Artificial intelligence is the driving force of change focusing on the needs and demands of the student. The research explores Artificial Intelligence in Education (AIEd) for building personalised learning systems for students. The research investigates and proposes a framework for AIEd: social networking sites and chatbots, expert systems for education, intelligent mentors and agents, machine learning, personalised educational systems and virtual educational environments. These technologies help educators to develop and introduce personalised approaches to master new knowledge and develop professional competencies. The research presents a case study of AIEd implementation in education. The scholars conducted the experiment in educational establishments using artificial intelligence in the curriculum. The scholars surveyed 184 second-year students of the Institute of Pedagogy and Psychology at the Abay Kazakh National Pedagogical University and the Kuban State Technological University to collect the data. The scholars considered the collective group discussions regarding the application of artificial intelligence in education to improve the effectiveness of learning. The research identified key advantages to creating personalised learning pathways such as access to training in 24/7 mode, training in virtual contexts, adaptation of educational content to personal needs of students, real-time and regular feedback, improvements in the educational process and mental stimulations. The proposed education paradigm reflects the increasing role of artificial intelligence in socio-economic life, the social and ethical concerns artificial intelligence may pose to humanity and its role in the digitalisation of education. The current article may be used as a theoretical framework for many educational institutions planning to exploit the capabilities of artificial intelligence in their adaptation to personalized learning.
In recent years, student-centered learning has undergone significant changes influenced by the introduction of the competency-based approach to the digital learning environment. The new approach places a teacher at the center of the educational process taking into account professional competencies and personal interests of educators to foster the improvements of methodological, organizational, and technological support of personalized learning. The sample (N = 36) consists of the 3rd year students of University (KazNPU). The research methodology uses the following metrics to test the psychological and emotional characteristics of students: Communication Skills Assessments and Analysis of Cultural and Value Orientations. The study revealed a background of discomfort with the current system of education - about half of the respondents experience psychological and emotional stress due to the current education format. In addition, after the implementation of the program it was found that the SCL configuration model, applied to distance learning, had a significant impact on students. Statistical analysis of the chi-square indices of general fit (χ2 = 122.77) shows a good fit to the set of data points. The results can be used by educators and in future research to analyze the feasibility and advantages of digital educational processes in other geographical regions.
The purpose of the research is to study and scientifically substantiate personalized strategies as the basis for personalized learning aimed at improving academic performance and student motivation. The study involved 65 teachers and 700 students of various specialties from three Russian and Kazakhstan universities. The survey analysis showed that the modern generation of students is no longer motivated to receive standardized educational services, and in this context, personalized strategies as a form of personalized learning are a key trend that has permeated all aspects of professional training. Unfortunately, currently, universities find it difficult to implement such an approach as personalized learning makes educational modules highly adapted and individualized to meet the needs of each particular student. To apply personalized strategies in the educational process, it is necessary to study the structure of a particular institution, to analyze educational programs, to conduct classes based on personalized learning strategies.
To date, the existing principles of a unified approach to schooling do not meet the requirements of a fundamental socio-economic transition characterized by personalization and customization of products and services that concern all areas, including education. The paradigm of education systems is being restructured in many countries towards a new approach of personalized learning that is adapted to students' needs, allows them to choose individual educational trajectories, and respects unique skills and qualities. The study aimed to determine the impact of personalization on the academic performance of engineering students in physics. The experiment on personalized student support was conducted during the academic year 2018-2019 at I.T. Trubilin Kuban State Agrarian University. The sample covered 78 students. The starting point of the research was the assessment of students' skills in mathematics, as the study of physics is based on mathematical analysis and interpretation. Test in physics and the criterion of alpha Kronbach (test reliability is determined with a coefficient of 0.87) were used as a toolkit for research. Besides, the statistical tools and covariance analysis of data processing were employed. The research was supported by the SPSS Statistics software package. According to the results obtained, higher post-test scores were recorded for students in the experimental group. The personalized learning has been found to have a significant impact on the academic performance of students. Those with low and medium ability in mathematics demonstrated higher growth in academic achievement than students with recorded high aptitude scores. A correlation between learning methods and mathematical skills to achieve high academic performance has been established. The influence of personalization in the learning process was determined to be moderately high (determinacy coefficient of 72.6%). The study is relevant for the development of constructive approaches that could help teachers improve their approach to learning and students improve academic achievements. The results may be of interest to researchers of educational technology, educators, and university administration management.
Digital gaming has become a regular part of life for today's pre-schoolers. Hence, there is a need to look at the integration of digital technology into the preschool education. The present study aims to examine the effect digital games have on children's behaviour and their social competence if played to reach an educational purpose (supervised play) and for fun (without educational aim). The study population consists of 54 pre-schoolers (26 girls and 28 boys), aged 4 to 6, who were recruited in Moscow, Russia. All children were divided in two groups: children playing digital games with peers (n = 28) and children playing digital games at home (n = 28). Findings revealed a higher level of social competence in the experimental group (+11.71, p 0.05) as compared to children playing without being told what they were expected to achieve. The experimental group also scored lower on Anxiety-Withdrawal (-7.94, p 0.05). A higher Anxiety-Withdrawal score normally means that a child experiences some degree of depression or anxiety, and exhibits overly dependent behaviour. The results of this study may help parents and teachers to use digital learning tools, in particular video games, effectively when working with young children.
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