Personalized Education in the Artificial Intelligence Era: What to Expect Next

Lan, Andrew S.; Xu, Jie; Schaar, Mihaela van der

doi:10.1109/msp.2021.3055032

Cited by 132 publications

(41 citation statements)

References 27 publications

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“…AI-based digital learning solutions can adapt to individual students' level of knowledge, learning rates, and desired goals to get the most out of their education. Furthermore, it has the potential to analyze students' previous learning histories to identify weaknesses and offer courses best suited for an improved personalized learning experience [4,5]. At the same time, the use of AI can reduce the time needed for routine administrative tasks, allowing teachers in higher education to focus more on teaching and research [6].…”

Section: Introductionmentioning

confidence: 99%

Artificial Intelligence and Machine Learning Approaches in Digital Education: A Systematic Revision

2022

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The use of artificial intelligence and machine learning techniques across all disciplines has exploded in the past few years, with the ever-growing size of data and the changing needs of higher education, such as digital education. Similarly, online educational information systems have a huge amount of data related to students in digital education. This educational data can be used with artificial intelligence and machine learning techniques to improve digital education. This study makes two main contributions. First, the study follows a repeatable and objective process of exploring the literature. Second, the study outlines and explains the literature’s themes related to the use of AI-based algorithms in digital education. The study findings present six themes related to the use of machines in digital education. The synthesized evidence in this study suggests that machine learning and deep learning algorithms are used in several themes of digital learning. These themes include using intelligent tutors, dropout predictions, performance predictions, adaptive and predictive learning and learning styles, analytics and group-based learning, and automation. artificial neural network and support vector machine algorithms appear to be utilized among all the identified themes, followed by random forest, decision tree, naive Bayes, and logistic regression algorithms.

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Section: Introductionmentioning

confidence: 99%

Artificial Intelligence and Machine Learning Approaches in Digital Education: A Systematic Revision

2022

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“…Although the studies classified in this group by this SLR also showed many approaches, all of the research collected was related to the possibility of providing individualized education through AI solutions, which makes this kind of investigation a specific topic of research. Adaptative systems for the personalization of the learning process have been considered important to all educational levels, but especially to distance education due to its heterogeneity (Maghsudi et al, 2021). For developing countries like Brazil, which still have large socioeconomic disparities, personalized education has the potential to improve the learning environment.…”

Section: Discussionmentioning

confidence: 99%

Artificial Intelligence in Distance Education: A Systematic Literature Review of Brazilian Studies

Durso

Arruda

2022

PEC

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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. Keywords: artificial intelligence, distance education, educational technology, systematic literature review

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“…The new paradigm influences the quality of education based on the characteristics and expectations of each student, such as personality, talent, and individual goals and backgrounds. Continuing education promotes the educational process, as well as help student to acquire new skills and competencies important for the future (Maghsudi et al, 2021). Personalised learning systems, automated assessment systems, facial recognition systems, chatbots (social networking sites) and predictive analytics tools that run on machine learning systems and algorithms are increasingly adopted in educational establishments to ensure effective teaching.…”

Section: Aied For Building Personalised Learning Pathways Acquiring K...mentioning

confidence: 99%

Artificial Intelligence in Education: AIEd for Personalised Learning Pathways

Tapalova

Zhiyenbayeva

2022

EJEL

175

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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.

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Personalized Education in the Artificial Intelligence Era: What to Expect Next

Cited by 132 publications

References 27 publications

Artificial Intelligence and Machine Learning Approaches in Digital Education: A Systematic Revision

Artificial Intelligence and Machine Learning Approaches in Digital Education: A Systematic Revision

Artificial Intelligence in Distance Education: A Systematic Literature Review of Brazilian Studies

Artificial Intelligence in Education: AIEd for Personalised Learning Pathways

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