Dirbtinis intelektas edukacijoje: integravimo galimybių teorinė analizė

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Collection:
Mokslo publikacijos / Scientific publications
Document Type:
Straipsnis / Article
Language:
Lietuvių kalba / Lithuanian
Title:
Dirbtinis intelektas edukacijoje: integravimo galimybių teorinė analizė
Alternative Title:
Artificial intelligence in education: the theoretical analysis of integration possibilities
In the Journal:
Regional formation and development studies. 2022, Nr. 2 (37), p. 19-28
Summary / Abstract:

LTDirbtinis intelektas vis labiau skverbiasi į mokyklas ir edukacijos procesą. Tad svarbu nustatyti, kaip jis gali padėti tobulinti mokymo(si) procesą. Šiame straipsnyje apžvelgiamos ir sisteminamos šiuolaikinės dirbtiniu intelektu paremtos edukacinės technologijos, atskleidžiant jų galimus privalumus ir trūkumus, kuriant personalizuotas mokymo(si) aplinkas. Siekiant išsikelto tikslo, taikytas mokslinės literatūros analizės metodas. Jo pagrindu skiriamos pagrindinės dirbtinio intelekto integravimo į edukacines technologijas tendencijos, jos išsamiai aptariamos. Teigiama, kad įvertinus dirbtinio intelekto privalumus ir galimybes edukacijoje, jis turėtų būti vertinamas kaip edukacijos praktiką transformuojantis procesas, kur būtina iš esmės persvarstyti pagrindinius vaidmenis. Svarbiausias efektyvaus dirbtinio intelekto naudojimo edukacijoje veiksnys – mokytojų raštingumas dirbtinio intelekto srityje. PAGRINDINIAI ŽODŽIAI: dirbtinis intelektas, edukacija, šiuolaikinės technologijos. [Iš leidinio]

ENArtificial intelligence is increasing its role in schools and in the educational process. As a result, it is important to identify how it can help improve the learning process, but before that to find out what the existing technologies are. The aim of this article is to review and systematise literature on modern educational technologies based on artificial intelligence, revealing their possible advantages and disadvantages in creating personalised learning environments. To achieve this goal, the method of analysis of scientific literature was used. Based on an analysis of scientific literature, the main tendencies in the integration of artificial intelligence into educational technologies were singled out and discussed in detail. The search for scientific articles was performed on four online scientific databases. Publications since 2005 were considered suitable for systematic analysis, and 30 publications were selected for analysis. The data are presented according to five main trends in the integration of artificial intelligence into educational technologies (Southgate et al., 2018): intelligent tutoring systems, pedagogical agents, smart classes, learning analytics, and adaptive learning. Intelligent tutoring systems simulate individual human learning (Luckin et al., 2016). Studies (van Lehn, 2011; Baker, 2016; du Boulay, 2016; etc) show that intelligent tutoring systems are significantly more effective than many other teaching/learning tools, such as regular lessons, homework and textbook learning. It is important to emphasise that the technologies of intelligent tutoring systems are still evolving and do not yet cover all areas and content. Therefore, if intelligent tutoring systems are available in a particular field of education (e.g. mathematics), they can effectively complement students learning inside or outside the classroom.However, these systems are unlikely to replace teachers and lecturers in all areas and/or close gaps in achievement between different groups of pupils and students. Another possibility for integrating artificial intelligence into educational technologies is through pedagogical agents. Pedagogical agents are digital or virtual characters integrated into learning technologies with the aim of facilitating teaching/learning. Also, smart class environments are more advanced in a pedagogical sense because, unlike reductionismbased smart learning systems, they rely on constructivist approaches (according to Mitchell, Howlin, 2019). The above-mentioned systems are directly related to the idea of adaptive learning and the data obtained. Adaptive/individualised teaching is an important pedagogical strategy and goal that promotes the development of technological solutions for adaptive learning. And the data obtained is an area of learning analytics. Learning analytics leaves the teachers and students to make a decision, but provides some automated data analysis. It is argued that, given the merits of artificial intelligence and its benefits in education, it should be seen as a process transforming educational practices that requires a fundamental rethink of the key roles. The most important factor in the effective use of artificial intelligence in education is teacher literacy in the field of artificial intelligence. KEY WORDS: artificial intelligence, education, modern technologies in education. [From the publication]

DOI:
10.15181/rfds.v37i2.2418
ISSN:
2029-9370; 2351-6542
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Permalink:
https://www.lituanistika.lt/content/98617
Updated:
2022-11-07 17:17:07
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