Critical thinking is a fundamental skill for 21st-century citizens, and it should be promoted from elementary school and developed in computing education. However, assessing the development of critical thinking in educational contexts presents unique challenges. In this study, a systematic mapping was carried out to investigate how to assess the development of critical thinking, or some of its skills, in K-12 computing teaching. The results indicate that primary studies on the development of critical thinking in K-12 computing education are concentrated in Asian countries, mainly focusing on teaching concepts such as algorithms and programming. Moreover, the studies do not present a fixed set of critical thinking skills assessed, and the skills are selected according to specific teaching and research needs. Most of the studies adopted student self-assessment using instruments that are well-known in the literature for assessing critical thinking. Many studies measured the quality of instruments for their research, obtaining favorable results and demonstrating consistency. However, the research points to a need for more diversity in assessment methods beyond student self-assessment. The findings suggest a need for more comprehensive and diverse critical thinking assessments in K-12 computing education, covering different educational stages and computing education concepts. This research aims to guide educators and researchers in developing more effective critical thinking assessments for K-12 computing education.
In K-12 computing education, there is a need to identify and teach concepts that are relevant to understanding machine learning technologies. Studies of teaching approaches often evaluate whether students have learned the concepts. However, scant research has examined whether such concepts support understanding digital artefacts from everyday life and developing agency in a digital world. This paper presents a qualitative study that explores students’ perspectives on the relevance of learning concepts of data-driven technologies for navigating the digital world. The underlying approach of the study is data awareness, which aims to support students in understanding and reflecting on such technologies to develop agency in a data-driven world. This approach teaches students an explanatory model encompassing several concepts of the role of data in data-driven technologies. We developed an intervention and conducted retrospective interviews with students. Findings from the analysis of the interviews indicate that students can analyse and understand data-driven technologies from their everyday lives according to the central role of data. In addition, students’ answers revealed four areas of how learning about data-driven technologies becomes relevant to them. The paper concludes with a preliminary model suggesting how computing education can make concepts of data-driven technologies meaningful for students to understand and navigate the digital world.
Information technology (IT) is transforming the world. Therefore, exposing students to computing at an early age is important. And, although computing is being introduced into schools, students from a low socio-economic status background still do not have such an opportunity. Furthermore, existing computing programs may need to be adjusted in accordance to the specific characteristics of these students in order to help them to achieve the learning goals. Aiming at bringing computing education to all middle and high-school students, we performed a systematic literature review, in order to analyze the content, pedagogy, technology, as well as the main findings of instructional units that teach computing in this context. First results show that these students are able to learn computing, including concepts ranging from algorithms and programming languages to artificial intelligence. Difficulties are mainly linked to the lack of infrastructure and the lack of pre-existing knowledge in using IT as well as creating computing artifacts. Solutions include centralized teaching in assistive centers as well as a stronger emphasis on unplugged strategies. However, there seems to be a lack of more research on teaching computing to students from a low socio-economic status background, unlocking their potential as well to foster their participation in an increasing IT market.
Nowadays, SPOCs (Small Private Online Courses) have been used as complementary methods to support classroom teaching. SPOCs are courses that apply the usage of MOOCs (Massive Open Online Courses), combining classroom with online education, making them an exciting alternative for contexts such as emergency remote teaching. Although SPOCs have been continuously proposed in the software engineering teaching area, it is crucial to assess their practical applicability via measuring the effectiveness of this resource in the teaching-learning process. In this context, this paper aims to present an experimental evaluation to investigate the applicability of a SPOC in a Verification, Validation, and Software Testing course taught during the period of emergency remote education during the COVID-19 pandemic in Brazil. Therefore, we conducted a controlled experiment comparing alternative teaching through the application of a SPOC with teaching carried out via lectures. The comparison between the teaching methods is made by analyzing the students’ performance during the solving of practical activities and essay questions on the content covered. In addition, we used questionnaires to analyze students’ motivation during the course. Study results indicate an improvement in both motivation and performance of students participating in SPOC, which corroborates its applicability to the software testing teaching area.
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.
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.
In today’s society, creativity plays a key role, emphasizing the importance of its development in K-12 education. Computing education may be an alternative for students to extend their creativity by solving problems and creating computational artifacts. Yet, there is little systematic evidence available to support this claim, also due to the lack of assessment models. This article presents SCORE, a model for the assessment of creativity in the context of computing education in K-12. Based on a mapping study, the model and a self-assessment questionnaire are systematically developed. The evaluation, based on 76 responses from K-12 students, indicates a high internal reliability (Cronbach’s alpha = 0.961) and confirmed the validity of the instrument suggesting only the exclusion of 3 items that do not seem to be measuring the concept. As such, the model represents a first step aiming at the systematic improvement of teaching creativity as part of computing education.
Although Machine Learning (ML) has already become part of our daily lives, few are familiar with this technology. Thus, in order to help students to understand ML, its potential, and limitations and to empower them to become creators of intelligent solutions, diverse courses for teaching ML in K-12 have emerged. Yet, a question less considered is how to assess the learning of ML. Therefore, we performed a systematic mapping identifying 27 instructional units, which also present a quantitative assessment of the students’ learning. The simplest assessments range from quizzes to performance-based assessments assessing the learning of basic ML concepts, approaches, and in some cases ethical issues and the impact of ML on lower cognitive levels. Feedback is mostly limited to the indication of the correctness of the answers and only a few assessments are automated. These results indicate a need for more rigorous and comprehensive research in this area.
The journal Informatics in Education and the conference Koli Calling are compared, starting with Simon's system for the classification of computing education papers and going on to conduct a brief bibliometric analysis of the authors of papers in both publications, including their repeat rates and the countries from which they come. The analysis finds that despite their different natures, the Lithuanian journal and the Finnish conference are highly comparable in many respects. The broad conclusion is that the two publications work well together - but it would be good to see some Lithuanian authors contributing papers to Koli Calling.
As part of a wide-ranging phenomenographic study of computing teachers, we explored their varying understandings of the lab practical class and discovered four distinct categories of description of lab practicals. We consider which of these categories appear comparable with non-lecture classes in other disciplines, and which appear distinctive to computing. An awareness of this range of approaches to conducting practical lab classes will better enable academics to consider which is best suited to their own purposes when designing courses.