Limited studies have quantitatively summarized the effect of personalized learning systems on learning achievement. To address this research gap, this study conducts a systematic review and a meta-analysis of personalized learning systems, where 19 studies (N = 3822) were included. The obtained results revealed that personalized learning has an overall medium positive effect (g = 0.45) on learning achievement. They further revealed that personalized learning systems based on Prompts & feedbacks and Diagnosis & suggestions do not significantly impact learning achievement. Finally, the results revealed that educational level, subject domain and continent might impact the effect of personalized learning systems on learning achievement. The findings of this study can contribute to the literature by explaining how the effect of personalized learning systems might vary depending on different moderating variables.

Several organizations urged to assess the readiness level of each country to the digital transformation, hence better harness its opportunities in education. Motivated by this, this study analyzes the latest Chinese curriculum standards to investigate the readiness level of China to adopt technology in education. Specifically, 16 curriculum standard documents were analyzed. The obtained results revealed that China is taking major steps in education reformation, where the use of traditional and emerging technologies is emphasized in almost all curriculum standards. Particularly, traditional technologies were mentioned more frequently to cater to the needs of students on a national level. Additionally, it is seen that the use of emerging technologies in curriculum standards where mentioned depending on the curriculum feature. For instance, the use of virtual reality (VR) and augmented reality (AR) where emphasized in science curricula, where sensors and Internet of Things (IoT) where emphasized in physics curriculum. These findings contribute to a better understanding of how to promote the development of digital education from the perspective of curriculum standards.

Blockchain is becoming a core technology in all application domains as it brings several advantages, such as immutability, transparency, high availability, strong data consistency, and interoperability. Despite these advantages, blockchain systems still have several concerns that might significantly reduce their effectiveness, including motivational, human concerns and miners’ involvement and participation. Gamification, on the other hand, was proposed as a solution for these concerns, among others. However, little is known in the literature on the use of gamification for blockchain systems, calling for more investigation in this regard. Therefore, this study conducts a systematic literature review to investigate why and how gamification is used in blockchain systems. Specifically, 41 studies were included and analyzed in this systematic review. The obtained results highlighted that gamification is integrated into blockchain systems to achieve different purposes, including motivating users/miners and increasing data validation and trust. Additionally, the findings revealed that Ethereum is the most used blockchain platform, where points and challenges are the most used game elements in blockchain systems. Furthermore, when using gamification as an incentive mechanic in blockchain, there is no difference in the effect of the consensus algorithm on miners’ motivation. The findings of this study provide insights into the ways of integrating gamification to enhance blockchain systems, as well as reveal future research directions to consider before deploying the next generation of gamified blockchain systems.

The International Conference on Advanced Learning Technologies (ICALT) is an annual conference organized by the IEEE Computer Society and IEEE Technical Community on Learning Technology. It aims to bring together people who are working on the design, development, use, and evaluation of technologies that will be the foundation of the next generation of e-learning systems and technology-enhanced learning environments. After its kick-off as IWALT in Palmerston North, New Zealand (2000), ICALT has been held in Madison, USA (2001), Kazan, Russia (2002), Athens, Greece (2003), Joensuu, Finland (2004), Kaohsiung, Taiwan (2005), Kerkade, The Netherlands (2006), Niigata, Japan (2007), Santander, Spain (2008), Riga, Latvia (2009), Sousse, Tunisia (2010), Athens, Georgia, USA (2011), Rome, Italy (2012), Beijing, China (2013), Athens, Greece (2014), Hualien, Taiwan (2015), Austin, USA (2016), Timisoara, Romania (2017), Mumbai, India (2018), Maceió, Brazil (2019), Tartu, Estonia (2020, Online), and Virtual (2023, Online) due to the COVID-19 pandemic, Bucharest, Romania (2022, Hybrid). The 23nd IEEE International Conference on Advanced Learning Technologies (ICALT 2023) is organized by IEEE TCLT and held in Orem, Utah, United States, in a hybrid model due to the pandemic.

Various meta-analysis studies were conducted to investigate the effects of Intelligent Tutoring Systems (ITSs). However, no study, to the best of our knowledge, examined ITSs in social experiments in real and natural learning contexts (not in lab experiment or specific research experiment) to reveal their true effects. To cover this gap, this study conducts a meta-analysis of ITSs examined in social experiments, where 14 studies ($N=3496$) were finally included and analyzed. The obtained results revealed that ITSs have an overall small positive effect ($g=0.36$). They further revealed that ITSs have a better positive effect on knowledge (medium effect) compared to skills (small effect), as a learning outcome. The results also revealed that ITSs have a better positive effect (huge) when used for language knowledge learning compared to other domain subjects. Finally, ITSs have better positive effect (large) when used in primary education and for less than one year. The findings of this study can contribute to the literature by explaining how the effect of ITSs might vary when examined in real educational contexts, i.e., in the “field”.

Although several studies suggested considering gender in online learning, the literature about how male and female students would behave is fragmented. Little attention has been paid to the effect of gender on online learning behavioural patterns. This study aimed at investigating the roles of gender in online learning behaviours by analyzing the gender-related differences of students’ online learning behavioural patterns. We used the case study approach with descriptive statistical analysis, lag sequential analysis, and temporal log data analysis to investigate gender-related differences in students’ online learning behaviours. The results indicated no significant difference in the counts of occurrence of online single learning behaviours between female and male students. However, differences were observed in online learning behaviour patterns and how the online learning activities were performed over time. Females were more active in learning behaviours associated with achievement reports and peer list viewing. They tended to view their achievement reports before starting the main course learning activities, indicating that female students might be achievement-oriented. The findings provide further insights from a temporal perspective about how gender is associated with online learning. Implications on designing personalized online learning interventions based on considering gender-related differences are also discussed.

The growing adoption of learning analytics (LA) approaches and data mining (DM) techniques using educational gamification data sets is reflected in increased publications on this topic. However, with different gamified contexts and a variety of LA methods available, no comprehensive review summarized the obtained findings. Therefore, this research aims to identify studies’ characteristics, objectives, and methods used in gamification learning analytics (GaLA) research. To identify these, this study comprehensively reviewed the literature of 24 studies selected from an initial pool of 221 search results. The findings show that GaLA methods can be categorized into: visualization, data mining, social network analysis (SNA), statistics, and correlations. In conclusion, GaLA is defined as a data-driven approach using various methods of data analysis and mining techniques in gamified contexts for collecting, analyzing, and reporting data to assess or enhance the gameful experience, understand student behaviour, and improve learning outcomes.

While massive research has been conducted to see how remote learning and teaching is conduct during the COVID-19 pandemic, less focus has been paid on remote special education for students with disabilities. Therefore, it is still not clear how those students learned and what types of challenges they faced. To fill this gap, this study first collected data from the literature via a systematic literature review, and from both 51 teachers and 21 students with disabilities who were involved in this remote teaching and learning experiences via surveys. It then conducted bibliometric, content and thematic analysis to draw conclusions. The obtained findings highlighted that online and offline remote teaching methods from home were applied. Additionally, different learning assessment methods, such as mini-projects and simple quizzes were adopted by teachers to assess the gained knowledge of students remotely, but none of these methods relied on emerging technologies, such as big data and learning analytics. Finally, parents were a core actor to maintain remote learning from home for students with disabilities.

Despite several studies highlighted the importance of considering gender in online learning, the current literature about how male and female students would behave is still fragmented. Additionally, little attention has been paid to investigating the impact of gender on online learning behavioral patterns. This study applies lag sequential analysis (LSA) to investigate gender-related difference in the behavioral patterns of 116 students in an online course for six weeks. The obtained results indicated that overall there is no significant difference in the frequency of online learning behaviors between female and male students. However, the LSA showed that males and females demonstrated different transitional patterns in their online learning behaviors. Female behaviors were more coherently linked to each other. In contrast, some of the male behaviors were relatively isolated without significant antecedents and consequences, calling for learning supports. Also, females tended to view their achievement reports before starting the main course activities, showing that female students were more achievement-oriented. The findings provide explanations about how gender affects online learning and implications on how to design personalized online learning interventions based on considering gender-related differences.

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 tutorial aims to help beginner participants start developing their own web-based games using game engines. Particularly, this tutorial uses "Construct2" game engine to help participants develop a mini game from scratch. It then shows them how to export and deploy the files of the game (developed using Construct2) on an online server. This allows other users to access the game from their computers using their web browsers and play it. In this tutorial, the instructor will apply the hands-on learning strategy where he develops the game on his laptop with the help of a projector, so participants can see the programming process. The participants then start doing the programming as well on their computers. The instructor can also go between the participants when needed and help them in case there any bugs.

Designing an educational game can be a difficult task for individuals who do not have appropriate background towards game developments. Several game genres exist in the literature which can make beginners confused about which are the appropriate or required game elements and functionalities for a particular game genre. At the same time, many studies highlighted the effectiveness of mind-mapping techniques in enhancing learning and thinking task. Therefore, this study deploys the powerful graphical representation of Unified Modeling Language (UML) class diagram to present a mind-mapping guide for people who are developing educational role-playing games. A total of 1 13 students used the developed mind-mapping guide in a public Tunisian University, and the obtained results showed that the guide can: (1) significantly enhance beginner students’ level of knowledge regarding developing role-playing educational games; and, (2) promote the creative thinking when it comes to imagining educational role-playing game scenarios. Also, these results showed that students have a favorable attitude towards using the mind-mapping guide to learn and design their games.

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.

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.

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.