Influence of Artificial Intelligence in Education on Adolescents’ Social Adaptability: A Machine Learning Study

Xie, Chuyin; Ruan, Minhua; Lin, Pei; Wang, Zheng; Lai, Tinghong; Xie, Yangyang; Fu, Shimin; Lu, Hong

doi:10.3390/ijerph19137890

Cited by 8 publications

(7 citation statements)

References 24 publications

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“…The results of the study confirm the adaptability of educational AI solutions identified in the publication (Xie et al, 2022): intelligent AI systems can customise content and tasks according to learning progress, contributing to a more efficient learning process.…”

Section: Discussionsupporting

confidence: 72%

Application of artificial intelligence in Ukrainian education of the future

2023

FeD

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The purpose of this study is to determine the most appropriate list of digital tools based on the use of artificial intelligence to improve the educational sector in Ukraine. The study included the following stages: compiling a list of expert organisations with assessments of the impact of AI technologies on education; evaluating AI solutions by experts and forming individual ratings; calculating relative ratings based on the frequency of mentions of AI solutions; identifying priority AI solutions by their leading positions; forming an optimal nomenclature of AI solutions; developing practical recommendations for the introduction of AI in education; analysing the future development of education using AI. The study found that the use of AI to modernise the Ukrainian education system is best done using a comprehensive three-tier deployment system. The first level involves creating an infrastructure for AI, ensuring the interaction of systems. The second level involves optimising and enhancing learning. The third level is aimed at automating and improving educational and support processes. The proposed practical recommendations address the ethical, technical, and pedagogical aspects of AI implementation, allowing for the creation of a modern, efficient educational system that meets the requirements of the present and forms competent specialists of the future. The research findings are crucial for modern education in Ukraine. The study identified opportunities and benefits of using AI in education, such as individualised learning, improved communication, and process automation. Recommendations for optimal artificial intelligence solutions will allow for a balanced approach to the implementation of these technologies, avoiding negative consequences and ensuring safety. These results provide a basis for the development of national standards for the use of AI in education and determine the vectors of further development of the industry, contributing to the creation of a modern, individualised and effective educational system that trains competent specialists of the future. Overall, the research findings define a strategic course for the integration of artificial intelligence into the educational space, which can significantly improve the quality and accessibility of education in Ukraine.

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Section: Discussionsupporting

confidence: 72%

Application of artificial intelligence in Ukrainian education of the future

2023

FeD

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“…These factors play a crucial role in effective learning and motivation. Incorporating social interactions, emotional support, and feedback mechanisms into AIED design can enhance the overall learning experience (Xie et al, 2022). For instance, Lai et al (2023) noted the need for the development of social adaptability in AIED system.…”

Section: Current Problems In Aied Designsmentioning

confidence: 99%

Activity Theory-based Ecosystem for Artificial Intelligence in Education (AIED)

Uden,

Ching

2024

IJRSE

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The integration of Artificial Intelligence in Education (AIED) stands as a pivotal trend in education, yet comprehensive design frameworks remain a subject of ongoing exploration.While many AIED studies are still in their early stages of development and implementation, the uncertainties and challenges surrounding the ethical and responsible use of AI in education persist. Anchoring on the Activity Theory, this paper proposes a conceptual framework, aiming to construct a sustainable ecosystem for AIED design within the dynamic landscape in all levels of education. Within the constructs of Activity Theory, this framework endeavors to scrutinize the intricate relationship between individuals (learners), their learning activities, and the broader socio-cultural context wherein these activities unfold. Moreover, the paper advocates for collaborative agreements among educators, learners, and educational institutions as essential pillars in the design and implementation of AIED systems tailored for education. In essence, this conceptual paper serves as a theoretical proposition, utilizing Activity Theory as a lens to envisage an adaptive and ethically responsible AIED ecosystem specifically crafted to address the nuanced dynamics inherent in all levels of education. It urges designers to meticulously consider the interplay between learners, educators, technology, and the sociocultural fabric when devising strategies for fostering effective, inclusive, and engaging learning experiences.

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“…So that artificial intelligence can be embedded in the learning media created. The existence of artificial intelligence will add value to the usefulness of the media [42,43]. R12B states: The development of science and technology today, allows students to access various learning media available in cyberspace.…”

Section: Question 2: What Media Do Lecturers Use In Teaching Topics I...mentioning

confidence: 99%

Learning Problems of Prospective Teachers in Lectures Modern Physics During the Covid-19 Pandemic

Juandi,

Kaniawati,

Samsudin

et al. 2024

KSS

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Since the COVID-19 pandemic hit the world, many problems have been caused by accompanying effects, including impacts in the field of education. This study aims to explore the problems faced by physics education study program students in modern physics lectures in online learning during the COVID-19 pandemic. The method used in this study is a qualitative description with a questionnaire as a data collection technique. A total of 28 students who contracted modern physics courses and two lecturers who taught modern physics courses were participants in this study. The collected data were analyzed descriptively-qualitatively. After data analysis, several problems faced by students in attending modern physics lectures can be identified, namely: difficulty mastering concepts, internet signal interference, less interesting/monotonous learning, and never doing modern physics practicum. Limited tools are the main factor in the inability to carry out practicum. Even though practicum allows students to master abstract concepts of modern physics. Based on these findings, further research can be carried out that can facilitate students to more easily master modern physics concepts that are integrated with a practicum in the learning process. Keywords: learning problems, prospective teachers, lectures modern physics, covid-19 pandemic

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Influence of Artificial Intelligence in Education on Adolescents’ Social Adaptability: A Machine Learning Study

Cited by 8 publications

References 24 publications

Application of artificial intelligence in Ukrainian education of the future

Application of artificial intelligence in Ukrainian education of the future

Activity Theory-based Ecosystem for Artificial Intelligence in Education (AIED)

Learning Problems of Prospective Teachers in Lectures Modern Physics During the Covid-19 Pandemic

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