assisted instruction intelligent tutoring systems marzano's taxonomy |
url |
https://www.ijimai.org/journal/bibcite/reference/2950 |
work_keys_str_mv |
AT franciscocervantesperez bayesianknowledgetracingfornavigationthroughmarzanostaxonomy AT joaquinnavarroperales bayesianknowledgetracingfornavigationthroughmarzanostaxonomy AT analfranzonivelazquez bayesianknowledgetracingfornavigationthroughmarzanostaxonomy AT luisvalentin bayesianknowledgetracingfornavigationthroughmarzanostaxonomy |
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1721419112455864320 |