Towards Design-Loop Adaptivity: Identifying Items for Revision

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F22%3A00128708" target="_blank" >RIV/00216224:14330/22:00128708 - isvavai.cz</a>

Výsledek na webu

<a href="https://jedm.educationaldatamining.org/index.php/JEDM/article/view/600" target="_blank" >https://jedm.educationaldatamining.org/index.php/JEDM/article/view/600</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.5281/zenodo.7357331" target="_blank" >10.5281/zenodo.7357331</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Towards Design-Loop Adaptivity: Identifying Items for Revision

Popis výsledku v původním jazyce

We study the automatic identification of educational items worthy of content authors’ attention. Based on the results of such analysis, content authors can revise and improve the content of learning environments. We provide an overview of item properties relevant to this task, including difficulty and complexity measures, item discrimination, and various forms of content representation. We analyze the potential usefulness of these properties using both simulation and analysis of real data from a large-scale learning environment. We also describe two case studies where we practically apply the identification of attention-worthy items. Based on the analysis and case studies, we provide recommendations for practice and impulses for further research.

Název v anglickém jazyce

Towards Design-Loop Adaptivity: Identifying Items for Revision

Popis výsledku anglicky

We study the automatic identification of educational items worthy of content authors’ attention. Based on the results of such analysis, content authors can revise and improve the content of learning environments. We provide an overview of item properties relevant to this task, including difficulty and complexity measures, item discrimination, and various forms of content representation. We analyze the potential usefulness of these properties using both simulation and analysis of real data from a large-scale learning environment. We also describe two case studies where we practically apply the identification of attention-worthy items. Based on the analysis and case studies, we provide recommendations for practice and impulses for further research.

Druh

J_SC - Článek v periodiku v databázi SCOPUS

CEP obor

—

OECD FORD obor

10200 - Computer and information sciences

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2022

Kód důvěrnosti údajů

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

Název periodika

Journal of Educational Data Mining

ISSN

2157-2100

e-ISSN

—

Svazek periodika

14

Číslo periodika v rámci svazku

3

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

25

Strana od-do

1-25

Kód UT WoS článku

—

EID výsledku v databázi Scopus

2-s2.0-85145995438