Personalized recommendations for learning activities in online
environments: a modular rule-based approach

J 2024

Personalized recommendations for learning activities in online environments: a modular rule-based approach

PELÁNEK, Radek; Tomáš EFFENBERGER a Petr JARUŠEK

Základní údaje

Originální název

Personalized recommendations for learning activities in online environments: a modular rule-based approach

Autoři

PELÁNEK, Radek; Tomáš EFFENBERGER a Petr JARUŠEK

Vydání

User Modeling and User-Adapted Interaction, DORDRECHT, Springer Netherlands, 2024, 0924-1868

Další údaje

Jazyk

angličtina

Typ výsledku

Článek v odborném periodiku

Obor

10201 Computer sciences, information science, bioinformatics

Stát vydavatele

Německo

Utajení

není předmětem státního či obchodního tajemství

Odkazy

URL

Impakt faktor

Impact factor: 3.500

Označené pro přenos do RIV

Ano

Kód RIV

RIV/00216224:14330/24:00135849

Organizační jednotka

Fakulta informatiky

Klíčová slova anglicky

Recommender system; Education; Learning environment; Adaptive practice; Domain modeling

Příznaky

Mezinárodní význam, Recenzováno

Změněno: 4. 4. 2025 11:26, RNDr. Pavel Šmerk, Ph.D.

Anotace

V originále

Personalization in online learning environments has been extensively studied at various levels, ranging from adaptive hints during task-solving to recommending whole courses. In this study, we focus on recommending learning activities (sequences of homogeneous tasks). We argue that this is an important yet insufficiently explored area, particularly when considering the requirements of large-scale online learning environments used in practice. To address this gap, we propose a modular rule-based framework for recommendations and thoroughly explain the rationale behind the proposal. We also discuss a specific application of the framework.

Přiložené soubory

s11257-024-09396-z.pdf

Citovat

PELÁNEK, Radek; Tomáš EFFENBERGER a Petr JARUŠEK. Personalized recommendations for learning activities in online environments: a modular rule-based approach. User Modeling and User-Adapted Interaction. DORDRECHT: Springer Netherlands, 2024, roč. 34, č. 4, s. 1399-1430. ISSN 0924-1868. Dostupné z: https://doi.org/10.1007/s11257-024-09396-z.

@article{2395999,
   author = {Pelánek, Radek and Effenberger, Tomáš and Jarušek, Petr},
   article_location = {DORDRECHT},
   article_number = {4},
   doi = {https://doi.org/10.1007/s11257-024-09396-z},
   keywords = {Recommender system; Education; Learning environment; Adaptive practice; Domain modeling},
   language = {eng},
   issn = {0924-1868},
   journal = {User Modeling and User-Adapted Interaction},
   title = {Personalized recommendations for learning activities in online environments: a modular rule-based approach},
   url = {https://link.springer.com/article/10.1007/s11257-024-09396-z},
   volume = {34},
   year = {2024}
}

TY  - JOUR
ID  - 2395999
AU  - Pelánek, Radek - Effenberger, Tomáš - Jarušek, Petr
PY  - 2024
TI  - Personalized recommendations for learning activities in online environments: a modular rule-based approach
JF  - User Modeling and User-Adapted Interaction
VL  - 34
IS  - 4
SP  - 1399-1430
EP  - 1399-1430
PB  - Springer Netherlands
SN  - 09241868
KW  - Recommender system
KW  - Education
KW  - Learning environment
KW  - Adaptive practice
KW  - Domain modeling
UR  - https://link.springer.com/article/10.1007/s11257-024-09396-z
N2  - Personalization in online learning environments has been extensively studied at various levels, ranging from adaptive hints during task-solving to recommending whole courses. In this study, we focus on recommending learning activities (sequences of homogeneous tasks). We argue that this is an important yet insufficiently explored area, particularly when considering the requirements of large-scale online learning environments used in practice. To address this gap, we propose a modular rule-based framework for recommendations and thoroughly explain the rationale behind the proposal. We also discuss a specific application of the framework.
ER  -

PELÁNEK, Radek; Tomáš EFFENBERGER a Petr JARUŠEK. Personalized recommendations for learning activities in online environments: a modular rule-based approach. \textit{User Modeling and User-Adapted Interaction}. DORDRECHT: Springer Netherlands, 2024, roč.~34, č.~4, s.~1399-1430. ISSN~0924-1868. Dostupné z: https://doi.org/10.1007/s11257-024-09396-z.

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