Informatics in Education

Computational Thinking (CT) has emerged in recent years as a thematic trend in education in many countries and several initiatives have been developed for its inclusion in school curricula. There are many pedagogical strategies to promote the development of elementary school students’ CT skills and knowledge. Unplugged learning tasks, block-based programming projects, and educational robotics are 3 of the most used strategies. This paper aimed to analyze the effect of Scratch-based activities, developed during one scholar year, on the computational thinking skills developed and concepts achieved by 4th-grade students. The study involved 189 students from two school clusters organized into an experimental group and a control group. To assess students’ computational knowledge, the Beginners Computational Thinking Test developed by Several Zapata-Cáceres et al. (2020) was used. The results indicate statistically significant differences between the groups, in which students in the experimental group (who performed activities with scratch) scored higher on the test than students in the control group (who did not use Scratch).

Connecting theory and practice in teaching is sometimes difficult, as it requires expensive or delicate equipment, thus limiting the teacher to giving demonstrations in which students are passive participants. Numerical mathematics, as an applied discipline, should be taught on real world examples. By using inexpensive Arduino hardware, we can create simple experiments that are easily reproduced by students. Furthermore, the experiments generate tangible data, which can be processed numerically. The choice of the software used for numerical processing is also an important issue. We present several exercises in numerical mathematics that are based on experiments in electrical engineering with Arduino, and show how to turn them into motivational examples. We also present our experiences in teaching using the developed exercises, as well as some important points and conclusions, which stem from discussions with the participating students and teachers.

The use of computers as teaching and learning tools plays a particularly important role in modern society. Within this scenario, Brazil launched its own version of the 'One Laptop per Child' (OLPC) program, and this initiative, termed PROUCA, has already distributed hundreds of low-cost laptops for educational purposes in many Brazilian schools. However in spite of the numerous studies conducted in the country since PROUCA was launched, Brazil shows a lack of proficiency in basic information crucial for managing and improving any OLPC initiative (e.g., number of effectively used laptops, use time and distribution per subject, use location and school performance of users, and others). Therefore, the focus of this article is to introduce MEMORE, a computational environment for longitudinal on-line data collection, integration and an analysis of how PROUCA laptops are used by schools. Technical details about MEMORE's architecture, database and functional models are supplied and the results from real data collected from Brazilian public schools are presented and analyzed. They elucidate how MEMORE can be a valuable management tool in OLPC contexts.

Computer programming is perceived as an important competence for the development of problem solving skills in addition to logical reasoning. Hence, its integration throughout all educational levels, as well as the early ages, is considered valuable and research studies are carried out to explore the phenomenon in more detail. In light of these facts, this study is an exploratory effort to investigate the effect of Scratch programming on 5th grade primary school students' problem solving skills. Moreover, the researchers wondered what 5th grade primary school students think about programming. This study was carried out in an explanatory sequential mixed methods design with the participation of 49 primary school students. According to the quantitative results, programming in Scratch platform did not cause any significant differences in the problem solving skills of the primary school students. There is only a non-significant increase in the mean of the factor of "self- confidence in their problem solving ability". When the thoughts of the primary students were considered, it can be clearly stated that all the students liked programming and wanted to improve their programming. Finally, most of the students found the Scratch platform easy to use.

Text mining has been used for various purposes, such as document classification and extraction of domain-specific information from text. In this paper we present a study in which text mining methodology and algorithms were properly employed for academic dishonesty (cheating) detection and evaluation on open-ended college exams, based on document classification techniques. Firstly, we propose two classification models for cheating detection by using a decision tree supervised algorithm. Then, both classifiers are compared against the result produced by a domain expert. The results point out that one of the classifiers achieved an excellent quality in detecting and evaluating cheating in exams, making possible its use in real school and college environments.