Transforming geography education: the role of generative AI in curriculum, pedagogy, assessment, and fieldwork
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11310%2F25%3A10503311" target="_blank" >RIV/00216208:11310/25:10503311 - isvavai.cz</a>
Výsledek na webu
<a href="https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=I6r_VpR6to" target="_blank" >https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=I6r_VpR6to</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1080/10382046.2025.2459780" target="_blank" >10.1080/10382046.2025.2459780</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Transforming geography education: the role of generative AI in curriculum, pedagogy, assessment, and fieldwork
Popis výsledku v původním jazyce
Generative artificial intelligence (GenAI) represents a major leap forward in AI technology, offering the potential to reshape education in various aspects. This paper explores the transformative potential of GenAI in geography education, focusing on its impacts across curriculum, pedagogy, assessment, and fieldwork, through the lens of the Substitution, Augmentation, Modification, and Redefinition (SAMR) model. In curriculum development, GenAI enables automatic generation and personalization of geographic content. Pedagogical approaches are evolving from text-based instruction to data-driven learning experiences where students analyze geographic phenomena using GenAI tools. Assessment methods are shifting to adaptive evaluation systems with continuous feedback, while fieldwork benefits from real-time data processing and opportunities for global collaboration. Nevertheless, these advancements are accompanied by substantial risks, including challenges such as overreliance on AI, content inaccuracies, biases, and data privacy concerns.
Název v anglickém jazyce
Transforming geography education: the role of generative AI in curriculum, pedagogy, assessment, and fieldwork
Popis výsledku anglicky
Generative artificial intelligence (GenAI) represents a major leap forward in AI technology, offering the potential to reshape education in various aspects. This paper explores the transformative potential of GenAI in geography education, focusing on its impacts across curriculum, pedagogy, assessment, and fieldwork, through the lens of the Substitution, Augmentation, Modification, and Redefinition (SAMR) model. In curriculum development, GenAI enables automatic generation and personalization of geographic content. Pedagogical approaches are evolving from text-based instruction to data-driven learning experiences where students analyze geographic phenomena using GenAI tools. Assessment methods are shifting to adaptive evaluation systems with continuous feedback, while fieldwork benefits from real-time data processing and opportunities for global collaboration. Nevertheless, these advancements are accompanied by substantial risks, including challenges such as overreliance on AI, content inaccuracies, biases, and data privacy concerns.
Klasifikace
Druh
J<sub>imp</sub> - Článek v periodiku v databázi Web of Science
CEP obor
—
OECD FORD obor
50301 - Education, general; including training, pedagogy, didactics [and education systems]
Návaznosti výsledku
Projekt
—
Návaznosti
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Ostatní
Rok uplatnění
2025
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název periodika
International Research in Geographical and Environmental Education
ISSN
1038-2046
e-ISSN
1747-7611
Svazek periodika
34
Číslo periodika v rámci svazku
3
Stát vydavatele periodika
GB - Spojené království Velké Británie a Severního Irska
Počet stran výsledku
17
Strana od-do
237-253
Kód UT WoS článku
001412982600001
EID výsledku v databázi Scopus
2-s2.0-85216865345