Lupa

Show document Help

A- | A+ | Print
Title:Učinkovitost generativne umetne inteligence za personalizirano učenje matematike
Authors:ID Lipovec, Alenka (Author)
ID Arcet, Barbara (Author)
Files:.pdf ZUP_Lipovec_Alenka_2025.pdf (160,03 KB)
MD5: 6DD9DD2F82D2F70A19C29841095930D7
 
Language:Slovenian
Work type:Unknown
Typology:1.16 - Independent Scientific Component Part or a Chapter in a Monograph
Organization:ZUP - University of Primorska Press
Abstract:Generativna umetna inteligenca (GUI) postaja nepogrešljivo orodje v izobraževanju tudi pri pouku matematike, saj omogoča prilagoditev nalog znanju posameznih učencev, s čimer spodbuja personalizirano učenje in izboljšuje učne dosežke. Med dodatnimi zaznanimi prednostmi so izboljšanje besedišča, povečanje radovednosti, okrepljene sposobnosti povezovanja, izboljšana sposobnost reformulacije vprašanj ter poglobljeno kritično vrednotenje odgovorov. Kljub temu naloge, ki jih ustvarja umetna inteligenca, pogosto ne odražajo kulturnih ali osebnih značilnosti učencev, kar lahko omejuje njihovo avtentičnost. Raziskave kažejo, da je GUI še posebej koristna za učence z nižjim predznanjem, saj jim omogoča hitrejše napredovanje, pri čemer je njena največja vrednost dosežena ob aktivni podpori učiteljev, ki usmerjajo delo in vrednotijo rezultate – pristop, znan kot hibridno tutorstvo. V šolskem okolju lahko GUI deluje v različnih vlogah – kot učenec, učitelj, mentor ali sošolec. Ključno za njeno uspešno uporabo je skrbno oblikovanje pozivov, ki naj bodo jasni, specifični, kontekstualizirani in prilagodljivi. Med učinkovitimi strategijami so »veriga misli«, ki spodbuja postopno in poglobljeno reševanje problemov, »negativni pozivi« za preprečevanje napak ter »metapozivi«, ki učence usmerjajo k refleksiji in h kritičnemu razmišljanju. Čeprav se članek osredotoča na uporabo pri pouku matematike, so njegove ugotovitve prenosljive na druge predmete ter širši izobraževalni proces.
Keywords:generativna umetna inteligenca (GUI), poučevanje matematike, oblikovanje pozivov, personalizirano učenje, učenje matematike
Publication status:Published
Publication version:Version of Record
Year of publishing:2025
Number of pages:Str. 203-219
PID:20.500.12556/RUP-22335 This link opens in a new window
UDC:37.091.33:51:004.8
DOI:10.26493/978-961-293-431-6.10 This link opens in a new window
COBISS.SI-ID:244073731 This link opens in a new window
Publication date in RUP:23.12.2025
Views:87
Downloads:0
Metadata:XML DC-XML DC-RDF
:
Copy citation
  
Average score:(0 votes)
Your score:Voting is allowed only for logged in users.
Share:Bookmark and Share


Hover the mouse pointer over a document title to show the abstract or click on the title to get all document metadata.

Record is a part of a monograph

Title:Izobraževanje v dobi generativne umetne inteligence : mednarodne smernice in raziskave
Editors:Andrej Flogie, Sonja Čotar Konrad
Place of publishing:Koper
Publisher:Založba Univerze na Primorskem
Year of publishing:2025
ISBN:978-961-293-431-6
COBISS.SI-ID:237356291 This link opens in a new window
Collection title:Knjižnica Ludus
Collection numbering:58
Collection ISSN:2630-3809

Document is financed by a project

Funder:Other - Other funder or multiple funders
Funding programme:Republika Slovenija, Ministrstvo za vzgojo in izobraževanje
Project number:3350-24-3502
Name:Generativna umetna inteligenca v izobraževanju

Licences

License:CC BY-SA 4.0, Creative Commons Attribution-ShareAlike 4.0 International
Link:http://creativecommons.org/licenses/by-sa/4.0/
Description:This Creative Commons license is very similar to the regular Attribution license, but requires the release of all derivative works under this same license.

Secondary language

Language:English
Title:The effectiveness of generative artificial intelligence for personalized mathematics learning
Abstract:Generative artificial intelligence (GEN-AI) is becoming an indispensable tool in education and mathematics instruction, as it enables the adaptation of tasks to the knowledge level of individual students, thereby promoting personalized learning and improving academic outcomes. Additional benefits include enhanced vocabulary, increased curiosity, strengthened connection-building skills, improved ability to reformulate questions, and deeper critical evaluation of answers. However, tasks generated by AI often fail to reflect the cultural and personal characteristics of students, which can limit their authenticity. Research indicates that generative AI is particularly beneficial for students with lower prior knowledge, as it facilitates faster progress. Its greatest value is achieved when combined with active teacher support, who guides the learning process and evaluates outcomes—a method known as hybrid tutoring. In educational settings, generative AI can assume various roles, such as the role of a student, teacher, mentor, or peer. Its successful implementation relies on carefully crafted prompts that are clear, specific, contextualized, and adaptable. Effective strategies include “chain-of-thought” prompts to encourage step-by-step problem-solving, “negative prompts” to prevent errors, and “meta-prompts” that guide students toward reflection and critical thinking. Although this article focuses on applications in mathematics, the findings are equally applicable to other subjects and broader educational contexts.
Keywords:mathematics education, generative artificial intelligence, prompt design, personalized learning, learning mathematics


Comments

Leave comment

You must log in to leave a comment.

Comments (0)
0 - 0 / 0
 
There are no comments!

Back
Logos of partners University of Maribor University of Ljubljana University of Primorska University of Nova Gorica