Proceedings of the Brazilian Symposium on Computers in Education (SBIE)
Sociedade Brasileira de Computação - SBC
This document brings the pre-textual elements and committees of SBIE 2025.
Development and Validation of a Web-Based Augmented Reality Platform for Educational Applications
EducaAR is a web-based Augmented Reality (AR) platform that uses textbooks as markers to display 3D models, allowing students to answer quizzes via mobile devices while teachers monitor their performance and access. The platform was tested by 31 high school students in Biology, with 3D models developed by Software Engineering undergraduates. Teachers rated its usability as excellent, and students reported high engagement and increased curiosity about the content. Tutorials were suggested for less tech-savvy teachers, and developers emphasized the need for training in simplified tools. Students showed lower confidence in complex concepts, indicating the need for complementary teaching strategies.
Challenges and Barriers for Students with Disabilities in Computing Programs: A Systematic Literature Review
People with disabilities have gradually advanced in gaining access to spaces that were historically inaccessible, and education in computing is one of these challenges. This systematic review analyzes the barriers faced by students with physical disabilities in computing courses, highlighting the obstacles they encounter and existing strategies to mitigate these challenges. The results highlight the need for inclusive policies and pedagogical strategies to ensure equitable and effective access to computing education, promoting greater accessibility and participation of these students in the field.
EduEmotion: An EEG Dataset of Emotional Responses in Simulated Learning Tasks
This paper presents EduEmotion, an EEG-based dataset designed to support emotion recognition in distance education. It captures affective dynamics during self-guided, domain-neutral digital interactions that reflect common online learning experiences. Data from 22 participants contain EEG signals and self-reported emotions. The study emphasizes the representativeness of emotional responses in authentic educational scenarios and the elimination of disciplinary bias. Results show consistent patterns of engagement and mild frustration—emotional states common in remote learning—providing a realistic foundation for adaptive educational technologies.
Preferences and Challenges in the Use of Exergames to Support Autistic Individuals: A Literature Review
Introduction: Several literature reviews point out the benefits that exergames can bring to autism therapies, however, information on how to implement exergames in daily therapeutic practice is scarce. Objective: To seek information on preferences and challenges in the application of exergames in autism therapies. Methodology: Systematic literature review. Result: Of 18,007 articles found, 37 were selected. Conclusion: The results found on the application of exergames for autism show a growth in this area, even though it faces several challenges. Overcoming these requires more rigorous research and a multidisciplinary approach to integrate them into daily therapeutic practice.
Applying Playful and Gamified Educational Robotics to Complement Therapies for Children with ASD
Educational Robotics (ER) represents a teaching approach that has been consolidating as a tool for technological practice. By analyzing ER as a way to complement the work carried out in child therapies, this study presents an experience report on the application of playful and gamified activities related to ER teaching, incorporated into therapies for children with Autism Spectrum Disorder (ASD). As a result, despite the children’s creation of their own unique micro-world, it was possible to bring them into the “magic circle” of ER, thus achieving psychopedagogical and psychomotor benefits based on the activities performed.
Business Intelligence in Higher Education Management Systems: A Systematic Mapping Study
Higher Education Institutions have expanded considerably in recent years. Along with this expansion, which has increased the total number of students enrolled, places, courses offered, and employees, there has also been a considerable increase in the data they generate. However, this data may need to be used more effectively, especially when supporting strategic decision-making. Business Intelligence (BI) techniques can be helpful in this process. In this study, we sought to understand and to systematize which BI strategies have been used in these institutions by a systematic mapping study. The results revealed some tools and techniques are used, but there are still difficulties in properly implementing BI in this context.
Learning Analytics in Moodle: Building a Data Dashboard with Educational Indicators
Although the use of Learning Management Systems (LMS) allows for the collection of diverse information about students and courses, leveraging this data to generate relevant management indicators remains an ongoing challenge in Learning Analytics. Moreover, the lack of a free platform that consolidates different indicators limits the extensive use of LMS data in university management. This paper presents the development of an educational indicators dashboard for the Moodle environment, focusing on the analysis of students’ academic trajectories across six dimensions. The proposed solution integrates theoretical and functional contributions identified in the literature and existing tools, organizing the data in a clear and accessible manner through discretizations.
Predictive Modeling for Student Retention: Evaluation of Machine Learning Algorithms with Temporal Validation
This study aims to develop and evaluate predictive models to identify students at risk of dropout at a campus of the Federal Institute of Paraíba (IFPB), using administrative data from 2017 to 2023 obtained from the Nilo Peçanha Platform. Several supervised machine learning algorithms were applied, including interpretable models such as Logistic Regression, Decision Tree, and K-Nearest Neighbors (KNN), as well as more complex models like Support Vector Machine (SVM), Random Forest, and XGBoost. Model performance was assessed through stratified cross-validation and a prospective test with unseen data from 2023. The Random Forest model achieved the best overall results, particularly in AUC-ROC and Recall, offering a balanced trade-off between generalization and sensitivity. These findings demonstrate the feasibility of integrating predictive models into institutional decision-support systems to strengthen student retention strategies. Future work involves deploying the model in a monitoring system and incorporating concept drift detection techniques to maintain long-term reliability in dynamic educational contexts.
Exploring the Potential of Generative AI in Virtual Learning Environments: A Systematic Review
This study aims to understand, through a systematic literature review, how Generative AI (GenAI) technologies and tools are being used in practice in conjunction with Learning Management Systems (LMS). Observing a considerable scarcity of studies on the integration of GenAI with LMSs, it is possible that there is a significant gap between the potential of GenAI and its effective implementation in formal educational contexts. The aim is to understand the current scenario and indicate where future research can contribute to a comprehensive understanding of the potential and challenges of integrating GenAI into LMSs, considering ethical, security, and privacy issues, adapted to the needs of different educational contexts, especially those with low computational resources.
The challenges of teaching computing during the Covid-19 pandemic and its relation to Education 5.0
This paper investigates the challenges in computer education during the Covid-19 pandemic and its relation to Education 5.0, through a systematic review of the SciELO, SOL, and Science Direct databases. It analyzes changes in computer education, actions taken during the pandemic, and their connections to Education 5.0, as well as the effects on students’ and teachers’ learning, social interaction, and quality of life. The results indicate greater use of Education 5.0 concepts after the pandemic, including Hybrid Learning and Active Methodologies. The 2030 Agenda is mentioned as a reference for educational goals focused on well-being and social engagement.
Evaluating the Effect of Test Creation on the Learning and Performance of Programming Students
Programming requires transforming problems into systematic instructions. However, many students face difficulties early on, particularly in interpreting problem statements and constructing correct solutions. This study evaluates a strategy based on interaction with a reference solution accessible only through inputs and outputs, encouraging students to formulate their own tests. The results indicate that the strategy contributed to improved student performance, notably reducing failures, increasing success rates, and enhancing the reliability of solutions. These findings highlight the potential of the approach as a pedagogical support tool in programming education.
Diagramming for All “Perspectives”: Digital Accessibility for Teaching and Practicing Entity–Relationship Diagrams
The article addresses the challenges faced by people with visual impairments in higher education, especially in fields such as computing, where courses with predominantly visual content, such as databases, present significant barriers. The work proposes the development of an inclusive web environment, Diagrama Além da Visão (DAV) (”Diagram Beyond Vision”), aimed at creating entity-relationship diagrams with a focus on accessibility for visually impaired users. The methodology involved qualitative research and development with data analysis using the System Usability Scale (SUS). As a result, participants praised the readability of the diagram elements and the ease of use, while also suggesting adjustments such as changes to accessibility shortcut keys and the ability to modify the speech rate of the integrated screen reader.
Automatic Scoring of Elementary School Essays in Brazilian Portuguese with LLMs: Comparing Gemini, GPT-4o, Claude, and Mistral
Writing is an essential skill for the development of students’ critical thinking, communication, and language competencies. However, evaluating written productions efficiently and within an appropriate timeframe remains a challenge, especially in contexts of high teaching demands. This study investigates the use of Large Language Models (LLMs) for the automated analysis of essays with a focus on achieving accurate and consistent assessments. Four advanced models such as Gemini, GPT-4o, Claude 3.7 and Mistral were examined and applied to the evaluation of narrative texts written in Brazilian Portuguese by elementary school students. The results indicate that the Gemini 2.0 Pro model demonstrated greater accuracy in score assignment, while Claude 3.7 stood out for consistency in alignment with human evaluation. The findings highlight the potential of LLMs to support pedagogical practices by providing consistent assessments and contributing to the development of students’ writing skills. The study proposes viable alternatives for the use of artificial intelligence in educational contexts with limited resources.
Personalized Inclusion with GenAI: An Adaptive Strategy to Support Students with ASD in Higher Education
Inclusion in abstract, cognitively demanding courses is difficult. This study presents an adaptive strategy that merges Universal Design for Learning (UDL) and Generative AI to tailor propositional-logic activities for a student with Autism Spectrum Disorder (ASD). Across four formative, reflective cycles, existing tasks were progressively reshaped; evidence came from observations, journals, and rubrics. The ASD learner showed sustained gains in engagement, conceptual grasp, and autonomy, indicating the value of the approach. The results suggest that educator-mediated GenAI, aligned with UDL, can foster more responsive and inclusive learning in higher education.
Integrated Simulator and Game for Teaching Gynecological Cytology: A Tribute to Women in Science
This study aims to propose an integrative methodology for teaching gynecological cytology by combining a digital simulator (PapSim) and a board game (HPV Combat), connected via microcontroller to enhance interactivity. Cervical cancer remains a public health concern in Brazil, with human papillomavirus (HPV) responsible for most cases. Characters inspired by women scientists are featured to honor their legacy and promote gender equity in health education. A proof of concept with nursing students indicated high engagement and positive emotional responses such as discovery and challenge. The integrated tools showed potential to strengthen both theoretical knowledge and practical cytological skills. This approach offers a meaningful and socially conscious learning experience for future health professionals.
Proposal and Development of an Adaptive Learning Strategy Based on Information Retrieval for the TôSabendo Platform
This article presents the proposal, development, and validation of an adaptive learning strategy for the TôSabendo platform, aimed at solving questions through Quizzes. The strategy uses Information Retrieval (IR) models and a user model, which are responsible for adapting the content according to the individual needs and learning pace of students. Through practical experiments using three IR models: Vector Model, Extended Boolean Model, and Probabilistic Model, positive results were obtained regarding question retrieval. Furthermore, through the Lighthouse tool, satisfactory usability of the platform integrated with the adaptive learning strategy was verified.
Evaluation of Prototyping a Web Tool for Customizing and Managing Rubrics: A Focus Group Study
The study focuses on evaluating a web tool designed for customizing and managing rubrics to enhance educational assessment. The aim is to assess the usability of the tool’s prototypes by gathering insights from a focus group comprising experienced professors. We engaged in a focus group session with five professors as part of an exploratory evaluation process. The qualitative feedback we collected helped us identify the strengths and limitations of the tool, offering valuable guidance for future improvements. The study emphasized the importance of participatory evaluation to enhance educational tools, stressing the significance of clarity and objectivity in assessments.
A quality analysis of the use of large language models for automatic generation of assessment items in portuguese
Educational assessment plays a fundamental role in monitoring the quality of education. The manual creation and development of test items is a costly and highly specialized task, and the use of large language models (LLMs) has become a popular solution in the field of automatic item generation (AIG). This study proposes a quantitative and qualitative analysis of the use of general-purpose LLMs for generating Portuguese language items intended for large-scale Brazilian assessments, which have well-defined requirements for item construction and quality verification. The results indicate that current technologies are not yet capable of fully addressing this problem and that significant research challenges remain in this area.
João Vítor de Castro Martins Ferreira Nogueira
Accessibility in Integrated Development Environments: Specification of Guidelines Oriented to the Needs of Blind Students
In Computer Science courses, particularly in Programming disciplines, the use of tools reliant on visual elements, combined with the characteristics of programming languages, creates significant barriers for blind students. These obstacles hinder learning and may result in unequal access to educational resources, thereby impacting the quality and equity of instruction. To ensure equitable access to essential tools, it is crucial to enhance their accessibility. Within this context, this work describes the process of specification, validation, and refinement of Accessibility Guidelines for Integrated Development Environments (IDEs) aimed at blind students, with the goal of fostering an inclusive experience based on the functionalities of these environments.
Finite-State Transducers for Oral Spelling Detection
Reading fluency assessment plays a central role in early education systems worldwide. Countries such as the United States and Brazil administer large-scale oral reading assessments to monitor educational outcomes and guide intervention. However, most of the automatic assessments are often coarse in granularity. As a result, they are poorly equipped to handle children who do not yet decode words fluently and instead rely on spelling out individual letters or syllables. We show that finite-state transducers can be used to detect spelling to improve oral reading assessments. We demonstrate the effectiveness of our method on a corpus of annotated child speech, showing that it provides insight into early decoding strategies.
From Algorithm to Inclusion: The Use of AI for Creating Lesson Plans in Educational Robotics
The integration of innovative technology in education has shown to be a growing trend, with emphasis on educational robotics, which promotes the development of skills such as computational thinking, creativity, and collaboration. This article proposes a reflection on the use of Artificial Intelligence (AI) as a support tool for teachers in the creation of lesson plans on inclusive educational robotics, aimed at students with Autism Spectrum Disorder (ASD). The methodology adopted included the generation of lesson plans through AI, iterative testing, and expert evaluations. The results demonstrated that AI can be an ally for the creation of personalized and adaptable lesson plans, promoting inclusion and reducing the workload of teachers.
Estimating the Difficulty of Programming Problems in Brazilian Portuguese with Few Examples: An Evaluation of BERTimbau Embeddings
Programming practice is a fundamental step in learning to program. In this context, estimating the difficulty of programming questions is crucial for effective adaptive learning. Some approaches address this problem by analyzing students’ past performance, but this can be impractical as sometimes only the problem text is available. For this reason, this study evaluates the use of semantic embeddings of exercise text (QDET) extracted with BERTimbau, a state-of-the-art BERT model pre-trained for Brazilian Portuguese, in a context where only a small sample is available for training, a task referred to as few-shot learning. The results show that the embeddings generated by BERTimbau do not effectively capture the difficulty of problems based solely on textual information. This emphasizes the need for models trained specifically for this task.
A Framework for Search as Learning Experiments: Design, Implementation, and Usability Insights
Search as Learning (SAL) explores how users engage with search systems to acquire knowledge and develop understanding. Despite advances in SAL, the lack of general-purpose tools hinders reproducibility and standardization in experimental studies. This paper presents a framework to support researchers in designing SAL experiments, encompassing task creation, data collection, and learning assessment. To evaluate the proposal, we conducted a usability study with 12 participants, which yielded a score of 83.07, indicating excellent usability. Feedback of the participants also provided suggestions for improvement, guiding future development. This work contributes to strengthening methodological practices and fostering reproducibility in SAL research.
LudoTech: A Board Game for Developing Computational Thinking
This paper presents the development and evaluation of LudoTech, a board game designed to support the learning of Computational Thinking in a playful and engaging way for teenagers. Inspired by the traditional Ludo game, LudoTech introduces questions, challenges, and minigames covering topics such as Algorithms and Logic, Data Structures, Computer Networks, and Digital Security. Evaluation results indicated that the game was well received by participants, fostering engagement, learning, and interest. Additionally, the evaluation process allowed for the identification of aspects that could be improved in future iterations.
Agentic Artificial Intelligence in Education: A Conversational Agent for Competency Building in Basic Education
This paper presents the development of a conversational agent based on Agentic Artificial Intelligence for competence development in basic education. The study involved a systematic literature mapping to identify benefits, challenges, application areas, and technologies used in educational chatbots. A proof of concept was then developed, integrated with a self-assessment system, feedback mechanism, and learning resource recommendations. The architecture leverages OpenAI’s API with RAG and learning experience tracking via xAPI. Results highlight the potential of Agentic AI to foster more autonomous, adaptive, and student-centered interactions. The solution represents progress in personalized learning and competence-based assessment support.
An extensible environment for Game Learning Analytics
Game Learning Analytics (GLA) explores techniques for analyzing learning data within the context of educational objectives in serious games. This work presents an extensible Web platform for GLA, developed to collect, analyze, and visualize data from educational games created in Unity. The platform allows users to customize the data to be collected, configure different chart types for visualization, and incorporate new mathematical functions for analysis. Its effectiveness was validated with two games, one focused on physics and the other on history, and an evaluation using NASA-TLX indicated that the platform imposes a low workload on users.
Improving automated literacy assessments through a multiple output grapheme-to-phoneme approach
Fluency assessments are essential for monitoring literacy development, but automatic systems still struggle with the phonetic diversity of Brazilian Portuguese and the specific characteristics of children’s reading. We propose a rule-based grapheme-to-phoneme converter that generates multiple acceptable transcriptions per word, accounting for regional variations and child speech. Validated on children’s reading data, the module reduces errors, increases accuracy from 89% to 95% on the PARC-2019 dataset, and improves performance among inconsistent readers. Flexible G2Ps make assessments fairer and more reliable.
An evolutionary approach for the automatic generation of word list fluency assessment items
This paper presents a Genetic Algorithm (GA) to automate the generation of reading fluency assessment items, reducing manual effort while meeting pedagogical constraints. Candidate solutions are sequences of words optimized by a multi-objective function that penalizes constraint violations and repetitions. Constraints include canonicity, syllabic variety, grapheme presence, and prosodic continuity. Experiments show that the GA effectively produces valid word lists, with larger populations yielding faster and more stable convergence. A 5% mutation rate was sufficient to preserve diversity. The method is flexible, scalable, and aligned with educational standards.
A Systematic Mapping Study on Chatbots in Programming Education
Educational chatbots have gained prominence as support tools for teaching programming, particularly in introductory learning contexts. This paper presents a Systematic Mapping Study (SMS) that investigated how such agents have been developed and applied in programming education. From an initial set of 3,216 publications, 54 studies were selected and analyzed based on five research subquestions, addressing chatbot types, programming languages used, educational content covered, interaction models, and application contexts. The results reveal a predominance of chatbots designed for Python instruction, focusing on fundamental programming concepts, and employing a wide variety of pedagogical approaches and technological architectures. In addition to identifying trends and gaps in the literature, this study provides insights to inform the development of new educational tools for programming instruction.
Between Folds and Codes: Folding Algorithms Integrated into GeoGebra
Paper folding integrated with digital technologies can redefine mathematics teaching, creatively connecting geometric and computational concepts. In this context, a workshop was conducted for teachers, promoting investigative experiences with paper folds and their transposition to GeoGebra, encouraging the creation of plug-in algorithms. The objective was to examine the interactions established and the learning achieved by the participants. The workshop combined computational thinking, creativity, and reflective abstraction, expanding the participants’ teaching repertoire. The potential of paper folding as a “thinking-with” object is highlighted, serving as an investigative and innovative resource.
Generative AI Assisting Programming Learning: Functional Roles, Comparative Analysis, and Emerging Challenges
This study examines the role of generative Artificial Intelligence (AI) in programming education through a systematic literature mapping of 52 studies across seven databases. Our analysis reveals three distinct functional roles for AI: collaborative participant, support tool, and pedagogical mediator. We compare AI-enhanced programming instruction with traditional teaching methods, finding shifts in pedagogical approaches, communication, and cognitive engagement. The research identifies key challenges spanning technical, pedagogical, ethical, and assessment dimensions. We propose a functional classification framework for AI roles and offer recommendations for responsible AI integration in programming education.
The integration of informatics in teacher education programs at UFAL
In an educational context increasingly impacted by digital technologies, teachers are expected to integrate these resources in a critical and creative way. Initial teacher education thus becomes essential to promote reflection on the pedagogical uses of technology. This study analyzes how Educational Informatics is incorporated into undergraduate teaching programs at the Federal University of Alagoas (UFAL), through a qualitative-quantitative, documentary, and exploratory approach. ased on the analysis of the content of the Course Pedagogical Projects (PPCs), the study investigated how the technological theme is addressed in the curricular structures and how it contributes to the training of pre-service teachers. The research aims to strengthen teacher education in the face of the challenges of the digital era.
Strategy for adapting adaptive curriculum sequencing solutions in Moodle
Online education requires personalized approaches that adresses the individual aspects of each student. In this context, Adaptive Curriculum Sequencing (ACS) appears as a promising solution, although its application remains limited. This study critically analyzes ACS approaches, exploring their adaptation in virtual learning environments, with a focus on Moodle. A survey was conducted of the key data and approaches employed in ACS, mapping these elements to native Moodle resources. As a result, we propose a proof of concept demonstrating the viability of establishing adaptive learning paths in the platform. This research contributes to transforming theoretical models into practical solutions, advancing toward personalized education.
Profile of National Databases in the Field of Educational Data Mining
Educational Data Mining (EDM) has emerged as an effective approach for investigating challenges within the educational context. School dropout, in particular, is a recurring phenomenon that affects many educational institutions and has been widely studied using EDM and Machine Learning techniques. The quality of such analyses largely depends on the selection of appropriate data sources — those that are comprehensive, accessible, rich in relevant attributes, and sufficiently large. In this context, this study aims to map and characterize the data sources used in EDM research focused on school dropout. The analysis considers aspects such as dataset size, number of attributes, availability (public or private), and types of data used.
Exploring Self-Regulated Learning in Virtual Environments: An Experimental Clustering-Based Approach
Following the COVID-19 pandemic, there was a substantial increase in the volume of educational data generated in online environments. In this context, this study investigates signs of self-regulated learning (SRL) in virtual environments by applying educational data mining techniques to analyze student behavior. Data were collected from Moodle logs of a technical course offered by a federal public educational institution and underwent a preprocessing phase. Clustering algorithms such as K-Means, HDBSCAN, and Agglomerative Clustering were then applied to identify behavior patterns related to SRL. Differing from previous studies that mainly focused on student profiling or general engagement-performance correlations, this research explores how behavioral patterns revealed by clustering are directly associated with SRL indicators, with the results showing that HDBSCAN and K-Means were more effective in forming meaningful groups. The analysis revealed that students who exhibited stronger indications of SRL tended to achieve better academic performance, demonstrating greater engagement with learning resources, which was reflected in higher grades. This study contributes to a more nuanced understanding of SRL dynamics in virtual environments and highlights the potential of educational data mining techniques in identifying relevant behaviors, offering valuable insights for the development of pedagogical practices that promote student autonomy.
The effectiveness of Intelligent Tutoring Systems in teaching: a study based on a Systematic Literature Mapping
With technological advances, it is essential to develop new forms of teaching that explore the use of technologies and the digital environment. In this context, Intelligent Tutoring Systems (ITS) can play a crucial role in making teaching more accessible to everyone. Given this, this article aims to evaluate the effectiveness of ITS in teaching, investigating whether these systems have an impact on academic performance. To this end, a Systematic Literature Mapping was carried out and 15 articles on the application of these systems were analyzed. The results indicate that it has a positive impact on learning, promoting significant improvements in grades and student confidence in the teaching and learning process
Supporting Curriculum Matrix and Course Design with Generative AI and Knowledge Graphs in Undergraduate Programs
This work proposes a method to support the development of curricular matrices by integrating Generative Artificial Intelligence (GenAI), Natural Language Processing (NLP), and Graph Analysis techniques. The approach employs embeddings and cosine similarity to identify similar courses within heterogeneous university curricula, generate new courses by merging content, and structure the curriculum based on centrality metrics (Degree, Betweenness, Closeness). The results demonstrate a high similarity between the generated and original courses, with an average similarity of 0.91, and effectiveness in promoting interdisciplinary integration. The matrix generated in the case study for a Data Science program adheres to the guidelines of the Brazilian Computer Society (SBC) and the existing curricula of universities (UFC/UFPB), in addition to presenting a coherent pedagogical structure validated by a curricular graph structure with 40 courses and 311 connections, as well as by the validation of the relationships between courses in the matrix.
An Empirical Investigation of Personality Traits, Self-Perceived Distractions, and Programming Performance in an Introductory Programming Class
We investigated the interrelationships between personality traits, self-perceived distractions, and programming performance in an introductory programming class (IPC). Thirty-two undergraduate students participated in personality assessments and programming exercises on an Integrated Development Environment (IDE) platform that captured detailed behavioral interactions. We found that conscientiousness—one of the personality traits—was the strongest predictor of academic success, such as Grade Point Average (GPA). Internal distractions were significantly associated with reduced programming performance. Several IDE metrics strongly predicted academic performance, with successful submissions correlating highly with GPA. After applying False Discovery Rate correction (FDR) for multiple testing, no personality-distraction interactions remained statistically significant among the 190 moderation tests conducted, suggesting that apparent moderation effects may be attributable to chance. In our work, personality traits showed weak associations with distractions, potentially due to bias inherent in self-report measures. Our findings suggest that programming interventions should prioritize conscientiousness-based self-regulation training and internal distraction management, while some of the IDE behavioral patterns can serve as predictors for identifying at-risk students.
Stimulating Students’ Metacognition through Virtual Tutoring with Generative AI
Generative AI has emerged as a potential solution to extend the abilities of tutoring systems. However, while beneficial at first glance, features such as high flexibility and ability to create ready-to-use answers also pose risks to the educational process, potentially fostering dependencies that reduce students' critical thinking, creativity, and problem-solving abilities. This paper proposes the use of generative AI based on a metacognitive teaching model, encouraging students to reflect on their learning process by planning and evaluating their actions, going beyond the traditional question-answer paradigm. The evaluation was conducted via a multi-layered analytical framework, which highlighted the potential benefits for learning.
Development and Evaluation of the Quiz Legends Platform: A Gamified Approach in the Educational Process
This study explores the development and evaluation of the ”Quiz Legends”platform, an educational tool that incorporates gamification by combining elements such as battles, rankings, virtual shops, and clan formation. The platform aims to create a dynamic and interactive learning environment. A System Usability Scale (SUS) test was applied to 33 computer science students to evaluate the platform’s usability. The results indicated an above-average usability score, suggesting positive feedback regarding the system’s ease of use and functionality. Additionally, qualitative feedback highlighted the appeal of the platform’s competitive elements and the impact of gamification on student motivation.
Digital Educational Escape Room as a Learning Tool in a Database Course
Educational escape rooms are activities that contribute to student learning through playful and immersive experiences. In computer science education, many approaches involve the use of escape rooms in classic subjects such as algorithms, for example, often neglecting their potential for learning about databases. In this article, we address the planning, creation, and use of an digital educational escape room for the database course, focusing on SQL queries. The educational escape room was used in a real classroom with a database class in higher education, being evaluated by the students regarding their experience and perceived learning related to this activity. As a result, evidence of positive perceptions was observed regarding the use of the educational escape room for learning SQL and other database concepts. Therefore, it is understood that this study contributes to the field of computer science education by presenting a tool and a report on the application of an educational escape room used in database teaching, which can be utilized as an active learning tool by other educators.
Design Principles for Computing Education in Early Childhood
This study addresses the need for clear guidelines to teach computing in early childhood, given young children’s growing exposure to technology. It investigates how to design activities that integrate computational concepts while supporting holistic development. Aimed at teachers planning design processes, these principles ensure children actively collaborate in creating computing tools and that the experience remains meaningful. Derived from thematic analysis of scientific literature and validated by a focus group of computing and early education experts, five principles emerged. Findings demonstrate that linking family experiences to cooperative tasks provides educators foundation to cultivate digital literacy and computing education from the earliest school years.
GPT-3.5 for Data Augmentation in Automatic Essay Scoring: A Preliminary Analysis
Machine learning models are susceptible to the dataset used during its training. Dealing with limited or imbalanced datasets is challenging, and a commonly adopted approach to mitigate this limitation is data augmentation. For example, expanding the training set in a computer vision problem may involve rotation and resizing images; however, this task is more complex when dealing with textual data. This work investigates the use of GPT-3.5 for data augmentation in a dataset of argumentative essay texts from the National High School Exam (ENEM), which is used as a selection criterion for entry into public universities in Brazil. More specifically, we adopted traditional Natural Language Processing (NLP) techniques for essay scoring and compared the results with and without the data augmentation. Our results show that the long argumentative essays generated by GPT in the data augmentation process did not improve the performance of NLP models. Moreover, GPT could not adequately classify its synthetic data, suggesting poor quality of the generated data, and did not outperform NLP models in classifying real data.
An LLM-Based Approach for Automated Feedback Generation in Computer Programming Education
Learning programming, particularly in introductory courses, is often associated with high failure rates. Tools such as online judges, when integrated into virtual learning environments, can support this process by providing automatically graded exercises. However, the feedback typically offered is limited to error messages or test results, which are not particularly effective in fostering learning. This paper proposes an approach based on Large Language Models (LLMs) to generate more detailed and pedagogically meaningful feedback from students’ solutions to programming exercises. We present the results of experiments conducted in an Introduction to Programming course, demonstrating the potential of LLMs to enhance the teaching and learning experience.
OntoObADi: An Ontology for a Semantic Web Repository of Digital Learning Objects
Digital Learning Objects (DLOs) facilitate teaching, but the lack of diversity and difficulty in organizing traditional repositories hinder their reuse. The Semantic Web emerges as a solution, with ontologies playing a key role in this approach. This work presents OntoOBADI, developed to structure and describe DLOs in semantic web repositories. The methodology includes a literature review, requirements gathering, development using Ontology Development 101, specification in Web Ontology Language (OWL), and evaluation through the Focus Group technique. The results validated its representation capacity, with positive participant feedback and suggestions for improvement.
LLMAgentGrader: A Multi-Agent System with DeepSeek for Enhanced Automatic Short-Answer Grading
Automatic Short Answer Grading (ASAG) is crucial for scaling educational assessment but faces challenges in accuracy. Large Language Models (LLMs) like GPT-4 have shown potential, yet single-LLM approaches can have limitations. This paper introduces LLMAgentGrader, a multi-agent system using DeepSeek-Chat designed for ASAG. The system employs specialized agents to: (i) generate reference answers (including web search), (ii) extract key concepts from answers, and (iii) suggest grades based on semantic comparison and completeness, using a dynamic few-shot learning strategy with a randomly sampled history of prior gradings. We validated LLMAgentGrader on the TEXAS (English) and ASAG 2018 (Portuguese) datasets, comparing it with results from a GPT-4 system and traditional Machine Learning models. Results demonstrate that our multi-agent DeepSeek-Chat approach achieves significantly superior performance in MAE and RMSE, outperforming not only GPT-4 but also some traditional models in specific scenarios.
Assistive methodologies and technologies in biology teaching for visually impaired students: a systematic literature review
This systematic review aims to map and analyze assistive methods and technologies applied to Biology education for visually impaired students, with a particular focus on content related to blood types. The research examined 17 publications from 2019 to 2025, identified in the CAPES Journal Portal, IEEExplorer and Google Scholar databases. The findings indicate a prevalence of tactile materials (high-relief models, sensory maps, and heredograms), multimodal solutions (software with auditory feedback and voice command interfaces), and innovative pedagogical approaches (inquiry-based learning and gamification). The study concludes that, despite significant advancements in the development of resources for general Biology education, the teaching of blood types remains largely underexplored, necessitating further research, initiatives, and the development of specialized tools.
Applications of Multiple Intelligences Theory in Digital Educational Environments: A Systematic Literature Review
This article presents a systematic literature review on the application of Multiple Intelligences Theory in the development of digital educational environments. The review aims to identify, map, and describe how the theory has been operationalized in such environments, with particular attention to its functional and pedagogical integration. A total of 106 studies published between 2000 and 2025 and retrieved from five academic databases were analyzed. The findings reveal a conceptual and methodological dispersion, which introduces challenges to the standardization of classification and evaluation of these environments. Although the integration of the theory was structured in a significant portion of the studies, it often emphasized certain intelligences disproportionately and distanced itself from the principle of personalization, in ways that are inconsistent with the pedagogical foundations of the theory. The review concludes that the application of Multiple Intelligences Theory in digital educational environments still demands integrated models and greater methodological rigor, so that cognitive diversity may effectively serve as a guiding principle for technological development aimed at assessing and fostering students’ different learning styles and intelligences.
Rosa Binary: A Tool to Support the Teaching of Digital Circuit Synthesis
This paper presents an educational tool aimed at supporting the teaching of digital circuit synthesis. It integrates Boolean expression minimization via the Quine-McCluskey algorithm with physical circuit construction on a logic grid, using the A* algorithm for automatic connection routing. Developed in Java with a Swing-based interface, the tool fosters the articulation between symbolic reasoning and structural representation through interactive visualization. Twenty undergraduate students participated in the activity; seventeen completed all stages and answered the evaluation questionnaire. Analysis combining descriptive statistics and thematic categorization revealed satisfactory usability and a positive perception of the tool’s effectiveness in supporting conceptual learning.
Algorithm development for creating exercises on Deterministic Finite Automata
Theory of Computation is an important topic in Computer Science, and teaching it presents a significant challenge, as it involves many abstract and mathematical concepts. This complexity hinders and delays the adoption of educational activities that require a large number of questions, such as exercise lists or mock exams. In this context, automatic question generation has the potential to support student learning by focusing their attention on the presented material and reinforcing knowledge through the repetition of basic concepts across varied exercises. In this work, we present a tool integrated with Jupyter Notebook to generate exercises for the construction and minimization of deterministic finite automata and their corresponding answer, using regular expressions and a genetic algorithm to optimize the generation of questions with varying difficulty levels. Additionally, the proposed tool is capable of grading the generated exercises, presenting counterexamples that can help students understand why their submitted solution is incorrect.
Guilherme Augusto Anício Drummond do Nascimento
Teacher-centered technology design for educational assessment
This paper presents the design and evaluation of a mobile-first, teacher-centered application that enables photo-based student assessment using standard smartphones. The system generates real-time feedback dashboards tailored to teachers, principals, and school managers, promoting data-informed decisions across classroom, school, and system levels. Two empirical studies were conducted: a prototype usability test with five teachers and a real-world case study in a public school. Results highlight the app’s usability, alignment with teachers’ workflows, and potential to enhance pedagogical planning in under-resourced contexts. We conclude with design guidelines for scalable, low-infrastructure assessment technologies.
Use of Artificial Intelligence and Computational Thinking in Cognitive Stimulation of Older Adults: A Systematic Literature Review
The accelerated population aging requires the development of actions that can positively impact active and healthy aging. Thus, this study investigates, through a Systematic Literature Review, how Artificial Intelligence (AI) and Computational Thinking (CT) can promote cognitive development in older adults. The results show that AI personalizes stimulation by adjusting exercises and assessing performance. Regarding the pillars of CT, the findings reveal its application through multidomain cognitive exercises. Therefore, it is also essential to consider teaching AI and CT to older adults, bringing the benefits of logical reasoning and problem-solving into their daily lives.
Solving problems? No problem! An analysis of gamified tools with scoring and ranking in programming education
Gamification techniques have proven to be effective in the context of programming education, both in terms of adoption and outcomes, by promoting performance, interaction, and engagement. As a result, gamified platforms designed for solving algorithm-related exercises have emerged in various styles and systems. This study aims to evaluate platforms that utilize gamification techniques through inspection and investigation methods, enabling the identification and highlighting of both positive and negative aspects of these tools from the perspectives of both students and teachers. This inspection allows a discussion and summary of the elements that make these tools appealing in an educational environment.
Evaluation of the Impact of Gender and Student Aid on Student Survival in STEM Programs
Courses in the fields of Science, Technology, Engineering, and Mathematics (STEM) often present challenges related to student retention, with disparities observed between different groups. This study seeks to analyse the academic retention of 7,432 students in STEM courses at UFRPE. To this end, it employs survival analysis, using the Log Rank, Effect Size, and Hazard Ratio tests to examine retention patterns based on gender, shift offered, and access to student assistance. The comparison between genders in the STEM area reveals a statistically significant difference from the 6th semester onwards, with women having an approximately 62% probability of retention and men around 56%, while students who do not receive assistance and are enrolled in evening classes have a significantly higher risk of dropping out. The results provide support for institutional policies that promote equity and retention.
A Literature Mapping on the Use of Tools to Support the Teaching and Learning of Parallel Programming
The objective of this work is to report the results found from a Systematic Mapping of Literature (MSL) on tools and/or online environments that can serve as support in the teaching and learning process of Parallel Programming. Four international databases were used and thirteen papers considered relevant in this process were identified. Among the main points highlighted are the main concepts of Parallel Programming, libraries, languages, learning methodologies, description of tools and/or environments found, as well as the evaluation of teachers and students in the processes used.
From Latin to Portuguese on Digital Screens: Innovating Portuguese Teaching Through Digital Storytelling
This study explores the application of Digital Storytelling (DS) in teaching the history of the Portuguese language, with a focus on students’ perceptions regarding clarity, interest, emotions, and content retention. The activity was conducted with high school students from a federal public school, utilizing the narrative “The Journey of Zuri”, developed with the support of the Learner’s Journey Application (JoLApp), a tool that facilitates the creation of educational narratives through Generative AI. Data analysis revealed high student engagement but also highlighted criticisms concerning the pacing and depth of the narrative. The results underscore the potential of DS to enrich the curriculum, emphasizing the importance of incorporating student feedback for more effective pedagogical practices.
Computing as a Curriculum Component in Early Elementary Education: Discussions on the BNCC Computing and the Municipal Organizer Framework
This study presents the process of implementing Computing as a specific curricular component for the Early Years of Elementary Education in a public school system in the city of [omitted]. Based on current legislation, the Internal Committee for Curricular Integration of the Digital and Media Education Component was established, whose attribution included the evaluation of the organizing framework that adapts the BNCC Computing to the local Curricular Reference. To this end, an evaluation instrument was developed and individual analyses were carried out, followed by collective discussions. The results allowed mapping advances, weaknesses and future developments, which are presented and discussed in this study.
Impacto de la Robótica Educativa en el Desarrollo de Nociones Espaciales en Niños de Edades Tempranas *(o título já está em espanhol)*
Educational robotics has shown promising outcomes in teaching; however, its application to the development of spatial concepts in early childhood remains underexplored. This study proposes and evaluates an innovative pedagogical strategy integrating two educational robotics interfaces: tangible (button-based) and hybrid, to foster the development of spatial notions. We designed this strategy based on pedagogical principles, literature review, and developmental characteristics of children aged 5 to 6. We performed a quantitative quasi-experimental design with two nonequivalent experimental groups (N=13). Findings suggest that the intervention effectively strengthened spatial understanding, particularly concepts such as left and right, and fostered social skills including teamwork and collaboration.
AUTISMALG: An Application to Support Teaching Number Identification and Counting to Children with Autism Spectrum Disorder
Autism Spectrum Disorder (ASD) poses challenges to child development, especially in learning basic skills such as mathematics. This article presents the results of a project that developed AUTISMALG, an educational application based on Applied Behavior Analysis (ABA) and the ALVINA Protocol, aimed at teaching auditory-visual identification and counting numbers from 1 to 10 to children with ASD. The solution includes a mobile application and an integrated web system, both evaluated by a multidisciplinary team in terms of usability, therapeutic applicability, and pedagogical potential. The evaluations indicated high acceptance and highlighted aspects such as interface clarity, effectiveness of reinforcers, adherence to ABA, and alignment with the target audience needs. The results reinforce the potential of AUTISMALG as an accessible, effective, and evidence-based assistive tecnology, suitable for empirical studies with children with ASD.
LLM-Based Automatic Generation of Multiple-Choice Questions With Meaningful Distractors
Creating effective Multiple-Choice Questions (MCQs) with high-quality distractors that carefully evaluate students is challenging. Large Language Models (LLMs) can contribute by automatically generating questions. This study presents a novel framework for generating distractors for Portugueselanguage. We evaluate the framework using Sabía-3 (Portuguese-specific) and GPT4o-mini (multilingual). We assessed the grammatical and semantic diversity of the generated distractors and devised a qualitative evaluation through Claude-3 Haiku. Results show that integrating educational principles into prompts enhances the relevance and diversity of distractors, marking progress in automated activity and assessment generation for the Portuguese language.
Representing BNCC Computing Through Its Competencies and Knowledge Graphs
The National Common Curricular Base (BNCC) is organized around ten general competencies aimed at the integral formation of students. This study proposes the use of knowledge graphs to represent and analyze the relationships between these competencies, the competencies of BNCC Computing, and the global dimensions. In the graph, competencies are represented as nodes and the dimensions as edges. The analysis highlights Computing as a transversal area contributing to a systemic view of education. Competencies are articulated through multiple dimensions. The graphical representation enhances the understanding of pedagogical connections and supports lesson planning.
Digital Game Players from an InfoVis Perspective: A Systematic Literature Mapping Study
This paper presents a systematic literature mapping on information visualization (InfoVis) in digital games for studies on player cognition. Relevant results were obtained from the following academic search engines: ACM Digital Library, IEEE, Springer, and Scielo. From an initial set of 2,050 articles, only those that met all the established criteria were selected, resulting in a total of 27. The study investigated aspects such as types of data analyzed, methods, techniques, and visualization resources employed. The results indicate a gap in the InfoVis field regarding the development of a reference model for representing player data in digital games.
Explainability in Intelligent Analysis of Students considering Dropout Factors: some insights
Context: In public institutions, there is great concern about the average number of students graduating at the end of undergraduate studies, which substantially impacts public higher education policies and public investments in Brazilian universities. Moreover, dropout imposes a financial and human burden, preventing students from learning. Problem: Brazil witnessed a university dropout rate of almost 55%. This problem affects society in general, which needs more suitably qualified professionals to face the challenges of the job market. Solution: This work aims to analyze, through AI explainability algorithms, the specific factors that lead to student dropout, considering specific courses from the great areas of science. We strive to explore the profile of students who have dropped out in recent years, stratified by course. Explainability algorithms allow the formal inspection of each factor that led to the dropout. Method: We used the Design Science Research methodology to conduct our study. An analysis with data from a specific university, considering the GDPR, was conducted to verify the proposal’s feasibility. Results: Our results show that the solution can help identify key factors that lead to dropping out, stratified by areas, helping to provide specific actions to deal with this problem in universities.
A chatbot trained to understand students’ intentions in dialogues about software testing
This paper presents the evolution of TOB-STT, a chatbot designed to support the software testing education. The chatbot assists students in resolving doubts, illustrating concepts, and demonstrating the application of testing criteria for generating test cases. The initial version, based on pattern matching, was promising but showed limitations in terms of response precision and understanding students’ intentions. Seeking to improve the quality of interactions and the effectiveness of educational support, its architecture was redesigned using natural language processing and natural language understanding techniques, resulting in a new version named TOB-STT 2.0. To evaluate it, an experimental study was conducted between the two versions. The results showed that the new version was considerably more adequate in correctly addressing students’ intentions. These findings indicate that the chatbot’s evolution has successfully improved its comprehension capabilities and, consequently, the quality of educational support it provides.
A Comparative Analysis of LLMs with Prompt Engineering Techniques for Automatic Short-Answer Classification
Automatic Short Answer Grading (ASAG) aims to reduce human effort in large-scale educational assessments, but there is still limited research in Brazilian Portuguese. This study compares three large language models (GPT-4o-mini, Sabiazinho-3, and Gemini 2.0-Flash) and analyzes the impact of seven prompt engineering elements on their performance. Using a dataset in Brazilian Portuguese, we evaluated all possible combinations of these elements. The combination of few-shot examples with an explicit rubric proved most effective; step-by-step reasoning provided additional benefit specifically for GPT-4o-mini. Sabiazinho-3 showed the highest agreement with human raters, Gemini 2.0-Flash achieved the lowest mean absolute error but produced more hallucinations, and GPT-4o-mini generated cleaner numerical outputs.
Uso de Game Analytics no Jogo Pac-Man para Análise de Jogadores: Uma Revisão Sistemática da Literatura
This article presents a systematic literature review on the use of the Pac-Man game in scientific research focused on data analysis. A total of 25 studies were selected from 7 academic databases, using both inclusion and exclusion criteria. The review identified the data collection methods employed (such as automated collection, screen capture, and sensors) and the different types of data extracted, organized into game characters, game environment, and external sources. The results reveal a wide variety in the use of Pac-Man as a study environment but also highlight a lack of standardization in data description and the still limited application of systematic analyses among internal game variables.
The Role of LLM-Based Tools in Shaping Data Science Student Behavior
This study evaluates the impact of tools based on Large Language Models (LLMs) in data science education, focusing on how reliance on these tools affects students’ analytical and technical skills. The research examines two main aspects: students’ perceptions of the tools’ impact on their analytical abilities and their behavior during data science activities. The study involved 27 students who participated in a practical exercise using a chatbot and completed questionnaires to assess their perceptions of such tools. The results suggest that students with higher levels of reliance tend to have a more positive perception of the tools, although this perception does not necessarily correlate with better performance in analytical and visualization tasks. Moreover, students who actively explore alternative approaches and modify the generated code perform better in data clustering tasks. These findings suggest that LLM-based tools can support data science education, provided that students are encouraged to develop critical thinking and go beyond the solutions automatically generated by the models.
Deu Merge*: An inclusive learning journey through pair programming between a neurotypical student and a student with ASD
This work presents a qualitative case study on the development of computing skills and competencies of a student with Autism Spectrum Disorder (ASD) and a neurotypical student during the development of an application for people with ASD. The research is presented in a life history format and draws on data sources such as ethnographic records from the students and teachers involved, student reports, code analysis, and the development strategies adopted. The results indicate that the use of pair programming can be beneficial, especially considering the unique characteristics associated with neurodivergence.
Evaluation of LLMs Regarding Basic Computer Networks Questions
The popularization of LLMs (Large Language Models) in people’s daily lives is becoming increasingly evident. Technology students with basic knowledge and internet access can consult them to support their learning. In Computer Science, computer networks are a fundamental topic, as they underpin all the infrastructure of today’s digital world. The aim of this study is to analyze responses from LLMs regarding introductory and fundamental topics in computer networks. To this end, questions covering these topics were submitted to four different LLMs. Original multiple-choice questions, a rewritten multiplechoice version, and an essay-type version were used. The results showed that the overall accuracy rate of the LLMs was equal to or higher than 97.5%.
Designing an LLM-based Multiagent System for Generating Activities and their Rubrics: A Study on Data Mining
Assessment is the primary way in which instructors evaluate students’ progress. However, the development of high-quality assessments and their corresponding rubrics requires a significant workload from instructors. In this context, Artificial Intelligence can be explored to assist in co-creating assessments and rubrics. This study proposes MASGAR, a multi-agent system designed to create activities and rubrics. We define the system’s architecture and employ a simulated test study to assess the viability of MASGAR in a Data Mining course by generating two activities and their rubrics. Results indicate that co-creation is essential for conveying human experiences and leveraging LLM-based systems in educational contexts. Students’ feedback from the course revealed that activities were coherent and creative, and suggested criteria for improvements.
Use of the Revised Bloom’s Taxonomy in an Educational RPG Game on Introductory Programming Concepts
Programming classes face several challenges, especially in terms of understanding introductory concepts and student motivation and engagement. Digital games emerge as technologies to support this teaching. In this scenario, we introduce Codeverse: Hacking Worlds, an educational game designed in the style of a role-playing game to support the teaching and learning of introductory programming concepts. It includes five worlds that progressively cover content such as variables, data types, data input and output, conditional and repetition structures, with challenges organized based on Bloom’s Revised Taxonomy as a pedagogical framework for organizing content hierarchically and providing a gradual increase in complexity.
Visual Reference Research for Image Creation: Possibilities and Challenges in RPG Game Design by Students with High Abilities/Giftedness
This article investigates the use of digital technologies in the research and creation of visual images within the context of RPG design developed by high abilities/giftedness students participating in the GEIM project at UFSM. Based on a case study, four main categories of visual reference research were identified. The results indicate that, although students show familiarity with technology, the search for images requires technical proficiency and pedagogical mediation. These findings highlight the importance of digital mediation in the creative process and the potential of RPGs as a means of enrichment for children and adolescents.
The interface at play: an analysis of cognitive load in a game on data structures
To what extent can game elements cause cognitive overload to the point of negatively impacting learning? This study, based on a design-based research (DBR) approach, investigates the user experience in an educational game about data structures, with a focus on the interface. Both qualitative and quantitative methods were used, such as thinking aloud, NASA-TLX, MEEGA+, and heatmaps, to analyze usability, aesthetics, cognitive load, and game design elements. The experiment involved computer science students and professionals with experience in educational games. The results indicate high cognitive demand in tasks requiring logical reasoning, as well as limitations related to readability and visual inconsistency. However, interest in the game and understanding of the content suggest that it may be a promising tool.
Analysis of the Production of the Amazon Hub of the Professional Master’s in Physics Teaching (MNPEF)
This paper presents a documentary analysis of the academic output of Polo 29 of the MNPEF (National Master’s Program in Physics Teaching) at the Federal University of South and Southeast Pará (Unifesspa), between 2020 and 2025, considering theses, educational products, and institutional data. The research, of a qualitative nature, reveals a predominance of didactic sequences and educational games, with a thematic concentration on Particle Physics. Competencies developed by the students were identified, such as digital literacy, the use of Digital Information and Communication Technologies (DICT), and the application of active methodologies. The results show a strong alignment with the program’s educational objectives and point to the need for thematic diversification and the strengthening of competencies for the use of emerging technologies. The study contributes to the understanding of the MNPEF’s educational impacts and provides input for continuous improvement actions.
Digital games in teaching programming logic in Brazil: a literature review
Learning abstract concepts related to programming logic and computational thinking is challenging for Computer Science courses, which leads to the search for innovative teaching methodologies. In this scenario, the use of digital games emerges as an alternative to make this learning more attractive and meaningful. To understand the panorama of Brazilian research on this topic, this paper presents the results of a Systematic Literature Review. Among the results discussed, the study reveals that although digital games promote active learning and facilitate understanding of different topics, challenges such as curricular alignment, infrastructure, and teacher training still limit their effectiveness.
Estimating Item Response Theory Parameters with NLP and Machine Learning
Item calibration in Item Response Theory (IRT) is a costly process that depends on student responses. We propose a methodology to predict the difficulty (b) and discrimination (a) parameters of new items from their text, eliminating this dependency. The method trains a regression model using real IRT parameters as a target and a feature set that combines rubrics generated by a Large Language Model (LLM) with embeddings. The results indicate that the interpretable rubrics are as predictive as the embeddings, validating a workflow for a priori item calibration that can streamline the creation of assessments.
Use of Augmented Reality in Science and Biology Teaching and Learning in Elementary and High School: A Systematic Literature Review
This paper presents a systematic literature review on the use of Augmented Reality (AR) in Science and Biology education, covering elementary and secondary levels. It analyzes 15 studies published between 2019 and 2024, identifying tools, application areas, devices, technologies, and key pedagogical trends associated with AR. The results highlight the primary use of mobile devices and development platforms like Unity 3D in AR-based educational solutions.
Automatic Generation of School Activities for Teaching English to Children
Activity sheets are essential tools for developing basic skills, integrating theoretical and practical knowledge. For children, they should be playful, creative and interactive, facilitating the association of ideas. Creating these sheets is a challenge, requiring technical and pedagogical skills, especially in language teaching. This article proposes the use of Large Language Models (LLMs) with fine-tuning to generate English as a Second Language (ESL) exercises for children. Different models were evaluated and compared against fine-tuned GPT-3.5. The approach was evaluated with the help of ESL teaching experts, based on criteria such as naturalness, usefulness, diversity and personalization. The results indicated that the fine-tuning approach is promising.
Innovation in Teaching Logic: Development and Evaluation of a Tool for Constructing Truth Tables
This paper introduces the Construir Tabelas, integrated into the Trueble learning environment, which teaches propositional logic by guiding students through the manual construction of truth tables with immediate cell-level feedback. The implementation features a custom logical keyboard, automatic sub-formula detection, and an interactive validation workflow. Usability was assessed through a heuristic inspection involving four experts, who identified 42 issues—the most critical concerning error prevention, status visibility, and visual consistency. We outline a set of prioritized fixes and, as future work, propose user studies with students, gamification features, teacher dashboards, and accessibility enhancements to broaden the tool’s educational reach.
PythonCraft: Educational Game to Reinforce Python Learning Using Minecraft Education
This article presents an educational game applied in the Introduction to Computer Programming course to reinforce control structure content. Computational thinking and gamification strategies were implemented on a per-level basis in each minigame, featuring a Programming Dojo in the final phase as a distinguishing element. The assessment method was defined by level and through observation by the facilitators. The pedagogical intervention was immediate, considering the domains of syntax, interaction, content, and mathematical concepts. The evaluation of teaching, learning, accessibility, and usability was carried out by means of a questionnaire, and the results demonstrated that the platform promotes and assesses learning in an engaging and playful manner.
Rubric-Based Assessment Following Bloom’s Taxonomy in Learning Diagnostics in Algorithms
Este artigo investiga a aplicação de rubricas como ferramentas alinhadas à Taxonomia de Bloom Revisada no diagnóstico da aprendizagem de algoritmos. No estudo foi construído e aplicado um formulário com questões que contemplam cada um dos níveis propostos pela taxonomia com o objetivo de avaliar a evolução cognitiva dos discentes por níveis e permitir uma análise detalhada das respostas facilitando o acompanhamento mais granular do processo de ensino-aprendizagem. Os resultados obtidos até então validam a proposta, sustentando a viabilidade da metodologia, possibilitando assim uma investigação dos padrões de erros, e o aprimoramento das atividades e rubricas associadas aos objetos de estudo.
ConRec: An Ontology-Based Recommender System for Concept Coverage in Education Enhanced with a Gamified Chatbot Interface
This paper presents an improvement to ConRec, an ontology-based recommender system designed to personalize learning by ensuring concept-level coverage of educational content. The system models students and learning objects using an ontology enriched with pedagogical metadata and SWRL inference rules. To enhance usability and engagement, a gamified chatbot interface was integrated into the system. The solution was evaluated in a real classroom with Computer Science undergraduates, demonstrating high satisfaction levels, increased student engagement, and improved effectiveness in supporting learning and clarifying conceptual doubts.
Computational Thinking in Food Education: A Study on Abstraction Using Problem-Based Learning and Scratch
This study investigated the integration of Computational Thinking and Problem-Based Learning into food education for 23 high school adolescents, using Scratch. The research, conducted in a public school in countryside Rio Grande do Sul, demonstrated that this interdisciplinary methodology and collaborative work promoted contextualized learning about healthy eating and developed Computational Thinking skills, even in students without prior programming experience.
Computer Vision Solution for Automatic Grading of Multiple-Choice Answer Sheets
Manual grading of multiple-choice tests is time-consuming and delays student feedback. While scanners are a common solution, they are inaccessible to many institutions. This paper proposes an alternative using smartphone cameras, addressing a gap regarding the cost-effectiveness of mobile solutions. We developed a tool using the You Only Look Once (YOLO) model to recognize answers on response sheets. After iterative testing and refinement, our solution achieved 97% accuracy with an inference time of 25ms, optimizing the grading process and accelerating evaluative feedback.
Automated Formative Feedback with LLMs: Development and Analysis of a System for Progressive Learning in Programming
Providing high-quality formative feedback to programming students remains a key challenge, especially in large-scale educational settings. Addressing this need, the present work introduces and validates an adaptive framework grounded in large language models (LLMs) for automatic code assessment and personalized feedback generation. The solution leverages pedagogical strategies and advanced prompt engineering to foster conceptual mediation and meaningful student support. Analysis of 300 real student submissions showed 74.7% agreement with traditional autograders and 93.3% of feedbacks rated as qualitatively coherent, highlighting the potential to enhance learning outcomes and expand innovative assessment practices.
TrustMatchMaker: Materializing Interpersonal Trust in VLE
Trust is a multifaceted and dynamic phenomenon, which makes it challenging to support in software systems. This article presents a prototype to support trust among students in Virtual Learning Environments (VLEs). Based on previous studies, five features emerged: trust profile, peer review, collaborative teams, network of friends, and recommendation mechanism. These features reflect key properties of trust, such as subjectivity, asymmetry, propagation, and evolution over time. The prototype allows students to evaluate their peers, recognize positive behaviors, and identify trustworthy students. In the validation process, participants highlighted the solution’s potential to improve collaborative practices by helping students identify trustworthy peers.
Exploring Educational Software in Computing Education for Students with Autism Spectrum Disorder: A Systematic Mapping Study
The growing inclusion of students with Autism Spectrum Disorder (ASD) in mainstream schooling requires adapted pedagogical approaches, especially in Computing. Educational software shows significant potential for developing computational thinking, but barriers in personalization and accessibility persist. This study presents a systematic mapping of 17 primary studies on educational software for teaching Computing to students with ASD. Our analysis reveals tools like visual programming and serious games focusing on fundamental skills, yet a lack of personalization and empirical validation remains. This mapping highlights critical research gaps and provides a structured overview to guide future development. We also classify the pedagogical strategies using Bloom’s Taxonomy and the Computational Thinking competencies using Brennan and Resnick’s framework to inform more inclusive solutions.
Reconstruction of a Logic Application Based on Functional and Pedagogical Reengineering
This article presents the functional and pedagogical reengineering of the TRUEBLE application, aimed at teaching propositional logic. The proposal integrates principles from Virtual Learning Environments (VLEs), Nielsen’s usability heuristics, and Human-Computer Interaction (HCI) guidelines. The methodology was based on an analysis of student evaluations, which revealed issues in the ”Build”and ”Learn”modules, including usability flaws, lack of didactic support, and interface clarity. Based on these findings, functional, non-functional, and pedagogical requirements were reformulated. The resulting system offers a more accessible, personalized, and educationally effective environment.
Accessibility of Mathematical Formulas in Scientific Web Articles for Visually Impaired Students in Higher Education
Accessibility in digital content is essential for educational inclusion, especially in higher education, where access to mathematical formulas in scientific articles still represents a major challenge for people with visual impairments. This study aims to evaluate the accessibility of mathematical formulas present in scientific articles. The methodology adopted involved the technical inspection of formulas in different publishers, using tests with the NVDA and JAWS screen readers. The results show some positive scenarios, but also highlight important limitations in the reading and interpretation of these contents. The importance of standardization and appropriate interaction techniques to promote inclusion is demonstrated.
Smarter Questions, Smaller Models: RAG-Enhanced Multiple-Choice Question Generation for POSCOMP
Generating high-quality multiple-choice questions (MCQs) for specialized exams like POSCOMP remains a complex and labor-intensive task. This paper proposes a Retrieval-Augmented Generation (RAG) approach to support MCQ creation using Large Language Models (LLMs). We introduce a novel data set of 1,340 past POSCOMP questions, enriched with LLM-classified themes that show strong agreement with human annotations. The RAG method was compared to a few-shot baseline across five LLMs, generating 120 MCQs evaluated by human experts and an LLM-as-a-judge using a detailed rubric. Results show that the RAG approach improves question quality in up to half of the evaluated criteria, highlighting its potential for educational assessment tasks.
Discovery Deck: constructing the concept of electric circuits from the perspective of Equilibration
This study investigated the construction of the concept of electric circuit in 4th-grade elementary school students, based on the Theory of Equilibration (PIAGET, 1976). It was grounded in a participant observation study with a qualitative approach, focusing on the interaction of the subjects with the created instrument: a card game called Baralho da Descoberta, supported by progressive challenges using the Makey Makey board. The study analyzed how the cognitive disequilibria promoted by the game mobilized the subjects' learning processes. The analysis revealed that the disequilibria produced significant cognitive perturbations, activating mechanisms of regulation and major equilibration, evidenced by the students' ability to anticipate outcomes, explore materials, and develop arrangements distinct from those suggested.
TRACE in Education: an agile and iterative approach to interdisciplinary educational projects
Higher education has been challenged to prepare professionals for complex and technologically dynamic contexts. Active methodologies based on problemand project-based learning have gained prominence, but face obstacles in interdisciplinary settings due to the lack of structured processes. This study describes and analyzes the application of the TRACE methodology as an alternative to less systematized approaches. The results revealed positive evaluations, with an emphasis on formative relevance. Male students reported higher scores in the Confidence and Satisfaction dimensions, while female students with internship commitments scored lower. It is concluded that TRACE supports student engagement and the integration of theory and practice.
Codefólio Platform: A Tool to Enhance Learning in Hybrid Education
The advancement of hybrid education demands solutions that combine personalization, automation, and student agency. In this work, we present the Codefólio platform, designed to support the Educator 5.0 in the creation and mediation of learning pathways. The platform integrates augmented intelligence (AuI) to organize content into microlearning blocks, automatically generate questionários, and apply gamification to foster engagement. The educator remains at the center of pedagogical decisions, acting as curator of the content and quizzes generated by Artificial Intelligence (AI), with the ability to customize them if desired. The system also provides detailed dashboards with learning metrics, enabling responsive interventions. The platform’s evaluation in a real-world environment indicated high acceptance by students, highlighting its potential to enhance student-centered educational practices.
Perceptions of Basic Education Computing Teachers About the History and Philosophy of Technology
The objective of this study is to present the perceptions that computer science teachers in the São Paulo state public school system have regarding concepts from the History and Philosophy of Technology, contextualized within the Digital Culture computational competence, as well as the role of continuing education in shaping these understandings. The results show that educators hold diverse views on the topic, with 43% of the responses reflecting realist perspectives on the Nature of Technology, which are reproduced in the classroom through both the formal and hidden computer science curricula.
Exploring the use of open-source LLMs for Game Learning Analytics: an empirical study
Game Learning Analytics (GLA) is essential for analyzing player behavior and identifying their learning progress through data collection and analysis. However, data modeling for GLA is a complex and challenging process. Large Language Models (LLMs) can be an alternative, especially opensource models with no usage limitations. This study investigates how the models “Gemma 2 (9B),” “Qwen 2.5 (14B),” “LLaMA 3.1 Instruct (8B),” and “Phi4 Mini (3.8B)” are capable of modeling data and filling out the data capture template from the GLBoard model. Seven GLA experts evaluated each model’s responses and identified the “Qwen” model as the most satisfactory, highlighting the potential of open-source LLMs in GLA activities.
How do LLMs analyze and interpret data from educational games? A study with GLA experts
Game Learning Analytics (GLA) holds promise for extracting insights into player learning, especially with visual analytics techniques such as dashboards. However, data analysis and interpretation are not always straightforward. An emerging alternative is the use of Large Language Models (LLMs). In this work, we investigated ChatGPT, Gemini, DeepSeek, and GLA Specialist in analyzing data from an educational game collected by the GLBoard model. We conducted an empirical study in which two GLA experts evaluated the results. In its two tested versions, Gemini performed best, excelling in profile analysis, generating pedagogical insights, and providing detailed assessments.
Assessment of Computational Thinking Learning: A Systematic Literature Mapping
This paper presents a study analysis regarding Computational Thinking (CT) evaluation focused on Elementary School, that was published in cientific digital libraries between 2016 and 2025. A systematic literature mapping was conducted focused on papers that evaluate the learnability in CT students, towards identifying which evaluation strategies and methodologies were used. A total of 913 papers were screened, of which 52 were selected. The results confirm the lack of standardized methods and metrics for evaluation and show the increasing use of digital resources and digital games as evaluation tools.
Prompt Engineering for LLM-Assisted Automated Question Generation: A Comparative Analysis
Education 5.0, powered by advances in Large Language Models (LLMs), fosters personalized, accessible, and student-centered learning experiences. In this context, the automated generation of multiple-choice questions (MCQs) emerges as a promising solution to support scalable and adaptive assessment. The effectiveness of this process largely depends on the quality of instructions provided to LLMs—defined through Prompt Engineering (PE). We present a comparative analysis of five PE, to MCQ generation in the domain of Requirements Engineering using four different LLMs. The evaluation combines cross-model assessments and human pedagogical validation based on linguistic and educational criteria. Results provide insights for a more critical and effective adoption of LLMs in educational contexts.
Evaluation of a specialist agent in Game Learning Analytics by learning designers: a case study
Using Game Learning Analytics techniques, or Learning Analytics for Serious Games, provides valuable insights to stakeholders, allowing the validation of game design and the identification of learning evidence. However, learning designers consider a preliminary step complex: modeling the data to list GLA variables. Using Large Language Models is an alternative in this scenario, which motivated us to create the “GLA Specialist” – an intelligent GLA agent – in a previous work. This research consists of a case study to evaluate it with computer science students from a public university as learning designers. The results were positive, indicating good acceptance of the agent and data models compatible with the GLBoard model, along with a list of corrections.
Elementary School teachers’ perspectives on Game Learning Analytics
Many Educational Digital Games work as a black box since they don’t allow professors to check on their students’ progress. Although the use of Game Learning Analytics can assist (GLA) in this context, there aren’t many tools and use standards, and we need more research about the stakeholders’ perceptions of this field. Therefore, this work presents a use case involving Early Education professors who interacted with a GLA system and completed a questionnaire about the field. Thus, we noticed that the professors know a few benefits related to the use of GLA, and are willing to use these technologies in their classes.
Computational Thinking and Soft Skills in the Context of Programming Education: A Systematic Mapping Study
In recent years, the teaching of computational thinking has gained prominence in scientific literature, while soft skills have been recognized as one of the major challenges in the field of Computing in Education. This paper presents a systematic review of the literature with the aim of analyzing how computational thinking and soft skills have been addressed in programming education. The results indicate a concentration on technical competencies, with little integration of interpersonal skills. Furthermore, there is a lack of well-defined pedagogical approaches and tools to guide teachers in adopting planned strategies. Therefore, the need for integrated educational proposals that promote a more comprehensive student education and expand programming teaching practices is reinforced.
Sabiá: A Generative AI Chatbot for Daily Support in Higher Education
Students often report difficulties in accessing day-to-day academic information, which is usually spread across numerous institutional documents and websites. This fragmentation results in a lack of clarity and causes confusion about routine university information. This project proposes the development of a chatbot using Generative Artificial Intelligence (GenAI) and Retrieval-Augmented Generation (RAG) to simplify access to such information. Several GenAI models were tested and evaluated based on quality metrics and the LLM-as-a-Judge approach. Among them, Gemini 2.0 Flash stood out for its quality and speed, and Gemma 3n for its good performance and open-source nature.
Connecting Knowledge: Computation’s Domains and Systems Thinking in Basic Education
Facing the challenges of integrating Computing into Brazil’s BNCC and the fragmentation of knowledge, Systems Thinking (ST) emerges as an integrative approach that enhances critical perspective, the interconnection of knowledge, and reflective practice among educators. This article provides a qualitative analysis of a pedagogical framework that articulates ST with the Computing axes in the formation of 21 educators who completed the free online course Connecting Knowledge in the Digital Age, offered by Fundação CECIERJ/CEDERJ within a continuing teacher education program. The qualitative analysis was based on reflective essays produced at the conclusion of the course. Results indicate significant transformations in teaching practices and professional identities, critical re-signification of technology, development of a transdisciplinary vision, and the emergence of an investigative stance .
A Gamification-Based Approach to Enhance Student Engagement and Attendance in High School Education
This study explores the design of Class Cup, a gamification approach to enhance student attendance, engagement, and participation that was implemented in a non-profit institution located in southeastern Brazil. The initiative confronts a critical educational challenge: low student engagement and elevated dropout rates. Class Cup aims to reframe school participation as a collective and competitive experience by utilizing team-based point systems, dynamic leaderboards, and tangible rewards. We conducted an exploratory case study to evaluate the Class Cup approach through the perceptions of 159 high school students and six teachers across five classes. After a semester of implementation, 80% of the classes showed improved attendance, resulting in an average increase of 6.22%. The results underscore the potential of a gamified approach to drive measurable behavioral change in educational settings.
Buckle Up… the Copilot Is Gone! The Impact of Secure Programming Teaching in Computing
Courses focused on computer programming are fundamental components of computing curricula. However, many programs do not adequately emphasize secure programming techniques, resulting in professionals who, although capable of developing software, do not do so securely. In this study, 85 questionnaires completed by students from two computing programs were analyzed. The students were divided into two groups: those who considered themselves capable of secure programming and those who did not. The results are concerning, revealing no significant difference in secure programming ability between the two groups. Additionally, the performance of students who received basic programming instruction with the simultaneous introduction of secure programming techniques was compared to that of students who were taught programming alone. Once again, no significant differences were observed, suggesting that teaching secure programming techniques during the initial stages of learning to program may be insufficient, or inadequate, for students to effectively acquire these skills.
Augmented Reality Applied to Education: An Immersive Experience in the Training of Information Systems Students
Augmented Reality (AR) allows the enrichment of the real world with virtual objects. This article investigates the benefits of using this immersive technology in the educational field of Computing in Higher Education, in addition to evaluating the general aspects of a digital instructional resource called ARbrnx applied in the scope of Computer Architecture knowledge. Therefore, the realization of a pedagogical workshop concatenated in a methodological path presented satisfactory results in creating a holistic pedagogical construct with experimental and engaging teaching directives.
Purpose-Driven Technical Learning: Prototyping Digital Solutions for the Community with Informatics Students
This paper presents a technical education experience that integrated computing knowledge with real social demands. Students from a technical course participated in an interdisciplinary project involving the identification of local problems and the prototyping of mobile applications as possible solutions. The methodology included collaborative demand mapping, technical analysis, and visual development using Canva. As a result, interactive prototypes were developed addressing issues such as floods, urban safety, and selective waste collection. The initiative demonstrated the potential of active and contextualized learning to enhance technical and social skills. The prototypes are currently being implemented in the final year course subjects.
Anna Carolina Rodrigues Boldrini do Nascimento
Evaluation of Critical Thinking Development in Programming Education for Technical and Higher Education Students: A Pilot Application
Critical thinking is essential in programming education, yet validated assessment instruments are scarce. This paper reports results from a pilot of ProgCTQ, based on Evidence-Centered Design, with open and Likert-scale items, applied to 29 undergraduate students. ProgCTQ showed adequate reliability (α = 0.813), but low convergent validity (r̄ = 0.121) and fragmented factorial structure (21.2% explained variance). Only 55.6% of items had satisfactory construct validity. Despite limitations, “Interpretation” and “Self-regulation” dimensions performed well, indicating the instrument’s potential for contextualized critical thinking assessment in computing.
From Signs to Text: An Intelligent System for Automatic Libras Translation Focused on Educational Inclusion
The Brazilian Sign Language (Libras) is essential for communication within the deaf community but still faces barriers in translation to written Portuguese. The lack of effective tools limits accessibility and interaction between deaf and hearing individuals. This work proposes a system based on artificial intelligence and image processing to convert Libras signs into text. The development involved video collection, preprocessing, and machine learning model training. Preliminary results indicate potential for accurate and automated translation. The solution aims to promote social and educational inclusion and assist hearing individuals interested in learning Libras.
CoderBot 2.0: Integrating LLM and Prompt Engineering in the Evolution of an Educational Chatbot
Teaching programming to beginner students remains a significant challenge, as it requires the development of complex cognitive skills. Given this, this article presents CoderBot 2.0, an evolution of a pedagogical agent designed for introductory programming instruction based on Example-Based Learning (EBL). The new version integrates Large Language Models (LLMs) and prompt engineering techniques to generate both correct and erroneous examples on demand, as well as code explanations and progressive feedback, without relying on fine-tuning. Aligned with Cognitive Load Theory, its architecture promotes metacognitive strategies such as self-explanation, fading, and contextual variation. The system offers adaptive support, adjusting to the student’s level and encouraging engagement, autonomy, and reflection.
Computing Through Play: Digital Culture in Early Elementary Education
This study presents the design and structure of an educational resource aimed at developing the skills outlined in the Digital Culture axis of the BNCC Computing curriculum for 4th and 5th grade students in Elementary School. The material consists of five chapters with playful and interdisciplinary activities on topics such as digital safety, information verification, and online citizenship. Grounded in active learning and curricular alignment, it seeks to promote student agency and support teaching practices. The resource was designed to be accessible to various school contexts, integrating unplugged activities and the use of simple digital tools.
Open Educational Resources for Teaching Computing in Early Elementary Education: Collection Available on the MECRed Platform
The implementation of computing in the Brazilian school context represents a recent and challenging development. With the expansion of the National Common Curricular Base (BNCC) and the inclusion of skills related to Computational Thinking, the Digital World, and Digital Culture, teachers face the need to find and use educational resources that address these new learning objectives. In this context, the present study aims to identify and analyze the educational resources available on the [Name Omitted] platform, with the goal of providing Early Years teachers with guidance for selecting teaching materials aligned with the requirements of the BNCC for Computing.
Assessment of Programming Learning with Generative AI in Professional and Technological Education
This article presents a generative artificial intelligence (GenAI)–mediated assessment model for programming education in Vocational and Technological Education (VTE). Grounded in principles of formative assessment and self-regulated learning, the AURAIA model integrates epistemological personalization, automated feedback, and teacher mediation through large language models (LLMs), learning management systems, and virtual tutoring. Anchored in students’ actual work, the AURAIA prototype comprises a conceptual model and a functional implementation currently undergoing preliminary validation with graduate students and faculty members.
SICAD: Digital Academic Certification System
This article presents the development of SICAD (Digital Academic Certification System), a technological solution aimed at managing and issuing certificates for complementary and extension activities. The proposal arose from the need to prove student participation in extension activities as required by Resolution No. 7/2018 of the MEC, combined with the effort required to certify these activities that occur manually or with little automation. It is expected that the proposed software product will assist in automating the certification process for students who participate in the proposed activities, providing agility to the organizers responsible for certifying these activities.
An Artificial-Intelligence-Based Application for Socio-Psychopedagogical Support: A Proposal for a System to Prevent School Dropout
School dropout in public education systems represents a critical challenge and requires more effective preventive strategies. This article proposes an intelligent system for sociopsychopedagogical support aimed at identifying students at risk of dropping out. The solution uses real data from CEMASP, including attendance, performance, and psychosocial aspects, applying supervised Artificial Intelligence techniques such as decision trees, neural networks, and SVM. The developed web application provides alerts, dashboards, and intervention suggestions. The artifact construction follows the Design Science Research methodology, aiming for validation and replication across other public education networks.
How the Educator 5.0 Will Not Be Replaced by AI: An Adaptive Microlearning Architecture Based on Augmented Intelligence
Education 5.0 proposes a human-centered model that integrates personalization, technology, and the active roles of both instructors and students. However, current educational tools still face limitations such as a lack of flexibility and monitoring capabilities. This work proposes an educational architecture that supports the Educator 5.0 in generating, customizing, and monitoring adaptive microlearning paths. The concept of augmented intelligence enhances the educator’s role as a critical curator of AI-generated content, based on their teaching materials, and as a mediator of formative learning experiences. As a result, learners obtain customized, real-time adaptive content blocks, ensuring learner diversity is respected and enabling the generation of pedagogical alerts.
Relations Between Board Game Mechanics and the Pillars of Computational Thinking
This article discusses the use of board games for the development of Computational Thinking (CT), aligned with the Unplugged Computing approach. The mechanics presented in the games are identified and an analysis is performed relating them to the pillars of CT. This provides a basis for teachers to use these games as pedagogical tools within a playful environment, resulting in a scenario where students develop cognitive problem-solving skills without the need for digital technology.
Gamification with Kahoot! in Technical Database Modeling Education: A Quasi-Experimental Study
Conceptual database modeling is a challenging topic in technical education, often associated with learning difficulties and student demotivation. This study evaluates the effectiveness of gamification, through the use of Kahoot!, in teaching this subject in technical high school courses. A quasi-experimental design was adopted, with preand post-tests comparing an experimental class (gamified instruction) and a control class (traditional teaching). The results indicate statistically significant learning gains in both groups, with greater and more consistent improvements in the gamified group. These findings suggest that gamification can effectively enhance student engagement and promote improved learning outcomes in database education.
Building New Paradigms: Computational Thinking in Architecture Education
This paper presents the preliminary results of the design, implementation, and assessment of a curriculum that incorporates Computational Thinking in the field of design. As part of the research outcomes, a lesson plan was developed for a course in a Bachelor’s degree program in Architecture and Urbanism, where the proposal is currently being applied. The initial results indicate the potential for fostering Computational Thinking in the educational process of designers, primarily through the pillar of Abstraction and the combined use of visual programming and textual programming tools.
Conquering Space with Augmented Reality and the Web in Education
Aerospace knowledge remains insufficiently represented in Brazilian educational contexts. To address this gap, the application “Conquistando o Espaço” was developed, employing Augmented Reality (AR) to enhance aerospace science education more engaging and accessible. Initially released as an Android application, technical barriers led to the development of a new web-based version in 2024, broadening its reach. This article presents the redesign process and highlights the application’s role in promoting aerospace science learning through educational and science outreach activities.
Claudia Celeste Celestino de Paula Santos
Win-win situation: Generative AI in Educational Constrained Environments
The global digital divide remains a major barrier to equitable access to technology, and this scenario compromises the pedagogical use of technology and limits learning opportunities for students from disadvantaged communities. Inequality in access to technology is a global issue that directly affects educational and socioeconomic development, especially in countries like Brazil, where there is a significant disparity in access to the Internet and technological devices between different regions and social classes. Despite ongoing efforts, 6% of the public schools still lack broadband, and 3.3% remain without electricity, according to the Ministry of Communications. This gap is most severe in rural and undeserved communities, where limited infrastructure and resources further hinder quality education. Traditional educational technology models are inadequate in such contexts. To address this challenge, we propose Unplugged Artificial Intelligence in Education (AIED), a framework designed to deliver accessible educational technologies without relying on modern infrastructure, stable internet or advanced digital skills. Our goal is to bridge the digital divide and empower students and educators with innovative tools that promote inclusion and reduce educational inequalities. This study presents a model for the deployment of LLMs in offline environments to support literacy and learning in resource-constrained areas. The proposed solution is low-cost and adaptable, allowing schools without internet access to benefit from generative AI. By deploying LLMs locally, the system provides real-time language support and generates educational content without requiring an internet connection. Preliminary results demonstrate the feasibility of running optimized generative models locally, offering practical insights into AI-powered solutions for low-resource environments. By integrating AI agents with curated educational resources, this approach promotes equity and sustainability, ensuring that generative AI serves as a tool for inclusion and innovation in education.
Minerva: An Adaptive and Personalized Solution for Organizing Studies Based on Learning Cycles
This paper presents Minerva, a mobile application designed to help students organize their study routines through adaptive and personalized learning cycles. Grounded in principles such as meta-cognition, spaced repetition, and self-regulated learning, Minerva offers features like a habit tracker, learning trail, progress dashboard, and intelligent scheduling. Unlike traditional study methods, the application enables users to dynamically adjust study goals based on personal performance and availability, promoting autonomy and motivation. An exploratory study involving 50 students was conducted based on the UTAUT model. The results indicate a high level of acceptance of the app’s concept, particularly among students with no prior experience using similar tools. Participants emphasized its innovation, usefulness, and potential impact on their study habits. While still under development, the proposal demonstrates its potential to the scientific community by integrating evidence-based educational theories with user-centered design practices. This study contributes to the advancement of adaptive educational technologies. It opens up discussions for future investigations into the efficacy of learning cycle-based study tools.
Codes of Science: A Challenge Through the Paths of Women Scientists
The escape room “Códigos da Ciência” offers an interactive journey through the history of five female scientists: Ada Lovelace, Marie Curie, Sônia Guimarães, Katherine Johnson and Bertha Lutz. Participants are invited to unravel puzzles in logic, physics, maths, computing and critical thinking based on the trajectories of these women. The proposal aims to awaken girls’ interest in STEM areas, promoting gender equity in science and popularising scientific knowledge. This article describes the design, development and preliminary results of the escape room applications, highlighting its potential as a pedagogical tool for engagement and raising awareness of the importance of female representation in science.
Generating Questions with Lightweight LLMs: An Initial Study on Educators’ Perceptions
LLMs can assist in the automatic generation of questions but require internet access or robust infrastructure, which poses a barrier in low-resource settings. Lightweight LLMs, capable of running offline on regular smartphones, emerge as an alternative, although evidence regarding the quality of the generated content is still limited. This study investigates the use of such models to generate math questions. A total of 59 questions were produced and evaluated by a pedagogue, yielding mixed results. Most were considered usable, especially those involving addition and subtraction, but showed conceptual, grammatical, and semantic limitations. The study highlights the potential of lightweight LLMs and the need for human review to ensure pedagogical quality.
Human-AI Heuristic Evaluation: Uncovering usability insights of an LLM Chatbot Interface for Personalized Learning in Autism
The rise of Large Language Models (LLMs) and Generative AI (GenAI) offers new possibilities for personalized learning but also introduces usability challenges, especially in applications designed to customize the learning experience for individuals with autism spectrum disorder (ASD). To analyze whether an LLM-powered chatbot interface is effective for this specific use case, we propose a usability heuristics inspection carried out by both human experts and an AI agent to evaluate an LLM interface for ASD curriculum personalization. Preliminary results reveal human and AI-driven usability insights towards a frictionless experience for GenAI educational interventions.
Introducing Machine Learning Through a Multisensory Approach for Young People with Down Syndrome
This paper presents an ongoing educational activity to introduce Machine Learning concepts to children and young people with Down Syndrome. In Brazil, the lack of a standard for Computer Science Education until 2022 led to disparities, with public schools often lacking resources. A 2022 regulation made Computing mandatory in K-12, aligning with the Brazilian National Common Curricular Base, which includes Artificial Intelligence-related competencies. In the Brazilian context, Computing is still not part of the school curriculum for most students without disabilities. Students with developmental disorders, such as Down Syndrome, have even less access to activities designed to teach computational skills in their learning environments. However, it is possible to observe that, when provided with technologies adapted to their needs, these students can learn and develop effectively. Therefore, this work proposes a multisensory unplugged activity tailored to introduce Machine Learning concepts to people with Down Syndrome. Given the multisensory approach, we expect to observe benefits beyond computational learning, promoting the development of fine motor skills through a playful and fun experience.
Voice-Command Virtual Assistant to Support the Education and Autonomy of Students with Motor Disabilities
Technological advances have expanded the use of computational systems, yet people with motor disabilities still face barriers in accessing these tools. This work proposes a voice-command virtual assistant, developed in Python, to promote digital inclusion. The solution uses speech recognition libraries and enables tasks such as opening applications, browsing the internet, and moving the cursor. The methodology involved exploratory research, iterative development, and practical testing. Results demonstrate the prototype’s effectiveness in controlled environments. It is concluded that the tool is promising as a foundation for more accessible and customizable assistive technologies.
Application of Kalman Filter for student enrollment prediction in public schools in Northeastern Brazil
Brazil faces logistical challenges that require advance planning for textbook acquisition under the National Textbook and Teaching Materials Program (Programa Nacional do Livro e do Material Didático, PNLD). Moreover, planning relies on past School Census data, leading administrators to estimate student numbers with at least a two-year delay. Traditional forecasting models often fail to accurately predict student enrollment, motivating the search for alternative approaches. In this study, we propose using the Kalman Filter to estimate enrollment in public schools in Brazil’s Northeast, comparing its performance against traditional time-series baselines. We analyzed 11,971 classes and observed a reduction in the average error of 1.47 students per class, indicating potential improvements.
CG.lab: development and evaluation of an interactive platform to support the teaching of linear algebra applied to computer graphics
Computer graphics is a field of technology that heavily relies on various concepts of linear algebra. Students often report difficulties with theoretical mathematical concepts, such as the lack of visualization of the practical applications of what is learned. To bridge this gap, this paper proposes the development and analysis of an interactive and visual platform for linear algebra applied to computer graphics. The platform, called CG.lab, allows students to solve problems interactively, with visualization of mathematical concepts and real-time feedback on their mistakes and correct answers. Although still in its early stages, the study conducted in this work indicated a positive reception from the students.
Integration of Digital Games and Gamification in English Teaching in the Classroom: A Case Study of the Sabará Program
Introduction: This study investigates the application of digital games and gamification in pedagogical practices for teaching English to Middle School students. Objective: The conducted investigation sought to determine the quality of impact of the analyzed educational strategies on students’ language learning. Methodology or Steps: Using a quasi-experimental approach, the methodology included assessment instruments to measure the intervention’s impact on two main metrics: English proficiency and self-confidence in linguistic abilities. Results: The results indicated an overall improvement of students across the two metrics, with notable progress in English acquisition, demonstrating the effectiveness of the applied model.
An API for Managing Digital Learning Objects Based on Semantic Web Technologies
Digital Learning Objects (DLOs) support teaching in different contexts, but still face a scarcity of open repositories and access difficulties. Semantic Web emerges as an alternative to standardize and organize these repositories. In previous work, we developed the OntoObADi, an ontology aimed at describing DLOs in semantic repositories. In this work, we propose a RESTful service that encapsulates OntoObADi, promoting the interoperability and content reuse. The API was implemented in Python with the Owlready2 library, allowing for manipulation of ontologies in OWL. With it, it is possible to create and classify individuals, apply SWRL rules, and integrate reasoners for logical inference.
Exploring innovative practices in teaching Mathematical Functions with Mathbot: a pilot study
This study presents the pilot implementation of MathBot, an interactive chatbot designed to support the teaching of Mathematical Functions with students from the Três Rios/RJ, School Network, conducted between May and June 2025. The aim was to evaluate the effectiveness of artificial intelligence in educational support, based on the Design Science Research (DSR) methodology. The chatbot provided instant responses and adaptive content, promoting personalized learning. The analysis of student interactions and feedback indicated positive acceptance, highlighting the tool’s potential and suggesting opportunities for future improvements.
Creation and Application of an Educational Chatbot for Teaching Analytic Geometry
This paper presents the development and implementation of the educational chatbot IAralítica, aimed at teaching analytic geometry to high school students. The tool is designed to support the understanding of concepts such as the Cartesian plane, distance between two points, midpoint, and alignment of three points. The research followed the Design Science Research (DSR) methodology, which guided the construction and evaluation of the artifact. The assessment, conducted with 35 students, indicated that the chatbot was effective in supporting learning, being considered useful and clear. The results highlight its potential as a complementary resource to traditional teaching, promoting more active and personalized learning.
Digit.all: An Educational Tool with Gamification for Digital Literacy of Older Adults
This article presents the Digit.all tool, developed to promote digital literacy among older adults through critical pedagogical approaches and gamification strategies. The application was designed with a focus on content modularity and support for user autonomy. To achieve this, methodologies such as microlearning, Problem-Based Learning (PBL), and engaging visual elements were employed. A preliminary evaluation was conducted with 18 experts using the SUS scale, resulting in an average score of 86.5 points, indicating excellent usability. The results demonstrate the tool’s feasibility, highlight its positive aspects, and suggest areas for improvement.
Feasibility of Parsec as a Remote Access Tool for Heavy Educational Software: A case study
Access to educational software that demands high computational performance is a challenge for university students with limited equipment. This paper investigates the feasibility of the Parsec tool as a remote access solution for technology students at Universidade do Estado do Amazonas (UEA). The research involved a diagnostic survey with 26 students and a hands-on experiment with 10 participants, who used Parsec to access the Unity software on university machines. The results indicate high acceptance of the tool, with a positive perception of its ease of use. We discuss Parsec’s potential to mitigate access disparities. It is concluded that Parsec represents a viable and promising alternative for the investigated context.
Exploring the Micro:bit in the Interdisciplinary Development of Computational Thinking and the BNCC
This paper complements the previously established relationship between the pillars of Computational Thinking (CT) and the skills and competencies of the National Common Curricular Base (BNCC), extending it to the 8th and 9th grades of elementary school. The research advances in a practical way by conducting a continuing education workshop for teachers, using the micro:bit as a pedagogical resource in the interdisciplinary development of CT and the BNCC, through the construction of educational robotics projects that encompass different areas of knowledge. The work also provides for the use of an evaluation instrument for feedback and validation by the teachers on the applicability of the proposal.
Navigable Emotions: Educational/Therapeutic Application for Emotion Recognition by People with ASD
This article discusses the process of creating an educational application aimed at recognizing emotions in adolescents and young adults with Autism Spectrum Disorder (ASD). The research is being carried out at the Specialized Rehabilitation Center (CER III) located in Tucuruí-PA, using an action research methodology and a case study. The initial phase consisted of gathering requirements from psychologists and specialists, followed by the creation of interface prototypes in Figma, and later the development of a functional prototype using Flutter following a case study at the CER in Tucuruí. Different levels of complexity were established to explore basic, intermediate and advanced emotions, combining images, descriptions and social stories. So far, progress on the project is encouraging. The gathering of requirements was successfully completed through meetings with a psychologist and a psychology assistant from the CER, as well as the prototyping of the graphical interface using Figma. These initial phases formed a robust foundation for future application development using the Flutter framework, enabling precise definition of functional and non-functional requirements, as well as providing valuable considerations for future improvements.
Generative Text-Based AI Tools in Basic Education: A Teacher Perspective
This work presents the experiences gained during a workshop in the Amazon region, aimed at training public basic education teachers in the use of artificial intelligence tools for text generation. The study employed the methodology of action research, exploring theoretical concepts and demonstrating freely available tools. The results indicated a positive impact of AI on basic education. Additionally, most of the 47 teachers reported greater efficiency in preparing teaching materials and considered that AI contributes to a more inclusive and dynamic education in the teaching-learning process.
ODS Adventure: An Educational RPG for Teaching Sustainability and Stimulating Computational Thinking in Children with ASD
This paper presents ODS Adventure, an educational RPG designed to support the teaching of the Sustainable Development Goals (SDGs) and to foster the development of computational thinking in children with Autism Spectrum Disorder (ASD). Developed based on Design Thinking principles, the game incorporates playful elements that promote computational thinking skills, aligned with the Brazilian National Common Curricular Base (BNCC) for Computing. The proposed solution aims to provide an accessible and inclusive digital environment, contributing to innovative pedagogical practices and enhancing inclusion within the field of Computing Education.
Dungeons and Diabetes: co-design of an educational game to promote diabetes awareness
Given the challenges related to a lack of knowledge about diabetes and low adherence to self-care practices, this work presents the initial proposal for the educational game Dungeons and Diabetes. Its development followed an educational game design process involving reviewing existing research and identifying learning gaps. We created the game in co-design with a student in computer science who has diabetes, and it aims to raise awareness through playful challenges that encourage reflection on daily care routines. The proposal incorporates principles from Multimedia Learning and Narrative Learning theories, resulting in a 2D proof of concept with mechanics and elements aligned with educational goals in the health context.
Proposal of a serious game to support the teaching of early math skills to children with autism spectrum disorder using tangram
Understanding mathematical abstraction is challenging for children with autism, especially those with difficulties in language and social interaction. This study presents an ongoing proposal for the development of a serious game aimed at supporting the teaching of early mathematical skills—such as matching, identification, and composition of geometric shapes—for children with Autism Spectrum Disorder (ASD), using tangram as a pedagogical tool adapted to their specific needs. The methodological approach involves an exploratory design with a qualitative focus, encompassing field research and culminating in the development of a serious game for mobile devices. Preliminary results include observations, interactions with the target audience, the construction of concrete activity prototypes, and their transposition into a virtual environment.
Big Data in Education: Student Dropout Prediction with Machine Learning
This work presents a methodology for dropout prediction using big data (N = 466,387) from an AWS data lake environment. Model training is conducted automatically using the AWS SageMaker Autopilot framework, which is less dependent on data scientists and AI specialists. As a result, models were generated for different stages of the semester, achieving an accuracy of up to 83%. The methodology offers a replicable framework for educational institutions, filling a literature gap on the practical application of ETL and AutoML in educational contexts and providing a basis for the development of decision support systems that can lead to effective and personalized interventions.
Codebricks: A 2D Educational RPG for Mobile Devices for Teaching Programming Logic with Visual Blocks
This paper presents the development of “Codebricks”, a 2D educational RPG game designed to teach programming logic to elementary and high school students. Featuring a visual block-based interface inspired by Scratch, the game allows students to build algorithms to control a character in an interactive environment. The proposal aims to make learning more accessible, engaging, and aligned with the preferences of digital natives, with a focus on usability on mobile devices. The project combines elements of gamification and computational thinking to foster engagement and meaningful learning.
Emerging Results in the Development of a Recommender System for Self-Regulated Learning
Self-regulated learning (SRL) is essential for academic performance, especially in Virtual Learning Environments (VLEs), where students require greater autonomy. However, many students have difficulty implementing effective SRL strategies. This paper presents the potential of personalized recommendation systems to assist higher education students in adopting these strategies. The paper presents significant emerging results, including: (i) the development and validation of two questionnaires to diagnose the SRL profile; (ii) the design and implementation of NeoSRL, a prototype recommendation system integrated with Google Classroom; and (iii) the modeling of SRL scenarios that support the recommendations. Initial findings indicate the feasibility of the approach and the positive acceptance of the developed tools, signaling a promising path for promoting SRL in VLEs.
A Serious Game to Reduce the Vulnerability of Children in Combating Sexual Violence – Extended Abstract
Assessment of Critical Thinking Skills in Technical and Higher Education Computing Programs: A Systematic Mapping Study
Critical thinking is an essential 21st-century skill and particularly crucial for computing professionals, who need to constantly solve complex problems and make informed decisions in a rapidly evolving technological landscape. This study presents a systematic mapping of the literature on critical thinking assessment in technical and higher education in computing. Twelve articles published between 2013 and 2024 were analyzed, identifying trends and gaps in this area. The results indicate a predominance of studies in Asian countries, focusing on higher education, especially for incoming students in Computer Science and Engineering courses. Most studies use self-assessment and standardized instruments, such as the Computational Thinking Scale (CTS), to evaluate critical thinking skills. The most frequently assessed skills are Evaluation, Analysis, Self-regulation, and Inference. Variability was observed in the quality and reporting of psychometric properties of the instruments. This mapping provides findings for educators and researchers, highlighting the need to develop more robust and specific assessment instruments for the computing context, as well as to conduct longitudinal studies on the development of critical thinking in computing education.
Supporting the Monitoring of National Education Plan Goals: A Technological Approach for Data-Driven Educational Management – Extended Abstract
The National Education Plan (PNE), enacted in 2014, established twenty goals to guide Brazilian education. States and municipalities are responsible for developing subnational plans aligned with the PNE, yet they face challenges in accessing and monitoring educational indicators. This article presents the Conecta PNE platform, developed through stakeholder interviews and the analysis of best practices and existing platforms. Grounded in open and connected data, the solution fosters transparency, strengthens interoperability across sources, and expands possibilities for comparative analysis. In doing so, it provides accessible and essential information to support managers in decision-making and in improving public education policies.
We see You: Understanding Math Teachers from Brazilian Public Schools to Design Equitable Educational Technology - Extended Abstract
Alunos de escolas públicas brasileiras precisam de auxílio em matemática. Nesse sentido, a literatura científica tem explorado maneiras de, por meio da tecnologia, auxiliar professores e alunos no processo de ensino-aprendizagem. No entanto, as pesquisas geralmente visam propor soluções sem antes investigar as necessidades de quem está na linha de frente: os professores. Assim, este artigo tem como objetivo investigar aspectos relevantes do cotidiano em sala de aula sob a ótica de professores de matemática de escolas públicas brasileiras. Utilizamos as duas primeiras fases do Design Thinking: empatizar e definir. Na primeira fase, realizamos um grupo focal com quatro professores de quatro escolas públicas de ensino fundamental, que analisamos qualitativamente utilizando a Teoria Fundamentada (Grounded Theory - GT). Com base nos resultados da GT, na segunda fase do Design Thinking, propusemos a persona e o mapa de empatia. Nossos resultados fornecem implicações para designers e desenvolvedores de soluções tecnológicas educacionais a partir da aplicação prática da pesquisa em experiência do usuário. Além disso, esperamos que nosso estudo seja um ponto de partida para novos pesquisadores da área explorarem as necessidades dos professores de escolas públicas brasileiras.
Unplugged Computing: A Resource to Stimulate Skills Related to Computational Thinking in Early Elementary Education – Extended Abstract
This study investigated the impact of Unplugged Computing activities on the development of Computational Thinking in elementary school students. Preand post-tests indicated a 45% increase in Computational Thinking related skills, demonstrating the effectiveness of the interventions. To this end, a playful and concrete pedagogical material was developed, which favored student engagement. The findings reinforce the importance of implementing continuous Unplugged Computing practices, aligned with the BNCC guidelines and the National Digital Education Policy, from the early years of basic education.
Open Educational Practices Mediated by Technology in Initial Teacher Education: Toward the Dissemination and Implementation of Open Culture in Basic Education – Extended Abstract
Desde a promulgação, em 2011, da primeira legislação específica sobre recursos educacionais abertos (REA) no país, as políticas públicas nessa área têm avançado no cenário brasileiro. Contudo, o desconhecimento ou a baixa adesão ao uso de REA ainda limitam a efetiva implementação da cultura aberta nos diferentes níveis de ensino. Nesse contexto, o objetivo deste trabalho é apresentar e discutir os resultados da aplicação de práticas educacionais abertas (PEA) em um curso superior de licenciatura, apoiadas por um repositório dinâmico de REA que integra, em um único software, as ações para reter, reusar, adaptar, remixar, redistribuir e avaliar os recursos compartilhados. Dessa forma, uma das contribuições do trabalho consiste na disponibilização de uma ferramenta de software que habilita e facilita as PEA, mitigando-se sobrecargas cognitivas para educadores e aprendizes com diferentes níveis de fluência computacional. Os resultados dos estudos de caso, realizados em três anos consecutivos, indicam que a inclusão de PEA em cursos de licenciatura promove a divulgação da cultura aberta, estimula o engajamento discente, mobiliza habilidades interdisciplinares, fomenta o protagonismo discente na produção de conhecimento e provê a curricularização da extensão. Consequentemente, enfatiza-se a relevância de adoção de PEA desde a formação inicial docente, de modo que os egressos sejam potenciais multiplicadores da cultura aberta nas escolas, com vistas à efetiva implementação e consolidação das políticas públicas atinentes.