Abstract—Processing human facial expressions is a computer vision challenge in a mobile technology environment. On the other hand, facial expression is an effective tool in behavioral studies on learning environment. Since, mobile technologies possess educating potential for today’s generation, the introduction of behavior as a consideration for mobile user opens up many opportunities for the design and development of a mobile learning system that can cater personalized learning. This undertaking was concerned with the enhancement of learners’ learning engagement and the enrichment of learners’ benefits. The mobile learning system approximates the learners’ facial expressions. The facial expressions will be used to identify the learning moods that will then be used to match the appropriate learning materials and activities of the learners. These steps are done to achieve optimal experience in learning. Approximation of learners’ facial expressions, learning moods, and matching of learning materials and activities to the learners are done through the use of intelligent computing techniques. In order for the stated endeavors to be achieved this undertaking considered three (3) stages of actions. Stage one focused on identifying the requirements needed to design, develop and assess the proposed facial expression driven mobile learning system. The second stage focused on the actual design and development of a prototype for the proposed facial expression driven mobile learning system and the third stage focused on the assessment of the prototype of the proposed facial expression driven mobile learning system. Assessment was done by pilot testing the mobile learning system prototype to a student sample from the researchers’ locality. Index Terms—Mobile learning, facial expression recognition, attention state, learning styles. I. INTRODUCTION Modern human civilization is the product of education; and today, knowledge is recognized as an important asset. To improve knowledge, the process of learning plays an important role. Thus, improving the process of learning is important because of the need of people for more knowledge. Content delivery, assessment and feedback comprise the learning process. This can be confirmed by the traditional education process. An improvement to the traditional education is the use of Computer-Assisted Learning, where the computer is utilized as a tool to deliver the content and assessment. Further, researches on the education process have paved way to mobile learning as an improvement. It is known that mobile earning is doing the learning process at one’s own time and pace. This has broadened the recipients of education such as working individuals, professionals, Manuscript received June 4, 2013; revised August 7, 2013. Jeffrey S. Ingosan, Thelma D. Palaoag, and Josephine S. Dela Cruz are with the University of the Cordilleras, Philippines (e-mail: jeff_ffej2002@yahoo.com, tpalaoag@gmail.com, delacruzpen@gmail.com). distant students, and physically incapacitated individuals. However, these educational technologies are unsuccessful due to limited contact between the teacher and students, diversity of platform, and unsatisfactory learning content. There are several approaches to achieve optimal learning experience. First, regulate the environment that controls the flow of learning that is used to present the learning content. Computer-Based learning, Computer-Assisted learning and eLearning could be some of the terms used to describe the environment. Second, regulate the learning content; and lastly, regulate the process to which these contents can be combined [1]. Facial expressions play an important role in human interactions and non-verbal communication. Classifying the facial expressions could be used as an effective tool in behavioural studies. The use of technology in the delivery of knowledge to learners is seen on institutions around the world. Indeed, the use of eLearning is present both inside and outside the classroom. With the advancement of technology, mobile learning became a trend where one can learn anywhere and anytime through mobile devices. Even formal and informal learning as part of lifelong learning are taking advantage of what technology can offer. Unfortunately, electronic learning tools are not able to recognize if students are engaged and attentive to the lesson unlike actual teachers in a traditional classroom setting. Therefore, it would be an innovation if these electronic learning tools are able to approximate the level of engagement and attention of learners through the use of facial expression recognition, attention state recognition and fuzzy logic. This is to enable the electronic learning tool to use the appropriate learning materials and activities based on the level of engagement and attention of the learner. Further, most of the e-learning systems today are adaptive to the learning styles or preferences of learners that it would be necessary to consider this in the design and development of electronic learning tools. A. Statement of the Problems This undertaking tried to enhance the learning engagement of learners by the use of the facial expression driven mobile learning system. Specifically, the undertaking attempted to address the following: 1) What facial expressions shall be considered to identify the learning moods of learners? 2) What shall be the use of fuzzy logic in the proposed facial expression driven mobile learning systems? 3) What classification of facial expressions, attention states, and learning materials and activities shall be in a facial expression driven mobile learning? 4) What is the difference of the learner’s engagement in a Facial Expression Driven Mobile Learning System Jeffrey S. Ingosan, Thelma D. Palaoag, and Josephine S. Dela Cruz International Journal of e-Education, e-Business, e-Management and e-Learning, Vol. 4, No. 1, February 2014 6 DOI: 10.7763/IJEEEE.2014.V4.291