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Significant interest in teaching children to code since Preschool Education has arisen in recent years. This paper focuses on the benefits of preschoolers learning to code at such short age. The research questions are whether by coding they can improve skills such as sequencing and plotting a route? Which factors influence the learning? And, to what extent? To start coding, preschoolers might use robots such as Cubetto or KIBO, or other unplugged resources such as foam. Moreover, stories could be used to provide a context and a goal for the coding experience. An experiment was carried out with 192 children between 3 and 6 years old in age to gather some data. The hypothesis that the skills were improved by coding was proved; and that age, resources, and initial knowledge influence the learning process. This paper contributes more evidence of the benefits of coding in early years.

In this paper, a multi-mode digital teaching approach is proposed based on the use of the VARK (Visual, Aural, Read/Write, Kinaesthetic) model where students have different styles (one or more) that improve their learning (face-to-face and online). Our research question is on the effectiveness of this approach in terms of learning efficacy and students' satisfaction. An experiment with 41 students has been carried out for five months to answer the research question and to provide a first validation of using VARK for multi-mode digital HCI teaching. During the experiment, the theoretical sessions were given through videoconference using Microsoft Teams and with the support of Moodle. In the practical sessions, students had to create a software prototype following a User-Centred Design with a real client. For this, they used Discord to collaborate in their groups, Teams to ask questions to teachers and PowerPoint and Genially to present their work online to the class through a Teams videoconference. A regression model has been provided to predict the VARK indicated by the questionnaire to each student with a prediction success of nearly 77%. Using the VARK multi-mode digital teaching approach has proved valid, and effective and beneficial in the teaching of HCI with a significant improvement in the learning scores and satisfaction levels of the students even with respect to pre-COVID-19 where the teaching was face-to-face.

Computational Thinking (CT) can be defined as the thought processes involved in formulating problems so that their solutions can be represented as sequential steps and algorithms. It is a key skill for children in the 21st century. However, it is unclear how CT can be developed most effectively in children. Several pedagogical methodologies have been proposed and are being investigated. The main aim of this paper is to test the hypothesis which states that using three‐dimensional (3D) simulated robots helps in the learning of programming and CT concepts, such as directions, loops, conditionals, and functions. The research questions are: Does this hypothesis hold true? Are some concepts easier or better learned than others and to what extent? The goal is to measure and evaluate the effect of using as a learning tool a platform with 3D simulated robots and realistic physics, and compare it with the standard Scratch learning tool which does not use robotics but a two‐dimensional (2D) cartoon avatar they are already familiar with. For practical reasons, a quasiexperimental design with nonequivalent groups and 85 second‐year Secondary Education students (ages 12–13) was performed. They were separated into control and experimental groups and followed a seven‐session intervention with the baseline 2D Scratch and the 3D simulated robots platform, respectively. Both used a visual block programming language and the same activities. To have quantitative and reliable results, a widely accepted CT test has been used, pre‐ and postintervention. Also qualitative feedback is presented. The obtained results show that using the platform with simulated 3D robots significantly helps when developing students' CT. With it, the students do learn basic programming concepts and reach higher scores in the CT test. This improvement applies to all CT‐analyzed concepts except in functions where the grades are maintained. Furthermore, students manage to master the activities on the 3D simulated robots platform, which reflects on the empowerment the platform has got in them. [ABSTRACT FROM AUTHOR]

Featured Application: Altogether, UniCTCheck, a method for measuring the main components of computational thinking of CS university students, was employed by using the following two instruments: firstly, a web application, CTScore, to precisely measure seven of the main components of computational thinking (pattern recognition, creative thinking, algorithmic thinking, problem solving, critical thinking, decomposition, and abstraction); secondly, a psychometric scale, CTProg, to measure CT programming concepts skills (basic directions and sequences, conditionals, loops, functions, and data structures). The measurement of computational thinking ability among computer science (CS) university students is of paramount importance. This study introduces UniCTCheck, a novel method designed to assess the main components of computational thinking in CS students. Utilising two key instruments, namely, the web application CTScore and the psychometric scale CTProg, this research aims to precisely evaluate seven core components of computational thinking and six programming concepts skills essential for CS students. The study, conducted at Rey Juan Carlos University and Atlantic Technological University Galway, involved a diverse sample of students from different year levels and programme specialisations. Through a rigorous research design, including sampling strategies and data collection tools, this study seeks to address critical research questions related to the measurement of variations in students' computational thinking and programming skills by gender, university level, and location. By shedding light on the significance of computational thinking and programming in the educational realm, this research contributes to the existing literature and underscores the essential role of computational skills in the modern era. [ABSTRACT FROM AUTHOR]

An evaluation of the educational effectiveness of a didactic method for the active learning of greedy algorithms is presented. The didactic method sets students structured-inquiry challenges to be addressed with a specific experimental method, supported by the interactive system GreedEx. This didactic method has been refined over several years of use. Additional elements are lecture contents and the scheduling of classes and lab sessions. Learning gain in the topic of greedy algorithms was measured in the short term for two groups of students: an experimental group taught with the new didactic method, and a control group taught with a traditional approach. The results show a significant learning gain improvement in the experimental group, while the students taught with a traditional method had little learning gain. In addition, the levels of Bloom's taxonomy at which improvements occurred were identified. In the control group, improvements were found at the knowledge level. In the experimental group, however, improvements were found at the knowledge and the comprehension levels, although not at the analysis level. These results are encouraging and indicate directions for future research, as analysis skills are important in algorithm courses.

Significant interest in teaching children to code since Preschool Education has arisen in recent years. This paper focuses on the benefits of preschoolers learning to code at such short age. The research questions are whether by coding they can improve skills such as sequencing and plotting a route? Which factors influence the learning? And, to what extent? To start coding, preschoolers might use robots such as Cubetto or KIBO, or other unplugged resources such as foam. Moreover, stories could be used to provide a context and a goal for the coding experience. An experiment was carried out with 192 children between 3 and 6 years old in age to gather some data. The hypothesis that the skills were improved by coding was proved; and that age, resources, and initial knowledge influence the learning process. This paper contributes more evidence of the benefits of coding in early years. [ABSTRACT FROM AUTHOR]

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Copyright of Informática Educativa Comunicaciones is the property of Asociacion para el Desarrollo de la Informatica Educativa and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)