Informatics in Education

The rapid development of technology in today’s times make business’ survival a rather complex task. It is therefore necessary for the specialized organization and administration of each company to differentiate and strengthen its competitive advantages. Gamification is an established practice in many business domains and can enforce employees to engage in business processes and change aspects of their behavior. Even though numerous gamification patterns that are described in literature have been used so far by businesses to various working environments, the outcomes were not the best possible that we would expect in terms of their right utilization to business non-game contexts. Thus, there is need for concise gamification patterns that can offer right guidance to game designers in business. Gamification design patterns can provide a distilled knowledge of techniques of how to design object-oriented software. This paper aims to address this gap in existing literature by describing new gamification design patterns, classifying them according to specific criteria and providing new information to this research domain. Our study is a descriptive literature review and is based on review of previous works. This descriptive literature review tries to give a better understanding by proposing new gamification design patterns in the continuously evolving research domain of gamification design patterns.

We describe a collaboration between Marelli and Università degli Studi di Milano that allowed the latter to add a course on «Architectures for Big Data» in its Master programme of Computer Science, with the aim of providing a teaching approach characterized by an intertwined exposition of discipline, methodology and practical tools. We were motivated by the need of filling, at least in part, the gap between the expectation of employers and the competences acquired by students. Indeed, several big-data-related tools and patterns of widespread use in working environments are seldom taught in the academic context. The course also allowed to expose students to company-related processes and topics. So far, the course has been taught for two editions, and a third one is currently ongoing. Using both a quantitative and a qualitative approach, we show that students appreciated this new form of learning activities, in terms of enrollments, exam marks, and activated external theses. We also exploited the received feedback in order to slightly modify the content and the structure of the course.

Scrum is a widely-used framework in industry, so many schools apply it to their software engineering courses, particularly capstone courses. Due to the differences between students and industrial professionals, changing Scrum is necessary to fit capstone projects. In this paper, we suggest a decision-making process to assist instructors in developing a strategy to adapt Scrum for their course. This framework considers critical differences, such as student’s workloads and course schedules, and keeps the Agile principles and Scrum events. To evaluate the adapted Scrum, we investigated student’s learning experiences, satisfaction, and performance by quantitatively analyzing user story points and source codes and qualitatively studying instructor’s evaluations, student’s feedback, and Sprint Retrospective notes. Our two case studies about adapted Scrum showed that having daily stand-up meetings in every class was not helpful, student’s satisfaction positively correlated to the difficulty of the task they tackled, and the project provided good learning experiences.

The misalignment between the skills learned in tertiary education and the skills demanded by industry is well documented. One of the ways this misalignment can be reduced is through the introduction of an internship phase in degrees. This article identifies the perceived benefits and challenges that internship programmes offer academic staff in a tertiary educational facility. It also determines how feedback from the industry helps shape the curriculum of the degree. A qualitative case study is employed through interviews with various staff working at a tertiary education institution. The data generated is analysed using a thematic approach. The results show that internships not only place value on soft skills but also build a communication channel between the mentors that visit students whilst out on placement and the industry staff that oversee the students during the work-based phase. This mutually beneficial interaction between the industry and the education institution helps the mentors maintain familiarity with the latest technologies adopted in the industry and allows the industry to influence the curriculum of the degrees. Internships were shown to offer a means of advertising the skills gained in academia to the audience that would eventually employ the graduates.

The objective of this article is to present the creation process of Pedagogical Strategies (PS) based on Socio-affective Scenarios mapped in a Virtual Learning Environment (VLE). Every year, enterprises are looking for new technologies that can improve the skills of their collaborators, bringing VLE resources to e-training formations. The PSs are actions carried out by professors or manager in their practice, both for e-learning and e-training. In order to develop a PS, it is important to consider the socio-affective profile. For data inference were used: Social and Affective Map. Using these two tools, 38 Socio-affective Scenarios were mapped and their strategies were developed. This study utilizes an applied qualitative approach. As a result, a total of 228 PSs based on Socio-affective Scenarios were developed by 15 specialist professors. Its main contribution is the creation of PS based on criteria that can be adapted to be applied in the industry context.

According to the United Nations’ sustainable development goals education has a central role and progress has been made to offer a quality educational lifelong learning path to all. Unfortunately, recent crises, namely the pandemic and wars, have hampered progress and a prompt recovery is mandatory. Similarly, OECD recommendations on creating better opportunities for young people1 addressing key areas such as: ensuring relevant knowledge and allowing to develop appropriate skills and competencies; supporting youth in the transition to the labor market; promoting social inclusion. In this regard computing is considered important with a central role both as a discipline “per se” and as a supporting cognitive tool for all knowledge domains. The informatics reference framework for schools (Caspersen, 2022) offers a solid foundation, as does the STEM teaching framework (Tasiopoulou, 2022). Considering the current shortage in computing and information technology professionals and the projected need of a highly skilled workforce with increasing cognitive competencies, the importance of a quality lifelong education, including computing, is considered mandatory. An alliance between the educational system, from school to universities both formal and informal, and the Information Technology (IT) sectors has the potential for a win-win collaboration offering a more focused education with the right mix of foundational competencies and cutting-edge technical skills. Supporting all learners in improving their education by offering both quality content, pedagogies, technologies, and financial support is of highest importance and should be considered central to any organization’s corporate social responsibility agenda. In this respect the guest editors would like to rise a call for action for an even greater collaboration between the whole educational system and etenterprises with the ultimate goal of reducing the number of young people who are neither employed nor in education and training. The work for this special issue has been embraced with the aim to contributing with a grain of sand in this direction.

This study aims to provide a deeper understanding about the Bebras tasks, which is one of the computational thinking (CT) unplugged activities, in terms of age level, task category, and CT skills. Explanatory sequential mixed method was adopted in the study in order to collect data according to the research questions. The participants of the study were 113,653 school students from different age levels. Anonymous data was collected electronically from the Turkey 2019 Bebras challenge. Factor analysis was employed to reveal the construct validity to determine how accurately the tool measured the abstract psychological characteristics of the participants. In addition, the item discrimination index was calculated to measure how discriminating the items in the challenge were. Qualitative data gathered through the national Bebras workshop was analysed according to content analysis. The findings highlighted some interesting points about the implications of the Bebras Challenge for Turkey, which are discussed in detail. Furthermore, common problems of Bebras tasks are identified and possible suggestions for improvement are listed.

Teaching algorithmic thinking enables students to use their knowledge in various contexts to reuse existing solutions to algorithmic problems. The aim of this study is to examine how students recognize which algorithmic concepts can be used in a new situation. We developed a card sorting task and investigated the ways in which secondary school students arranged algorithmic problems (Bebras tasks) into groups using algorithm as a criterion. Furthermore, we examined the students’ explanations for their groupings. The results of this qualitative study indicate that students may recognize underlying algorithmic concepts directly or by identifying similarities with a previously solved problem; however, the direct recognition was more successful. Our findings also include the factors that play a role in students’ recognition of algorithmic concepts, such as the degree of similarity to problems discussed during lessons. Our study highlights the significance of teaching students how to recognize the structure of algorithmic problems.

This study aims to explore the usability of the virtual robotics programming curriculum (VRP-C) for robotics programming teaching. Pre-service computer science (CS) teachers were trained for robotics programming teaching by using VRP-C in a scientific education activity. After training, views of the participants were revealed by using a scale and an evaluation form consisting of open-ended questions. Results show that VRP-C is compatible with the curriculum for robotics programming teaching in schools, and pre-service CS teachers tend to use VRP-C in their courses. They think that VRP-C will be beneficial for robotics programming teaching in terms of content, functionality, and cost. Compatibility, visual design, feedback, time management, fiction, gamification, and cost are the characteristics that increase the usability of VRP-C. VRP-C can be used as an online tool for robotics programming training due to the necessity of transition to distance education because of the COVID-19 pandemic.

Although Machine Learning (ML) is used already in our daily lives, few are familiar with the technology. This poses new challenges for students to understand ML, its potential, and limitations as well as to empower them to become creators of intelligent solutions. To effectively guide the learning of ML, this article proposes a scoring rubric for the performance-based assessment of the learning of concepts and practices regarding image classification with artificial neural networks in K-12. The assessment is based on the examination of student-created artifacts as a part of open-ended applications on the use stage of the Use-Modify-Create cycle. An initial evaluation of the scoring rubric through an expert panel demonstrates its internal consistency as well as its correctness and relevance. Providing a first step for the assessment of concepts on image recognition, the results may support the progress of learning ML by providing feedback to students and teachers.