<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Bo Zhou</style></author><author><style face="normal" font="default" size="100%">Seong Pek Lim</style></author><author><style face="normal" font="default" size="100%">Nahdia Kabir</style></author><author><style face="normal" font="default" size="100%">Asna</style></author><author><style face="normal" font="default" size="100%">Tian Nan Lu</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">FROM AUTOMATION TO SOCIO-AFFECTIVE LEARNING: A BIBLIOMETRIC ANALYSIS OF ARTIFICIAL INTELLIGENCE IN ENGLISH AS A FOREIGN LANGUAGE EDUCATION</style></title><secondary-title><style face="normal" font="default" size="100%">Problems of Education in the 21st Century</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">artificial Intelligence</style></keyword><keyword><style  face="normal" font="default" size="100%">bibliometric analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">EFL</style></keyword><keyword><style  face="normal" font="default" size="100%">socio-affective learning</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2026</style></year><pub-dates><date><style  face="normal" font="default" size="100%">February/2026</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://journals.indexcopernicus.com/search/article?articleId=4771008</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">84</style></volume><pages><style face="normal" font="default" size="100%">continuous</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Artificial intelligence (AI) has become a driving force in education. Within English as a Foreign Language (EFL) pedagogy, it is reconfiguring instructional approaches by linking automation with learner-centered and affective learning design. Nevertheless, empirical research remains fragmented across cognitive, affective, and social domains, necessitating a comprehensive approach. Drawing on data from the Web of Science (WoS) Core Collection (2021–2025), this study examines the bibliometric landscape of the field. Following PRISMA-based screening, 281 peer-reviewed publications were analyzed with VOSviewer and CiteSpace. Results demonstrate a sharp rise in publications and a conceptual evolution from performance-driven to socio-affective perspectives. Co-citation analysis delineates three major research domains–conversational AI in pedagogy, AI-based assessment tools, and affective–motivational learning–while co-occurrence mapping identifies four thematic clusters: chatbots and emotions, generative AI and critical thinking, automated writing evaluation and feedback, and technology adoption and motivation. Burst detection indicates a growing focus on positive psychology and communication skills. Building on these results, the study suggests the Affective–Cognitive–Social Integration Model (ACSIM), which extends existing acceptance frameworks to encompass motivation, emotion, and ethics. The model bridges automation-oriented AI research with socio-affective pedagogy and informs emotionally intelligent instruction, AI literacy among teachers, and institutional practices for responsible and sustainable use.</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue><work-type><style face="normal" font="default" size="100%">Original article</style></work-type><section><style face="normal" font="default" size="100%">229-247</style></section></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Lessing, M. J.</style></author><author><style face="normal" font="default" size="100%">Ugorji Iheanachor Ogbonnaya</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">ARTIFICIAL INTELLIGENCE IN MATHEMATICS EDUCATION OF STUDENTS WITH SPECIAL EDUCATIONAL NEEDS</style></title><secondary-title><style face="normal" font="default" size="100%">Problems of Education in the 21st Century</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">artificial Intelligence</style></keyword><keyword><style  face="normal" font="default" size="100%">conceptual knowledge</style></keyword><keyword><style  face="normal" font="default" size="100%">disabilities</style></keyword><keyword><style  face="normal" font="default" size="100%">learning disabilities</style></keyword><keyword><style  face="normal" font="default" size="100%">mathematics</style></keyword><keyword><style  face="normal" font="default" size="100%">special education</style></keyword><keyword><style  face="normal" font="default" size="100%">special needs</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2025</style></year><pub-dates><date><style  face="normal" font="default" size="100%">December/2025</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://journals.indexcopernicus.com/search/article?articleId=4714161</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">83</style></volume><pages><style face="normal" font="default" size="100%">continuous</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">This study examined the role of artificial intelligence (AI) in supporting the mathematics education of students with special educational needs (SEN). Thirty peer-reviewed articles were analysed to examine (i) the types of AI technologies implemented in mathematics education, (ii) evidence on the effectiveness of AI interventions in improving learning, (iii) the benefits and limitations of AI in special education, (iv) comparisons of AI applications with traditional methods in terms of personalisation, engagement, and accessibility, and (v) applications of AI in supporting specific disabilities. The findings indicated that intelligent games, chatbots, personalised learning systems, and intelligent tutoring systems were the most frequently utilised AI-powered tools. All studies assessing effectiveness reported positive impacts on mathematical achievement, as well as benefits such as reduced mathematics anxiety, increased motivation, and enhanced independence among learners. Reported challenges included high costs, ethical concerns, teacher preparedness, and a digital divide limiting equitable access. Compared to traditional methods, AI offers more accurate diagnosis of learning difficulties, greater opportunities for personalised learning, and increased accessibility. AI showed promise in addressing specific disabilities such as dyscalculia and autism through adaptive and diagnostic tools. The review concluded that AI should be viewed as a complementary tool that extends teachers’ capacity to individualise mathematics instruction for students with SEN.</style></abstract><issue><style face="normal" font="default" size="100%">6</style></issue><work-type><style face="normal" font="default" size="100%">Original article</style></work-type><section><style face="normal" font="default" size="100%">786-806</style></section></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Andie Tangonan Capinding</style></author><author><style face="normal" font="default" size="100%">Franklin Tubeje Dumayas</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">TRANSFORMATIVE PEDAGOGY IN THE DIGITAL AGE: UNRAVELING THE IMPACT OF ARTIFICIAL INTELLIGENCE ON HIGHER EDUCATION STUDENTS</style></title><secondary-title><style face="normal" font="default" size="100%">Problems of Education in the 21st Century</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">artificial Intelligence</style></keyword><keyword><style  face="normal" font="default" size="100%">descriptive-comparative</style></keyword><keyword><style  face="normal" font="default" size="100%">higher education</style></keyword><keyword><style  face="normal" font="default" size="100%">impact on learning</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2024</style></year><pub-dates><date><style  face="normal" font="default" size="100%">October/2024</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://oaji.net/articles/2023/457-1728583451.pdf</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">82</style></volume><pages><style face="normal" font="default" size="100%">Continuous</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Artificial Intelligence (AI) has become a transformative force in education, significantly influencing students. This research explores AI's impact on learning experiences, academic performance, career guidance, motivation, self-reliance, social interaction, and AI dependency. Utilizing a descriptive-comparative design, 194 student respondents were chosen through stratified sampling. The results show that students generally perceive AI positively. Students agree that AI enhances personalized learning, engagement, and critical thinking, although practical hands-on learning experiences received less favorable feedback. Academically, students concur that AI helps them identify weaknesses, improve assignments, and track progress, despite some reservations about its efficacy in exam preparation. For career guidance, students agree that AI effectively matches skills with career options, recommends internships, and provides resources, though it is less effective for long-term planning. Students also believe AI boosts motivation through gamified learning and progress tracking and fosters self-reliance via self-directed learning and critical thinking support. Socially, students agree that AI facilitates collaboration, peer learning, and networking. Additionally, students demonstrate a reliance on AI for their learning processes. Notably, female students report a more significant impact on social interactions than male students. The type of device used (laptop vs. cellphone) significantly affects the learning experience, with laptop users reporting a more substantial impact. Differences in AI's impact are noted among various courses, particularly benefiting education students more than those in hospitality management and agriculture. However, age and family income do not significantly influence AI's overall impact.</style></abstract><issue><style face="normal" font="default" size="100%">5</style></issue><work-type><style face="normal" font="default" size="100%">Original article</style></work-type><section><style face="normal" font="default" size="100%">630-657</style></section></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Durso, S. D. O.</style></author><author><style face="normal" font="default" size="100%">Arruda, E. P.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">ARTIFICIAL INTELLIGENCE IN DISTANCE EDUCATION: A SYSTEMATIC LITERATURE REVIEW OF BRAZILIAN STUDIES</style></title><secondary-title><style face="normal" font="default" size="100%">Problems of Education in the 21st Century</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">artificial Intelligence</style></keyword><keyword><style  face="normal" font="default" size="100%">distance education</style></keyword><keyword><style  face="normal" font="default" size="100%">educational technology</style></keyword><keyword><style  face="normal" font="default" size="100%">systematic literature review</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2022</style></year><pub-dates><date><style  face="normal" font="default" size="100%">October/2022</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://oaji.net/articles/2022/457-1667682748.pdf</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">80</style></volume><pages><style face="normal" font="default" size="100%">Continuous</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Artificial Intelligence (AI) is changing the way people live in society. New technologies powered by AI have been applied in different sectors of the economy and the educational context is no different. AI has been considered a key to the development of learning strategies, especially in distance education. In this sense, this research aimed to identify the current state of Brazilian literature on AI applied to distance education. The Higher Education market in Brazil, which is the biggest in Latin America regarding the number of individuals able to enroll in a program, is still developing and distance education has grown rapidly. To reach the purpose of this paper, it was performed a Systematic Literature Review (SLR) to find the research conducted in graduate programs that investigate the subject of AI applied to distance education. The final analysis used a total of 63 studies – 26 master’s theses and 37 doctoral dissertations. The main results show that most of the research on AI in distance education in Brazil was conducted in Computer Science (56%) and Engineering (27%). Only 6% of the studies reviewed are from masters’ or doctoral programs in Education. The result also shows that limited attention is paid to critical topics related to the growing introduction of AI in distance education, as such teachers’ employability and technological training or the ethical implications of using AI for the educational process. As a result of this SLR, it was possible to suggest research opportunities considering the international agenda on AI.</style></abstract><issue><style face="normal" font="default" size="100%">5</style></issue><work-type><style face="normal" font="default" size="100%">Original article</style></work-type><section><style face="normal" font="default" size="100%">679-692</style></section></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Boris Aberšek</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">CHANGING EDUCATIONAL THEORY AND PRACTICE</style></title><secondary-title><style face="normal" font="default" size="100%">Problems of Education in the 21st Century </style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">artificial Intelligence</style></keyword><keyword><style  face="normal" font="default" size="100%">cognitive neuroeducation</style></keyword><keyword><style  face="normal" font="default" size="100%">Cognitive Science</style></keyword><keyword><style  face="normal" font="default" size="100%">educational systems</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2015</style></year><pub-dates><date><style  face="normal" font="default" size="100%">August/2015</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://oaji.net/articles/2015/457-1441441743.pdf</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">66</style></volume><pages><style face="normal" font="default" size="100%">Discontinuous</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">How do we think, how do we learn, memorize and dream, how does pleasure come to be, where are the emotions hidden and how do we reach decisions? Cognitive science and neuroscience tries to answer such questions. It tackles the fields of the human mind in an interdisciplinary, even transdisciplinary way – by connecting discoveries from all the disciplines that could shed light on cognitive occurrences. Cognitive science brings together psychology, philosophy, linguistics, artificial intelligence, social sciences and many others. It tries to deal with mental processes in a holistic way and to create a deeper understanding of the field that is empirically closest to us.</style></abstract><work-type><style face="normal" font="default" size="100%">Editorial</style></work-type><section><style face="normal" font="default" size="100%">4-6</style></section></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Boris Aberšek</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">INTERDISCIPLINARITY IN EDUCATION</style></title><secondary-title><style face="normal" font="default" size="100%">Problems of Education in the 21st Century</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">artificial Intelligence</style></keyword><keyword><style  face="normal" font="default" size="100%">cognitive modelling in education</style></keyword><keyword><style  face="normal" font="default" size="100%">cognitive scientists</style></keyword><keyword><style  face="normal" font="default" size="100%">teaching/learning process</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">October/2014</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://oaji.net/articles/2015/457-1422203467.pdf</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">61</style></volume><pages><style face="normal" font="default" size="100%">Discontinuous</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Questions about the nature of the teaching/learning process originate in ancient Greek philosophy. What is the role of language? What is the relationship between the individuals? Are we free in our choices? Important ancient philosophers, Democritus, Plato, Aristotle and Lucretius answered these questions in different ways, while Descartes, Spinoza, Hume, Kant and many others continued where they left off. Even today in the Age of Technology, contemporary researchers from the fields of philosophy, cognitive science, neurobiology, and artificial intelligence ask similar, albeit technologically informed, questions. Among these, there are also questions about the relationship between humans and machines, and implications which they carry for solving traditional problems within philosophy, i.e. the mind-body problem, mental causation problem and the problem of consciousness. </style></abstract><work-type><style face="normal" font="default" size="100%">Editorial</style></work-type><section><style face="normal" font="default" size="100%">5-8</style></section></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Janez  Bregant</style></author><author><style face="normal" font="default" size="100%">Boris Aberšek</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">ARTIFICIAL INTELLIGENCE VERSUS HUMAN TALENTS IN LEARNING PROCESS</style></title><secondary-title><style face="normal" font="default" size="100%">Problems of Education in the 21st Century</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">artificial Intelligence</style></keyword><keyword><style  face="normal" font="default" size="100%">brain based learning</style></keyword><keyword><style  face="normal" font="default" size="100%">intelligent tutors</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2011</style></year><pub-dates><date><style  face="normal" font="default" size="100%">December/2011</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://oaji.net/articles/2014/457-1408435723.pdf</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">37</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">To highlight the differences between conventional educational systems and CBLS - computer based learning systems. It is useful to consider CBLS, as the class of a system most closely related to artificial intelligence - AI. In such a system, the ultimate goal is to create a virtual duplicate of reality for learning, analysis, training, experimentation, or other purposes. Simulating reality is an approach that may or may not be useful at creating experience. This distinction yield several consequences. In CBLS, behaviour should be as realistic as possible, the representation of environment tends to be uniform and consistent and allowing users to act freely within that environment. 
 To teach users through realistic experience CBLS design techniques can make the experience much more memorable. In such an environment the context and control afforded by design techniques allow the integration of technologies and evaluation of the overall experience. Perhaps it is time to take lessons of CBLS and AI in a learning design and teaching tools seriously.
 At the beginning we will point out one simple question: could the ideas, methodology and techniques of AI also be applied to a development of relatively serious mind applications and can they substitute human teachers? And the answer will be continued in our paper.</style></abstract><work-type><style face="normal" font="default" size="100%">Original article</style></work-type><section><style face="normal" font="default" size="100%">38-47</style></section></record></records></xml>