Artificial Intelligence and Big Data: The Advent of New Pedagogy in the Adaptive E-Learning System in the Higher Educational Institutions of Saudi Arabia

Abstract

The operations of many industries, such as banking, insurance, energy, healthcare, and retail, have been improved and transformed by the application of artificial intelligence. The education sector is the particular one which has more potential for artificial intelligence and its applications. Universities and colleges are currently facing a number of challenges, including high rates of dropouts and student disengagement in their classes, as well as the failure of traditional learning techniques in the face of ongoing outbreaks. Major issues in the educational sector can be resolved by the proper application of artificial intelligence and big data, which can facilitate learner-centred approaches as per the needs of today’s era. This can be better described as a personalised learning approach, in which the needs of each and every student can be considered and education can be provided uniquely for them. In this way, the educator can provide a better learning experience according to the needs and ability of the learners/students. Thus, it also assists in enhancing the motivational level of the learners and minimising the dropout rates of the students. The main purpose of the study is to examine the role of artificial intelligence and big data in the adaption of the E-learning system for imparting better education facilities to the students of various colleges and universities situated in Saudi Arabia. The sample dataset for this study was collected through a purposive sampling technique from the 290 students enrolled in numerous higher educational institutions. The collected data were analysed using SPSS and SmartPLS 3 software. The findings of this study reveal that AI and big data assist educators and students as well to run the teaching and learning process smoothly even in the period of an ongoing pandemic at the higher levels of the education system. It also explores the educational inferences of transpiring technologies in the ways of students’ “learning and institutions” teaching and their adaption. In recent eras, technological evolution and an increase in the adoption of latest technologies in the field of higher education have been scouted to forecast the essence of higher education globally in the near future, where AI will be the gist for universities. This study reveals some issues faced by higher educational institutions and students related to the adaptation of these technologies for learning, teaching, administration, and student support. The implications of the present study will be helpful for students and teachers to access educational resources effectively and for educational institutions to improve the efficiency and personalization of learning tasks. Furthermore, it will allow students to get more time with their respective teachers.

Students’ Perception towards New Face of Education during This Unprecedented Phase of COVID-19 Outbreak: An Empirical Study of Higher Educational Institutions in Saudi Arabia

“…The researchers collected primary data from 294 sample students enrolled in various universities and colleges located in the KSA [ 35 ]. Therefore, we can say that the sample size was adequate and also representative of the population for the current study [ 36 ].…”

EFL Learning and Vision 2030 in Saudi Arabia: A Critical Perspective

“…The third factor is the insufficient exposure to EFL usage. Outside the class, the Saudi students find fewer occasions to communicate in English for the convenience of using Arabic with those who are not competent in EFL, be it family members, neighbors, friends, and others (Khan, 2011). There are rare real situations that require the knowledge and usage of EFL (Alharbi, 2015).…”

“…With the sample of 150 Saudi citizens, the study has established that SV2030 is a significant political intervention in EFL learning as it generates an instrumental motivation to the participants. Motivation is a key factor in the Saudi context for its link with achievement, learning, and competence in English (Al-Khairy, 2013;Alrabai, 2014b;Khan, 2011). Most Saudi learners are unmotivated, and their proficiency in English is low even after graduation (Alhawsawi, 2013;Al-Johani, 2009;Fareh, 2010;Khan, 2011;Rajab, 2013).…”

“…Motivation is a key factor in the Saudi context for its link with achievement, learning, and competence in English (Al-Khairy, 2013;Alrabai, 2014b;Khan, 2011). Most Saudi learners are unmotivated, and their proficiency in English is low even after graduation (Alhawsawi, 2013;Al-Johani, 2009;Fareh, 2010;Khan, 2011;Rajab, 2013). Hence, Al- Zahrani & Rajab (2017) argues that the current EFL learning condition is inadequate to materialize SV2030 because, in the knowledge economy of the present post-industrial era, the incompetence in EFL learning can fail the Saudi students to adapt to the new competitive scenario of globalization, technology, artificial intelligence, and international workforce.…”

Design of An Adaptive E-learning Model Based on Artificial Intelligence for Enhancing Online Teaching

“…The problem of the dynamicity and adaptability of distance learning platforms has attracted the interest of researchers in the field, with a focus on the development or use of new approaches for upgrading these platforms. In the literature, there are several approaches to personalize learning paths to learner profiles, including: artificial intelligence, big data, neuroscience, neuropedagogy and robotics, etc [4][5][6][7][8].…”