Adapting Is Difficult! Introducing a Generic Adaptive Learning Framework for Learner Modeling and Task Recommendation Based on Dynamic Bayesian Networks

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F23%3A00130708" target="_blank" >RIV/00216224:14330/23:00130708 - isvavai.cz</a>

Result on the web

<a href="http://dx.doi.org/10.5220/0011964700003470" target="_blank" >http://dx.doi.org/10.5220/0011964700003470</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.5220/0011964700003470" target="_blank" >10.5220/0011964700003470</a>

Result language

angličtina

Original language name

Adapting Is Difficult! Introducing a Generic Adaptive Learning Framework for Learner Modeling and Task Recommendation Based on Dynamic Bayesian Networks

Original language description

The process of learning is a personal experience, strongly influenced by the learning environment. Virtual learning environments (VLEs) provide the potential for adaptive learning, which aims to individualize learning experiences in order to improve learning outcomes. Adaptive learning environments achieve individualization by analyzing the learners and altering the instruction according to their specific needs and goals. Despite ongoing research in adaptive learning, the effort to design, develop and implement such environments remains high. Therefore, we introduce a novel, generalized adaptive learning framework based on the methodological Evidence-Centered Design (ECD) framework. Our framework focuses on the analysis of learners’ competencies and the subsequent recommendation of tasks with an appropriate difficulty level. With this paper and the open-source adaptive learning framework, we contribute to the ongoing discussion about generalized adaptive learning technology.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

—

Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2023

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

Proceedings of the 15th International Conference on Computer Supported Education - Volume 1

ISBN

9789897586415

ISSN

2184-5026

e-ISSN

—

Number of pages

9

Pages from-to

272-280

Publisher name

SciTePress

Place of publication

Prague

Event location

Prague

Event date

Jan 1, 2023

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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