Informatics in Education

Computing as a discipline has common roots with mathematics and written languages, and computing as a way of thinking and handling has been integral to human culture since ever. This is not only a reasonable argument for convincing society to consider informatics as one of the very fundamental pillars of education, but it also puts the potential contributions of teaching informatics in schools into the correct perspective in the context of science and humanities. Many European countries are switching from teaching information technologies to informatics education during the current second decade of this century. Informatics curriculum is becoming a central part of school education. We explain and design a way of developing informatics curriculum that offer the critical competences new generations need to survive and thrive in todays’ knowledge society and will allow them to contribute to the future development of society. These competences also strongly support the development of their intellectual potential and creativity. Our design of informatics curriculum takes into account the interaction with other scientific disciplines as well with the subject didactics, pedagogy and psychology. The starting point is merging constructionism and critical thinking. Constructionism with its “learning by doing” and “learning by getting things to work” enables designing a teaching process in which students acquire knowledge by creating products, analysing the properties and the functionality of their own products, and finally derive motivation to improve these products. Critical thinking asks us not to teach products of science and technology and their application, but to teach the creative process of their development. To implement this approach, we use the historical method allowing the students to learn by productive failures in the process of searching for a solution. To organize the process of learning and make the different steps available to the appropriate age groups we take into account the cognitive dimensions of the revised taxonomy of Bloom. To illustrate how the combination of all these concepts works we present a detailed curriculum for algorithm design, programming, robotics, and communication in networks.

Over its short disciplinary history, computing has seen a stunning number of descriptions of the field's characteristic ways of thinking and practicing, under a large number of different labels. One of the more recent variants, notably in the context of K-12 education, is "computational thinking", which became popular in the early 2000s, and which has given rise to many competing views of the essential character of CT. This article analyzes CT from the perspective of computing's disciplinary ways of thinking and practicing, as expressed in writings of computing's pioneers. The article describes six windows into CT from a computing perspective: its intellectual origins and justification, its aims, and the central concepts, techniques, and ways of thinking in CT that arise from those different origins. The article also presents a way of analyzing CT over different dimensions, such as in terms of breadth vs. depth, specialization vs. generalization, and in terms of skill progression from beginner to expert. Those different views have different aims, theoretical references, conceptual frameworks, and origin stories, and they justify their intellectual essence in different ways.

The development of communication and other soft skills among computer science students is not usually an easy task. Often, curricula focus on technical skills, with team projects being used for the improvement of communication skills. However, these teams usually comprise solely of computer science students. In this paper, we present a didactical methodology, called MIMI, which can be used in a short, intensive, programme for undergraduate students. This methodology has been implemented in real projects that have run annually since 2014. We advocate the use of team-based projects, with an important requirement that each team is both multidisciplinary and multinational. Additionally, the period of teamwork is short and intensive. A significant role in the project is given to team mentors. A mentor is a person, usually a university lecturer, who helps the team organize their work and tracks if the team’s planned didactical results are being achieved. The program has proved to stimulate an increase of soft skills among the students who participated and, in particular, among the computer science students. The detailed description of our process will allow others to implement and build similar events in their university or company environments, the focus of which is a Multinational, Intercultural, Multidisciplinary & Intensive (MIMI) methodology approach.

Intelligent Tutoring Systems (ITSs) for Math still use traditional data input methods: computers’ keyboard and mouse. However, students usually solve math tasks using paper and pen. Therefore, the gap between the manner the students work and the requirements imposed by these typing-based systems expose students to an extraneous cognitive load, impairing their learning. Our study investigates the impact of the data input method on students’ learning and fluency in solving equations using step-based math ITSs. More specifically, we have considered the standard typing and handwriting input methods. We hypothesized that the students would be more fluent using their handwriting with online recognition to solve math equations than using the typing input method. This fluency indicates a reduction in cognitive load, freeing working memory for logical reasoning instead of interface preconditions, leading to improved learning. We have conducted an experiment with 55 seventh-grade students from a private school to validate the hypothesis, randomly assigned to control and experimental groups. Each group used one of the input methods on two different devices (desktop computers and tablets). Although students using handwriting solved more equations and were faster than students who typed their equations, we could not find statistically significant differences in the learning between students that used typing or handwriting. Additionally, we have found that the input method used in a not ideal device (e.g., handwriting with a computer’s mouse instead of using a touch screen device) can negatively affect the students’ performance.

Nowadays, solving problems is substantial for the social relationship human. Computational Thinking (CT) emerges as an interdisciplinary thought process encompassing mental abilities to help students solve and understand problems. Researchers invest in the methodological proposal of activities aimed at CT stimulation, educational approaches, and the conception of technologies that support these activities’ execution. Educational Robotics (ER) is one of these technologies that stand out at different educational levels to favor teamwork, logical thinking, and creativity, skills intimately articulated with the computing paradigm. The main objective of this work is to investigate the impact of ER activities on CT development and subjects learning in the Technical and Vocational Education in High School. For this, we accomplished a study of intervention research type with students and teachers analyzing quantitative and qualitative aspects. The results indicate that the introduction of ER can favor students in the development of CT skills and learning High School subjects.

Education 4.0 (E4) aims to improve the teaching-learning process and democratize access to quality education by using Industry 4.0 technologies in educational environments. The main objective of this article is to propose a framework containing a package of policies and initiatives for the drivers of society (industry, government, and academia) to develop E4. The framework was elaborated through systematic review based on good practices, challenges, and opportunities of E4, which were systematized considering the technical-scientific literature and the authors' experience. The main scientific contribution of this work is the creation of a new block of knowledge about E4 that expands and at the same time deepens the existing literature and can support new research and foster initiatives on the subject. Its main applied contribution is to increase access to quality education through the development of E4.

Integrating computational thinking into K-12 Education has been a widely explored topic in recent years. Particularly, effective assessment of computational thinking can support the understanding of how learners develop computational concepts and practices. Aiming to help advance research on this topic, we propose a data-driven approach to assess computational thinking concepts, based on the automatic analysis of data from learners’ computational artifacts. As a proof of concept, the approach was applied to a Massive Open Online Course (MOOC) to investigate the course’s effectiveness as well as to identify points for improvement. The data analyzed consists of over 3300 projects from the course participants, using the Scratch programming language. From that sample, we found patterns in how computational thinking manifests in projects, which can be used as evidence to guide opportunities for improving course design, as well as insights to support further research on the assessment of computational thinking.

This paper proposes and validates a short and simple Expectancy-Value-Cost scale, called EVC Light. The scale measures the motivation of students in computing courses, allowing the easy and weekly application across a course. One of the factors related directly to the high rate of failure and dropout in computing courses is student motivation. However, measuring motivation is complex, there are several scales already carried out to do that job, but only a few of them consider the longitudinal follow-up of motivation throughout the courses. The EVC Light was applied to 245 undergraduate students from four universities. The Omega coefficient, scale items intercorrelation, item-total correlation, and factor analysis are used to validate and measure the reliability of the instrument. Confirmatory and exploratory factor analyses supported the structure, consistency, and validity of the EVC Light scale. Moreover, a significant relationship between motivation and student results was identified, based mainly on the Expectancy and Cost factors.

Research trends on computational thinking (CT) and its learning strategies are showing an increase. The strategies are varying, for example is using games to provide enjoyment, engagement, and experience. To improve the high level of immersion and presence of game objects, learning strategies through games can be improved by virtual reality (VR) technology and its application. However, a systematic review that specifically discusses game based in VR (GBiVR) settings is lacking. This paper reports previous studies systematically about the strategies used to learn CT through games and VR applications. 15 papers were selected through Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. As the result, this study proposes a conceptual framework for designing a strategy to learn CT through GBiVR settings. The framework consists of critical aspects of variables that can be considered in the learning environment like game elements, VR features, and CT skills. All the aspects are discussed below.

With the growing search for qualified professionals in the exact area, teaching in STEM (Science, Technology, Engineering, and Mathematics) areas is gaining importance. In parallel, it appears that drones are an increasingly present reality in the civil area; however, there are few scientific studies of their application in the pedagogical environment, and their insertion is still practically nil in the school environment. Thus, this work aims to analyze the feasibility of using a set of technologies based on drones, designed based on the theory of significant learning through the use of active methodologies. The study was carried out with 30 high school students and followed a line of quali-quantitative analysis, in which the quantitative data were collected from the results obtained in a pre and post-test and the qualitative ones through recordings during the interventions, observations of the researcher, and a semi-structured press interview. Finally, a triangulation between the methodologies was carried out, looking for congruent aspects between the different techniques used. As a result, it was found that the workshops with the platform based on drones helped in the understanding, construction, and interpretation of the content covered, and it can be concluded that there is a significant relationship between the use of the technological set proposed in the pedagogical process and the possibility of significant learning in the STEM areas by the students.