Artificial Intelligence in Education: A Review

Abstract

The purpose of this study was to assess the impact of Artificial Intelligence (AI) on education. Premised on a narrative and framework for assessing AI identified from a preliminary analysis, the scope of the study was limited to the application and effects of AI in administration, instruction, and learning. A qualitative research approach, leveraging the use of literature review as a research design and approach was used and effectively facilitated the realization of the study purpose. Artificial intelligence is a field of study and the resulting innovations and developments that have culminated in computers, machines, and other artifacts having human-like intelligence characterized by cognitive abilities, learning, adaptability, and decision-making capabilities. The study ascertained that AI has extensively been adopted and used in education, particularly by education institutions, in different forms. AI initially took the form of computer and computer related technologies, transitioning to web-based and online intelligent education systems, and ultimately with the use of embedded computer systems, together with other technologies, the use of humanoid robots and web-based chatbots to perform instructors' duties and functions independently or with instructors. Using these platforms, instructors have been able to perform different administrative functions, such as reviewing and grading students' assignments more effectively and efficiently, and achieve higher quality in their teaching activities. On the other hand, because the systems leverage machine learning and adaptability, curriculum and content has been customized and personalized in line with students' needs, which has fostered uptake and retention, thereby improving learners experience and overall quality of learning.

Challenges and Future Directions of Big Data and Artificial Intelligence in Education

“…A growing body of literature has attempted to uncover the value of big data at different education levels, from preschool to higher education (Chen N.-S. et al, 2020). Several journal articles and book chapters have presented retrospective descriptions and the latest advances in the rapidly expanding research area from different angles, including systematic literature review (Zawacki-Richter et al, 2019;Quadir et al, 2020), bibliometric study (Hinojo-Lucena et al, 2019), qualitative analysis (Malik et al, 2019;Chen L. et al, 2020), and social network analysis (Goksel and Bozkurt, 2019). More details can be found in the previously mentioned reviews.…”

The Role of Artificial Intelligence in Teacher Professional Development

“…The purpose behind this paper [25] was to assess the impact of Artificial Intelligence (AI) on training. Starting on an account and structure for evaluating AI identified from a fundamental examination, the extent of the investigation was restricted to the application and impacts of AI in organization, guidance, and learning.…”

“…Papers in Web of Science and Google Scholar in the last ten year with key words ``AI'' and `Education''[25].…”

An Integrated Approach to Air Passenger Index Prediction: Mutual Information Principle and Support Vector Regression (MI-SVR) Blended Model

“…Examples of shallow ML models are the support vector machine (SVM) invented by Cortes and Vapnik [2] in 1995, and neural networks (NN). Numerous shallow ML models have been deployed in many research fields, including speech and natural language processing, computer vision, and public opinion mining [3][4][5][6][7]. The linear and nonlinear shallow models have gained impressive results in regression and prediction studies, including the prediction of airport passenger throughput with high accuracy [8][9][10].…”