This paper presents an Adaptive Learning (AL) system for teaching Object-Oriented Programming (OOP). The OOP paradigm is one of the foundations for introductory programming education, being one of the ACM (Association for Computing Machinery) Computing Curricula's Programming Languages Fundamentals. However, studies show that students have difficulty associating abstract concepts with real-world analogies. When trying to solve a problem, the difficulty in understanding and applying concepts can hinder using the paradigm. Therefore, it is necessary to create alternatives to assist in teaching Object-Oriented Programming. One solution is to use Adaptive Learning, which aims to adjust the knowledge acquisition process according to the student. Learning Objects (LO), which can be games, quizzes, interactive experiences, videos, and images, among others, can be used to support this method. Thus, this work aims to present a proposal for an approach to teaching OOP using Adaptive Learning. The approach consists of a support system for OOP students, which will support their teaching with a Learning Object recommendation mechanism that is more relevant to the student's learning style. To this end, agents will be used to control the selection of LOs and adjust the profiles. The student's actions will be collected and used as a basis for the recommendation. From the data obtained, constant adjustments will be made to the recommendation of LOs and the student's profile, thus providing more suitable content for their learning. As a result of this study, a functional prototype of the recommendation method was developed in a mobile application. The use of this application will be evaluated quantitatively and qualitatively to validate the solution. After using the application, the evaluation results will provide us with information about the users' perception of the proposal, its recommendation accuracy, and usability. With this, we can build a version that will be used in the classroom and contribute to the student's OOP learning process.

This Research Full Paper presents a pedagogical approach to evaluate a virtual platform for teaching robotics at a distance. The virtual environment was developed using the principles of Collaborative Learning. This virtual platform, called groupware, should facilitate interaction between those involved in the teaching and learning process, whether the student or the teacher. In this research, we will use Educational Robotics as a mediating tool in the teaching and learning process, because it has become a powerful tool that has stimulated the acquisition of knowledge in computing. In the groupware used in this research, Multi-Agent Systems were used to collaborate with teachers in the management of activities. The purpose of this study was to evaluate the functionality and usability of this virtual environment. A qualitative, exploratory research was used and to assess the usability of this virtual environment, the usability evaluation techniques were used with the Syetem Usabily Scale metric, and the technique of evaluation of feelings through EmoCards. Ten computer teachers participated in this research, with training and specializations in the areas of computing. Collaborative Learning was used as a focus for solving the tasks proposed for this research. The results showed that the participants evaluated the groupware with great potential to collaborate in robotics teaching and with content appropriate to the students' initial level of learning. The teachers' perceptions regarding the usability of the evaluated groupware revealed that it is favorable in the teaching of robotics and allowed an analysis of the importance of collaborative learning in the educational environment, directly impacting their ways of conducting learning.

This full research paper presents a systematic mapping of applications of affective intelligent tutor systems in engineering education. These systems employ techniques such as self-questionnaires, voice or facial recognition, system usage tracking, or combinations of these approaches. The data collection occurs through the sensors that measure input from devices, such as microphones, cameras, and body sensors. This paper presents a systematic mapping of affective intelligent tutoring systems in engineering courses and seeks to answer the following questions: Q1. Which engineering courses employ affective intelligent systems?; Q2. What secondary or auxiliary technologies, if any, do the authors use in combination with affective tutoring systems?; Q3. How do these studies perform emotion recognition?; Q4. What emotions do these studies recognize?; Q5. Which evaluation methods do the studies use? The research concentrated on primary sources, such as articles and conference proceedings published between 2010 and 2022 on established scientific databases, including ACM Digital Library, IEEE Xplore, Science Direct, and Springer. We identified 413 potential articles and narrowed the options down to 23 papers that fully matched the inclusion criteria. We contribute to the literature by answering the proposed questions and categorizing the existing papers to find directions for future research.

This complete article of the research category presents proposes the application of Educational Data Mining (EDM) techniques using data generated by a web-based Intel-ligent Tutoring System (ITS) developed for teaching algebra. The aim is to classify students' academic performance, seeking evidence to assist teachers in the decision-making process. To achieve this goal, we utilized the Knowledge Discovery in Databases (KDD) methodology to analyze students' academic data and identify patterns, trends, and relationships that can be used to enhance the teaching and learning process and make informed decisions in the educational context. Practical results revealed that the Random Forest algorithm classified students' academic performance in each evaluation period with an accuracy of approximately 94 %. These findings derived from data analysis can serve as a basis for decision-making, aiding the teaching process for teachers, tutors, and administrators, as well as monitoring academic performance and identifying challenges present in each class. In summary, these results provide a comprehensive guide to the use of EDM techniques in a specific context.

This research paper discusses the impact of teaching and learning technologies on generating extensive data in education. Despite this data, a significant portion remains unanalyzed, creating a gap in utilizing its potential insights. Educational dashboards address this issue by presenting student information and interactions in online learning environments, utilizing Educational Data Mining (EDM) techniques. EDM aims to understand student behavior, enhance teaching processes, identify learning patterns, and personalize content. It aids in performance analysis, helping struggling students and guiding teaching adjustments. The study proposes an educational dashboard for analyzing Intelligent Tutoring System (ITS) data, specifically in algebra teaching. Using decision tree algorithm to extract insights from student interactions. The developed web dashboard organizes and visualizes student performance data, aiding monitoring, decision-making, communication, and transparency. Educational dashboards enhance decision-making, data analysis, and communication, benefiting both students and the educational system's performance.

This full paper of the research category describes the ERPLab as an innovative educational platform that aims to promote inclusivity and diversity in programming and robotics. It provides a unique learning experience, particularly in remote or resource-limited areas, making scientific education more accessible to a broader audience. ERPLab offers students an understanding and integration of scientific knowledge by combining biology, engineering, and programming. ERPLab plays a significant role in educational technology research by exploring new possibilities for remote teaching and providing valuable data and insights to evaluate the effectiveness of this approach. One of the standout features of ERPLab is its use of an automated greenhouse controlled by a 3D printer-produced robotic arm equipped with sensors, and two Wi-Fi cameras, esp32cam, facilitating observation from multiple angles, allowing students to explore new avenues of scientific learning. This system enables students to learn about plant cultivation while developing their programming and technological skills. ERPLab combines advanced technology with natural repellent plants to promote innovative teaching and research methods. The plant selection within the ERPLab includes natural repellents like rosemary (Rosmarinus officinalis), rue (Ruta graveolens), and basil (Ocimum basilicum). These essential programming skills are directly applicable to the rapidly advancing INDUSTRY 4.0. Some preliminary work was carried out in a school environment, and the results of feedback from some students and teachers were promising regarding the proposed approach. For future work, we will carry out qualitative and quantitative research to observe the interest and development of users for the program of the platform in the context of regular classes.

This full research paper presents a systematic literature review on adaptive learning in programming education. Learning how to program is a process that requires the ability to solve problems through logical reasoning. In the field of computer science education, various courses are focused on teaching programming. Research has been conducted to evaluate students' learning processes and the reasons for their dropouts in computer science courses. Students have individualized learning speeds and characteristics. The heterogeneity of student characteristics creates a difficulty in adapting the content taught in class, as it is necessary to generalize the approach in the classroom. To achieve this, approaches have used Adaptive Learning (AL) to adapt content according to the student's profile. Resources such as Learning Objects (LO), which can be games, quizzes, interactive experiences, videos, images, etc., are used to achieve this goal. Different authors have conducted studies on Adaptive Learning using algorithms, Human-Computer Interaction techniques, and other forms to analyze students' learning processes. Therefore, it is necessary to identify how Adaptive Learning has been applied to programming education in the existing literature studies. In addition, to characterize the learning styles and metrics used to evaluate these applied methods. Fifty-three articles from the last ten years related to the research objective were selected using the ACM Library, IEEExplore libraries, and Scopus. From these studies, we verified the main LO recommendation methods that use different approaches, such as Item Response Theory, Case-Based Reasoning - CBR, IEEE LOM, genetic algorithms, among others. As well as the learning styles become used, where Felder and Silverman's learning style stands out. In the analyzed studies, the LO that gained more prominence in the research were videos, both media produced by teachers on a local database and video lessons available on video-sharing sites. Finally, an analysis was made of the impact of these methodologies used in AL on the learning process. Thus, with the results obtained from the systematic literature review, it is possible to verify the current state of research regarding Adaptive Learning in programming education and demonstrate how adapting content for different student profiles is necessary.

This article presents a proposal for an Intelligent Tutoring System (ITS) for teaching Trigonometry in K-12 programs, using the teacher as an active agent in the learning process and employing the assumptions of the Theory of Mediated Learning Experiences (MLE). In the current scenario where Distance Learning (DL) has become a necessity, ITS offer an alternative to individualized study, however, for the construction of knowledge, mediation in learning is often necessary. MLEs offer pedagogical support focused on mediating and addressing learning problems, desirable characteristics for disciplines based on problem solving. Therefore, this research aims to present a proposal for an ITS to support the development of mathematical knowledge in trigonometry problems, inserting the teacher as an active agent in this process, exploring the potential of the MLE for the construction of the ITS. The proposed system, called CURUMIM, also has a Pedagogical Virtual Assistant (PVA) with the function of clearing up doubts arising from the subject, generating a dialogue according to the student’s reciprocity index.

This research-to-practice full paper is elaborated from the next problem, 'Augmented Reality's technology can assist in understanding the contents of Chemistry in a more concise way? The Case Study was conducted in a small-town school. The absence of structures, such as teaching laboratories, limited Internet access, or an insufficient number of computers is common in many small cities such as the one chosen. There is also a lack of teachers trained in pedagogical methods that make the student take an interest in learning. On the other hand, most young people and teachers have cell phones and enjoy recreational activities. So, we combine these various aspects to promote learning in a playful, cooperative way and based on a relevant learning theory. This paper is aimed at analyzing learning supported by Augmented Reality (AR) for Chemistry teaching. It was a quantitative study using Augmented Reality with the intent to check the benefits that AR brings to education. We focused on Organic Reactions because many students have difficulties with this topic and we evaluate that this topic is appropriate for using Augmented Reality. First, a pedagogical approach had been discussed with teachers of the proposed discipline and from that, an app for the Android system was developed, to assist in teaching Organic Compound Reactions, uniting Vygotsky concepts on the Proximal Development Zone. The proposal is integrated to the movement based on learning by design in basic schools, STEM, the system promotes students' abilities to work with technology to understand the teaching of Chemistry. Evaluations were carried out with 54 high school students during the semester, and the results obtained on the technology used identified that 84% of students considered the contents of chemistry relevant. A significant part suggested that the approach using Augmented Reality could be used in teaching other subjects. It was possible to observe the learning with cooperative characteristics highlighting the importance of working with this perspective, uniting attractive technologies that can collaborate effectively for the construction of knowledge in school disciplines.

This complete article of the research category presentes proposes the application of Educational Data Mining (EDM) techniques, based on data generated by a web-based Intelligent Tutor System (ITS), developed for the teaching of algebra, which helps students to develop fundamental knowledge of mathematics, in addition to carrying out a comparative study between the level of difficulty of the proposed algebraic questions. For this, we use the knowledge discovery methodology to perform the following steps from the data: cleaning, integration, selection, transformation, mining, evaluation and presentation of information. The practical results reveal that the proposed architecture can classify the academic performance of students in each evaluation period with an accuracy of around 80%. It was also possible to identify factors related to the resolution of questions, such as the rate of correct answers and the mathematical steps to solve an exercise, classifying the level of difficulty of the questions proposed by the system, acting on the student’s deficiencies, and the system. The results obtained from the data analysis can serve as a basis for decision-making, helping in the teaching process for teachers, tutors and managers to monitor academic performance, enabling the correction of problems and identifying the individual and collective difficulties present in each class. In summary, these results also provide a general roadmap on the performance of using EDM techniques in a given context.

This is a Full Paper on Research-to-Practice that presents the result of the application of a mediation model to the teaching-learning process of kinematic concepts in remote experimentation. Kinematics was proposed for the development of the work, as it deals with fundamental concepts of Physics, which is a science directly related to STEM education. For the execution of the model, a remote access laboratory was designed, implemented, and evaluated. The model was applied to high school Physics students and can be extended to other levels of education. The remotes interactions followed an organization proposed by the mediation model. The research was based on the mediation of Vygotsky and Zone of Proximal Development The system has been tested and evaluated by students and teachers.

This full paper of innovate-to-practice category presents a Multiagent System for recommending learning objects in Virtual Learning Environments (VLE), aiming to improve the customization of instructional guidance on educational content according to the student's profile. The methodology was initially research aimed at identifying the motivators of the students' performance and their weaknesses, adopting a personalized student model based on the level of knowledge, and providing predictive models to monitor the student's progress in the curriculum. This framework provides a distributed architecture, and consists of three layers: 1) Administrative layer; 2) Storage layer; 3) Pedagogical layer. For the recommendation of learning objects, a collaborative filter was used, which constitutes a successful technique in several recommendation applications, seeking similarities in users' habits to predict their future decisions.

This full paper of research category presents a proposal for a smart recommendation model to personalize the provision of teaching materials in Virtual Learning Environments (VLE), to continually learn from student feedback. This research presents a model that is divided into 4 parts: 1) Student model; 2) Domain model; 3) Mining module; and 4) Recommendation module. This research contributes to focus on the development of cognitive skills related to learning styles, aiming to help students understand the strengths and weaknesses of their cognitive and objective - cognitive strategies, with the construction of behavioral patterns generated from the exchange of messages information between the student and mining modules. It is hoped that with the implementation of e-learning models, this proposal can contribute to assist in guiding the teaching and learning process towards mastering a curriculum, with interactive regulations, and the acquisition of the corresponding skills through the discovery of knowledge and automation of the recommendation process. Besides, contributing to self-esteem and, mainly, helps to train professionals better prepared for the job market. Our focus is to describe complex processing of recommendations in e-learning environments in terms of knowledge, not the details of its implementation.

This Research Full Paper presents a proposal for a pedagogical approach to be applied to educational robotics on a virtual distance learning platform, to foster teaching and learning, knowledge sharing and interaction between teachers and students. Recent studies indicate that 21st century students can master different skills and competencies to achieve success in their education, among which we highlight collaborative learning and educational robotics. One of the resources which successfully employ collaborative activities is groupware, which is a virtual collaborative system that supports groups of people with common tasks or objectives and enables the management of group activities. Many research works show that educational robotics has become an important facilitating and motivating tool for students entering Computer-focused courses. Literature has shown that both tools are important for the application of a STEM approach and have led to good results in an educational environment. To analyse the learning perceptions of educational robotics in a collaborative environment, we have developed a pedagogical approach that relies on collaborative learning through a groupware called IGARA, developed on Moodle platform. Activities made available by the virtual environment were developed based on constructivist, interactionist principles, with task contextualization to enhance students' perception. In order to assess the functionality of such an approach, an exploratory study was carried out with a set of 14 students, divided into 3 groups, spatially distant due to Covid-19 pandemic safety measures. Preliminary results were very promising and groupware was well accepted by participants.

This Research Fully presents an approach to reducing the school dropout rate in Computer Technician courses, using robotics as a pedagogical tool. In a school context, the field of computer programming is considered the most important, because it contains concepts that form the basis of computing. However, few people can easily learn programming. Studies show that difficulties in assimilating programming concepts cause discouragement, and consequently lead to school dropout. In the face of this scenario, Educational Robotics has proved to be an important tool in expanding the STEM approach, in addition to presenting itself as a tool to motivate programming learning. With the goal of motivating students to stay in school, and to get a good start in learning programming, an approach called Arduino Baby was developed and employed, which uses Educational Robotics through the Arduino platform. It was structured and carried out in 4 main stages. During the execution, an integrating project was applied, the methodology of which included the creation of student teams, the distribution of bibliographic materials and kits, practice performance, and the exhibition of the developed works. At the end of the research, questionnaires were given, and semi-structured interviews were conducted for participating students, in order to find out the degree of motivation obtained. Results showed to be promising, and that they can be allies in the fight against school dropout.

This full paper aims to present a model of the Pedagogical Agents architecture to assist in activities and tutorial interventions for mastering the resolution of first-degree polynomial equations. With the impact of the educational situation in various parts of the world due to the Covid-19 pandemic and the difficulties identified in the interaction between student and teacher, this research uses a multi-agent approach to improve the architecture of an Intelligent Tutoring System aiming to assist in the context of distance education. Exploratory research in the literature was carried out, aiming at the problem and situation, which implies the process of development of the technological artifact and from the elaboration of a product based on the gaps found. As pedagogical support, Vygotsky's social interaction theory for instructional support is used. The implementation of this proposal will result in the improvement of Tutoring Systems, allowing to guarantee conditions for the teacher and the student to carry out the teaching and learning process flexibly and intelligently, aiming at the construction of knowledge.

Context: This innovative practice full paper presents a methodology to predict at-risk students in the context of a course assisted by an LMS (Learning Management System). LMSs generate large amounts of data about courses and students, which allows schools to make useful insights with the help of computational analytical tools. Most educational institutions claim that the most significant issue in virtual learning is high student dropout rates, and school performance is one of its main factors. Objective: Our study aims to use Machine Learning techniques based on logs from the Modular Object-Oriented Dynamic Learning Environment (Moodle). Those data are used to analyze student behavior and create a model that helps detect students at risk. Method: This paper used institutional data and trace data generated by LMS of a Computing education technical courses, blended and distance learning, at high school. We compared 7 algorithms with models trained at 6%, 20%, 40%, and 60% of the course duration, with the intent of exploring the compromise between early and late detection of at-risk students. Our model has 69% positive classe (failed) and 31% negative class (passed), and the false positives cost is important. Results: The results show 7 created models of predicting. The findings for Random Forest performed the best when predicting a student's performance. Conclusion: Our study provides a student at-risk prediction model using ML techniques on logs in Moodle LMS and may guide future studies and tool development to reduce these high dropout rates.

This Research Full Paper presents a method to select Learning Objects based on students' cognitive profiles, aiming to facilitate the explained content understanding and programming skills improve. STEM approach has favored the programming skills development in Computer Science courses. Due to initial concepts complexity, many students find it difficult to understand this discipline, causing demotivation or course abandonment. We propose a method using Petri Nets formalism to select a Learning Object that addresses the subject being studied. Petri Nets are formal description techniques used to specify competing systems through graphical and mathematical modeling. Intelligent Agents are computer programs created to automate and perform a certain task or direct interaction with student and propose solutions considered appropriate, based on based on knowledge obtained during the interactions. This research uses the Petri Net to create an Intelligent Agent model, which chooses the Learning Object from answers obtained by applying VAK, an educational questionnaire and results obtained shown to be promising and method was well evaluated by students.

This Research Full paper presents a Systematic Mapping Study of actions that are being carried out in the academic environment, aiming at teaching robotics and programming through collaborative procedures at a distance. Recent studies point to an increasing utilization of collaborative activities in teaching-learning process of robotics and programming, favoring the STEM fields, with encouraging results regarding the improvement of student's skills and better use of educational institutions infrastructure. Our goal is to collect information about state of the art on collaborative learning, employed through Groupware. To carry out this investigation, goals were defined by the Systematic Mapping Process, with the purpose of providing a better process understanding. The Research Questions were stipulated to be answered after the results analysis and the Search Strings, which allowed to select publications that satisfy the objective of this research articles in main digital repositories, all carried out in the last 5 years. After applying filters, 22 articles were considered more relevant according to the research objective. The results show the activities, modalities, methodologies, accomplished pedagogical concepts and the conclusions obtained. This work aims to assist researchers who seek information on referred topic.

This Innovative Practice Category Full Paper presents the proposal of a model to develop adaptive educational resources, with the aim to promote robotic teaching in STEM (Science, Technology, Engineering, and Mathematics) courses. This model was designed to be integrated with a Learning Management System, to suggest customized activities and teaching materials according to students' learning cognitive styles, and it is extensible, can be applied in others areas, not limited to robotics. This model aims at stimulating the teaching programming with robots, providing an environment that students can remotely program robots through a programming language, monitor their evolution in the environment and evaluate the activities that have been suggested. A feasibility study was realized with 6 professors to validate this proposal, and the UTAUT model was applied with 24 students, to validate the acceptance model study.

This full paper of research to practice category describes an experiment using an Intelligent Tutoring System to support teaching and learning that evolve solutions of first-degree equations. The difficulties encountered in solving algebra problems can make students consider math and related science a difficult task. We propose a Tutor to promote the learning of this class of problems. In this article, we describe the functioning and architecture of the tutor composed by the Interface, Student Model, Tutorial Strategies and Domain Model. Also, a Virtual Assistant was included to motivate students in the learning process. The tutoring strategies that comprise the tutor are projected from models found in the literature. To approximate the interactions of the tutor with the actions of the teachers, Lev Vygotsky's Concept of Zone Proximal Development was used. The methodology used in this project was the case study applied in a real-life context, obtaining a combination of quantitative and qualitative evidence about technical and pedagogical usability that show the degree of satisfaction of the students regarding the proposed approach.

This full paper presents the Multi-Agent Recommendation System for Recommending Accessible Learning Objects developed to attend students with disabilities and professors' computation area. The system was proposed based on the qualitative analysis of the questionnaires applied and answered by the professors of the area, to classify, organize and provide the most appropriate Learning Objects according to professors' preferences. In this way, the professor informs the type of impairment (visual, physical, hearing and/or cognitive), discipline and content, based on these requirements, receives the best recommendations of the intelligent agent. The methodology that we use is Multiagent Systems Engineering. The web page was developed using the Laravel Framework PHP, the data repository was created using the MySQL database, and to perform the implementation we used the Java Agent Development Framework. As a result of the research, we present a recommendation system of accessible learning objects using intelligent agents and communities of practice through the recommendation mechanism based on trust. The results obtained through the implementation of the system provide a new motivational practice trough accessible educational content, which contributes significantly to the teaching-learning process of the computation course and to inclusive education.

Context: This Research to Practice Full Paper presents a systematic review of methodologies that propose ways of reducing dropout rate in Virtual Learning Environments (VLE). This generates large amounts of data about courses and students, whose analysis requires the use of computational analytical tools. Most educational institutions claim that the greatest issue in virtual learning courses is high student dropout rates. Goal: Our study aims to identify solutions that use Machine Learning (ML) techniques to reduce these high dropout rates. Method: We conducted a systematic review to identify, filter and classify primary studies. Results: The initial search of academic databases resulted in 199 papers, of which 13 papers were included in the final analysis. The review reports the historical evolution of the publications, the Machine Learning techniques used, the characteristics of data used, as well as identifies solutions proposed to reduce dropout in distance learning. Conclusion: Our study provides an overview of the state of the art of solutions proposed to reduce dropout rates using ML techniques and may guide future studies and tool development.

This Full Paper of Research Practice Category presents a proposal for the mediation of learning through a remote access experiment. The proposal is targeted at Physics students at Secondary School and provides students with a reflective experience about basic kinematics concepts from the actual execution of experiments. The mediation experience will allow interaction between students and teacher, especially when there is a need for student orientation in experimental activities. The project is based on Vygotsky's ideas on learning with mediation, support and the Zone of Proximal Development. A feasibility study was conducted with a group of experienced Physics teachers, and a prototype was implemented.

This full paper of research category presents a Systematic Mapping Study of the state-of-the-art of research on adaptation content in Robotic Systems, in the fields of cognitive profile, learning style and student model. In general, teachers develop the material that is to be taught and organize pedagogical activities for the students. As a consequence, students have a learning environment that does not take into account activities that have already been completed, actions taken, learning preferences and cognitive profile. Activities and teaching materials in robotic environments are the same for all students, and may end up being insufficient for the effective learning of each one. The initial search of four main academic databases resulted in 137 papers out of which 15 papers were included in the final analysis. Our article presents different researches, which involve adapting content for learning in robotic environments.

Context: Since online discussion forums are widely used in Distance Learning platforms, instructors ought to be aware of what is happening in them. Goal: Our study aimed to identify scientific studies that investigate awareness in online forums in Learning Management Systems (LMS) and Massive Open Online Courses (MOOC). Method: We conducted a systematic mapping to identify, filter, and classify primary studies. Results: We selected 51 papers and categorized the difficulties faced by discussion forum users into four groups: visualization, motivation, structural, and accompaniment. In addition, we identified six types of awareness elements: informal, group-structural, workspace, social, task, and concept awareness. The results were divided into two types: system/framework and approach/investigation. Conclusion: our study provides an overview of the state of the art and challenges concerning awareness information in online forums and may guide future studies and tool development.

This paper presents the Inclusive Model for the Development of Accessible Learning Objects developed to assist students with Hearing Impairment. Previous studies have demonstrated the importance of using Accessible Learning Objects to support the educational process of students with disabilities. The Inclusive Model was designed to attend the needs of higher education teachers in computing. This model was designed and implemented with emphasis on the constructivist paradigm, and using the pedagogical model with the support of the techniques of Requirements Engineering and the computational model, using the PDCA and SCRUM Methodology. The proposal of development of the inclusive model has as main objective to attend Students with Special Educational Needs. Accessible Learning Objects was evaluated through of educational, usability, and informatics in education specialists. Also, was realized a case study in the Computer Science class, wich had a student with Hearing Impairment, which participated of the study. The results showed that the Accessible Learning Objects are appropriate for requirements previously defined bi teachers of the disciplines and are promising for the inclusive education.

This research presents the case study regarding the application of the Inclusive Model of Development and Evaluation of Accessible Learning Objects. The study was realized with undergraduate students in Computer Science. Universities in a general context need to adapt within the infrastructure, technology, training and qualification of teachers in order to meet the recent demand of Students with Special Educational Needs and Disabilities. The methodology was based on Project Based Learning, with an emphasis on the interactionist theory for the production of Accessible Learning Objects and adopted the standard Shareable Content Object Reference Model, so that the material produced is compatible with any Learning Management System. The results obtained demonstrate that the proposed teaching method has achieved significant results. The classes that participated in the case study developed their skills and acquired them through the artifacts produced, applying knowledge in their internship in public schools producing of educational solutions that support education at all levels. Also, this work allowed the motivation the group work, management, meeting schedules and activities, research, meeting standards and promoting of the importance of social and digital inclusion.

This paper presents the development of a Robotics and Programming Laboratory with the support of Multiagent Systems (MAS) to help users learn programming skills using robots. The developed laboratory is available in a Learning Management System (LMS) allowing people from geographically distant locations to gain experience with experiments of this nature. The choice of Robotics Education (RE) as object of scientific experimentation linked to teaching and learning systems has shown to bring significant improvement in the learning process. The system makes available on the Internet a space where it is possible to practice programming using Lego Mindstorms robots in the Python programming language. The system suggests several challenges based on the score and profile of users. Its features were tested with promising results, where users have felt very interested and motivated to continue learning programming and robotics. The work developed presents advances over remote robotics laboratories found in the literature, since it allows the robots to be remotely programmed through the programming language NXT-Python, and not only by using command arrows.

Frequently, the existing resources in Virtual Learning Environments (VLEs), used in distance education courses and blended, are presented in the same way for all students. This may complicate the effective learning process of each student. In order to solve this problem, one of the original goals of intelligent educational systems is to guide every student to the most appropriate educational contents. So, the approach adopted in this paper is based on a framework called ArCARE (Conceptual Framework of Educational Resources Adaptation in Virtual Learning Environments), which allows adaptation of resources for students in VLEs, allowing the construction of their knowledge, using multi-agent system technology that handles an open learner model ontology. These ArCARE resources are recommendation and adaptation of collaborative activities such as Pedagogical Architectures for the students have a more effective learning of particular course content. Results obtained from some tests in a flexible curriculum course of Computational Thinking show the feasibility of the proposal.

Social interactions, when analyzed, can provide several information to help intuitive understanding of individuals and their interactions. Social Network Analysis (SNA) is a study field that investigates people's interaction patterns. These patterns, when mapped, enable a detailed and in-depth view of individuals' groups. In the context of distance learning, this paper presents an analysis that uses SNA metrics for helping the teacher of a Learning Management System (LMS) to understand the social structure of students' interactions and more quickly identify active and inactive students within the class. The study was conducted in a discipline offered in a higher education institution. Four SNA metrics were used in the results. These metrics include: density, degree centrality, the relative centrality and global centrality. Through these metrics it became possible to measure the relationships between students and find out, for example, which students needed more attention from the teacher. In addition, it was possible to identify students who interact more and students who are relationship bridges on the network, among other information. Thus, the results showed that SNA helped the teacher in the understanding of the interaction structure between students.

A frequent concern among students and teachers working with educational robotics is about the results gathered through practical activities. Currently, educational institutions and robotics competitions lack of mechanisms that can evaluate the robot's behavior during the accomplishment of the proposed challenges. In this work, we propose the development of a technological solution using Computational Vision, whose purpose is to monitor and evaluate the performance of mobile robots during the execution of Robotics Pedagogic tasks. The developed system, named MonitoRE — Monitoring System for Educational Robotics, was tested on three categories of pedagogic robotics environments, obtaining promising results. Our tool uses an Absolute Location Method with descriptors based on color and shape to analyze the task environments, mapping the path taken by the robot, evaluating the achievements in the proposed tasks. The experiments carried out indicate that the adopted method is effective, performing satisfactory results in robotic monitoring. In addition, it was found that teachers and students felt more motivated, demonstrating interest in using monitored task environments, because it ease the understanding of the difficulties faced by the moving robot in completing the activities, assisting students in the teaching-learning process.

Distance Education is a modality widely used in the teaching-learning processes. To support the distance education or blended courses there are educational environments called Virtual Learning Environments (VLEs). These environments support the process of communication between students, teachers, tutors, and the community, allowing everyone to participate in an interactive mode and with availability of teaching materials, both in academia and in the corporate environment. Also, there are several techniques for adaptation resources for students in VLEs found in literature like context-awareness, collaborative learning, and adaptation by Artificial Intelligence (AI) technologies, such as agents and ontologies. Thus, this paper aims to summarize the information obtained in the literature about educational adaptation to students in VLEs supported by a pedagogical theory. For pedagogical theory, Piaget Constructivism was chosen. To obtain this information in literature, a Systematic Review was performed in order to answer three research questions. The results and analyses of the review are also discussed. This study intends to contribute with designers and developers of educational applications, giving a broad view of the area of adaptation resources supported by Constructivism and making some recommendations.

With the spread of distance education courses or blended, an increasingly common problem is the lack of a personalized accompaniment to the student and the delay in responding by mediators and other colleagues the doubts and requests from students in Virtual Learning Environments (VLEs), usually posted on forums or manifested via e-mail. The approach taken to solving this problem presented in this paper is based on multi-agent systems and a competency-based ontology of the learner model. Through such technologies, the student's doubts are identified and these are directed to community members who have the profile with best suited skills and competencies to resolve it, decreasing the response time of doubts from students. A Petri Net has been developed in order to represent interactions among agents. The system was tested in a Numerical Analysis class that makes use of the VLE Moodle. The results of the tests were used to prove the validity of the system and the viability of the solution. Survey questionnaires were passed in the classroom in order to obtain and evaluate the students' impressions about the resource available to them in the VLE.

The large number of messages posted on the forum, a key element in Distance Education Courses based on Virtual Learning Environment, which does not receive adequate feedback from the tutor in sufficient time is a typical problem faced by students in these environments. The tutors, in turn, feel a lack of tools to monitor activities carried out by the student. This article proposes an approach for solving these problems based on the concept of perception, using the multiagent system paradigm. The system is composed by intelligent agents, which act in a Moodle discussion forum using an AIML knowledge base. Agents solve questions about matters discussed at the forum, and they use perception to recommend the implementation of activities that the student has not done. The results from simulations based on real courses already completed show that there is a decrease in the workload of tutors. Students are reminded the deadline for the tasks automatically. It was necessary to create hundreds of AIML rules to get answers to good level. The partial results indicate that the approach of combining AIML and MAS is promising to improve the feedback from tutors and motivate students to conclude their work on time.

With the increasing use of Learning Management Systems, people who use them have gotten new opportunities to access knowledge through the Internet. This has drawn attention of researchers from the Informatics and Education on several research issues. Among them is the strategy proposed in this paper, describing an approach that uses multi-agent system and competency-based learner model ontology focused on adaptation of the Moodle system to assist students who have doubts or errors when performing certain activities proposed by the teacher or who have low skills levels required to perform these activities. Such assistance is a personalized recommendation of students with an appropriate profile based on their skills and competencies to help students' weaknesses.

Convention on biological diversity (CBD) recognizes that biodiversity loss must be reduced to promote poverty alleviation and direct benefit of all live on Earth. To achieve that, we must consider robust strategies and action plans based on knowledge and state of art technology. Parallel to that, research is underway in universities and scientific organization aiming to develop semantic Web as an additional resource associated to formal ontology and the avoidance of knowledge acquisition problems such as expertise dependence, tacit knowledge, experts' availability and ideal time importance. Ontology can structure knowledge acquisition process for the purpose of comprehensive, portable machine understanding and knowledge extraction on the semantic Web environment. These technologies applied to biodiversity domain can be a valuable resource for CBD. The paper presents a strategy for biodiversity knowledge acquisition based on a negotiation protocol which uses domain ontology to extract knowledge from data sources in the semantic Web domain.