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The Circuits and Systems Society (CASS) places a strong emphasis on advancing education within its domain. Various educational programs and resources have contributed to the professional development of CASS members for more than 20 years now. A major transformation within the Society was started in 2021 with a clear vision to become a premier educational resource within circuits and systems areas of interest. This article provides a comprehensive review of flagship educational programs and past initiatives. Insights from the lessons learned and future trends in the education ecosystem guided society’s strategies and frameworks for improving and developing new educational products and services. The benefits of learning with the CASS program are presented, highlighting the Society’s deep commitment to serving the community at large in educational pursuit for years to come. [ABSTRACT FROM AUTHOR]

Students’ diverse cognitive functions play a pivotal role in shaping their problem-solving behaviors, emphasizing the need to identify and cultivate these abilities to enhance learning outcomes in STEM education. Although learning variability is increasingly acknowledged, empirical research exploring the direct relationship between executive functions and problem-solving strategies remains limited. This study bridges that gap by investigating how specific executive functions influence students’ problem-solving behaviors in a puzzle-based learning environment. The results demonstrate that students with stronger working memory show greater adaptability in their problem-solving approaches, while those with enhanced response inhibition efficiently discard ineffective strategies to streamline their learning process. Furthermore, students excelling in interference resolution and cognitive flexibility exhibit methodical and strategic planning in their problem-solving tasks. These findings highlight the critical role of executive functions in fostering problem-solving skills and suggest that personalized instruction, tailored to students’ cognitive profiles, could significantly improve educational outcomes.

In the expanding realm of online learning, student mind wandering has become an increasingly prominent challenge, negatively impacting learning efficiency and engagement. This review systematically investigates the effectiveness of visual design as a strategic intervention to reduce mind wandering in digital educational settings. Through a comprehensive selection process, this study critically analyzes key indicators of mind wandering and evaluates existing theoretical models addressing this issue. Special attention is dedicated to interventions utilizing visual design elements, gaze tracking technologies, and Region of Interest (ROI) methods for detection and management. Additionally, the review explores advanced technological tools that apply visual design principles to enhance student focus and engagement. Findings underscore the significant potential of visual design interventions to improve the online learning experience and provide actionable insights for future research aimed at practical implementation and evaluation. This review equips educational technologists and course designers with strategies to develop more engaging and immersive online learning environments, effectively addressing the challenge of mind wandering.

Focused ultrasound devices can provide haptic sensations in a non-contact manner without constraint or weight. However, the presentation power is relatively low compared to contact-type devices. This study proposes a haptic presentation actuator that enhances the perception of virtual protrusions generated by a focused ultrasound device. Skin deformation is important for perceiving protrusion shapes. An actuator was designed by the research team consisting of a thin film and a contact body that induces skin deformation. Finite element simulation analysis and psychophysical experiments were conducted to determine the shape factor of the actuator. Questionnaires were conducted with experimental participants to determine the device’s impact on the experience in a virtual reality. As a result, the proposed device enabled the presentation of pressure perception with static pressure as small as 3 mN without vibrotactile sensation, which was previously difficult. Furthermore, it was found that the protrusion shape can be presented, improving the reality of protrusion shapes in a virtual reality setting.

Finite State Automata (FSA) serve as a fundamental mathematical model of computation, commonly explored in computer science degree programs. Traditionally, FSA are represented through state diagrams or tables, which, in educational settings necessitating assistive technologies, pose accessibility challenges, particularly for Visually Impaired People (VIP). This work is part of a broader initiative focused on creating tools for inclusive access to scientific information. Its main goal is to explore the effectiveness of a dialogue system (DS) as an alternative method for conveying FSA information to VIP, aiming to enhance their comprehension and user experience. To achieve this, a rule-based DS tailored for facilitating FSA access, with a primary focus on VIP as end users, was developed. The research involved an A/B test comparing participants’ comprehension of FSA using the rule-based DS versus standard tabular representations. Statistical analysis was also carried out to evaluate the performance differences between the two methods. The findings indicate that communication through the DS significantly outperforms the tabular representation, establishing it as a viable and effective alternative for both VIP and non-VIP. Although VIP participants displayed slightly varying performance depending on the questions, their feedback favoured the DS for its ease of use and overall user satisfaction. Additionally, the study analysed the capabilities and limitations of popular Large Language Models (LLMs) in describing graphical structures like FSA. Despite their general effectiveness in language tasks, LLMs proved inadequate for accurately and consistently describing FSA, highlighting the need for more controlled and explainable DS approaches in educational contexts.

Smart classrooms are physical learning spaces that, using data from the environment, students and teachers, are able to provide timely and valuable information to improve teaching and learning processes and foster decision-making. In this article, we provide an overview of how artificial intelligence techniques are being used to gain insights into the teaching and learning processes by analyzing data not only from the classroom context, but also from students and teachers. We identify the latest literature addressing the use of artificial intelligence techniques with data obtained from the smart classroom, present a taxonomy for the areas of application, review the state of deployment in schools, and discuss the current limitations. From the results, we conclude that the use of artificial intelligence techniques to analyze classroom data in real settings (i.e., primary and secondary schools) is still far from common. Most proposals are in the lower range of technological readiness levels and do not consider issues such as information security and privacy. Furthermore, most proposals focus on the development of technological products and do not address their impact on learning. Our paper concludes with an outlook on future work in this area with the aim of making the smart classroom a cornerstone for the future of education.

The present study is a comprehensive three-tiered empirical framework that investigates the processes of linguistic diversity and decolonization within the higher education systems of the Global South. It provides a novel complementary application of ARM for Topic Recommender Systems and explores the evolving landscape of scholarly discourse on language justice and educational reform by mapping the findings from Bibliometric Co-occurrence Analysis with LDA and BERTopic modelling respectively. Bibliometric Co-occurrence Analysis was employed to produce seminal relationships between key terms from the extant scholarly literature that subsequently leads to a detailed thematic review. Successive applications of LDA and BERTopic modelling generated a comprehensive thematic analysis that detailed the trends in academic discourse on inclusivity, multilingualism, translanguaging and decolonization of higher education curriculum. Furthermore, by the innovative use of ARM based on author keywords, this study revealed more intricate associations and patterns among research topics, giving important insights into future avenues of research. The analysis was based on data entirely retrieved from the Scopus database. It shows the consensus around the need for reform of language policies in higher education, as well as the transformative potential for advanced computational techniques in analyzing academic narratives. The findings from our methodological exploration, demonstrate the necessity of policy reform in higher education concerning linguistic pluralism and dismantling colonial legacies. This study extends the conversation around the complexities of decolonisation, linguistic equity and justice in higher education in the Global South and beyond.

The digital competences of university students are developed using a digital learning ecosystem that integrates: 1) virtual learning environments; 2) digital learning tools; and 3) learning methodologies. This research followed the methodology of systematic literature mapping and review, searching the WoS and Scopus databases and obtaining a total of 5,652 articles between 2001 and 2023. Inclusion and exclusion criteria were then applied to reduce the number of selected articles and carry out a systematic literature mapping and review. Among the relevant results of the literature mapping and systematic review, the geographic distribution of scientific publications, the educational areas in which they have been worked on, and the universities were identified. Educational methodologies, technological tools, and virtual learning environments used to develop university students’ digital competences holistically were also determined. This study is useful as it provides a comprehensive, general, and detailed overview of scientific production and its main contributions regarding the methodologies, tools, and environments that contribute to developing students’ the digital competences in higher education.

In recent years, transformer language models have made a significant impact on automatic text generation. This study focuses on the task of distractor generation in Spanish using a fine-tuned multilingual text-to-text model, namely mT5. Our method outperformed established baselines based on LSTM networks, confirming the effectiveness of Transformer architectures in such NLP tasks. While comparisons with other Transformer-based solutions yielded diverse outcomes based on the metric of choice, our method notably achieved superior results on the ROUGE metric compared to the GPT-2 approach. Although traditional evaluation metrics such as BLEU and ROUGE are commonly used, this paper argues for more context-sensitive metrics given the inherent variability in acceptable distractor generation results. Among the contributions of this research is a comprehensive comparison with other methods, an examination of the potential drawbacks of multilingual models, and the introduction of alternative evaluation metrics. Future research directions, derived from our findings and a review of related works are also suggested, with a particular emphasis on leveraging other language models and Transformer architectures.

Infographics are visual representations of data that utilize various graphic elements, including pie charts, bar graphs, line graphs, and histograms. Educators and designers can maximize the potential of infographics as powerful educational tools by carefully addressing challenges and capitalizing on emerging technologies. However, current education systems showcase the need for development guidelines and the best practices targeted at designing and developing infographics while exploring the major economic and social impacts of infographics on education. This study examines the concept and role of infographics in education, methodologies, trends, and obstacles. It evaluates potential economic implications and gives insights to design and development experts. The study is based on a scoping literature review methodology, uncovering the conceptual background and the role of infographics. The study emphasizes the unique functions of infographics in data visualization for educational purposes and investigates the current trends and practices in infographics creation. The key challenges associated with the use of infographics are also discussed. Furthermore, the study attempts to identify the cutting-edge frameworks for infographic creation and development while evaluating their economic implications for the role of global education. Finally, the potential recommendations for creating successful infographics while focusing on professional design and development are also covered. The guided literature review will be vital for understanding and using infographics in education.

Laboratory work is essential in most applied science and engineering specific coursers. The continuous advances in Information and Communication Technologies be able the use of online laboratories (OLs). Their use is increased due to the advantages they offer compared to conventional laboratories, as unfortunately verified during Covid-19 pandemic. OLs and Learning Management Systems (LMSs) are key technologies in the learning process field. Normally, the integration of OLs with LMSs is carried out using proprietary or ad-hoc solutions. Furthermore, there are standards that can be used for this integration, such as: LTI, IEEE P92741.1 (xAPI), SCORM and IEEE1876. This work elaborates a survey which has been provided to the experts of online laboratories for them to complete. Gathered information allowed authors to diagnose the level of knowledge and use of the main standards for creating and integrating OLs. In fact, the analysis of this information confirms that there is a lack of criteria for selecting one standard against the others and how use it in the online laboratory development. This work gives guidelines for selecting the most appropriate standard according to desired characteristics of the online laboratory under development.

Educational Recommender Systems (ERSs), intelligent tutoring systems that adapt their pedagogical recommendations to each student, are becoming increasingly common. Context-Sensitive Affective Educational Recommender Systems (CSAERSs) personalize the recommendations according to a learning context with multiple dimensions, including the affective dimension and the personality traits of the user. To date, in the field of educational technology, there is little or no research that focuses on offering context-sensitive, personalized, psycho-pedagogical affective support to distance-learning students in real time. Nor do there seem to be any proposals for approaches to the knowledge engineering (term which encompasses knowledge acquisition and knowledge representation) of these systems, in which the relation between the user and his or her context is crucial. There is little work on a systematic approach to the requirements-elicitation phase and to the use of ontologies in the development and validation of ERSs, in general, and CSAERSs, in particular. In this article, we report on a student-centred requirements-elicitation methodology that uses psycho-pedagogical theatre in combination with student surveys. We then illustrate its application in the design and validation of an ontology, together with a semantic-similarity function, that could serve as the nucleus of a CSAERS.

The ability to concentrate well is an important determinant of students’ learning outcomes but remains poorly understood. In this work we investigated whether there exists a mapping between students’ biosignals and perceived concentration levels. If we succeed in this mapping, a wearable can function as a Concentration Tracker, a novel feature that is missing from current wearables. For this, a wearable wristband was used to record students’ heart rate, heart rate variability, skin temperature, skin conductivity and acceleration from body changes. Additionally, students self-assessed their concentration levels using a smartphone application. We improved the accuracy by utilizing a big amount of unlabelled biodata from outside the study sessions. Our best boosted regression tree model predicted students’ concentration level with only 1.7% NMAE error. The predictions for a user not in the training set were much weaker; the best model, a convolutional neural network, achieved a prediction NMAE error of 30.7%. This implies that the users generated biosignals highly individually. Thus, models are not well transferable from one user to another without rooting them in user-specific data. Contrary to stress research, our results showed that skin conductivity had mostly a negative correlation with students’ concentration levels. Also diverging from stress reactions, skin temperature had mainly a positive correlation. Conductivity and temperature were the two dominant predictors. Further, the results suggest that an element of deep, effortless concentration was present in the learning experience of the subjects. Altogether, our work demonstrates that a concentration tracking wearable for improving learning is technically achievable.

Increasing student numbers in higher education, particularly in engineering and computer science, make it difficult for motivated lecturers to continue engaging in active teaching methods such as Flipped Classrooms and Work-Based Learning. In these settings, digital Peer Assessment can be one approach to provide effective and scalable feedback. In Peer Assessment, students assess each other’s performance whilst gaining useful reflection and judgment skills at the same time. This umbrella review of 14 review papers on the use of (digital) Peer Assessment in education provides a comprehensive overview of design choices and their consequences open to educational practitioners wishing to implement digital Peer Assessment in their courses, the type of tooling available and the possible effects of these choices on the learning outcomes as well as potential pitfalls and challenges when implementing Peer Assessment. The paper will inform and assist educators in finding or developing a tool that fits their needs.

This article demonstrates that didactic videos have the potential to enhance quality perception, performance and interest in engineering education. Emergency Remote Learning (ERL) imposed challenging conditions on education, and its impact was especially noticeable in the Science, Technology, Engineering and Mathematics (STEM) disciplines. This is mainly due to intrinsic cognitive load associated with the high presence of abstract concepts and to difficulties to establish connections among subjects to foster generative processing. Suitable integration of multimedia resources might be beneficial in both regards. The use of didactic videos as pedagogical aid is expected to yield positive results in electrical engineering education, mitigating the impact caused by ERL situations. Using concept maps to identify key concepts in the Electrical Engineering BSc, this article proposes the creation and integration of nine videos to enhance conceptual learning and the creation of links among subjects. This study encompassed three academic years (from 2019 to 2022), covering pre-ERL, ERL and post-ERL scenarios, and considering a total sample of 157 students. By using a Mixed Methods research design, this study has demonstrated how the integration of didactic videos mitigated the negative effects of the unprecedented ERL conditions, with positive impact on students’ perception on videos’ implications in enhancing their interest and understanding of the subject’s concepts.

A major challenge in education is to provide students with a personalized learning experience. This study aims to address this by developing a dialogue-based intelligent tutoring system (ITS) that imitates human expert tutors. The ITS asks questions, assesses student answers, provides hints, and even chats to encourage student engagement. We constructed the Dialogue-based Reading Comprehension Tutoring (DIRECT) dataset to simulate real-world pedagogical scenarios with the assessment labels and key sentences to support tutoring. The DIRECT dataset is based on RACE, which is a large-scale English reading comprehension dataset. In addition, we propose a neural pipeline approach to model the tutoring tasks and conduct a comprehensive analysis on the results, including a human evaluation. The results show that our model performs well in generating questions, assessing answers, and chatting, showing high potential although some challenges remain. The proposed model provides a good basis for further development of dialogue-based ITSs.

Student engagement is a key component of learning and teaching, resulting in a plethora of automated methods to measure it. Whereas most of the literature explores student engagement analysis using computer-based learning often in the lab, we focus on using classroom instruction in authentic learning environments. We collected audiovisual recordings of secondary school classes over a one and a half month period, acquired continuous engagement labeling per student (N=15) in repeated sessions, and explored computer vision methods to classify engagement from facial videos. We learned deep embeddings for attentional and affective features by training Attention-Net for head pose estimation and Affect-Net for facial expression recognition using previously-collected large-scale datasets. We used these representations to train engagement classifiers on our data, in individual and multiple channel settings, considering temporal dependencies. The best performing engagement classifiers achieved student-independent AUCs of.620 and.720 for grades 8 and 12, respectively, with attention-based features outperforming affective features. Score-level fusion either improved the engagement classifiers or was on par with the best performing modality. We also investigated the effect of personalization and found that only 60 seconds of person-specific data, selected by margin uncertainty of the base classifier, yielded an average AUC improvement of.084. [ABSTRACT FROM AUTHOR]

Education is a vital part of the development of society and it is changing over time in terms of methods, content, concepts, and models. Recently, it has been increasingly prevalent to benefit from the potentialities of Artificial Intelligence (AI) in addressing educational issues. In this research, the current state of the art of the integration of AI in K-12 education was provided. Specifically, different parts of education in which AI was employed along with the related AI categories were discussed according to different K-12 grades and courses. Additionally, technologies and environments that contributed to employing AI in education were discussed. To this end, a systematic literature review was conducted on articles and conference papers published between 2011 and 2021 in the Web of Science and Scopus databases. As the result of the initial search, 2075 documents were extracted and based on inclusive criteria and 210 documents were identified for further investigation. AI applications were categorized into Student performance, Teaching, Selection, and Behavior tasks, and Other. Machine Learning (ML) and Intelligent Tutoring System (ITS) were the most common approaches among AI categories. Furthermore, high school-related applications were more frequent and STEM courses were substantially targeted by AI. In conclusion, the remarkable impact of AI on education was concluded. The current study reveals information about the potentialities offered by AI in K-12 education which aids researchers in implementing AI-based education systems. As for future works, other databases such as ACM library and Google Scholar can be investigated as well. Furthermore, exploring the 95 papers that were excluded due to inaccessibility to their full texts can be taken into account. Finally, the papers can be also investigated in terms of pedagogical approaches or development tools.

Academics’ exposure to online learning solutions during the COVID-19 pandemic has positively changed their perception of online learning. Educational institutions have also realized the untapped potentials of blended learning. Therefore, it is almost certain that blended learning will become the new normal for course delivery in higher education in the Post-COVID-19 era. However, the existence of two modes of delivery, i.e., face-to-face and online, in addition to the large number of components that can be integrated into blended courses, raises two design challenges: (i) deciding the most appropriate proportion of online components to be integrated into a blended course; and (ii) selecting the most appropriate delivery methods to help students achieve the course outcomes. The majority of academics lack the institutional support and the tools to help them face these design challenges. To address this gap, this study presents a toolkit that can assist academics in designing successful blended learning courses. The toolkit was built based on knowledge extracted from experts in course design and online learning via two Delphi studies. It was evaluated in terms of effectiveness, efficiency, satisfaction, and quality of outcomes. The evaluation results show that in addition to providing an appropriate design, the toolkit can foster a better understanding of the different criteria that should be considered when designing a blended course.

The paper presents an empirical study conducted in the context of an advanced power electronics design course in a technical university. In selected points of the lectures formative assessments were introduced and supported by the use of clickers. The purpose of the article is to examine students’ perceptions of the effectiveness of clickers use. Individual, semi-structured student interviews conducted which were analysed using thematic content analysis. The findings reveal that the perceptions of the students with respect to the use of clickers were associated to: sustain student attention during the lecture, the provision of confirmatory and elaborative instructional feedback, the anonymity of the students’ answers, asking questions appropriate for this teaching/learning method, students’ motivation, students own suggestions for improvement, and the perceived existence of game-like elements. While in general the findings confirm the previous literature, there are a few points which are unique for this study, such as the relative importance of enhancing the students’ attention compared to other studies, as well as the importance of using appropriate questions from the subject-matter. Besides, the drawbacks of previous research on clickers are not in line with the perceived ones in the present study. The paper is concluded with providing research and practical implications. The former touch upon the potential of this study on informing the research on didactics in the field of electrical engineering in Higher Education, whereas the latter pertains to its contribution with respect to learning design in similar learning contexts.

Contribution: This article demonstrates the impact of today’s Information and Communication Technologies (ICT) in teaching software engineering (SE) course with design-based learning (DBL) and project-based learning (PBL). The results show a positive influence of integration of DBL and PBL in reducing industry gaps with improved student performance, engagement, and learning through designed PBL activities. Background: For an engineering graduate analysis, design, thinking, and validation of complex systems interactions is a desirable skill to support sustainability goals. A restructuring in delivery of the course through interactive lecture time and more project-based activities can improve students’ engagement, performance, and overall achievement in attaining desirable program learning outcomes (LOs). Intended Outcome: The objective is to provide student learning with an experience on how to apply critical thinking and creativity to specify, design, and validate software systems by focusing on challenges faced in the software industry. Application Design: Google classroom was used to conduct interactive class and tutorial sessions, design various PBL activities, exchange information, and work in teams. Throughout the semester, all learning and practice modules of the course were linked sequentially with intermediate milestones. Findings: The results show a positive outcome in helping students in attaining the knowledge, and understanding of both theoretical and practical concepts. These findings are based on academic results, PBL activities, and two anonymous surveys. The findings of statistical analysis suggest a positive influence of DBL and PBL in SE course to meet industry challenges, expectations, and overall course and program LOs. [ABSTRACT FROM AUTHOR]

Contribution: Understanding pupils’ conceptualization of robots and programming can help teachers to avoid a disconfirmation experience by selecting more appropriate educational tools, robot designers in improving the robot design, and researchers in further improvement of the field. Background: Human–robot interaction (HRI) is affected by the actual but also expected robot’s appearance and capabilities. Multiple factors, such as age, gender, media exposure, ICT exposure, or culture, influence mental models regarding robots; therefore, it is important to investigate those for a specific cohort in the designated geographical area. Research Questions: The mental models regarding robots and programming, and the way they are possibly biased by popular culture, exposure to ICT or parental influence were studied. Research questions concerned cognitive elements of mental models, namely, definitions and knowledge of robots, and programming and how those progress in time. Also, the research studied a figurative aspect of mental models regarding robots, with a focus on anthropomorphic features. Methodology: To research the influence of the short-term HRI, four classes of eight to nine years old elementary school pupils were included in a workshop where pre and postquestionnaires were used as research instruments. Besides pupils, later in this two-phase longitudinal research, after a year of formal education in Informatics, research instruments also included teachers and parents, to investigate their influence on children’s mental models. Findings: The change of mental models under the influence of the one-time workshop was not permanent. However, a combination of maturation with informal and formal intervention supports the conceptualization of programming. [ABSTRACT FROM AUTHOR]

Object-oriented programming (OOP) is not only an integral part of computing degrees but also a requirement in non-computing majors such as engineering. Understanding OOP concepts can be difficult for novice programmers, and often leads to the development of misconceptions. This is exacerbated when the discipline requires students to learn a technical low-level language such as C++, as is the case in many engineering disciplines. We propose a block-based programming language extension, Blockly-OOP, to help students learn core OOP concepts without the technical complexities associated with traditional textual languages. The Blockly-OOP Learning Environment was developed by integrating Blockly-OOP with learning activities that guide students through programming exercises that target popular OOP misconceptions. An evaluation (n = 238) in a second-year programming course (CS2) showed that a block-based programming language helps students improve their understanding of object-oriented concepts, warranting further research in this area. [ABSTRACT FROM AUTHOR]

Technologies already provide people with sophisticated and powerful digital ecosystems for lifelong and life-wide education. This article identifies grand challenges for ubiquitous and pervasive computing researchers to transform future education. It begins with a scenario to characterize learning on a day in 2030. Then it overviews broader educational needs and the pervasive computing elements for realizing them: mobile devices; embedded devices; importantly pervasive data infrastructures; and multidisciplinary foundations. Then it presents the grand challenges: 1) smart learning environments that feel safe, trusted, scrutable and controllable; 2) harness long-term, rich data for self-knowledge and shared understanding; 3) long-term personal digital learning companions; 4) augment classroom teacher's awareness and memory; 5) smart classrooms that seamlessly fit into teaching and learning; 6) metaresearch to understand if and when technology really supports learning. [ABSTRACT FROM AUTHOR]

This article explores the potential of emotional mimicry in identifying the leader and follower students in collaborative learning settings. Our data include video recorded interactions of 24 high school students who worked together in groups of three during a collaborative exam. A facial emotions recognition method was used to capture participants’ facial emotions during the collaborative work. Cross-recurrence quantification analysis was applied on the detected facial emotions to see the level and direction of emotional mimicry among the dyads in the same groups. In order to validate the cross-recurrence quantification analysis results, student interactions in terms of leading or following the task were video coded. Our findings showed that the leaders and followers identified by cross-recurrence quantification analysis findings matched the leaders and followers identified by the video coding in 70 percent of the dyadic interactions across the collaborating groups. The current findings show that video-based facial emotions recognition as a method can add to collaborative learning research, especially explaining some social, and affective dynamics about it. The study further discusses the possible variables that might confound the relationship between emotional mimicry and leader-follower interactions during collaboration. [ABSTRACT FROM AUTHOR]

One-dimensional (1-D) demonstrations, e.g., the black-box systems, have become popular in teaching materials for engineering modules due to the high complexity of the system’s multidimensional (e.g., 2-D and 3-D) identities. The need for multidimensional explanations on how multiphysics equations and systems work is vital for engineering students, whose learning experience must gain a cognitive process understanding for utilizing such multiphysics-focused equations into a pragmatic dimension. The lack of knowledge and expertise in creating animations for visualizing sequent processes and operations in academia can result in an ineffective learning experience for engineering students. This study explores the benefits of animation, which can eventually improve the teaching and student learning experiences. In this article, the use of computer-aided animation tools is evaluated based on their capabilities. Based on their strengths and weaknesses, the study offered some insights for selecting the investigated tools. To verify the effectiveness of animations in teaching and learning, a survey was conducted for undergraduate and postgraduate cohorts and automotive engineering academics. Based on the survey’s data, some analytics and discussion have offered more quantitative results. The historic data (2012–2020) analysis has validated the animations efficacy as achievements of the study, where the average mark of both modules has significantly improved, with the reduced rate of failure. [ABSTRACT FROM AUTHOR]

Self-regulated learning (SRL) is a cyclical process through which individuals plan their objectives, execute them and self-evaluate their own behavior so as to obtain their proposed goals. SRL has been investigated by different authors such as Zimmerman, Boekaerts, Winne and Hadwin, Pintrich, Efklides and Hadwin, Järvelä and Miller and it's being applied in learning environments. This systematic review describes the current state of the art in terms of the support for SRL in Massive Online Open courses (MOOC) using technologies based on psychological models. 66 studies conducted between 2010 and 2020 were analyzed by searching three multidisciplinary databases: Scopus, Web of Science and Google Scholar. The review methodology steps were the review planning, the search, literature analysis and the results report. Results show SRL in MOOCs is an emerging study area incentivized by the high dropout rate of the participants in MOOC. Regarding models of SRL, the most representative author reported was identified as Zimmerman. The most prominent self-regulation strategies used by MOOCs participants are: Goal setting, Help Seeking, Time management, Self-evaluation and Strategic planning. The platforms with research on SRL in MOOCs that stand out are Coursera, Edx, Open Edx and Moodle. We identified tools which have been developed to support SRL in MOOC and a set of good practices useful to support SLR that can be used by MOOC designers and tutors. Finally, a series of open problems and challenges that could lead to new research on the topic of SRL in MOOCs have been identified.

Universities around the world have been taking advantage of open educational resources (OERs) for publishing educational material. The teachers and students can access, the published material for teaching, learning and research through institutional repositories. This article proposes the design, construction and validation of the semantic platform (MIIDAS), considering two case studies of higher-level educational institutions (civil and military schools). The MIIDAS Platform integrates educational resources in institutional repositories related to the areas of Computing and Electronics engineering through the incorporation of Semantic Web technologies. The descriptions of resources consider metadata of the OAI-PMH protocol and also add educational metadata. The platform uses RDF resource descriptions, ontologies and the SPARQL query language to improve resource retrieval, in addition to proposing guidelines for the management of educational resources. The results of validation of the platform are presented through the development of evaluation instruments, which suggest possible ways to improve the platform. The article provides the basis for developing platforms that help in spreading open educational resources and allow the construction of semantically enrich data sets.

This study attempts to explore cognition during program comprehension through physiological evidence by recording and comparing electroencephalogram (EEG) activities in different frequency bands and the eye movements of the participants with high or low programming abilities. An experiment was conducted with thirty-three undergraduate students majoring in Computer Science. We recorded their EEG activities when they were reading two programs with three types of program constructs. At the same time, the participants’ eye movements were recorded by an eye tracker to further understand the relationship between the program comprehension process and EEG activities. Experimental results show that the high-performance participants displayed higher performance for working memory (theta power), attention resource allocation (lower alpha power), and interaction between working memory and semantic memory (upper alpha power) in program comprehension tasks of complex constructs, which proves related theories proposed in the existing research on programming and cognition. The results of this study not only offer objective evidence of the roles cognition plays in program comprehension but also provide educators with suggestions for designing suitable pedagogical strategies.

This paper explains the need for sustainable information-based management technologies for the online community-based ecosystem, its analogies, architecture design, and delivery. Subsequently, this paper describes the benefits of the proposed ecosystem compared to the currently available platforms. Additionally, this article investigates the problems in the systems of two higher learning institutions. Now, the systems used in higher education institutions are disintegrated. The proposed ecosystem objective is to bridge data redundancy and duplication gaps among higher learning institutions. The research methodologies used are document analysis, participant observation and in- depth interviews. This document creates a learning community culture among the five distinguished members: 1) Lecturers, 2) students, 3) administrators, 4) public, and 5) potential employers. Online Community-based Ecosystem (OnCE) is a system created specifically for the learning community culture. The result of the gathered data shows that the OnCE system can impact students’ learning proficiency and positively influence their learning culture. The implication of this research shows that the online community-based ecosystem is essential to support learning and ensure improved facilities, knowledge, and skills, thus preparing graduates before entering the job market, even though courses are taught remotely using educational technology.

Advancements in adaptive educational technologies, specifically the adaptive learning system, have made it possible to automatically optimize the sequencing of the pedagogical instructions according to the needs of individual learners. The crux of such systems lies in the instructional sequencing policy, which recommends personalized learning material based on the learning experiences of the learner to maximize their learning outcomes. However, limited available information such as cognitive, affective states, and competence levels of the learners ongoing knowledge points servers critical challenges to optimizing individual-specific pedagogical instructions in real-time. Moreover, making such decisions policy for every learner with a unique knowledge profile demands a trade-off between learner current knowledge and curiosity to learn next knowledge point. To address these challenges, this paper proposes a personalized adaptability knowledge extraction strategy (PAKES) using cognitive diagnosis and reinforcement learning (RL). We apply the general diagnostic model to track the current knowledge state of the learners. Subsequently, an RL-based Q-learning algorithm is employed to recommend optimal pedagogical instructions for individuals to meet their learning objectives while maintaining equilibrium among the learner-control and teaching trajectories. The results indicate that the learning analytics of the proposed framework can fairly deliver the optimal pedagogical paths for the learners based upon their learning profiles. A 62% learning progress score was achieved with the pedagogical paths recommended by the PAKES, showing a 20% improvement compared to the baseline model.

During the height of the CoViD-19 pandemic in 2020 and early 2021, schools throughout Europe have been closed for several months, leaving teachers with the responsibility of providing distance learning through video conferencing and remote-presence systems, while parents were scrambling for appropriate tools and support. School outings have also suffered from the limited mobility of students given by stay-at-home orders and other restrictions. In this paper we present a set of technologies developed to reproduce the school trip experience, allowing students to stay at home or in school and requiring only a Web browser and Internet access, while integrating communication tools that allow participants to actively be engaged in interactive lessons and educational experiences. In 2020 the tool has been used during the “CodyTrip” event, a two-day visit to the town of Urbino, attended by more than 15.000 students, followed up with a series of events in 2021 with over 115.000 participants. Results from the pilot events show very high engagement and demonstrate the feasibility of organizing online visiting experiences with massive participation without compromising the perceived interactivity of the proposed activities, which can be equally engaging for different audience demographics. Findings also suggest that this solution may be adopted not only as a contingent substitute for traveling during the pandemic, but as an effective tool to widen the scope and appeal of cultural tourism.

Existing literature has provided strong evidence that educational escape rooms are engaging and effective learning activities when they are properly conducted in the classroom. However, no prior research has determined whether the positive effects of these novel educational activities on students’ perceptions and learning persist when conducted remotely. This article performs, for the first time, a comparative study of the effectiveness of face-to-face and remote educational escape rooms. For this purpose, two versions of the same educational escape room were conducted: one in-class and one remotely. Both experiences were evaluated by means of three different instruments: (1) a pre-test and a post-test for measuring learning gains, (2) a questionnaire for assessing students’ perceptions, and (3) a web platform for recording student interaction data during the activities. The results obtained suggest that, although remote educational escape rooms for learning programming can be as engaging as their face-to-face counterparts, their learning effectiveness is somewhat lower.

Educational escape rooms are emerging as a new type of learning activity with the potential to enhance students’ learning through highly engaging experiences. However, conducting educational escape rooms effectively is very complex and there are no software tools available for this purpose. This lack of support is hindering the widespread use and adoption of these activities. This article presents Escapp, a web platform that allows teachers to conduct effective and highly engaging educational escape rooms. The platform has been used for conducting three different educational escape rooms (one face-to-face and two remotely) in three higher education settings. Three case studies were conducted to empirically evaluate the usefulness of Escapp for conducting these activities, which involved more than 400 students. On the one hand, a questionnaire was administered to students to gather their opinions on the Escapp platform, obtaining very positive results in terms of overall usefulness, usability and engagement. On the other hand, data automatically recorded by Escapp during the three educational escape rooms are presented as evidence of the high number of student interactions that take place during activities of this kind and the need of using a software system for conducting them in an effective way. The results of this article show that Escapp is a well-suited solution for conducting effective face-to-face and remote educational escape rooms.

Previous research on game-based learning has provided firm empirical evidence that playing educational video games can positively impact students’ motivation and learning outcomes at all levels of education and disciplines. However, the use and uptake of game-based learning in educational settings is being hampered by the lack of authoring tools capable of allowing teachers to easily create educational video games and adapt them according to their needs and contexts of use. Moreover, in order to determine to which extent this kind of tools are useful for teachers to conduct effective game-based learning experiences, further research is required to evaluate these tools from the teachers’ perspective, as well as to evaluate the instructional effectiveness of the educational video games that teachers can create by using them. This article contributes to fill this research gap by presenting a teacher-oriented authoring tool for educational games called SGAME, as well as by examining the teachers’ perceptions toward this tool and the effect of the educational video games it allows to create on students’ perceptions and learning outcomes. A total of three evaluation instruments were used: a questionnaire to collect teachers’ perceptions toward the SGAME authoring tool, another questionnaire to collect students’ perceptions toward a game created with SGAME, and a pre-test and a post-test to measure the students’ learning gains achieved by playing this game. A total of 201 teachers and 79 students participated in the evaluation reported in this article. The results of this article show that SGAME is an easy-to-use authoring tool that allows teachers to create motivating and effective educational video games.

Collecting student feedback is commonplace in universities. These surveys usually include both open-ended questions and Likert-type scale questions but the answers to open questions tend not to be analysed further than simply reading them. Recent research has shown that text mining and machine learning methods can be utilized to extract useful topics from masses of open student feedback. However, to our knowledge, not many off-the-shelf applications exist for processing open-ended student feedback automatically. Additionally, the use of text mining tools may not be available to all educators, as they require in-depth knowledge of text-mining, data analysis, or programming tools. To address this gap the current study presents a tool (Palaute) for analyzing written student feedback using topic modeling and emotion analysis. The utility of this tool is demonstrated with two real-life use cases: First, we analyze student feedback data collected from courses in a software engineering degree programme, and then feedback from all courses organized in a university. In our experiments, the analysis of open-ended feedback revealed that on certain software engineering course modules the workload is perceived as heavy, and on some programming courses the automatic code grader could be improved. The university-wide analysis produced indicators of good teaching quality, such as interesting courses, but also some concrete improvement points like the time given to complete course assignments. Therefore, the use of the tool resulted in actionable improvement points, which could not have been identified using only numeric feedback metrics. Based on the demonstrated utility, this paper describes the design and implementation of our open-source tool.

In terms of the leap-forward development for education experiment, both the Chinese and English educational experiment have been very successful, while the progress of the children’s mathematics education experiment in China has been relatively slow. It is believed that the main reason for this is the lack of an efficient cognitive tool or system that supports students’ study and exploration and correspondingly covers the whole curriculum of children’s math education. In recent years, basic mathematics education cognitive tools have undergone rapid development, whereas the lack of a common normalization method for continued in-depth inquiry of the relationships among Objects, Algebra, and Geometry (OAG) has led to the fragmentation of students’ mathematical knowledge. Thus, it is difficult for students to develop a systematic understanding of mathematics. Therefore this project attempts to construct a Children’s Mathematics Exploring System (CMES), which integrates with cognition theory, method, and contents of basic mathematics education to query the essence of the relationships among OAG. Specifically, the functions of CMES include the following: (1) providing cognitive tools with typical characteristics for the relationships among OAG; (2) offering a general normalized open system on which sustainable in-depth research can be conducted and a conversion tool through which the complete textbook unit of the basic mathematics education can be converted to reveal the relationships among OAG; and (3) presenting a set of cognitive theories, methods, and a system of basic mathematics education to further explore the relationships among OAG. This project will accelerate the development of cognitive technology in basic mathematics education, widen its practical applications, reduce the difficulty of mathematics cognition, and finally improve the quality and efficiency of basic mathematics education.

People with different capacities, such as the deaf and blind, have problems accessing educational content due to lack of accessible technology. Accessibility and usability are closely related concepts that share the goals for a satisfactory user experience. Existing literature establishes a direct relation between accessibility and usability, and reports that there are problems with both in learning platforms, and more generally with most websites. The objective of this paper is to evaluate the accessibility and usability of a learning platform by interrogating its participants. Three groups of students with different capacities (blind, deaf and deaf-blind) used an accessible learning platform prototype to assess the accessibility and usability of the platform and its contents. This article presents a comparative study of the perception and attitude of blind and deaf students towards the use of a learning platform adapted to their personal needs. Results showed that their attitude to the adaptation was very positive but there were differences in the perception of the ease of use of the application and with the level of difficulty to access the learning content. This work contributes to the body of knowledge by showing the effects that adaptations have on learning contents for blind and deaf students in terms of accessibility and ease of use through the analysis of the perceptions of participants. Future work may consider increasing the sample of students, as well as developing and testing new technologies and approaches that address other forms of functional diversity.

Educational robotics has proven its positive impact on the performances and attitudes of students. However, the educational environments that employ them rarely provide teachers with relevant information that can be used to make an effective monitoring of the student learning progress. To overcome these limitations, in this paper we present IDEE (Integrated Didactic Educational Environment), an educational environment for physics, that uses EV3 LEGO Mindstorms® educational kit as robotic component. To provide support to teachers, IDEE includes a dashboard that provides them with information about the students' learning process. This analysis is done by means of an Additive Factor Model (AFM). That is a well-known technique in the educational data mining research area. However, it has been usually employed to carry out analysis about students' performance data outside the system. This can be a burden for the teacher who, in most cases, is not an expert in data analysis. Our goal in this paper is to show how the coefficients of AFM provide valuable information to the teacher without requiring any deep expertise in data analysis. In addition, we show an improved version of the AFM that provides a deeper understanding about the students' learning process.

Automated Programming Assessment Systems (APAS) are used for overcoming problems associated with manually managed programming assignments, such as objective and efficient assessing in large classes and providing timely and helpful feedback. In this paper we survey the literature and software in this field and identify the set of necessary features that make APAS comprehensive - such that it can support all key stages in the assessment process. Put differently, comprehensive APAS is generic enough to meet the demands of “any” computer science course. Despite the vast number of publications, the choice of software turns out to be very limited. We contribute by developing Edgar, a comprehensive open-source APAS which, to the best of our knowledge, exceeds any other similar free and/or open-source tool. Edgar is the result of three years of development and usage in, for the time being, eight courses dealing with various programming languages and paradigms (C, Java, SQL, etc.). Edgar supports various text-based programming languages, multi-correct multiple-choice questions, provides rich exam logging and monitoring infrastructure to prevent potential fraudulent behaviour, and subsequent data analysis and visualization of students' scores, exams, question quality, etc. It can be deployed on all major operating systems and is written in a modular fashion so that it can be adjusted and scaled to a custom fit. We comment on the architecture and present data from real-world use-cases to support these claims. Edgar is in active use today (1000+ students per semester) and it is being constantly developed with new features.

MOOCs (Massive Open Online Courses) and NOOCs (Nano Open Online Courses), which are part of e-learning, are being incorporated into the online teaching strategies of higher education institutions around the world. Research on the outcomes of their implementation has shown both their educational potential and their limitations. However, little is known about the instructional effectiveness of these courses and their potential contribution to the acquisition of specific competencies linked to the TPACK (Technological Pedagogical Content Knowledge) model for the training of future Geography and History teachers. To this end, this study examines perceptions regarding the instructional effectiveness of two MOOCs and two NOOCs on geographical and historical education, through an analysis of the performance in TPACK competency dimensions of future teachers (n = 1993). Based on a cross-sectional descriptive approach, central tendency statistics analyses (mean and standard deviation) and inferential analyses (MannWhitney U test and Wilcoxon rank-sum) were used. Participants reported optimal levels of satisfaction across all competency dimensions of the model for their teacher training. Inferential statistical analyses further revealed the existence of statistically significant differences depending on participants' university and gender. Both the instrument applied and the results obtained are of use in making educational decisions regarding the design and implementation strategies of MOOCs and NOOCs specifically aimed at the professional development of future Geography and History teachers.

Currently digital educational applications are employed in education, since technological tools are very interesting and engaging for pupils. Augmented Reality (AR) is one of the most explored and successfully used technology. Thanks to the AR, the situated learning can occur; it suggests that people easily acquire new knowledge if learning occurs in a specific context and is embedded in a physical environment. This paper presents an AR application, called Geo+, for supporting primary school students in the acquisition of knowledge on the solid geometry. Geo+ has been developed by following a Human-Centered Design approach, thus several formative evaluation studies were performed to enhance the quality of the resulting application. A user study involving 96 pupils of the 3rd grade of primary school was performed in order to investigate the learning effectiveness, the engagement and the perceived workload of Geo+ at school. The results showed that Geo+ is effective in terms of student learning gain. In addition, pupils really appreciated the ease of use of the game; they were satisfied and felt engaging and comfortable during the interaction, none of them ask for help during the execution of the learning activities.

The application of natural language to improve students' interaction with information systems is demonstrated to be beneficial. In particular, advances in cognitive computing enable a new way of interaction that accelerates insight from existing information sources, thereby contributing to the process of learning. This work aims at researching the application of cognitive computing in blended learning environments. We propose a modular cognitive agent architecture for pedagogical question answering, featuring social dialogue (small talk), improved for a specific knowledge domain. This system has been implemented as a personal agent to assist students in learning Data Science and Machine Learning techniques. Its implementation includes the training of machine learning models and natural language understanding algorithms in a human-like interface. The effectiveness of the system has been validated through an experiment.

MOOCs (Massive Open Online Courses) users continue to rise in number globally, and accordingly, the electronic word of mouth (eWOM) for MOOCs is an important source of information for MOOCs learners, but research on the effects of MOOCs eWOM is still lacking. Therefore, from the perspective of group size and group recognition in the MOOCs online review forum and the internal relationships in the MOOCs course learning forum, this paper studies the influence mechanism of MOOCs eWOM on the number of registrations and completions. First, according to the literature review, based on the number of online reviews, the online rating valence and eWOM publishers in the MOOCs online review forum, as well as the number of posts and the number of teaching assistants in the MOOCs course learning forum, research hypotheses are proposed in this study to construct a conceptual model. Second, Coursera is the typical MOOCs platform that is selected as the research object to obtain data from November 2018 to August 2019. Third, after preprocessing the data, on the basis of the Hausman test, the corresponding fixed effect of an econometric model is established, and Stata is used to process the data to verify the research hypotheses. Finally, according to the research conclusions related to eWOM, to improve the number of registrations and completions of MOOCs, development suggestions are proposed for MOOCs platform providers and MOOCs course providers, as well.

The swelling use of computerized learning, accompanied by the rapid growth of information technology has become a surge of interest in the research community. Consequently, several technologies have been developed to maintain and promote computerized learning. In this study, we provided an in-depth analysis of two of the prominent computerized learning systems i.e., Intelligent Tutoring System (ITS) and Affective Tutoring System (ATS). An ITS is one of the training software systems, which use intelligent technologies to provide personalized learning content to students based on their learning needs with the aim of enhancing the individualized learning experience. Recently, researchers have demonstrated that the affect or emotional states of a student have an impact on the overall performance of his/her learning, which introduces a new trend of ITS development termed as ATS, which is the extended research of the previous one. Although there have been several studies on these tutoring systems, however, none of them has comprehensively analyzed both systems, particularly the transition from ITS to ATS. Therefore, this study examines these two tutoring systems more inclusively with regards to their architectures, models, and techniques and approaches used by taking into consideration the related researches conducted between 2014 to 2019. A crucial finding from the study is that ATS can be a promising tutoring system for the next generation learning environment by affiliating proper emotion recognition channels, along with computational intelligence approaches. Finally, this study concludes with research challenges and possible future directions and trends.

In the environmental sector, in recent years, policies and governance of marine issues have seen greater enhancement of participatory and community-based processes (for example the Blue Growth Actions of the Interreg Med Program of the European Union). The greater involvement of citizens in the processes and policies of the sea can greatly benefit the survival of the marine environment and support reforms, since most environmental problems are caused by human behavior. Changes in individual behaviors are desirable to ensure sustainable use of the ocean and its resources. These changes are possible only if there is an improvement in people's knowledge and awareness since the childhood. Ocean literacy interventions will allow people to understand their responsibilities towards the oceans and their health. For this reason, it is necessary to promote sustainable behavior changes using new educational approaches that can be effective with young pupils. The research presents a serious game and an explainer video, used in order to introduce the problem of marine litter, one of the main dangers for the marine species. The aim of the serious game was to enhance ocean literacy with a particular attention to the biodiversity of the Apulian and Mediterranean sea to raise children's awareness of the issue of caring for life in the sea. The measure of learning effectiveness confirmed that the knowledge gained can be actually acquired by children using new technologies, in general, and serious games in particular.

With the rise of distance learning, new challenges have emerged for educators. Among these challenges, developing effective and motivating group activities for students in the remote classroom is one of the top priorities to be addressed. According to existing literature, educational escape rooms have proven to be engaging and effective learning activities when conducted face-to-face. However, no prior research has analyzed the instructional effectiveness of these activities when they are conducted remotely. Furthermore, none of the educational escape rooms reported in the literature has been designed for teaching software modeling. This article analyzes an educational escape room conducted remotely in a software engineering fundamentals course for teaching software modeling. A total of three evaluation instruments were used: a pre-test and a post-test to measure students' learning gains, a questionnaire to collect students' perceptions, and a web platform for automatically gathering data on students' interactions. The contribution of this article is two-fold. On the one hand, it provides, for the first time, evidence that remote educational escape rooms can be effective learning activities. On the other hand, it provides, also for the first time, proof that educational escape rooms are effective and engaging activities for teaching software modeling.

A multi-camera system combines features from different cameras to exploit a scene of an event to increase the output image quality. The combination of two or more cameras requires prior settings in terms of calibration and architecture. Therefore, this paper surveys the available literature in terms of multi-camera systems' physical arrangements, calibrations, algorithms, and their advantages and disadvantages. We also survey the recent developments and advancements in four areas of multi-camera system applications, which are surveillance, sports, education, and mobile phones. In the surveillance system, the combination of multiple heterogeneous cameras and the discovery of Pan-Tilt-Zoom (PTZ) and smart cameras have brought tremendous achievements in the area of multi-camera control and coordination. Different approaches have been proposed to facilitate effective collaboration and monitoring among the camera network. Furthermore, the application of multi-cameras in sports has made the games more interesting in the aspect of analyses and transparency. The application of the multi-camera system in education has taken education beyond the four walls of the class. The method of teaching, student attendance enrollment, determination of students' attention, teacher and student assessment can now be determined with ease, and all forms of proxy and manipulation in education can be reduced by using a multi-camera system. Besides, the number of cameras featuring on smartphones is gaining noticeable recognition. However, most of these cameras serve different purposes, from zooming, telephoto, and wider Field of View (FOV). Therefore, future smartphones should be expecting more cameras or the development would be in a different direction.

Choosing a university specialization is a challenging decision for high-school students. Due to the lack of guidance and limited online resources, students base their decisions on subjective perceptions of family and friends. This increases the risk of high university dropout rates, and students changing their university disciplines. To address the aforementioned drawbacks, this research paper presents a Personalized Career-path Recommender System (PCRS) to provide guidance and help high school students choose engineering discipline. The design of PCRS is based on fuzzy intelligence of N-layered architecture and uses students’ academic performance, personality type, and extra-curricular skills. The association between personality type and engineering discipline was built using a sample of 1250 engineering students enrolled in seven engineering disciplines at An-Najah National University. PCRS is implemented as a mobile application and it is tested against an evaluation sample of 177 engineers. The sample consists of graduate or undergraduate engineers who are satisfied with their engineering disciplines. The evaluation examined the agreement between the recommendations generated by PCRS and the 177 actual engineering discipline of the sample. The evaluation results proved a slight agreement between the suggested recommendations of PCRS and the actual discipline of the research sample. Hence, PCRS is capable of providing guidance to high-school students who are interested in pursuing their studies in Engineering. The PCRS application is the first career-path recommender to target Palestinian community and other developing countries in the MENA region. The design of PCRS is scalable and it can be expanded in the future to consider other academic majors of higher education.

The paper describes the design and implementation of a semantic web service that retrieves theses and extends the keyword based-search of a DSpace repository taking into account the roles of advisors and steering committee members formally represented into a custom-made ontology. The service uses SPARQL queries and the serialization module of RDF DSpace, this links the item submission process and the ontology, thus the more theses are added into a repository, the more instances are inserted into the ontology. The paper provides empirical insights about how to reuse theses metadata and includes the results of an exploratory and self-management survey of usability heuristic evaluation of a web site that enables to access the proposed service. Heuristics were estimated with a purposive sample of students, teachers, and managers, the results indicated a high satisfaction level and showed that the service increased theses accessibility in the web environment. The service also generates semantically enriched datasets that coexist with the repository, they are of utility and value to educational organizations as they give institutional visibility.