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The advent of Version Control Systems (VCS) in computer science education has significantly improved the learning experience. The Learning Analytics community has started to analyze the interactions between students and VCSs to evaluate the behavioral and cognitive aspects of the learning process. Within the aforesaid scope, a promising research direction is the use of Artificial Intelligence (AI) to predict students' exam outcomes early based on VCS usage data. Previous AI-based solutions have two main drawbacks: (i) They rely on static models, which disregard temporal changes in the student–VCS interactions. (ii) AI reasoning is not transparent to end-users. This paper proposes a time-dependent approach to early predict student performance from VCS data. It applies and compares different classification models trained at various course stages. To gain insights into exam performance predictions it combines classification with explainable AI techniques. It visualizes the explanations of the time-varying performance predictors. The results of a real case study show that the effect of VCS-based features on the exam success rate is relevant much earlier than the end of the course, whereas the timely submission of the first lab assignment is a reliable predictor of the exam grade. [ABSTRACT FROM AUTHOR]

The main purpose of this study is to examine the implementation of active methodologies in the teaching–learning process in computer science. To achieve this objective, a systematic review using the PRISMA method was performed; the search for articles was conducted through the Scopus and Web of Science databases and the scientific search engine Google Scholar. By establishing inclusion and exclusion criteria, 15 research papers were selected addressing the use of various active methodologies which have had a positive impact on students' learning processes. Among the principal active methodologies highlighted are problem-based learning, flipped classrooms, and gamification. The results of the review show how active methodologies promote significant learning, in addition to fostering more outstanding commitment, participation, and motivation on the students' part. It was observed that active methodologies contribute to the development of fundamental cognitive and socio-emotional skills for their professional growth. [ABSTRACT FROM AUTHOR]

There is a nationwide effort to increase the representation and engagement of minoritized students in computer science education. Discourse about the barriers to diversity among computer science majors is often characterized by student pathologies and does not consider the impacts of classroom culture and instructor pedagogies. Amid the push for strategies to recruit and retain minoritized students in computer science, little has been done to transform curriculum and analyze faculty perspectives on curriculum and pedagogy as methods to increase students' access to the computer science major. This paper presents an example of curriculum redesign for an undergraduate introductory computer science course (ICS) that sought to address issues of inequitable representation by centering student identities and redistributing power in favor of students. The authors draw upon critical sociocultural and the 4Es heuristic for disciplinary literacy to reimagine the ICS course as a space that centers on the important roles of identity and power in solving for diversity in computer science education. We highlight for researchers and practitioners how our work may be used to disrupt meritocratic practices that alienate minoritized and economically disadvantaged students and to expand definitions of mastery and expertise in computer science education. [ABSTRACT FROM AUTHOR]

Analogy-based learning methods map the concept being learned to a concept well understood by the learner. An analogy is primarily useful when learners do not know the topic being studied. Computer science is an area where the concepts exhibit a high level of abstraction and, hence, are hard for students to comprehend. The use of analogies in instruction can significantly reduce the cognitive load a student faces in learning abstract computer science concepts. The role of analogies in helping students learn computer science topics has not been explored adequately. This paper presents our efforts related to using analogy-based teaching in computer science. Over the last several years, we have developed extensive analogies for many advanced computer science concepts. We have used these analogies extensively in classroom teaching at our institution. We list the analogies that we have developed and used in our classroom teaching and, as illustration, discuss two analogies: one from the field of operating systems and another one in modular software design. We have also conducted experiments to evaluate the impact of using these two analogies on student learning outcomes. Our results confirm our hypothesis that analogy-based instruction techniques are effective and result in improved student learning outcomes. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has completely transformed the education sector. Almost all universities and colleges have had to convert their normal classroom teaching to online/remote or hybrid teaching during the COVID-19 pandemic. Online teaching has been found quite useful during an emergency situation. This switch to online teaching forced educators to come out of their comfort zone and learn new tools and techniques for online teaching. It is important, therefore, to analyse the problems faced by educators in online teaching because this has become the new normal. There are several studies identifying the issues faced by educators in online teaching but less is known about the issues faced by Computer Science (CS) educators. In this paper, we perform an exploratory study of the problems, questions, and associated responses from CS educators posted on popular Q&A forums, e.g., CS educators StackExchange. We identified six main challenges related to online teaching: platform recommendation, Q&A management, academic dishonesty, pair programming, and feedback mechanism. Several recommendations are provided by other CS educators in each of the categories, which are discussed in detail in this paper. This study will help organizations come up with better solutions to support their educators so that they can deliver better quality education and reduce the overall stress levels of staff. [ABSTRACT FROM AUTHOR]

In the current era of artificial intelligence, large language models such as ChatGPT and BARD are being increasingly used for various applications, such as language translation, text generation, and human-like conversation. The fact that these models consist of large amounts of data, including many different opinions and perspectives, could introduce the possibility of a new qualitative research approach: Due to the probabilistic character of their answers, "interviewing" these large language models could give insights into public opinions in a way that otherwise only interviews with large groups of subjects could deliver. However, it is not yet clear if qualitative content analysis research methods can be applied to interviews with these models. Evaluating the applicability of qualitative research methods to interviews with large language models could foster our understanding of their abilities and limitations. In this paper, we examine the applicability of qualitative content analysis research methods to interviews with ChatGPT in English, ChatGPT in German, and BARD in English on the relevance of computer science in K-12 education, which was used as an exemplary topic. We found that the answers produced by these models strongly depended on the provided context, and the same model could produce heavily differing results for the same questions. From these results and the insights throughout the process, we formulated guidelines for conducting and analyzing interviews with large language models. Our findings suggest that qualitative content analysis research methods can indeed be applied to interviews with large language models, but with careful consideration of contextual factors that may affect the responses produced by these models. The guidelines we provide can aid researchers and practitioners in conducting more nuanced and insightful interviews with large language models. From an overall view of our results, we generally do not recommend using interviews with large language models for research purposes, due to their highly unpredictable results. However, we suggest using these models as exploration tools for gaining different perspectives on research topics and for testing interview guidelines before conducting real-world interviews. [ABSTRACT FROM AUTHOR]

Introducing computational thinking at elementary school can develop students' capabilities and interest in Computing skills. In this study, we introduced the Computer Science unplugged (CS-unplugged) technique in Pakistan. We use paper-based activities to equip students with basic Computer Science skills without introducing any programming language. This study contributes twofold: First, we report the impact of CS-Unplugged training on more than 350 elementary students. The empirical study reveals that the students perform better in solving problems after unplugged training. Improved results in the post-training activity support this impact. Second, we applied machine learning to predict students' performance. We employed different supervised machine learning algorithms to predict the students' performance. Our results indicate that the Logistic regression-based model can predict the positive response of the student with a 0.91 receiver operating characteristic curve (ROC curve). This pilot study results encourage introducing unplugged techniques at elementary schools in third-world countries. The goal is to have minimal changes in infrastructure and focus on better student learning. In the future, we plan to introduce more unplugged problem-solving techniques to elementary students by providing little training to the science or math teacher. [ABSTRACT FROM AUTHOR]

While the last two decades have seen an increased interest in STEAM (science, technology, engineering, arts, and mathematics) in K-12 schools, few efforts have focused on the teachers and teaching practices necessary to support these interventions. Even fewer have considered the important work that teachers carry out not just inside classrooms but beyond the classroom walls to sustain such STEAM implementation efforts, from interacting with administrators to recruiting students and persuading parents about the importance of arts and computer science. In order to understand teachers' needs and practices regarding STEAM implementation, in this paper, we focus on eight experienced computer science teachers' reflections on implementing a STEAM unit using electronic textiles, which combine crafting, circuit design, and coding so as to make wearable artifacts. We use a broad lens to examine the practices high school teachers employed not only in their classrooms but also in their schools and communities to keep these equitable learning opportunities going, from communicating with other teachers and admins to building a computer science (CS) teacher community across district and state lines. We also analyzed these reflections to understand teachers' own social and emotional needs—needs important to staying in the field of CS education—better, as they are relevant to engaging with learning new content, applying new pedagogical skills, and obtaining materials and endorsements from their organizations to bring STEAM into their classrooms. In the discussion, we contemplate what teachers' reported practices and needs say about supporting and sustaining equitable STEAM in classrooms. [ABSTRACT FROM AUTHOR]

This study aims to evaluate the impact of using augmented reality, gamification, and serious games in computer science education. The study presents the development process of an educational mobile application, describes an experiment that was conducted and involved 117 higher education students, and analyzes the results of a 49-item paper-based questionnaire. In total, 8 research questions were explored. The results of the study revealed that several educational benefits can be yielded when integrating such applications in teaching and learning activities and actively involving students in the design and development process. In particular, the application was assessed as an effective learning tool that could enrich and improve the educational process and create interactive, inclusive, and student-centered learning environments. Its use led mostly to positive effects and experiences while maintaining the negative ones to a minimum and most students expressed positive emotions. Students were able to learn in a more enjoyable and interesting manner, and their motivation, engagement, self-efficacy, and immersion were greatly increased. Students' innate need for autonomy, competence, and relatedness was satisfactorily met and both their intrinsic and extrinsic learning motivations were triggered. They felt a sense of belonging and cultivated their social skills. The potential of the application to improve students' knowledge acquisition and academic achievements was also observed. The application also enabled students to improve their computational thinking and critical thinking skills. Therefore, the potential of combining augmented reality, gamification, and serious games to enhance students' cognitive and social–emotional development was highlighted. [ABSTRACT FROM AUTHOR]

In this paper, a fuzzy-based evaluation method is presented for the impact of e-learning on several aspects of the learning lives of academic students of Information and Communication Technologies (ICT) during the COVID-19 pandemic. Specifically, the academic year 2020–2021 was considered when a general lockdown was imposed in Greece and all courses were delivered exclusively through the web. The evaluation criteria are (i) e-learning acceptance, (ii) learning effectiveness, (iii) students' engagement and (iv) socializing and interpersonal relationships in the educational community. The evaluation was conducted through questionnaires. Ninety two (92) undergraduate and postgraduate students and Ten (10) computer science in-structors of the department of Informatics of the University of Piraeus, Greece, participated in this survey. The questionnaire answers were analyzed using a fuzzy-based mechanism. Particularly, five fuzzy sets were used to describe the 5-point Likert scale answers to the questionnaires with linguistic values, and four other fuzzy sets were used for the description of the evaluation results concerning the four defined evaluation criteria. Moreover, 209 fuzzy rules were created to analyze and calculate the evaluation results per criterion, considering both the students' answers (119 fuzzy rules) and the instructors' answers (90 fuzzy rules) to the questionnaires. The gain of this approach is that the analysis of evaluation data with fuzzy rules imitates the human way of thinking and, thus, makes the process more explainable. The evaluation results showed a positive impact of e-learning on student confidence, self-discipline and active participation and a negative impact on student interpersonal relationships. The impact of e-learning on other learning issues was neutral. [ABSTRACT FROM AUTHOR]

This paper introduces Learn-CIAM, a new model-based methodological approach for the design of flows and for the semi-automatic generation of tools in order to support collaborative learning tasks. The main objective of this work is to help professors by establishing a series of steps for the specification of their learning courses and the obtaining of collaborative tools to support certain learning activities (in particular, for in-group editing, searching and modeling). This paper presents a complete methodological framework, how it is supported conceptually and technologically, and an application example. So to guarantee the validity of the proposal, we also present some validation processes with potential designers and users from different profiles such as Education and Computer Science. The results seem to demonstrate a positive reception and acceptance, concluding that its application would facilitate the design of learning courses and the generation of collaborative learning tools for professionals of both profiles. [ABSTRACT FROM AUTHOR]

The Centre for Schooling and Learning Technologies (CSaLT) at Edith Cowan University (ECU) was asked in 2016 to be the Western Australian arm of a national e-exam project. This project used a bespoke exam system installed on a USB-drive to deliver what would have been traditional paper-based exams in an enclosed computer-based environment that was isolated from the internet and any resources other than those provided by the lecturer. This paper looks at the two exams chosen by the Western Australian group for the trial; a programming exam for pre-service computing teachers and an occupational health and safety exam for pre-service design and technology teachers. Both groups were drawn from the Graduate Diploma in Education course at ECU. The paper looks at the nature of the exam environment and the procedure for creating e-exams. It also outlines the exam procedures used and examines the feedback provided by both the lecturers and students involved. Conclusions are drawn about the suitability of the e-exam system and improvements are recommended as well as a discussion about e-exams and digital assessment more generally. [ABSTRACT FROM AUTHOR]

Generation Z members use their smart devices as part of their everyday routine. Teaching methods may need to be updated to make learning materials more interesting for this generation. This paper suggests gamifying computer science subjects to enhance the learning experience for this generation. Additionally, many students face difficulty in understanding computer science materials and algorithms. Gamifying computer science education is one of the suggested teaching methods to simplify topics and increase students' engagement. Moreover, the field of computer science is dominated by males. The use of gamification could increase women's interest in this field. This paper demonstrates different techniques that were developed by the researchers to employ gamification in teaching computer science topics. The data was collected at the end of the two different courses. Results show that students enjoyed the suggested teaching method and found it useful. This paper also demonstrates two tools and their gamification elements. These tools were developed by the researchers to help people learn computer programming and information security. [ABSTRACT FROM AUTHOR]

In this study, we present the DP Plugin for IntelliJ IDEA, designed to extend the Drop Project (DP) Automatic Assessment Tool (AAT) by making it more suitable for handling small exercises in exercise-based learning environments. Our aim was to address the limitations of DP in supporting small assignments while retaining its strengths in project-based learning. The plugin leverages DP's REST API to streamline the submission process, integrating assignment instructions and feedback directly within the IDE. A student survey conducted during the 2022/23 academic year revealed a positive reception, highlighting benefits such as time efficiency and ease of use. Students also provided valuable feedback, leading to various improvements that have since been integrated into the plugin. Despite these promising results, the study is limited by the relatively small percentage of survey respondents. Our findings suggest that an IDE plugin can significantly improve the usability of project-oriented AATs for small exercises, informing the development of future educational tools suitable for mixed project-based and exercise-based learning environments. [ABSTRACT FROM AUTHOR]

Programming is acknowledged widely as a cornerstone skill in Computer Science education. Despite significant efforts to refine teaching methodologies, a segment of students is still at risk of failing programming courses. It is crucial to identify potentially struggling students at risk of underperforming or academic failure. This study explores the predictive potential of students' problem-solving skills through dynamic, domain-independent, complex problem-solving assessment. To evaluate the predictive potential of complex problem-solving empirically, a case study with 122 participants was conducted in the undergraduate Introductory Programming Course at the University of Maribor, Slovenia. A latent variable approach was employed to examine the associations. The study results showed that complex problem-solving has a strong positive effect on performance in Introductory Programming Courses. According to the results of structural equation modeling, 64% of the variance in programming performance is explained by complex problem-solving ability. Our findings indicate that complex problem-solving performance could serve as a significant, cognitive, dynamic predictor, applicable to the Introductory Programming Course. Moreover, we present evidence that the demonstrated approach could also be used to predict success in the broader computing education community, including K-12, and the wider education landscape. Apart from predictive potential, our results suggest that valid and reliable instruments for assessing complex problem-solving could also be used for assessing general-purpose, domain-independent problem-solving skills in computing education. Likewise, the results confirmed the positive effect of previous programming experience on programming performance. On the other hand, there was no significant direct effect of performance in High School mathematics on Introductory Programming. [ABSTRACT FROM AUTHOR]

Computational thinking (CT) has garnered significant interest in both computer science and education sciences as it delineates a set of skills that emerge during the problem-solving process. Consequently, numerous assessment instruments aimed at measuring CT have been developed in the recent years. However, a scarce part of the existing CT measurement instruments has been dedicated to early school ages, and few have undergone rigorous validation or reliability testing. Therefore, this work introduces a new instrument for measuring CT in the early grades of elementary education: the Computational Thinking Test for Children (CTTC). To this end, in this work, we provide the design and validation of the CTTC, which is constructed around spatial, sequential, and logical thinking and encompasses abstraction, decomposition, pattern recognition, and coding items organized in five question blocks. The validation and standardization process employs the Kuder–Richardson statistic (KR-20) and expert judgment using V-Aiken for consistency. Additionally, item difficulty indices were utilized to gauge the difficulty level of each question in the CTTC. The study concludes that the CTTC demonstrates consistency and suitability for children in the first cycle of primary education (encompassing the first to third grades). [ABSTRACT FROM AUTHOR]

The use of large language models with chatbots like ChatGPT has become increasingly popular among students, especially in Computer Science education. However, significant debates exist in the education community on the role of ChatGPT in learning. Therefore, it is critical to understand the potential impact of ChatGPT on the learning, engagement, and overall success of students in classrooms. In this empirical study, we report on a controlled experiment with 182 participants in a first-year undergraduate course on object-oriented programming. Our differential study divided students into two groups, one using ChatGPT and the other not using it for practical programming assignments. The study results showed that the students' performance is not influenced by ChatGPT usage (no statistical significance between groups with a p-value of 0.730), nor are the grading results of practical assignments (p-value 0.760) and midterm exams (p-value 0.856). Our findings from the controlled experiment suggest that it is safe for novice programmers to use ChatGPT if specific measures and adjustments are adopted in the education process. [ABSTRACT FROM AUTHOR]

Robotics is needed as education keeps up with challenges students are facing in a technological environment. A long-term research project focuses on developing a feasible robotics-based learning environment that enables primary school teachers to introduce computer science education. This paper shows educational robotics combining storytelling to promote computational thinking through the method of Tell, Draw, and Code. The study was conducted via pre–post test, using the Beginners Computational Thinking test (BCTt), with third and fourth graders (N = 40) to determine if the integration of robotics-based storytelling activities enhances computational thinking skills. Results show that an increase in computational thinking is evident after the intervention is implemented. The approach of combining stories, texts, and literature with educational robotics seems to be a promising concept to equip students with the required skills. [ABSTRACT FROM AUTHOR]

This paper synthesizes 20 years (1999–2019) of empirical research on women of color (WOC) in computing and tech graduate education. Using complementary theoretical frameworks of social pain and community cultural wealth (CCW), we identify factors in the research literature that affect WOC's experiences, participation, success, and persistence. This qualitative meta-synthesis employed systematic literature search and selection methods, a hybrid approach to coding and thematic analysis. Findings include the ways in which social pain from isolation, exclusion, and hostility from peers and faculty negatively affected WOC's experiences in their graduate programs. Often, WOC's motivation to persist and succeed in computing came from key social actors, such as mentors and families, and from individual and social strategies, such as seeking counterspaces, that leveraged their CCW. This meta-synthesis contributes to the knowledge base about the mechanisms that support and hinder the persistence of WOC in computing graduate programs and provides recommendations for institutions and for further research. [ABSTRACT FROM AUTHOR]

This paper reports a case study, developed in K-12 Portuguese Education, that aimed to analyze the computer science teachers' knowledge, interest, and self-confidence to use educational robotics and other programable objects in classroom activities to teach computer science concepts and to promote students' computational thinking skills. The research design was organized into a descriptive and exploratory quantitative approach. The participants were 174 in-service computer science teachers of Portuguese public education. The data was gathered from the participants, through the online application of the Robotics Interest Questionnaire scale (RIQ). Very positive levels of teacher's knowledge, interest, and self-efficacy to use educational robotics for teaching purposes were reported in the study outcomes. These constructs were underlined in several studies as relevant factors to promote the use of educational robotics and other similar technologies by the teachers. Despite the study limitations and the small context, a set of relevant results was highlighted on computer science in-service teachers' interest and preparation to use robotics and to support their students in learning activities with these artifacts. [ABSTRACT FROM AUTHOR]

Competitions are being widely used to motivate students in diverse learning processes, including those in computer programming. This paper presents a methodology for designing and assessing competitive learning scenarios that allow students to develop three different coding skills: the ability to compete against unknown competitors, the ability to compete against known competitors and the ability to compete against refined versions of known competitors. The proposal is based on peer code review, implemented as an improvement cycle after the dissemination of the code among participants. A case study evaluating the methodology was conducted with two cohorts of students in an undergraduate course. The analysis of the obtained grades suggests that while performance after our assistance was improved, students could still fail or succeed independently of the assistance. Complementary data from student questionnaires and supervisor observations are aligned with this finding. As a conclusion, the evidence supports the validity of the methodology. Additionally, several guidelines based on the experience are provided to transfer the proposal to other environments. [ABSTRACT FROM AUTHOR]

The Computer Science industry suffers from a vivid gender gap. To understand this gap, Computational Thinking skills in Computer Science education are analyzed by binary gender roles using block-based programming languages such as Scratch since they are intuitive for beginners. Platforms such as Dr. Scratch, aid learners in improving their coding skills by earning a Computational Thinking score while supporting effective assessments of students' projects and fostering basic computer programming. Although previous studies have examined gender differences using Scratch programs, few have analyzed the Scratch project type's impact on the evaluation process when comparing genders. Herein, the influence of project type is analyzed using instances of 124 (62 male, 62 female) projects on the Scratch website. Initially, projects were categorized based on the user's gender and project type. Hypothetical testing of each case shows that the scoring system has a bias based on the project type. As gender differences appear by project type, the project type may significantly affect the gender gap in Computational Thinking scores. This study demonstrates the importance of incorporating the project type's effect into the Scratch projects' evaluation process when assessing gender differences. [ABSTRACT FROM AUTHOR]

Automated assessment systems are increasingly used in higher education programming courses since the manual assessment of programming assignments is very time-consuming. Although a substantial amount of research work has been done on systems for the automatic assessment of programming assignments, most studies are focused on technical characteristics and further research is needed for examining the effect of using these systems on students' perceptions and performance. This paper examines the effect of using an instructor-centered tool for automatically assessing programming assignments on students' perceptions and performance in a web development course at a higher education institution. A total of three data sources were used: a survey to collect data regarding students' perceptions, and the grades of the student assignment submissions and of a practical programming exam in order to analyze the students' performance. The results show that the incorporation of the automated assessment tool into the course was beneficial for the students, since it allowed for increasing their motivation, improving the quality of their works, and enhancing their practical programming skills. Nonetheless, a significant percentage of students found the feedback that was generated by the tool hard to understand and of little use, and the generated grades unfair. [ABSTRACT FROM AUTHOR]

With more recognition being given to the diverse and changing demographics in education, there is a need to understand how well computer science education is meeting the needs of all learners as it starts to infiltrate K-12 schools. The CAPE framework is a newer model for assessing the equitable delivery of computer science education and can be used to understand a school's capacity to offer equitable computer science (CS) education, equitable student access to CS education, equitable student participation in CS, and equitable experiences of students taking CS. Since the CAPE framework is a new way to research CS education through an equity-lens, there are few, if any, frameworks that can be leveraged to explore research questions in a complex, multi-school intervention. To address this gap, we used a design-based research approach to create and determine the feasibility of a new model, Theory of Impacts, informed by the CAPE framework (the ToI-CAPE model), for evaluating a multi-school intervention. In this article, we provide a detailed explanation of creating and using the ToI-CAPE model for a specific intervention and the feasibility of using ToI-CAPE across factors based in experiences and how to use this model in other research and evaluation projects. Overall, the use of the ToI-CAPE model can be used to shed light on the critical subcomponents and agents at work in the intervention and the actions necessary across these components and agents to support intended outcomes. [ABSTRACT FROM AUTHOR]

Researchers in many disciplines are developing novel interactive smart learning objects like exercises and visualizations. Meanwhile, Learning Management Systems (LMS) and eTextbook systems are also becoming more sophisticated in their ability to use standard protocols to make use of third party smart learning objects. But at this time, educational tool developers do not always make best use of the interoperability standards and need exemplars to guide and motivate their development efforts. In this paper we present a case study where the two large educational ecosystems use the Learning Tools Interoperability (LTI) standard to allow cross-sharing of their educational materials. At the end of our development process, Virginia Tech's OpenDSA eTextbook system became able to import materials from Aalto University's ACOS smart learning content server, such as python programming exercises and Parsons problems. Meanwhile, University of Pittsburgh's Mastery Grids (which already uses the ACOS exercises) was made to support CodeWorkout programming exercises (a system already used within OpenDSA). Thus, four major projects in CS Education became inter-operable. [ABSTRACT FROM AUTHOR]

Most source code plagiarism detection tools only rely on source code similarity to indicate plagiarism. This can be an issue since not all source code pairs with high similarity are plagiarism. Moreover, the culprits (i.e., the ones who plagiarise) cannot be differentiated from the victims even though they need to be educated further on different ways. This paper proposes a mechanism to generate hints for investigating source code plagiarism and identifying the culprits on in-class individual programming assessment. The hints are collected from the culprits' copying behaviour during the assessment. According to our evaluation, the hints from source code creation process and seating position are 76.88% and at least 80.87% accurate for indicating plagiarism. Further, the hints from source code creation process can be helpful for indicating the culprits as the culprits' codes have at least one of our predefined conditions for the copying behaviour. [ABSTRACT FROM AUTHOR]

Problem-based learning is a widely used learning methodology in the field of technological disciplines, especially in distance education environments. In these environments, the most used tools, which provide learning scenarios, are remote and virtual laboratories. Internet of Things (IoT) devices can be used as remote or virtual laboratories. In addition to this, they can be organized/orchestrated to build remote maker spaces through the web. These types of spaces are called the Web of Things (WoT). This paper proposes the use of these types of spaces and their integration as practical activities into the curricula of technological subjects. This approach will allow us to achieve two fundamental objectives: (1) To improve the academic results (grades) of students; and (2) to increase engagement and interest of students in the studied technologies, including IoT devices. These platforms are modeled using archetypes based on different typologies and usage scenarios. In particular, these usage scenarios will implement a learning strategy for each problem to be solved. The current work shows the evolution of these archetypes and their application in the teaching of disciplines/subjects defined in computer science, such as distributed computing and cybersecurity. [ABSTRACT FROM AUTHOR]

Several approaches have been proposed to reduce the gap between software engineering education and the needs and practices of the software industry. Many of them aim to promote a more active learning attitude in students and provide them with more realistic experiences, thus recreating industry software development environments and collaborative development and, in some cases, with the involvement of companies mainly acting as potential customers. Since many degree courses typically offer separate subjects to teach requirements engineering, analysis and design, coding, or validation, the integration of all these phases normally necessitates experience in a project context and is usually carried out in a final year project. The approach described in this article benefits from the close involvement of a software house company which goes beyond the common involvement of a potential customer. Students are integrated into distributed teams comprising students, teachers and IT professionals. Teams follow the agile Scrum methodology and use the OutSystems low-code development platform providing students with the experience of an almost real scenario. The results show that this approach complements the knowledge and practice acquired in course subjects, develops the students' technical and non-technical skills, such as commitment, teamwork, and communication, and initiates them in the methodologies and development strategies used in these companies. The feedback from the teachers involved, software companies and students was very positive. [ABSTRACT FROM AUTHOR]

The analysis of what human capital (HC) is has a long history and culminates in the acknowledgment that HC and its growth are very important for both cognitive education (cognitive skills (CSs)) and personal life (noncognitive skills (NCSs)) and that CSs and NCSs have a strong reciprocal relationship, as studies by Heckman demonstrated. The present contribution (following Heckman's approach) analyzed the relationship between CSs and NCSs in a sample of middle school students in the Autonomous Province of Trento. The second goal of the research was to verify whether educational teaching behaviors improved students' personalities. Aside from the use of administrative data (INVALSI data, 2015 and 2018), one survey was administered in the 2018–2019 schooling year to verify the relationship between NCSs and CSs. Moreover, we sought to determine whether education teaching behavior improved the students' personalities (1522 students in 25 schools) and whether programs could enhance NCSs. Methodological tools for the analysis involved the generalized least squares approach to answer the first question and a difference-in-differences model for the second. The main results showed that the levels of NCSs affected the ability to learn and improve CSs; a challenging teaching approach, especially if accompanied by programs improving its quality, had positive results. Finally, the research suggested that a wider, national-based survey following students from primary to secondary school would allow for a greater understanding of the dynamics of CSs and NCSs. [ABSTRACT FROM AUTHOR]

In this study, we report findings from the PCBuildAR project, in which students developed augmented reality (AR) artifacts following a guided design-based learning (DBL) approach. Sixty-two students participated in the study and were either in their first year to learn about computer science or were more experienced computer science students. In terms of learning performance, only the firstyear students benefited from our guided DBL approach. In contrast, the experienced students were highly motivated to learn computer science not only immediately after the intervention, but also in the long term. For first-year students, this effect was only evident directly after the intervention. Overall, the guided DBL design proved to be effective for both motivation and learning, especially for younger students. For older learners, a better balance between guidance and autonomy is recommended. [ABSTRACT FROM AUTHOR]

This study investigated the role of virtual reality (VR) in computer science (CS) education over the last 10 years by conducting a bibliometric and content analysis of articles related to the use of VR in CS education. A total of 971 articles published in peer-reviewed journals and conferences were collected from Web of Science and Scopus databases to conduct the bibliometric analysis. Furthermore, content analysis was conducted on 39 articles that met the inclusion criteria. This study demonstrates that VR research for CS education was faring well around 2011 but witnessed low production output between the years 2013 and 2016. However, scholars have increased their contribution in this field recently, starting from the year 2017. This study also revealed prolific scholars contributing to the field. It provides insightful information regarding research hotspots in VR that have emerged recently, which can be further explored to enhance CS education. In addition, the quantitative method remains the most preferred research method, while the questionnaire was the most used data collection technique. Moreover, descriptive analysis was primarily used in studies on VR in CS education. The study concludes that even though scholars are leveraging VR to advance CS education, more effort needs to be made by stakeholders across countries and institutions. In addition, a more rigorous methodological approach needs to be employed in future studies to provide more evidence-based research output. Our future study would investigate the pedagogy, content, and context of studies on VR in CS education. [ABSTRACT FROM AUTHOR]

The hypervisor and container are emerging cloud computing and fog computing technologies, which enable rapid system deployment. However, both of the technologies depend on the operating system (OS) and applications that are installed on the host machines. System deployment is the activity to deliver and install OSs and applications onto computers. Such deployment activities are widely required in the infrastructure of cloud computing, fog computing, high-performance computing clusters, and classrooms of computer education. Albeit the concept of system deployment is not new, traditional solutions cannot support the rapid evolution of open source file systems. Furthermore, existing solutions cannot support the massive deployment of disks in a computer as well as the massive deployment in large-scale computers. To resolve the issue, the authors proposed novel system architecture as well as software that is openly available. The experiments are undertaken by deploying a Linux system to 1 to 30 Universal Serial Bus (USB) flash drives in a single machine and to 1 to 32 machines in a network using the software that is being developed in this work. The results have demonstrated the feasibility and efficiency of the proposed work. The relationships between the bus bandwidth, the writing rate of the USB flash drive, and the number of flash drives were also formulated as a govern equation. Performance evaluation and cost savings in comparing to the deployment cases adopting commercial software were also provided for demonstrating the performance enhancement and cost reduction by using the novel deployment system. In general, the proposed architecture and the developed software are highly effective from the aspects of both performance and cost. [ABSTRACT FROM AUTHOR]

Despite efforts to increase participation in science, technology, engineering and math fields (STEM), the role of students' perceptions of the social relevance of science in guiding their expectations to major in STEM remains largely unexplored. Though science education scholars predict that perceptions of social relevance likely matter equally for boys and girls, gender scholars suggest that these perceptions should matter more for girls than boys. Using longitudinal data from a large, urban, low-income, and predominantly minority-serving district, this study examines the potentially gendered role of perceptions of social relevance in ninth graders' expectations to major in STEM. Further, it examines these dynamics with respect to expectations to major in any STEM field as well as expectations to major in specific STEM fields. Findings largely support the perspective of gender scholars; perceptions of the social relevance of science positively and significantly predict female, but not male, students' intentions to major in STEM (vs. non-STEM fields). Subsequent analyses that look at intentions to major in specific STEM fields reveal a similar pattern, such that perceptions of relevance positively predict female students' intentions to major in the biological sciences, the physical sciences, and engineering, while male students' intentions are not similarly impacted. By contrast, positive perceptions of the relevance of science predict a modest increase in interest in computer science for both boys and girls. [ABSTRACT FROM AUTHOR]

More specifically, it presents the conception process of the interaction design with a strong theoretical base, as it considers a learning approach proposal that combines the Universal Design for Learning principles, the Inquiry-Based Science Education and the BSCS 5E Instructional Model. These can be combined with other technologies, such as Augmented Reality (AR) or Virtual Reality (VR), to increase students' motivation and engagement in learning processes [[5]]. The potential of digital games to promote learning is a growing field of research. [Extracted from the article]

Higher education is changing, and a new normal is coming. Students are even more demanding, and professors need to follow the evolution of technology and try to increase student engagement in the classrooms (presential or virtual). Higher education students recognise that the introduction of new tools and learning methods can improve the teaching quality and increase the motivation to learn. Regarding a question about which type of classes students preferred, ninety-one point ninety-nine per cent (91.99%) of the students wanted interactive classes over traditional. Having this concern in mind over the past years, a professor explored a set of methods, strategies and tools and designed a new and innovative paradigm using gamification. This approach is denominated TechTeach and explores a set of trending concepts and interactive tools to teach computer science subjects. It was designed to run in a B-learning environment. The paradigm uses flipped classrooms, bring your own device (BYOD), gamification, training of soft-skills and quizzes and surveys to increase the student's engagement and provide the best learning environment to students. Currently, COVID-19 is bringing about new challenges, and TechTeach was improved in order to be more suitable for this new way of teaching (from 0% to 100% online classes). This article details this method and shows how it can be applied in a real environment. A case study was used to prove the functionality and relevance of this approach, and the achieved results are motivating. During the semester, more than a hundred students experienced this new way of teaching and assessment. In the end, more than eighty-one per cent (81%) of the students gave a positive grade to the approach, and more than ninety-five per cent (95.65%) of the students approved the use of the concept of BYOD in the classroom. With TechTeach, the classroom is not a boring place anymore; it is a place to learn and enjoy regardless of being physical or not. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic imposed in many countries, in the short term, the interruption of face-to-face teaching activities and, in the medium term, the existence of a 'new normal', in which teaching methods should be able to switch from face-to-face to remote overnight. However, this flexibility can pose a great difficulty, especially in the assessment of practical courses with a high student–teacher ratio, in which the assessment tools or methods used in face-to-face learning are not ready to be adopted within a fully online environment. This article presents a case study describing the transformation of the assessment method of a programming course in higher education to a fully online format during the COVID-19 pandemic, by means of an automated student-centered assessment tool. To evaluate the new assessment method, we studied students' interactions with the tool, as well as students' perceptions, which were measured with two different surveys: one for the programming assignments and one for the final exam. The results show that the students' perceptions of the assessment tool were highly positive: if using the tool had been optional, the majority of them would have chosen to use it without a doubt, and they would like other courses to involve a tool like the one presented in this article. A discussion about the use of this tool in subsequent years in the same and related courses is also presented, analyzing the sustainability of this new assessment method. [ABSTRACT FROM AUTHOR]

In the last few years, it has been pointed out that teaching programming is a strong strategy to develop pupils' competences in computational thinking (CT). In the Portuguese context, the curriculum changes in 2018 made programming and CT compulsory for every pupil in primary and secondary education. Nowadays, there is an information and communication technology (ICT) subject, taught by a computer science teacher in each school grade. In Portugal, to become a computer science teacher in primary and secondary education, it is compulsory to have a master's degree in computer science education. This article reports on a pedagogical activity developed with student-teachers of a Master in Teaching Informatics at the University of Lisbon. Within the activities of the master's program, we developed a cross-analysis of the core characteristics of 26 block-based and visual programming applications (apps) used to teach computational thinking and programming in school classes. In order to organize the analysis, a framework with several dimensions was developed and used by student-teachers to register the characteristics of each app. The product of this work is a comparative matrix mapping the core characteristics of each of the 26 apps that student-teachers used to select the most appropriate one for teaching programming and computational thinking according to each grade, age group and other characteristics. [ABSTRACT FROM AUTHOR]

There has been considerable investment in pre-college educational interventions for all areas of STEM (including computer science). The goal of many of these initiatives is to engage and interest students early in their educational career. In this study, a systematic literature review was undertaken to determine the demographic and program data collected and reported for the field of computing education and for other STEM disciplines for activities that were not designed as part of the formal in-class curriculum (e.g., outreach activities). A comparison-contrast analysis of the resulting 342 articles found similarities and key differences in the reporting of this data as well as overarching characteristics of missing or incomplete reporting across disciplines. Authors from both fields reported equally well in the four categories studied: information about evaluation, participant gender, participant race and/or ethnicity, and activity demographics. However, the computing education articles were more likely to have clearly stated research questions and comparative analysis based on demographic characteristics. They were less likely to include the number of participants in the study, participant age/grade level, socioeconomic status, disability information, location of intervention, and instructor demographics. Through this analysis, it was determined that reporting can be improved across all disciplines to improve the quantity of data needed to replicate studies and to provide complete data sets that provide for the comparison of collected data. [ABSTRACT FROM AUTHOR]

There is a clear call for pre-collegiate students in the United States to become literate in computer science (CS) concepts and practices through integrated, authentic experiences and instruction. Yet, a majority of in-service and pre-service pre-collegiate teachers (instructing children aged five to 18) lack the fundamental skills and self-efficacy to adequately and effectively integrate CS into existing curricula. In this study, 30 pre-collegiate teachers who represent a wide band of experience, grade-levels, and prior CS familiarity participated in a 16-day professional development (PD) course to enhance their content knowledge and self-efficacy in integrating CS into existing lessons and curricula. Using both qualitative and quantitative methodology, a social constructivist approach guided the researchers in the development of the PD, as well as the data collection and analysis on teacher content knowledge and perceptions through a mixed-methods study. Ultimately, participants were introduced to CS concepts and practices through NetLogo, which is a popular multi-agent simulator. The results show that although the pre-collegiate teachers adopted CS instruction, the CS implementation within their curricula was limited to the activities and scope of the PD with few adaptations and minimal systemic change in implementation behaviors. [ABSTRACT FROM AUTHOR]