ARTICLE IN PRESS JID: CAEE [m3Gsc;November 3, 2017;21:46] Computers and Electrical Engineering 000 (2017) 1–14 Contents lists available at ScienceDirect Computers and Electrical Engineering journal homepage: www.elsevier.com/locate/compeleceng An immersive learning model using evolutionary learning  Deblina Bhattacharjee a , Anand Paul a,∗ , Jeong Hong Kim a , P. Karthigaikumar b a Department of Computer Science and Engineering, Kyungpook National University, Daegu, South Korea b Department of Electronics and Telecommunication Engineering, Karpagam College of Engineering, Coimbatore, TN, India a r t i c l e i n f o Article history: Received 28 February 2017 Revised 21 August 2017 Accepted 22 August 2017 Available online xxx Keywords: m-learning Immersive virtual reality Immersive learning Education Personalized learning Evolutionary learning Reinforcement learning a b s t r a c t In this article, we have proposed an educational model using virtual reality on a mobile platform by personalizing the simulated environments as per user actions. We have also proposed an evolutionary learning algorithm based on which the user learning path is de- signed and the corresponding simulated learning environment is modified. The main ob- jective of this study is to create a personalized learning path for each student as per their calibre and make the learning immersive and retainable using virtual reality. Our proposed model emulates the innate natural learning process in humans and uses that to customize the virtual simulations of the lessons by applying the evolutionary learning technique. A quasi-experimental study is conducted by taking different case studies to establish the ef- fectiveness of our learning model. The results show that our learning model is immersive and gives long term retention while enhancing creativity through reinforced customization of the simulations. © 2017 Elsevier Ltd. All rights reserved. 1. Introduction With the prevalent model of learning, students were found to be bored, disengaged and sometimes not even sure why they were learning about a topic in the first place. Thus, the paradigm of education shifted to incorporate new innova- tive teaching methods, such that classic textbooks turned into e-books, blackboards turned into YouTube videos, new course management and dashboards came into existence to somewhat personalise the user learning process, and lecture hall mono- logues turned into MOOCs (Massive Open Online Courses) while becoming more mobile and accessible as on the go class- rooms. But if we take a closer look at it, the teaching method in schools remained almost the same with no real innovation. Therefore, for an information age appropriate system, an open, customizable, interoperable (through learning objects) and immersive educational resources should be used in a personalized learning environment. This brings the decentralization of learning technologies with simulated learning methods and accessibility on mobile devices, thereby supporting better cus- tomization and use of a plethora of open resources. According to this decentralized learning system, the student can create the contents themselves and engage with education in a way that is meaningful for them. The content creation aspect by the students is inter-twined with the proposed evolutionary learning algorithm that has been realized with virtual environ- ment simulations on mobile platforms. This is done to effectively use the conjunction of different techniques in facilitating self-directed, interest based learning, where problem solving, innovation and creativity drive education (as per Education 3.0 TM model).  Reviews processed and recommended for publication to the Editor-in-Chief by Associate Editor Dr. R. Varatharajan. ∗ Corresponding author. E-mail address: paul.editor@gmail.com (A. Paul). https://doi.org/10.1016/j.compeleceng.2017.08.023 0045-7906/© 2017 Elsevier Ltd. All rights reserved. Please cite this article as: D. Bhattacharjee et al., An immersive learning model using evolutionary learning, Computers and Electrical Engineering (2017), https://doi.org/10.1016/j.compeleceng.2017.08.023