The aim of the article is to determine in the studied groups the multiple intelligence distribution defined in the 1980s by Howard Gardner. The research was conducted in three groups of respondents. The first study group was first-year students of computer science, the second was master (2nd degree) students, educationally 4 years older than the first group. Their intelligence distributions were compared with the intelligence distributions of the third group – graduates of the same university, the same field of study after several years of work in positions consistent with their education. Participants filled one of the multiple intelligence tests selected by answering 24 questions. A group of approximately 110 students and approximately 40 IT employees were examined. As there were statistically justified differences in several significant sub intelligences, a discussion was held on the forms of educational impact on student development paths. The research was carried out in conditions of full voluntary participation in the test and on the basis of self-assessment according to questions suggested in one of the online sources. According to the authors, the results seem interesting, although surprising.
In recent years, Artificial Intelligence (AI) has shown significant progress and its potential is growing. An application area of AI is Natural Language Processing (NLP). Voice assistants incorporate AI by using cloud computing and can communicate with the users in natural language. Voice assistants are easy to use and thus there are millions of devices that incorporates them in households nowadays. Most common devices with voice assistants are smart speakers and they have just started to be used in schools and universities. The purpose of this paper is to study how voice assistants and smart speakers are used in everyday life and whether there is potential in order for them to be used for educational purposes.
Information Visualisation strategies can be applied in a variety of domains. In the context of temporal networks, i.e., networks in which interactions between individuals occur throughout time, efforts have been conducted to develop visual approaches that allow finding interaction patterns, anomalies, and other behaviours not previously perceived in the data. This paper presents two case studies involving real-world education networks from a primary school and a high school. For this purpose, we used the Massive Sequence View (MSV) layout with the Community-based Node Ordering (CNO) method, two well established approaches for visual analysis of temporal networks. Our results show that the identified patterns involving students/students and students/teachers represent important information to benefit and support decision making about school management and teaching strategies, especially those related to strategic group formation.
As the number of software vulnerabilities discovered increases, the industry is facing difficulties to find specialists to cover the vacancies for security software developers. Considering relevant teaching and learning theories, along with existing approaches in software security education, we present the pedagogic rationale and the concrete implementation of a course on security protocol development that integrates formal methods for security research into the teaching practice. A novelty of the framework is the adoption of a conceptual model aligned with the level of abstraction used for the symbolic (high-level) representation of cryptographic and communication primitives. This is aimed not only at improving skills in secure software development, but also at bridging the gap between the formal representation and the actual implementation, making formal methods and tools more accessible to students and practitioners.
The purpose of this study is to investigate the effects of applications created using a web-based 3D design environment on the spatial visualisation and mental rotation abilities of secondary school students. A total of 63 school students from the sixth grade participated in the study. The researchers applied a mixed research method including both quantitative and qualitative measures. The Spatial Visualisation Test, Mental Rotation Test, and Santa Barbara Solids Test, which concurrently measure spatial orientation and spatial relations, were used as tools to measure the different components of spatial ability prior to and after the treatment application. Following the treatment, a focus group interview using structured questions was conducted. A statistically significant difference showed an increase in all three test scores of the students; also, the students stated that they were satisfied with being able to design and create something new.
This paper presents a systematic literature review of the coordinated use of Learning Analytics and Computational Ontologies to support educators in the process of academic performance evaluation of students. The aim is to provide a general overview for researchers about the current state of this relationship between Learning Analytics and Ontologies, and how they have been applied in a coordinated way. We selected 31 of a total of 1230 studies related to the research questions. The retrieved studies were analyzed from two perspectives: first, we analyzed the approaches where researchers used Learning Analytics and Ontologies in a coordinated way to describe some Taxonomy of Educational Objectives; In the second perspective, we seek to identify which models or methods have been used as an analytical tool for educational data. The results of this review suggest that: 1) few studies consider that student interactions in the Learning Management System can represent students’ learning experiences; 2) most studies use ontologies in the context of learning object assessment to enable learning sequencing; 3) we did not identify methods of evaluation of academic performance guided by Taxonomies of Educational Objectives; and 4) no studies were identified that report the coordinated use of Learning Analytics and Computational Ontologies, in the context of academic performance monitoring. Thus, we identify future directions of research such as the proposal of a new model of evaluation of academic performance.
The paper discusses a certain type of competitions based on distance interaction of a participant with simulation models of concepts from discrete mathematics and computer science. One of them is the “Construct, Test, Explore” (CTE) competition, developed by the authors, the other is the Olympiad in Discrete Mathematics and Theoretical Informatics (DM&TI). The tasks presented in this paper are generally devoted to the concept of a graph isomorphism. Most of the tasks are verified automatically.
The purpose of this systematic literature review is to explore the area of digital Game-Based Learning (GBL) for students with intellectual disabilities as a tool that enables positive impact on learning and mastering specific skills in order to make recommendations for future research. Twenty-one studies were selected from different databases. The results showed that the most common type of game was serious game, and the most common used technology was PC with additional equipment, but tablets were also often used. In addition, the studies were more focused on the development of cognitive abilities rather than of adaptive skills.
Although Machine Learning (ML) is integrated today into various aspects of our lives, few understand the technology behind it. This presents new challenges to extend computing education early to ML concepts helping students to understand its potential and limits. Thus, in order to obtain an overview of the state of the art on teaching Machine Learning concepts in elementary to high school, we carried out a systematic mapping study. We identified 30 instructional units mostly focusing on ML basics and neural networks. Considering the complexity of ML concepts, several instructional units cover only the most accessible processes, such as data management or present model learning and testing on an abstract level black-boxing some of the underlying ML processes. Results demonstrate that teaching ML in school can increase understanding and interest in this knowledge area as well as contextualize ML concepts through their societal impact.
eLearning is fast progressing scientific field proposing novel and specific approaches in a range of domains. It is well established practice in universities, schools and organizations for delivering interactive, adaptive and flexible training, taking advantage of contemporary and emerging technologies. Informatics is a continuously evolving science presenting its theoretical and practical advances applicable in various research areas, including in eLearning. The paper presents an exploration focused on the symbiotic connection between Informatics and eLearning that leads to contemporary and innovative solutions, facilitating and automating a wide variety of activities at information processing. The term eLearning Informatics is conceptualized and explained as a scientific field outlining the current research achievements and further directions for development. The applied research methodology is based on outlining the main vision in the domain eLearning Informatics through utilization of bibliometric approach and construction of bibliometric networks as well as on detailed examination of topic-related scientific papers.