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Digital literacy is a need for our current society. In Mexico, digital incursion programs are barely implemented, which represents an educational delay compared to other countries that have faced the need to integrate the teaching of digital skills, in a wide range of educational levels. This paper presents a learning environment of Computational Thinking called EasyLogic3D, which proposes a novel integration of emotional recognition, gamification, and a 3D environment. Experiments with 102 children from an Elementary School in Mexico were carried out, where cognitive and technological acceptance tests were performed. Analyzing the Cronbach’s alpha score, we found that students accepted the technology (learning environment). Also, the results showed that the perceived enjoyment when using the learning environment was positive. On the other hand, results show that the learning gained through using the learning environment was comparable to a class session in which the same topics and exercises were presented.

Augmented reality (AR)-based learning environments are argued to foster cognitive and emotional involvement. Immersion has been identified as one of the driving forces that promote learning in technology-based learning environments. This study evaluated the learning effectiveness and immersion appeal of an AR-marker-based learning activity targeted at practicing basic chemistry concepts. Data were collected from a cohort of 124 middle school students in Mexico and analyzed using pretest–posttest comparisons and cluster analysis. The results suggest that students with higher immersive learning profiles achieve better learning outcomes compared with those with lower immersive profiles. The authors acknowledge the eMadrid Network, which is funded by the Madrid Regional Government (Comunidad de Madrid) with grant No. P2018/TCS-4307. This work also received partial support from FEDER/Ministerio de Ciencia, Innovación y Universidades—Agencia Estatal de Investigación through project Smartlet (TIN2017-85179-C3-1-R) and received partial support from MCIN/AEI/10.13039/501100011033. The publication is part of the I+D+i project “H2O Learn” (PID2020-112584RB-C31). We also acknowledge the program PRODEP in Mexico that supported this work (511-6/2019-8474).

We present a Web-based environment for learning Java programming that aims to provide adapted and individualized programming instruction to students by using modern learning technologies as a recommender and mining system, an affect recognizer, a sentiment analyzer, and an authoring tool. All these components interact in real time to provide an educational setting where the student learn to develop Java programs. The recommender system is an E-Learning 3.0 software component that recommends new exercises to a student based on the actions (ratings) of previous learners. The affect recognizer analyze pictures of the student to recognize learning-centered emotions (frustration, boredom, engagement, and excitement) that are used to provide personalized instruction. Sentiment text analysis determines the quality of the programming exercises based on the opinions of the students. The authoring tool is used to create new exercises with no programming work. We conducted two evaluations: one evaluation used the Technology Acceptance Model to assess the impact of our software tool on student behavior. The second evaluation calculated the student’s t-test to assess the learning gain after a student used the tool. The results of the evaluations show the students perceived enjoyment and are willing to use the tool. The study also show that students using the tool have a greater learning gain than those who learn using a traditional method.

Gamification is the use of game design elements to enhance the teaching-learning process and turn a regular, non-game activity into a fun, engaging game. Simultaneously, serious games are proposed as an efficient and enjoyable way of conducting cognitive assessment, as they combine a serious intention with game rules and targets. In this scenario, game engines have emerged as information technologies for serious games and educational games development; however, this development has usually been performed without a guide to identifying game attributes to be present in the game. To address this gap, we present an analysis of the most used game engines to identify game and learning attributes supported for serious and educational games development. Findings from this analysis provide a guide of the most popular game engines that offer the largest support for game attributes, which were also classified by game categories.

Education has become a key component of any society since it is the means by which humanity functions and governs itself. It allows individuals to appropriately integrate into a given community. For this reason, new ways of interaction between students and educational contents are emerging in order to improve the quality of education. In this context, devices such as computers, smartphones, or electronic tablets represent new ways of accessing educational resources which do not limit students to their usage merely inside the classroom since these devices are available anywhere. Nowadays, television has become one of these technological tools able to support the teaching–learning process through documentary films or movies, among others. However, two main issues appear. First, some of these educational contents are not those needed by a professor since information is restricted, and second, the development of TV-based applications requires an integrative approach involving the support of several specialist...

This paper presents a Web 2.0 Learning Environment, for a systematic creation of adaptive and intelligent tutoring systems. Authoring contents is made by a community of users including teachers and students. The tutoring systems adapt the contents according to the best learning style using self-organizing maps (SOMs). The SOM was trained for classifying Felder-Silverman learning styles. The most important advantage of these unsupervised neural networks is that they do not require an external teacher for presenting a training set. The approach was implemented under an authoring tool that allows the production of personalized learning material to be used under collaborative and mobile learning environments. The tutoring systems together with the neural network can also be exported to mobile devices. We present different results to the approach working under the authoring tool.

Knowledge societies also named learning social networks allow interaction and collaboration between individuals (instructors and students), who share their connections under a scheme of learning communities around common learning interest. In this paper, we present an affective tutoring system inside a knowledge society implemented in a learning social network. We have designed a new architecture for an entire system that includes the social network with an educational approach, and a set of intelligent tutoring systems for mathematics learning which analyse and evaluate cognitive and affective aspects of the learners. The intelligent tutoring systems were developed based on different theories, concepts and technologies. In this paper, we present an affective tutoring system embedded in a social network which is used to improve poor student results in ENLACE test (National Assessment of Academic Achievement in Schools in Mexico). We also present results when applying the tutoring system to a group of students.