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Development of AIS using simulated learners, Bayesian networks and knowledge elicitation methods

Par Conseil national de recherches du Canada

DOITrouver le DOI : https://doi.org/10.1007/978-3-031-05887-5_11
AuteurRechercher : 1Identifiant ORCID : https://orcid.org/0000-0003-0901-8293; Rechercher : Identifiant ORCID : https://orcid.org/0000-0001-8423-0572; Rechercher : Identifiant ORCID : https://orcid.org/0000-0002-3478-2448; Rechercher : Identifiant ORCID : https://orcid.org/0000-0002-3872-8561; Rechercher : Identifiant ORCID : https://orcid.org/0000-0002-1029-3615; Rechercher : 2Identifiant ORCID : https://orcid.org/0000-0002-3371-1082; Rechercher : Identifiant ORCID : https://orcid.org/0000-0001-5450-4587
Affiliation
  1. Conseil national de recherches du Canada. Technologies numériques
  2. Conseil national de recherches du Canada. Génie océanique, côtier et fluvial
FormatTexte, Chapitre de livre
Conférence4th International Conference, AIS 2022, Held as Part of the 24th HCI International Conference, (HCII 2022), June 26 – July 1, 2022, Virtual Event
Sujetsimulated learners; Bayesian networks; expert knowledge elicitation; tutoring strategies; marine operations
Résumé
The development of adaptive instructional systems (AIS) is an iterative process where both empirical data on human performance and learning, and experimentation using computer simulations can play a role. The paper presents our current efforts to advance adaptive instructional system technology conceived as self-improvement systems [37]. The paper describes our methodological approach for informing the design and implementation of adaptive instructional systems by conducting concurrent research activities using 1) Bayesian networks for modelling learning processes, 2) knowledge elicitation of expert instructors, and 3) simulated learners and tutors to explore AIS system design options. Each activity fulfills separate but complementary objectives. Bayesian networks modelling of learners’ performance provides the means to implement predictions of learners’ performance, and selection of adaptive learning content. Knowledge elicitation methods are fundamental in understanding human capabilities and limitations in the context of AIS systems design that support and regulate the cognitive demands of the learner and instructor. Simulated learner and tutor interactions enable the specification of detailed cognitive process models of learning and instructions.
Date de publication
Maison d’éditionSpringer
Dans
  • Adaptive Instructional Systems. Proceedings of the 4th International Conference, AIS 2022, Held as Part of the 24th HCI International Conference (HCII 2022) (16 juin 2022) : 143–158.
Série
  • Lecture Notes in Computer Science 13332.
Langueanglais
Publications évaluées par des pairsOui
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Identificateur de l’enregistrement5dce9e81-72e4-49eb-b772-8aae3294e70a
Enregistrement créé2022-07-11
Enregistrement modifié2022-07-12
Date de modification :