Research Article Examining the Effectiveness of Using Adaptive AI-Enabled e-Learning during the Pandemic of COVID-19 Sayed S. Younes Umm Al-Qura University, Makkah 21955, Saudi Arabia Correspondence should be addressed to Sayed S. Younes; ssyounes@uqu.edu.sa Received 22 July 2021; Revised 19 August 2021; Accepted 27 August 2021; Published 17 September 2021 Academic Editor: Fazlullah Khan Copyright © 2021 Sayed S. Younes. is is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. is study aimed to identify the effect of using adaptive AI-enabled e-learning on developing digital content creative design skills among postgraduate students. e research tools included an achievement test and an observation checklist for rating the practical performance. Research results concluded that, regardless of learning styles, the proposed adaptive e-learning environment had a positive effect on developing both cognitive achievement and practical performance of digital content creative design skills. e results also indicated that there is a significant difference at the 0.01 level between the mean scores of the first experimental group’s students using the global learning style-based adaptive e-learning environment and the second experimental group’s students using the sequential learning style-based adaptive AI-enabled e-learning environment in the achievement test and observation checklist after measurement of digital content creative design skills in favor of the second experimental group’s students. e study provided a number of suggestions and recommendations for making the utmost use of various design layouts of adaptive AI- enabled e-learning environments in developing different cognitive and performance aspects of learning as well as taking full advantage of digital content creative design skills mastery in producing a plethora of advanced electronic educational applications in the foreseeable future. 1. Introduction Adaptive AI-enabled e-learning is a relatively recent educational term fundamentally based on analyzing each learner’s learning style and converting it into a unique model taking into account his cognitive level, needs, and interests in addition to identifying his requirements and preferred delivery modes for educational content and activities so that they can be transformed into an adaption model to master required knowledge and skills in a flexible adaptive way facilitating the learning process. In other words, adaptive AI-enabled e-learning is a set of techniques oriented to offer online students a personal and unique experience with the ultimate goal of maxi- mizing their performance [1]. Adaptive AI-enabled e-learning is widely seen as a modern educational approach in which knowledge and skills are presented according to students’ various learning styles employing special systems that have the ability to enhance learning via taking into account learners’ different features and characteristics [2]. Adaptive AI-enabled e-learning allows the learner to proceed in his learning at his own according to his characteristics and learning styles. In fact, information presentation methods and sequence differ from one student to another in terms of font size and color, pre- sentation modes of accompanying visual elements, whether adjacent, sequential or simultaneous, and audi- torystimuli,aswellasthelearningobjectsthatcanbeused to support the learning process, through adapting edu- cational materials presentation to reach satisfactory re- sults, thus enabling the learner to solve the problems he faces via understanding and recall [3]. For this to occur, an individual adaptive system must be provided drawing up an educational plan for each learner based on his peculiar needs and characteristics. Also, the designer should formulate a model for the learning envi- ronment which requires an atmosphere full of various and Hindawi Journal of Healthcare Engineering Volume 2021, Article ID 3928326, 14 pages https://doi.org/10.1155/2021/3928326