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The field of Artificial Intelligence (AI) has the potential to improve teaching and learning, for example, by analyzing data produced in educational environments. Furthermore, it can also worsen inequality, as it requires students and instructors to have access to the infrastructure (smartphones or computers) required by the majority of those tools to generate and analyse data. However, access to such infrastructure is not a reality for many students around the world. To shine a light on this problem, this paper investigates, through a Systematic Mapping Study (SMS), initiatives that enable a more inclusive data analysis using AI in education, especially in scenarios with few connectivity resources. We identified that these initiatives are scarce and they are focused in the first phase of the data analysis task: the data collection. Based on the SMS results, we propose a set of recommendations for researchers to offer directions toward a more inclusive analysis of educational data using AI. [ABSTRACT FROM AUTHOR]

The Covid-19 pandemic brought changes in people's lives and in various sectors of the economy, including the education sector. In this context, students and teachers were able, through digital technologies, to continue their academic activities even in these difficult times. Many of these digital technologies were used to bridge the gap between instructors and students. Thus, in this work we reviewed the literature to better understand the usage of one of the widely known tools adopted by several schools: the Google Classroom (GC). For a more conclusive analysis, we used a systematic literature review to obtain relevant articles (N = 25), and then, we grouped them by similarity using clustering algorithms to facilitate data analysis and summarization. The best clustering algorithm among the three compared was the k-medoids, as it generated clusters with better data separation. In our research, 56% of papers were published in 2020 and 44% of papers were published in 2021. Most of the articles reported positive reviews (72%) of using Google Classroom during the pandemic due to its good usability and the possibility of browsing through hyperlinks. Nevertheless, some weaknesses were found in 28% of papers (negative or neutral review) when teachers or students faced instability in the network. In addition, some authors have presented solutions to get around the problem about the GC usage during pandemic, such as the use of other networks to support learning and the use of tools that allow synchronous communication between teacher and student. [ABSTRACT FROM AUTHOR]

CSCL investigates ways of promoting students' collaboration through technology. Although affective states and socio-emotional factors have an important effect on learning, few studies have classified and analyzed the results obtained by the scientific community to show their real impacts on in CSCL settings. The lack of a comprehensive overview and understanding of previous findings hampers the survey on research gaps, challenges and trends. This work addresses a systematic mapping of the literature for the summarization of results and discussion on research directions for the use of affective states and socio-emotional factors to support the development of intelligent CSCL environments. Six digital libraries were queried and 58 studies were deeply analyzed and categorized. Over 90% of the studies considered emotion and personality traits in the CSCL environment; most studies used personality recognition by questionnaires rather than automatic sources of inference; most technological approaches employed instruments to collect, analyze and/or represent emotions; and most papers that reported empirical experiments focused on “emotional awareness” and “interaction among students in a CSCL environment”. We have identified three main challenges to be addressed by the community in the next decade for an adequate incorporation of affective states in CSCL environments: emotional awareness, orchestration of students' interaction and group formation. [ABSTRACT FROM AUTHOR]

Interactive or Dynamic Geometry System (DGS) is a tool that help to teach and learn geometry using a computer-based interactive environment. Traditionally, the interaction with DGS is based on keyboard and mouse events where the functionalities are accessed using a menu of icons. Nevertheless, recent findings suggest that such a traditional model of interaction has a steep learning curve and is inadequate to develop DGS for devices with multi-touch screens. Thus, we propose a new interaction model for DGS based on a gesture dictionary which enables the construction and manipulation of geometric objects without the need of accessing a menu of icons. The dictionary is divided into three types: (i) kernel gestures: which are the basis for defining gestures; (ii) navigation gestures: related to the manipulation and editing of geometric objects; and (iii) basic gestures of construction: to construct geometric objects. To validate our interaction model, a DGS for mobile device, GeoTouch, has been developed using the proposed dictionary. Usability tests were performed comparing GeoTouch with three other DGS for mobile devices. The results indicate that the GeoTouch interface has fewer usability problems than the other three DGS software and it is easier to learn and interact with. [ABSTRACT FROM AUTHOR]

The development and use of ontologies in creating more intelligent and effective applications have increased in recent years. This rise in popularity is due to the potential of ontologies in providing semantics for the data consumed by machines, allowing them to reason on these data. Providing sophisticated tools that improve the development of applications based on RDF and OWL can further accelerate the adoption of the Semantic Web. In this context, some types of ontology tools have been proposed, for instance, ontology editors, ontology reasoners, triple store tools, RDF frameworks and object triple mapping (OTM) systems. In particular, OTM systems (e.g., AliBaba, KOMMA, JOINT and so on) are of utmost importance for developing ontology-based applications through the object-oriented paradigm. They map RDF triples into data objects, enabling developers to handle RDF triples as objects in object-oriented applications. In a similar way, developers of relational database applications have been using object-relational mapping (ORM) systems, for example Hibernate, to map relational databases into objects as well as to manage the object states. The main object state that Hibernate provides is the detached one; however, except for Empire, current OTM systems do not provide detached objects. The great difference between these two types of objects is that the former one has its life cycle independent of the underlying database connection, while the latter one is bound to the connection. In this way, this paper presents an object triple mapping system that supports detached objects, named JOINT-Detached (JOINT-DE). By using JOINT-DE, developers of ontology-based applications can (i) use the objects coming from the triple store as objects of the business model, (ii) use such objects as data transfer objects (DTOs) between subsystems, and (iii) use of less resources (triple store connections) to load object properties. To evaluate the proposed tool, we first describe how we conducted an experiment to empirically compare our tool with another OTM widely used by the community. We measure performance and memory usage regarding create, retrieve and update operations. Our results indicate that: (1) JOINT-DE has better performance results in all three operations; (2) JOINT-DE has an advantage over AliBaba with respect to the memory usage in the retrieve operation; (3) AliBaba uses less memory than JOINT-DE in the update operation; and (4) we could not find statistically significant differences between the tools regarding memory usage in the create operation. Finally, to illustrate the benefits of the proposed system, a case study of a real application is presented, outlining the architectural limitations of the application using an existing OTM in the literature, as well as showing positive results to the use of JOINT-DE. [ABSTRACT FROM AUTHOR]

Highlights: [•] A toolkit to support the development cycle of ontology-based applications was created. [•] We carried out an experiment with 8 novice developers to compare the toolkit with another tool. [•] Results suggest that our toolkit helps developers to create applications faster and with less errors. [•] The tool was also successfully used to develop a complete intelligent education system. [ABSTRACT FROM AUTHOR]

When the goal of group activities is to support long-term learning, the task of designing well-thought-out collaborative learning (CL) scenarios is an important key to success. To help students adequately acquire and develop their knowledge and skills, a teacher can plan a scenario that increases the probability for learning to occur. Such a scenario defines pedagogically sound structures that prevent off-task behavior and engage students in more meaningful interactions. The main difficulty in designing effective CL scenarios is transforming the teacher's intentions into elements that constitute the learning scenario. This problem is frequently observed when novice teachers attempt to improve the quality of learning and instruction by blending collaborative activities with individual activities without careful planning. With the goal of helping teachers in planning collaborative scenarios, we have developed an intelligent authoring tool referred to as CHOCOLATO using Semantic Web technologies (e.g. ontologies) in order to represent knowledge about different pedagogies and practices related to collaboration. Through the use of this knowledge, CHOCOLATO can provide intelligent guidance that helps teachers to create theory-based CL scenarios which has proven to be effective in a variety of situations. We evaluated it by conducting two experiments. We were interested in verifying whether the recommendations given by CHOCOLATO help novice teachers to design pedagogically sound CL activities, and if these activities help students to learn collaboratively in real classroom settings. The first experiment had the participation of 58 pre-service teachers that created CL scenarios with and without our authoring tool and the second experiment was carried out in a Brazilian public school together with 218 students. The results suggest that the guidance provided by CHOCOLATO do help novice teachers plan, understand and share CL scenarios more easily. They also suggest that the continuous utilization of well-designed theory-based CL activities create favorable conditions for students (particularly less knowledgeable ones) to improve their overall performance throughout the school year. [Copyright &y& Elsevier]

One of the most useful ways to enhance collaboration is to create scenarios where learners are able to interact more effectively. Nevertheless, the design of pedagogically sound and well-thought-out collaborative learning scenarios is a complex issue. This is due to the context of group learning where the synergy among learners’ interactions affects learning processes and, hence, the learning outcome. Although many advances have been made to support the designing of collaborative learning scenarios through technology, a more systematic approach is lacking. With the limitations of the current designing methods and tools, it is difficult to develop intelligent authoring systems that can guide users in order to produce more effective collaboration. One of the main difficulties with creating a more consistent (computer-understandable) approach to designing collaboration is the necessity of proposing better ways to formalize the group learning processes. In this paper, we present an innovative approach that uses ontologies and concepts from learning theories to create a framework that represents collaborative learning and its processes. Ontologies provide the necessary formalization to represent collaboration, while learning theories provide the concepts to justify and support the development of effective learning scenarios. Such an approach contributes to establish the foundations for the development of the next generation of intelligent authoring systems referred to as theory-aware systems. To verify the viability and usefulness of our proposed ontological framework in the context of systematic design, the development and use of an intelligent authoring tool for CSCL design is presented. This system is able to reason on ontologies to give suggestions that help users to create theory-compliant collaborative learning scenarios. We carried out several experiments with teachers in a geometry drawing course and the results indicate that the system helps teachers to create and interchange their scenarios more easily and facilitates the selection of important pedagogical strategies that influence positively the designing and effectiveness of group activities. [Copyright &y& Elsevier]

One of the key issues in e-learning environments is the possibility of creating and evaluating exercises. However, the lack of tools supporting the authoring and automatic checking of exercises for specifics topics (e.g., geometry) drastically reduces advantages in the use of e-learning environments on a larger scale, as usually happens in Brazil. This paper describes an algorithm, and a tool based on it, designed for the authoring and automatic checking of geometry exercises. The algorithm dynamically compares the distances between the geometric objects of the student’s solution and the template’s solution, provided by the author of the exercise. Each solution is a geometric construction which is considered a function receiving geometric objects (input) and returning other geometric objects (output). Thus, for a given problem, if we know one function (construction) that solves the problem, we can compare it to any other function to check whether they are equivalent or not. Two functions are equivalent if, and only if, they have the same output when the same input is applied. If the student’s solution is equivalent to the template’s solution, then we consider the student’s solution as a correct solution. Our software utility provides both authoring and checking tools to work directly on the Internet, together with learning management systems. These tools are implemented using the dynamic geometry software, iGeom, which has been used in a geometry course since 2004 and has a successful track record in the classroom. Empowered with these new features, iGeom simplifies teachers’ tasks, solves non-trivial problems in student solutions and helps to increase student motivation by providing feedback in real time. [Copyright &y& Elsevier]

Flow experience is one of the most ambitious targets of any user interface designer. However, it has remained elusive to evaluate how well user interfaces give rise to flow experience outside conducting invasive self-reporting-based questionnaires, which remove the users from the flow experience and can't be massively applied. At the same time, otherwise, well-built systems do track the behaviour of users on the interface, and therefore, user behaviour data could act as a reliable proxy for assessing the experience of users. Currently, there is little empirical research or data about which indices of user behaviours might correspond with having a flow experience as well as the different psychological constituents of the flow experience. Therefore, facing the challenge of using users' behaviour data to model users' experience, we investigated the associations between users' behaviour data (e.g. mouse clicks, activity time in the system, and average response time) and their self-reported flow experience by using data mining (i.e. associations rules) analysing data from 204 subjects. Results demonstrate that the speed of users' actions negatively affects the flow experience antecedents while also positively affecting the loss of self-consciousness. Our study advances the literature, providing insights to identify users' flow experience through behaviour data. [ABSTRACT FROM AUTHOR]

"Flow experience" is a term used to describe the state of being fully immersed in what you are doing. The Flow State Scale (FSS-2) was developed to assess how people feel when they are in the flow state while participating in certain sports activities. The goal of this study was to obtain a short adapted version of the FSS-2 for the Brazilian-Portuguese language and for general activities (FSS-BR-S). To do this, we translated it both ways (forwards and backwards) and verified that the translation was accurate. Methods: After getting answers from 396 Brazilian participants, we performed (1) the construct validity of the FSS-BR-S and (2) the psychometric item quality analysis. The confirmatory factorial analysis shows that a FSS-BR-S factorial model is the best fit for the data (χ2 = 44.36, p =.023, df = 27, χ2/df = 1.64, CFI = 0.99, TLI = 0.98, and RMSEA = 0.04). Reliability tests done in this structure show that the FSS-BR-S (which only has nine items) has good internal consistency. The item quality analysis reveals that its difficulty and differentiating parameters are good for estimating the overall flow state. The test information curve for the short version demonstrates that it is very useful for estimating the flow states of each disposition. Discussion and Conclusions: Based on these findings, we can conclude that the FSS-BR-S has demonstrated sufficient validity to be used with Brazilians. [ABSTRACT FROM AUTHOR]

We have investigated the formation energies and electronic structure of native defects in ZnO by a first-principles plane-wave pseudopotential method. When p-type conditions are assumed, the formation energies of donor-type defects can be quite low. The effect of self-compensation by the donor-type defects should be significant in p-type doping. Under n-type conditions, the oxygen vacancy exhibits the lowest formation energy among the donor-type defects. The electronic structure, however, implies that only the zinc interstitial or the zinc antisite can explain the n-type conductivity of undoped ZnO. © 2001 American Institute of Physics. [ABSTRACT FROM AUTHOR]

Os dados abertos educacionais trazem informações importantes sobre o cenário educacional de um país. Sua publicação traz impactos tanto em transparência quanto no aumento do potencial econômico para a sociedade como um todo por meio da gestão da aprendizagem e da tomada de decisão baseada em evidências. A Web traz muitas funcionalidades que podem estender esse potencial e, para isso, o W3C - organização responsável pelas padronizações na Web - criou a recomendação DWBP (Data on the Web Best Practices), para a produção de dados abertos que tirem proveito da arquitetura da Web. Contudo, até o momento não foram encontradas pesquisas que avaliem os dados de acordo com esse referencial. Assim, neste trabalho aplicamos um estudo de caso múltiplo, com a técnica de casos diversos considerando diferentes categorias de dados educacionais, analisando as práticas da DWBP. Como resultado, notamos poucas práticas plenamente atendidas atualmente e muitas práticas atendidas parcialmente. Isso ocorre, pois as informações disponibilizadas são de fácil acesso para o consumo humano, mas não para o processamento automático por agentes de software, inviabilizando a análise automática e contínua dos dados disponibilizados. Ao final, discutimos a adequação à recomendação, as possibilidades de intervenções tanto para a produção dos dados quanto para os portais que os hospedam e outras características percebidas durante a análise. [ABSTRACT FROM AUTHOR]

Gamification has been applied in different fields over the last years, impacting the development of technologies, services, and products towards a more game-like world. Albeit its success, some results indicated personal differences influencing the success of its application, leading to the creation of user models (e.g., Hexad), a way to represent user profiles in gamified environments. Even though a great effort has been made to create and discuss instruments to represent these user models, many of them lack investigation into their psychometric properties. At the same time, although gamification can be particularly interesting in engaging adolescents, few attempts analyzed instruments considering this population. Addressing this lack, in this study, we evaluated the psychometric properties of the gamification Hexad scale in Brazilian Portuguese considering a sample ( N = 110 ) of adolescents aged between 13 and 16 years old. Through a quantitative study (i.e., confirmatory factor analysis and correlation), we analyzed the psychometric properties of the scale and the correlations between user types when using data collected from adolescents. Results demonstrated that the current version of the scale needs improvements to better assess the user types of the Brazilian adolescent population, especially regarding the Disruptor user type. Also, the user types presented fewer correlations when compared with the adult sample. At the same time that the results of this study can be used in the academy and industry as a source of measurement of user types from Brazilian adolescents, it also opens several possibilities for new studies in personalized gamification considering this population. [ABSTRACT FROM AUTHOR]

There is an increase use of Peer Assessment (PA) approaches in On-line Learning Environments to support students and teachers on educational process. However, the community still lacks a comprehensive understanding of how Peer Assessment behaves within these educational environments, since there are no studies that make an analysis of the researches which has been conducted in this context, analysing the benefits and disadvantages of the use of Peer Assessment. Thus, the main goal of this work is to investigate and better understand how PA contributes in student learning as well as can bring benefits to the teachers involved. In order to meet our goal, we conducted a systematic literature review (SLR). In summary, the main findings are: (1) there are empirical evidences of the benefits of using PA in both industry and academy, and in several educational levels; (2) PA is most addressed to the correction of written activities on on-line courses; (3) About 60% of the articles showed PA improvement in student performance; (4) About 1/3 of the studies showed PA brings some benefits to teachers; (5) In some studies the use of the PA had difficulties, especially issues related to student motivation, which impairs the peer review process. [ABSTRACT FROM AUTHOR]

Peer Assessment (PA) offers a powerful solution that helps teachers in online learning environments to correct essays by distributing the workload among students. Nevertheless, the quality of the results in PA depends on good evaluations of reviewers. Thus, the main drawback for scaling up the use of PA is the presence of inadequate behaviours, such as being too harsh or too soft in the assessment, or even not offering a helpful feedback. This usually occurs due to the lack of motivation and engagement of students in the PA process. To deal with this problem, this paper proposes a gamified peer assessment model, where gamification elements are used to engage students in PA activities. Two experiments using the proposed model within an intelligent tutoring system called MeuTutor shows satisfactory outcomes. We verified that the average grade given by students to an essay are equivalent to those given by experts, but the time and costs to complete the assessments were largely reduced. Furthermore, the use of gamification helped to increase the amount of students' access to the system in 64.28%; increase in 10.53% the number of essays written and submitted; and improve the quantity and quality of assessments for each essay. [ABSTRACT FROM AUTHOR]

The use of Computer-Support Collaborative Learning (CSCL) scripts is an effective approach to support meaningful interactions and better learning. Unfortunately, in some situations, scripted collaboration decreases the motivation and engagement of students, which makes more difficult to use it over time. To deal with this problem, we propose to apply gamification as Persuasive Technology (PT) to induce the students to follow the scripts in the proper way without the sensation of obligation, avoiding in this way the motivation problems. To achieve this goal, it is necessary an exhaustive knowledge on gamification and its impact on Collaborative Learning (CL). Thus, we are developing an ontology to provide a formal systematization of the knowledge on gamification and its proper application in CL scenarios. In this paper, we focus in the formalization of basic concepts related to gamification as a PT in CL scenarios. Furthermore, to demonstrate the applicability of our approach, we present a case study, where we built and apply a personalized gamification model based on the ontological structures defined here. [ABSTRACT FROM AUTHOR]

Recent studies point to gamification as a resource capable of increasing student motivation and engagement in educational environments. However, an important current challenge is to understand how the implemented gamification is perceived by end users. To face this challenge, in this research, we conducted an observational study (cross-sectional, descriptive, and temporally prospective) analyzing the perception of 61 post-graduate students regarding the gamification implemented in a gamified educational system (used for 23 months) as well as, the psychological and behavioral effects of gamification on students. The main results indicate that i) students had different perceptions of the gamification elements implemented in the system and ii) they present different positive psychological and behavioral effects resulting from gamification. The study results especially contribute to the areas of educational technologies and gamification in education, providing insights related to the design of gamified education systems. [ABSTRACT FROM AUTHOR]

Autism is a neurodevelopmental disorder with deficits in communication, social interaction, and restricted and repetitive patterns of behavior. Due to these restrictions, one can cite the literacy process as a learning problem for people with autism. Although psychological interventions have been used to mitigate this problem, technology plays an essential role in this public. Recent studies show that children with autism demonstrate interest and best performance results when in contact with technology. Nevertheless, it is still a challenge to find studies that gather technological approaches to help the improvement of literacy skills. Based on this premise, this work focus on identifying technological approaches used to aid in the literacy process of children with autism. To achieve our goal, we conducted a systematic mapping where six studies were analyzed to answer our research questions. We identified several computational contributions, like software, desktop, and web applications that benefit the enhancement of the learning process of children with autism. [ABSTRACT FROM AUTHOR]

In the context of early childhood education, students need to acquire fundamental writing skills for their lifelong development. Public schools, especially in low- and middle-income countries, should monitor individual student progress to mitigate the detrimental effects of socioeconomic vulnerabilities in education. Furthermore, the volume of students often overwhelms teachers responsible for assessing handwriting texts and providing feedback. This article conducts a Systematic Literature Review (SLR) focusing on solutions for automatically evaluating students' handwriting, discussing their performance, future research directions, and areas needing further investigation. We used a mixed-methods approach to conduct our SLR, encompassing a search across four databases (ACM Digital Library, IEEE Xplore, ScienceDirect, and SpringerLink) and employed the snowballing technique. We used the initial set of papers from the database search as the foundation for the subsequent snowballing search. Findings revealed that the studies introduced computational techniques, examined or enhanced existing methods, and developed assessment tools. These solutions predominantly employed techniques such as artificial neural networks and used available datasets comprising handwritten images, answers, or student essays. Only some studies provide low-cost solutions for automatically assessing the writing abilities of underserved public school students. • We reviewed 491 papers, extracting data from 22 focusing on handwriting assessment. • We applied a mixed method using database search and the snowballing technique. • Studies frequently adopt deep learning methods to tackle the handwriting recognition problem. • Studies employ various methods to automatically assess text production, such as ANN, latent semantic analysis, content vector analysis, and CNN. • The mean accuracy for handwriting assessment was notably high at 93.64%, suggesting that the models in this group exhibited good performance. [ABSTRACT FROM AUTHOR]

Gamification has become a significant direction in designing technologies, services, products, organizational structures, and any human activities towards being more game-like and consequently being more engaging and motivating. Albeit its success, research indicates that personal differences exist with regards to susceptibility to gamification at large as well as to different types of gamification designs. As a response, models and measurement instruments of user types when it comes to gamification have been developed. One of the most discussed related instruments is the Hexad user types scale. However, there has been paucity of research related to the validity and reliability of the Hexad instrument in general but also of its different formulations and language versions. To face this gap, our study focused on analyzing the psychometric properties of the Hexad scale in Brazilian Portuguese by conducting two confirmatory factor analyses and two multi-group confirmatory factor analyses. The survey was answered by 421 Brazilian respondents (52% self-reported women, 47% self-reported men, 0.5% preferred not to provide their gender, and 0.5% checked the option "other"), from the five Brazilian regions (23 different states and the Federal District), and aged between 10 and 60 years old. Findings support the structural validity of the scale as an oblique model and indicate opportunities for small improvements. Further research, both at academy and practice, may use this study as the source of measurement of user types related to gamification (in Brazilian Portuguese), as well as, as a theoretical and practical source for further studies discussing personalized gamification. [ABSTRACT FROM AUTHOR]

In Brazil, online education has become more present in higher education institutions. To meet all the demand provided by this paradigm shift, educational technologies emerge as mediators for the realization of learning. Through this, several benefits linked to educational technologies make the technologies a fundamental measure to provide education, further reinforcing the teaching-learning process: how to teach and learn, mainly in the pandemic scenario generated by Covid-19. However, some educational technologies have limitations in their design, disregarding attributes that can be used for an adequate construction of educational technologies, in a way that makes the technology more personalized, such as: (i) age; (ii) gender; (iii) motivations; and, finally, (iv) profile and categories of students. The inequalities resulting from the current limitation in the construction of existing educational technologies are objects of study of an emerging area in the literature called Stereotype Threat. The objective of this work is to present and discuss challenges present in the development of educational technologies, as well as to discuss in the light of the literature the problems associated with stereotyping of these technologies from their elaboration to their use by the public-targeted, in view of the possibilities of producing biases and inequalities that may harm specific groups, We conclude that the theme related to Stereotyped Educational Technologies is a diversified area and needs to be better explored in view of the benefits that can come from the improvement of gamified virtual educational environments. [ABSTRACT FROM AUTHOR]

Introduction: Flow state is a psychological concept used to describe the optimal engagement in different activities. Therefore, the DFS-2 has been developed as an instrument to measure an individual's dispositional tendency to flow state as a personality trait. Objective: Aiming to obtain an adapted version of the DFS-2 for the Brazilian-Portuguese language (DFS-BR) and for general activities, we performed its forward- and backward-translation, and we validated it. Methods: After gathering answers from 681 Brazilian participants, we performed: (1) the construct validity of the DFS-BR; and (2) the psychometric item quality analysis. Results: the Confirmatory Factorial Analysis (CFA) indicates the best fit for the gathered data is a nine multi-correlated factorial model (χ2/df = 4.23, CFI = 0.94, TLI = 0.93 and RMSEA = 0.069). Reliability tests performed in this structure indicates excellent internal consistency for the DFS-BR. The item quality analysis indicates that its difficulty and discriminating parameters have a good endorsement to estimate the dispositional flow state. Additionally, we proposed and validated a short version of the DFS-BR (composed of only nine items). The validation results indicates good fit (χ2/df = 2.94, CFI = 0.98, TLI = 0.97 and RMSEA = 0.053) and good internal consistency. The Test Information Curve of the short version indicates that it is very informative in the estimation of individual dispositional flow state. Discussion and Conclusions: In view of these results, we conclude that the DFS-BR showed good evidence of its validity to be used with Brazilian people. We also suggest the use of a short version when we need only measure the person's flow state based on the principle of Occam's razor. This principle is supported by the analysis presented in this article. [ABSTRACT FROM AUTHOR]

Emotions influence cognitive processes and are essential during learning. Some emotions can negatively affect learning, as frustration and boredom; others, such as engagement, can positively affect. On the other hand, confusion can influence either negatively or positively. When students experience confusion, they may feel encouraged to seek their knowledge through focus and attention on the activity, resulting in a positive impact on learning. However, when they feel it for an extended period and cannot deal with it, the confusion can generate a cognitive overload on the students and increases the chances of the student to reject the subject that is being learned. Besides, the students' personality and their previous knowledge on the subject influence the time they can deal with confusion. Therefore, the confusion must be regulated to maximize learning, promoting a more significant engagement and preventing the abandonment of the exercise or content. The problem investigated by this work is how and when an Intelligent Tutoring System could support the regulation of confusion when felt for an extended period by a student. For this purpose, we developed an algorithm to support the choice of multimedia elements (video, figure, or text) to regulate confusion. The choice of the elements considers the student's personality traits and previous knowledge on the subject. To evaluate our algorithm, we have conducted an experiment with students (N=111) from elementary and higher education from two schools and a college for three months. We analyzed the algorithm's capacity to influence the regulation of confusion during first-degree equations solving in an Intelligent Tutoring System (PAT2Math) in subjects with extroversion and neuroticism personalities. The results show that the students who used the PAT2Math with our confusion regulation algorithm (experimental group) made fewer mistakes and solved the exercises more quickly than students who have not received any assistance regarding confusion regulation. The results indicate that the system would be regulating the confusion or negative emotions that happens after it. [ABSTRACT FROM AUTHOR]

Tools for automatic grading programming assignments, also known as Online Judges, have been widely used to support computer science (CS) courses. Nevertheless, few studies have used these tools to acquire and analyse interaction data to better understand the students' performance and behaviours, often due to data availability or inadequate granularity. To address this problem, we propose an Online Judge called CodeBench, which allows for fine‐grained data collection of student interactions, at the level of, eg, keystrokes, number of submissions, and grades. We deployed CodeBench for 3 years (2016–18) and collected data from 2058 students from 16 introductory computer science (CS1) courses, on which we have carried out fine‐grained learning analytics, towards early detection of effective/ineffective behaviours regarding learning CS concepts. Results extract clear behavioural classes of CS1 students, significantly differentiated both semantically and statistically, enabling us to better explain how student behaviours during programming have influenced learning outcomes. Finally, we also identify behaviours that can guide novice students to improve their learning performance, which can be used for interventions. We believe this work is a step forward towards enhancing Online Judges and helping teachers and students improve their CS1 teaching/learning practices. [ABSTRACT FROM AUTHOR]

Objective: To develop a web-based application for a colour pattern memory recognition task as the secondary task of a dual-task paradigm and to compare the listening effort required by adolescents with hearing loss (HL) under two conditions (HA and HA+FM system), to adolescents with normal hearing (NH). Design: Cohort study. The participants underwent a dual-task paradigm, including the Hearing in Noise Test as the primary task and a colour memory task as the secondary task. A platform, PALETA, was developed to assess the secondary task. Study sample: In total, 31 adolescents were enrolled, of which 13 adolescents had HL and 18 adolescents had NH (mean age, 14years). Results: Adolescents with NH scored significantly better on the secondary task compared to participants with HL using a HA. However, on analysing response time, no significant differences were observed among the groups. Conclusion: PALETA is proposed as a test procedure for the secondary task. The results revealed that the use of an FM system reduces the listening effort that adolescents with HL deploy to recognise speech in noise, and that listening effort data by number of correct responses is a way of investigating the benefits of using FM system. [ABSTRACT FROM AUTHOR]

Corrects an error in an article published in the volume 90 of the 'Journal of Applied Physics.'

One of the main goals of gamification in educational settings is to increase student motivation and engagement. To facilitate the design of gamified educational systems, in recent years, studies have proposed various approaches (e.g., methodologies, frameworks and models). One of the main problems, however, is that most of these approaches are theoretical, and do not provide a proof-of-concept. This paper advances the state of the art by providing a practical way to help implement this kind of system. In this study, we present, for the first time, how one can apply gamification elements in a learning system using the Design Sprint method, to guide designers and developers on replicating this process. Additionally, as starting point, we use a taxonomy composed of 21 game elements, proposed to be used within learning environments, organised into five game element categories, according to their goal/usage. Our main contribution is to present how to systematically implement the gamification elements focused on educational ends, which is of special value to practitioners, designers and developers. [ABSTRACT FROM AUTHOR]

Applying artificial intelligence in education is relevant to addressing the current educational crises. Many available solutions apply Convolutional Neural Networks (CNNs) to help improve educational outcomes. Therefore, a series of works have been developed integrating techniques in different educational contexts, for instance, in online teaching practices. Given the various studies and the relevance of CNNs for educational applications, this paper presents a systematic literature review to discuss the state-of-the-art. We reviewed 133 papers from the IEEE Xplore, ACM Digital Library, and Scopus databases. Based on our revision, we discuss characteristics of studies such as publication venues, educational context, datasets, types of CNNs models, and performance of models. We evidence that the literature regarding CNNs still misses more studies discussing educational problems faced by Global South students, considering both teaching and learning perspectives. Such a population cannot be neglected during experiments due to specific educational weaknesses (for example, basic skills) demanding personalized solutions. • A systematic literature review of 133 published papers. • China covered most publications, followed by India. • There is a research gap regarding using CNNs in some regions of the Global South. • The main educational context with CNN applications is students' performance. [ABSTRACT FROM AUTHOR]

Infographics have been used as learning materials due to their informative nature. Empirical evidence shows that this kind of visualization affects students' learning and interest. However, providing further details on which parameters ensure positive results is still required. An example of such parameter is the complexity of the infographics. Therefore, there is a need to obtain information on the impact of infographics of different levels of complexity in learning. Observing the lack of guidelines to classify the complexity of infographics, we propose a framework that considers three dimensions (i.e., visual, verbal and conceptual) to score infographics and, generate a complexity measure. We carried out a controlled experiment to evaluate the framework and verify if our complexity measure reflects the real perception of the users. Our results showed that users learned more from infographics classified as low and medium complexity. We conclude that the complexity of an infographic is a factor that affects learning and should be considered by teachers and content creators when deciding to use infographics as learning materials. [ABSTRACT FROM AUTHOR]

Purpose: This article introduces concepts and a general taxonomy used by the educational data mining (EDM) community, as well as examples of their applications, with the aims of providing audiology educators with a referential basis for developing this area. Method: A narrative review was carried out to present an overview of EDM and its main methods. Some of these methods were exemplified with analysis of real data from an Internet-based specialization course on pediatric auditory rehabilitation. Results: The review introduced EDM main concepts and applications and described methods from its area. Real data examples illustrated EDM use to predict interpersonal help-seeking, model interpersonal interaction, analyze students' trajectories within a course's module, and understand how students approached group assignments. Some of the insights provided by EDM to support teaching and learning processes were also described. Conclusions: EDM methods offer new tools to discover knowledge from digital traces (i.e., logs) and support key stakeholders (students, instructors, or course administrators) to raise awareness about course dynamics. This approach has the potential to foster a better understanding and management of educational processes in audiology distance education. [ABSTRACT FROM AUTHOR]

Flow Theory has been increasingly applied to Computers and Education to address several topics within this field (e.g., motivation, engagement, learning performance and so on). At the same time, in comparison with other recent theories related to Computers and Education, (e.g., Self-Determination Theory, S-Curve Theory, Intrinsic motivation, etc.), is a young topic, with different open research questions. Additionally, the Computers and Education community still lacks a comprehensive understanding of how Flow Theory is used in the area. Thus, this paper presents a Systematic Literature Review aiming to identify how students' flow state are measured during learning activities, how such activities are designed, which are the flow models used in Computers and Education and which are the main benefits of being in the flow state for the students. The main findings of this work are: (1) there is positive evidence about the benefits of applying Flow Theory in Computers and Education, especially, for increasing students' learning, to generate students' satisfaction, and to enable exploratory behavior; (2) the majority of studies use questionnaires to manual identify students' flow state; (3) a great diversity of flow state scales have been used; (4) the majority of studies are not designing activities for leading students to the flow state, and (5) the Csikszentmihalyi' flow model is more used. Finally, we conclude this work by showing some promising and interesting research opportunities that are underexplored in current research and practice. [ABSTRACT FROM AUTHOR]

Purpose Data providers have been increasingly publishing content as linked data (LD) on the Web. This process includes guidelines (i.e. good practices) to publish, share, and connect data on the Web. Several people in different areas, for instance, sciences, medicine, governments and so on, use these practices to publish data. The LD community has been proposing many practices to aid the publication of data on the Web. However, discovering these practices is a costly and time-consuming task, considering the practices that are produced by the literature. Moreover, the community still lacks a comprehensive understanding of how these practices are used for publishing LD. Thus, the purpose of this paper is to investigate and better understand how best practices support the publication of LD as well as identifying to what extent they have been applied to this field.Design/methodology/approach The authors conducted a systematic literature review to identify the primary studies that propose best practices to address the publication of LD, following a predefined review protocol. The authors then identified the motivations for recommending best practices for publishing LD and looked for evidence of the benefits of using such practices. The authors also examined the data formats and areas addressed by the studies as well as the institutions that have been publishing LD.Findings In summary, the main findings of this work are: there is empirical evidence of the benefits of using best practices for publishing LD, especially for defining standard practices, integrability and uniformity of LD; most of the studies used RDF as data format; there are many areas interested in dissemination data in a connected way; and there is a great variety of institutions that have published data on the Web.Originality/value The results presented in this systematic review can be very useful to the semantic web and LD community, since it gathers pieces of evidence from the primary studies included in the review, forming a body of knowledge regarding the use best practices for publishing LD pointing out interesting opportunities for future research. [ABSTRACT FROM AUTHOR]

Systems development based on the application of semantic web technologies is gradually growing, especially in the field of e-learning. A key aspect in the field of e-learning is instructional design, which facilitates the creation of online courses. Several studies have been conducted on the use of ontologies and semantic web technologies in open e-learning platforms, which have obtained several benefits in terms of better learning and better orchestration of instructional practices. Nevertheless, there are notably few reports related to instructional design using semantic web technologies. Thus, the primary objective of this paper is to present a systematic literature review of primary research proposals that involve the field of instructional design combined with the use of semantic web technologies. From a total of 5035 initially gathered papers, 21 of them were related to instructional design and were deeply analyzed. Our results indicate a lack of interest in including certain aspects, such as pedagogical approach, standards, and compatibility with virtual learning environments. It is suggested that the systems should incorporate characteristics of semantic web technologies in virtual learning environments. [ABSTRACT FROM AUTHOR]

The use of ontologies to represent CSCL scenarios have been investigated by several researchers in the literature. Despite of important contributions of such works, we have observed the lack of studies that consider the aspects related to student's affect (e.g., personality trait) to represent such scenarios. Thus, this paper aims at extending the ontological structure of Affective Collaborative Learning (ACL) role to represent the relation between Stable/Unstable Extroverted personality traits and Full Participant role defined by the Distributed Cognition learning theory. Based on such ontological structure we create three CSCL scenarios to deal with lack of student's reflection. In order to evaluate the impact of low and high impulsivity characteristics on such scenarios, we developed a case study with children aged between 09-10 to verify three alternative hypotheses. The results indicate that low impulsivity in homogeneous groups, where students performed the ACL role Extroverted Stable Full Participant, does not influence the group performance. Based on such ontological structure we hope to contribute with solutions to create more effective and personalized CSCL scenarios. [ABSTRACT FROM AUTHOR]

The international Semantic Web community has produced several tools, known as API – application programming interfaces, to help development teams to create applications using semantic technologies. One important family of tools developed to date is related to the manipulation of instances in ontology-based applications. There are two main approaches for manipulating ontology instances in currently developed APIs: (a) using RDF (resource description framework) triples or (b) using classes in object-oriented programming (OOP). In APIs based on RDF triples the development teams need to understand how ontology works in the RDF layers in order to manipulate data for each triple in the application code. Such an approach is highly desired to develop clean applications based strongly on Semantic Web Technologies. Nevertheless, it requires development teams to change their programming paradigm and master those technologies. In APIs based on OOP developers can manipulate data at object level in order to make application development simple and flexible using the conventional programming paradigm. Because of that, several developers have shifted from RDF triples to OOP. Although several tools have been developed to manipulate ontologies at object level, many have not been adequately evaluated for performance and scalability. In effect, there is an urgent demand for effective research results regarding metrics and systems to evaluate the performance and scalability of ontology persistent APIs. As a result, these systems should facilitate the evaluation of persistent APIs to developers. This study thus aims to provide a system for developers to evaluate ontology persistent APIs at object level. In order to validate the feasibility of our system, we have conducted an experiment by considering two solutions used by community of ontology persistence. [ABSTRACT FROM AUTHOR]

In this work, we present an approach to model and analyze students interactions, within a gamified on-line learning environment, in order to assist teachers and tutors (education professionals) decision-making, regarding their students learning experience. We noticed that asking students this information might not bring precise and dynamic results for all students. This way, we characterize the educational resources available in the studied environment, and collected data from students interactions with these resources. Our objective was to generate the students’ interactional profile (a model of their interactions). The information, then, is presented to teachers and tutors, who should use it to guide their pedagogical decision-making process. In this study, the types of interactions were used to personalize gamification elements named missions. We experimented the approach with two groups of users from the studied environment (MeuTutor). The data analysis showed differences in the way these groups were performing, where group B was considerably above group A. We sent the personalized missions (following our approach) to every student from group A, and waited some time for them to interact with it. In the end we checked the effect of this treatment, which, according to the results, promoted relevant improvement in group A interactions. [ABSTRACT FROM AUTHOR]

There is an increase use of ontology-driven approaches to support requirements engineering (RE) activities, such as elicitation, analysis, specification, validation and management of requirements. However, the RE community still lacks a comprehensive understanding of how ontologies are used in RE process. Thus, the main objective of this work is to investigate and better understand how ontologies support RE as well as identify to what extent they have been applied to this field. In order to meet our goal, we conducted a systematic literature review (SLR) to identify the primary studies on the use of ontologies in RE, following a predefined review protocol. We then identified the main RE phases addressed, the requirements modelling styles that have been used in conjunction with ontologies, the types of requirements that have been supported by the use of ontologies and the ontology languages that have been adopted. We also examined the types of contributions reported and looked for evidences of the benefits of ontology-driven RE. In summary, the main findings of this work are: (1) there are empirical evidences of the benefits of using ontologies in RE activities both in industry and academy, specially for reducing ambiguity, inconsistency and incompleteness of requirements; (2) the majority of studies only partially address the RE process; (3) there is a great diversity of RE modelling styles supported by ontologies; (4) most studies addressed only functional requirements; (5) several studies describe the use/development of tools to support different types of ontology-driven RE approaches; (6) about half of the studies followed W3C recommendations on ontology-related languages; and (7) a great variety of RE ontologies were identified; nevertheless, none of them has been broadly adopted by the community. Finally, we conclude this work by showing several promising research opportunities that are quite important and interesting but underexplored in current research and practice. [ABSTRACT FROM AUTHOR]

Serious games are being used ever more for purposes of learning, training and human performance evaluation. However, to be successful as a final product, its development has to be systematic and multi-disciplinary. Thus, the choice of support tools impact beyond the financial cost. This paper describes an overview of the iterative and integrative methodology for developing serious games, expanding the specification with open source tools. Appropriate tools are reviewed and selected in order to provide a set of applications that could be used according to serious games design needs. They are grouped into support tools to general use, database management systems, game engines, design and implementation. In addition, the uses of this methodology and these tools are exemplified with two different scenarios. [ABSTRACT FROM AUTHOR]

Flow is the affective state in which a learner is so engaged and involved in an activity that nothing else seems to matter. In this sense, to help students in the skill development and knowledge acquisition (referred to as learners' growth process) under optimal conditions, the instructional designers should create learning scenarios that favor the learner's flow. One-way to obtain these scenarios is to incorporate the conditions postulated by the Flow Theory in the context of the instructional design process. However, little attention has been drawn to this integration, and how to apply the Flow Theory based on learning theories that provide theoretical justifications during the instructional design process. Thus, in this paper, we propose a framework to integrate the learner's growth process and the Flow Theory. It provides adequate support for the instructional design of learning scenarios that lead and maintain learners in flow state. We demonstrate the usefulness of this framework by presenting an application that helps designers to search and select learning objects that have the potential to maintain the learner's flow in a learning scenario. [ABSTRACT FROM AUTHOR]

Purpose The purpose of this paper is to describe an experimental study to reduce cognitive load and enhance usability for interactive geometry software. Design/methodology/approach The Graphical User Interface is the main mechanism of communication between user and system features. Educational software interfaces should provide useful features to assist learners without generate extra cognitive load. In this context, this research aims at analyzing a reduced and a complete interface of interactive geometry software, and verifies the educational benefits they provide. We investigated whether a reduced interface makes few cognitive demands of users in comparison to a complete interface. To this end, we designed the interfaces and carried out an experiment involving 69 undergraduate students. Findings The experimental results indicate that an interface that hides advanced and extraneous features helps novice users to perform slightly better than novice users using a complete interface. After receiving proper training, however, a complete interface makes users more productive than a reduced interface. Originality/value In educational software, successful user interface designs minimize the cognitive load on users; thereby users can direct their efforts to maximizing their understanding of the educational concepts being presented. [ABSTRACT FROM AUTHOR]

One of the great challenges for Computer Supported Collaborative Learning (CSCL) research area is the creation of learning groups, ensuring the synergy among their members, so that the educational benefits are fully achieved. In order to promote this synergy, researchers on Affective Computing discuss the importance of considering the affective states (emotion, mood and personality trait) in the creation of learning groups. However, there are few papers that study, classify and analyze the results obtained by the scientific community showing the real impacts of affective states in learning group. This paper presents the development of a systematic mapping that investigates which and how affective states are considered in the learning group formation. In particular we intend to answer the research questions: (i) What are the affective states used in group formation in CSCL environment? (ii) Which techniques are used in group formation to (affective states) recognition, modeling and expression? (iii) Which pedagogical strategies are used to support the group formation with affective states in CSCL environment? (iv) What are the empirical results obtained using affective states in group formation? To conduct this research nine digital databases were consulted. From 1081 analyzed papers, only 21 of them were selected with relevant information to help answer the research questions defined. As a major results, we highlight that: (i)76,19% of the studies considered the personality trait in CSCL environment group formation; (ii) most papers used affective state recognition in CSCL environment by questionnaires fill out by students; (iii)it was confirmed the lack of studies which use pedagogical theories or strategies; and (iv) although 8 studies have been empirically evaluated, it was observed that the obtained results by scientific community about affect in group formation in CSCL environments are still incipient, with several gaps and further research opportunities. [ABSTRACT FROM AUTHOR]

A software product line (SPL) is a set of software systems that have a particular set of common features and that satisfy the needs of a particular market segment or mission. Feature modeling is one of the key activities involved in the design of SPLs. The feature diagram produced in this activity captures the commonalities and variabilities of SPLs. In some complex domains (e.g., ubiquitous computing, autonomic systems and context-aware computing), it is difficult to foresee all functionalities and variabilities a specific SPL may require. Thus, Dynamic Software Product Lines (DSPLs) bind variation points at runtime to adapt to fluctuations in user needs as well as to adapt to changes in the environment. In this context, relying on formal representations of feature models is important to allow them to be automatically analyzed during system execution. Among the mechanisms used for representing and analyzing feature models, description logic (DL) based approaches demand to be better investigated in DSPLs since it provides capabilities, such as automated inconsistency detection, reasoning efficiency, scalability and expressivity. Ontology is the most common way to represent feature models knowledge based on DL reasoners. Previous works conceived ontologies for feature modeling either based on OWL classes and properties or based on OWL individuals. However, considering change or evolution scenarios of feature models, we need to compare whether a class-based or an individual-based feature modeling style is recommended to describe feature models to support SPLs, and especially its capabilities to deal with changes in feature models, as required by DSPLs. In this paper, we conduct a controlled experiment to empirically compare two approaches based on each one of these modeling styles in several changing scenarios (e.g., add/remove mandatory feature, add/remove optional feature and so on). We measure time to perform changes, structural impact of changes (flexibility) and correctness for performing changes in our experiment. Our results indicate that using OWL individuals requires less time to change and is more flexible than using OWL classes and properties. These results provide insightful assumptions towards the definition of an approach relying on reasoning capabilities of ontologies that can effectively support products reconfiguration in the context of DSPL. [ABSTRACT FROM AUTHOR]

Highlights: [•] Middle school students learned to solve decimal problems with a web-based tutoring system. [•] ExErr group received erroneous examples to correct and explain. [•] PS group received problems to solve and explain. [•] ExErr group outperformed PS group on a delayed test and on judging answer correctness. [•] PS group reported liking the lessons better than the ExErr group. [Copyright &y& Elsevier]

Highlights: [•] A formalization of instructional design for CSCL using HTN planning is proposed. [•] We used the proposed formalization to model and design adaptive CSCL scenarios. [•] To validate our approach a CSCL courseware generator was created. [•] Case studies are presented showing that the generator can automatically design personalized CSCL scenarios. [ABSTRACT FROM AUTHOR]

Highlights: [•] We described the implementation of an expert system (ES) module of an Algebra ITS. [•] The ES is composed by meta-rules that aim at reducing the number of possible paths to explore when correcting a student’s solution. [•] We also described a quasi-experiment with 43 7th grade students. [•] The students who interacted with our tool showed statistically higher scores on equation solving tests. [ABSTRACT FROM AUTHOR]