Several research studies have highlighted that the traditional method of identifying dyslexia within learners is time consuming, expensive and might not be effective as some people acquired the skills to hide their disability. Particularly, no tool or method was reported in the Arab region (22 countries) that could help identify dyslexia within Arab learners. Therefore, this paper presents a developed and validated educational game to implicitly identify the level of dyslexia within learners based on their game play traces. The game was played by twenty-six children within a private school for special education with the supervision of experts from a private center for learners with disabilities. The obtained results showed that the accuracy level of identifying learners with dyslexia with the use of the game is high. Additionally, the experts reported a favorable perception and high technology acceptance degree towards the game. The findings of this research could enhance the educational technology field by providing an educational game design for implicit identification of dyslexia level.

Promoting intrinsic motivation in classrooms is the central focus of many researchers. Particularly, several studies found that students' individual differences might affect their level of intrinsic motivation. Since personality is considered as one of the most important indicators of individual differences, this study investigates the effect of personality on students' level of intrinsic motivation in a gamified and self-determined online environment. The obtained results showed that only extraversion, conscientiousness and openness personality traits significantly affect students' level of intrinsic motivation to learn. These findings can be considered by designers of gamified learning environments to provide more game design elements in order to enhance students' intrinsic motivation based on their personalities.

This research evaluated an annotation recommendation system – GRACE (General Rapid Annotation Clustering Enhancement) – which gives suggestions of what annotations might be missing when students were reading the teaching materials. A pilot is done in two computer science classes in a college in Tunisia. The results show that system’s usability is acceptable for students doing online reading activities on GRACE.

While gamification has gained considerable scholarly and practitioner attention, less concern is paid regarding individual differences in gamified learning environments. Personality in particular is considered as the source of individual differences even within students. Therefore, this study investigates how personality can affect students' perceived preferences for eight game elements in a gamified Modular Object-Oriented Dynamic Learning Environment (Moodle). One hundred and five students, from a public Tunisian university, used this gamified Moodle during two years to learn "Object Oriented Design Methodology", "Basic Software" and "Information Monitoring Methodology" courses. The obtained results showed that only extraversion, conscientiousness and openness personality traits may affect students' perceived preferences for particular game elements. These findings can be exploited by researchers and practitioners to design personalized and gamified learning environments based on personality.

Gamification in education is gaining an increasing attention, since it enhances the learner's engagement and motivation. While carrying a big promise, prior research offers little guidance regarding how learners with different personalities may react to game elements in a gamified learning environment. Therefore, this study investigates the relationship between the learner's personality to be distinguished on an introvert/extrovert dimension and the attitude of preferring to use game elements. In this context, a gamified online Moodle Learning Management System was developed where fifty seven learners used it to learn "Object Oriented Design Methodology" course. These learners then answered two questionnaires about preferences on game elements and personality. Data gathered from the instruments was analyzed using the statistical ChiSquare test. The obtained results highlighted that the learner's personality can affect the attitude of preferring to use a particular game element. These findings can be exploited by researchers and practitioners to provide personalized and gamified learning experiences based on personality. They also can be used by designers by providing design guidelines for targeting specific learners based on personality.

Social networking services specifically Facebook has recently shown exponential growth in its number of users, which attracted researchers to investigate its educational potentials. While various studies have investigated learners' attitudes towards incorporating Facebook in classrooms, limited attention has been paid to examine learners' level of knowledge and motivation involved in online learning using Facebook. Therefore, this study proposes a new designed Facebook learning tool with various applied design strategies to enhance the learning process in classrooms. Thirty five learners, from a public University in Tunisia, participated in a quasi-experiment to validate this designed Facebook learning tool. The findings highlight that this tool has had a positive impact on the learners' level of knowledge regarding learning "game development" course. Besides, learners found this tool useful, interesting and safe, resulting in better engagement and a competitive attitude.

Various research work have highlighted the importance of modeling learner's personality to provide a personalized computer based learning. In particular, questionnaire is the most used method to model personality which can be long and not motivating. This makes learners unwilling to take it. Therefore, this paper refers to Learning Analytics (LA) to implicitly model learners' personalities based on their traces generated during the learning-playing process. In this context, an LA system and an educational game were developed. Forty five participants (34 learners and 11 teachers) participated in an experiment to evaluate the accuracy level of the learners' modeling results and the teachers' satisfaction degree towards this LA system. The obtained results highlighted that the LA system has a high level of accuracy and a "good" agreement degree compared to the questionnaire paper. Besides, the teachers found the LA system easy to use, useful and they were willing to use it in the future.

Integrating e-learning personalization systems in cloud computing environment is a relatively recent trend in technology enhanced learning. Cloud computing is a new model that allows users to access applications through Internet. It is characterized by several advantages such as reducing the cost of development, high availability of information, scalability and so on. In literature, several works have taken into consideration these advantages for applying this model in learning systems. However, very little research is available that focuses on selecting and assembling the best personalization parameters according to the teachers' preferences. This paper proposes a solution based on the cloud for the composition of personalization parameters with minimal cost. Through this solution, teachers can easily access these parameters from anywhere and anytime.

Recently, educational games are gaining increasing attention from researchers and practitioners in the learning field. This is because they are fun, motivating and immersive. However, designing educational games can be difficult for people who do not have appropriate background towards game development. This is further complicated by the fact that there are many genres of games (role playing, action, puzzle, etc.) and each genre has its own game elements and functionalities. This makes the game design process confusing, especially for beginners. This paper deploys the powerful graphical representation of Unified Modeling Language class diagram to present a generic model of educational role playing games. This model uses knowledge representation (game elements, functionalities and features) to support designing educational role playing games. Fifty eight game developers participated in evaluating the model and they have revealed its high perceived usefulness while designing educational role playing games. In addition, they reported that they were willing to use this model again in the future in their context.

Using computer games that support learning and teaching can offer various benefits to learners. The use of learning games can consume the attention of learners and increase their motivation and engagement which can then lead to stimulate learning. In particular, the use of learning versions of existing computer games has been found to have success in improving learners' motivation, increasing their desire to learn and making learning more enjoyable. However, most of the research to date on educational games, in particular learning versions of existing computer games, focused only on learner with typical development. Rather less is known about the designing of educational games for learners with special needs. For that, this paper presents a new educational game for deaf learners, called learning version of memory match game for deaf learners. This learning game was specially designed to foster vocabulary acquisition for deaf learners, to engage them, to keep them motivated and to render the learning experience with more fun.

Many researchers proved the efficiency of using educational games in the learning field. Thanks to the new wave of mobile technology, these games became even possible to run on mobile devices. On the other hand, various learners found learning the "computer architecture" subject dry and hard using the tradition way in classrooms. This paper presents a new mobile educational game which aims to teach the "computer architecture" subject. In particular, the different learning activities implemented within this game allow learners to learn this subject in a fun and interesting way.

The learner model is a key component of any adaptive E-Learning system, including educational games, as it stores the information about the learner, which can then be used to provide personalized experience. Recently, there has been growing interest in creating learner models using educational games. This is due to the limitations of traditional E-Learning systems, since the learner interaction with the computer is rather restricted in such systems. Educational games, on the other hand, not only stimulate learners by increasing their motivation and engagement, but also facilitate a lot of learner interaction that could be observed to create learner models. This paper presents a survey of the field of learner modelling using educational games. In particular, it describes the main methods of learner modelling. This paper also lists several educational games that are suitable for experimentation. Compiling this information can be important to the researchers and developers working in this field, especially to new researchers.

Learning vocabulary is a very important part of learning a new language. It is vitally important for beginners and children to learn the keywords needed to understand what they hear and read, and to express their own ideas. Despite this importance, vocabulary acquisition stills the hardest part of the language and faces the problem of low motivation of learners. One of the effective ways of raising motivation and increase learners' desire to learn is to use learning games. This paper describes a learning version of memory match game specifically designed for second language acquisition. The objective of this learning game is to render the learning experience with more fun, to engage learners and to keep them motivated.

Recently, many works have investigated the identification of learner's working memory capacity (WMC) from his/her behavior in learning systems. These works used a mechanism, called dichotomic node network, able to create representation of the learner's WMC taking into account different theories from the literature. However, this mechanism could only provide a binary representation of learner's WMC (High or Low), whereas the WMC is estimated by 7 (plus or minus two) items. This paper presents an alternative based on fuzzy logic for precisely estimate the WMC of the learner while using learning system or playing educational games. The proposed approach can improve the accuracy of learner model and then enable the fine grained recommendations that positively affect the learners' learning.

In recent years, there has been a growing interest in computer learning games. This is due to the belief that games can offer various learning benefits to learners. Specially, learning games which focus on programming language are needed today given that programming is seen as an important subject for learners. So, developing games which enhance learners' motivation for the programming subject is the main issue of this work. This paper describes a learning game for higher education. This new game is called Instruction right place Game and it allows learners to benefit from the drag and drop technology to construct a program in an amusing way.

Teachers and course authors need to apply various instructional strategies in order to personalize their courses. It is not a trivial task and the time, the efforts and the learning objects needed for preparing personalized learning scenarios depend on the personalization strategy to be applied. This paper presents an approach for selecting appropriate personalization strategies according to the feasibility of generating personalized learning scenarios with minimal burden on the author. Two metrics are proposed for putting in order and selecting useful personalization strategies. The calculation of these metrics is automated based on the analyses of the Learning Object Metadata (LOM) standard according to the semantic relations between data elements and learners' characteristics.

When there are many possible personalization strategies, it is important to select the most appropriate of them according to the specificities of the course. In this context, rises the contribution of this work, which is the analysis of learning objects as well as the metadata describing them for the selection of appropriate personalization strategy.

Several researches have demonstrated the effectiveness of graphical languages in knowledge representation and the numerous advantages of using graphs in the context of learning. On the other hand, many researches in the e-learning domain have focused on the personalization of learning materials by using adaptive educational hypermedia. However, most adaptive educational hypermedia systems do not benefit from the power of graphics because they do not use an expressive graphical language for presenting educational hypermedia to the learners. Our approach fills the existing gap between current educational hypermedia languages with the learnerspsila requirement of a standard graphical language for the visualization of adaptive hypermedia and the navigation through it. In this way, new possibilities are added to adaptive hypermedia expressiveness such as the presentation of the relations between concepts and the organization of these concepts in compartment allowing the arrangement of their semantics.

In this paper, we present an approach for the personalization of learning scenarios integrating different personalization parameters. In addition to "classical" ones such us learner preference, learning style, learner motivation and learner background, we integrate another aspect of personalization which focuses on the pedagogical approach. In fact, the context of learning, as well as the personalized object (contents and activities) and the personalization parameters depends strongly on the pedagogical approach.

This paper addresses the graphical representation of Context-Free Grammars (CFG) written in extended Backus- Naur Form (EBNF), using UML class diagrams. These diagrams can help understand the grammar for users who are not familiar with concepts of EBNF grammars. The additional structure afforded by UML could help to clarify how the derived language is constructed and allows learner to build significance relations between the concepts presented. We propose derivation rules of EBNF grammars into UML class diagrams which will be illustrated over an example of a grammar written in EBNF.