Reading, or the ability to infer meaning from printed words in order to correctly interpret relevant information, is the most fundamental component of education. To recognize letters, letter strings, and words, one must possess the ability to decode abstract graphemes accurately and fluently into their corresponding phonemes. Additionally, processing text requires the capacity to read and comprehend text with both fluency and accuracy. Thus, reading requires a variety of cognitive abilities, including effective processing speed, phonological awareness, syntactic processing, auditory and visual word recognition, and phonological awareness. The present study reports the outcomes of a research that evaluated the identification of students with reading disabilities using an artificial neural network. The neural network consisted of structured tasks aiming at a) reading, b) distinguishing words and pseudowords and c) reading two texts. Participants were 235 children attending grades from third to sixth class. Audio is converted into a spectrogram and students with disabilities are identified using machine learning algorithms and auditory analysis. The outcome of the present study suggests that a neural network that is comprised from three tasks can identify the reading abilities and classify the school aged children between typical achievers and reading disabled. Furthermore, including the mAP scores, the results show that the model is highly effective in identifying and classifying reading difficulties in real-time, offering a promising avenue for future research and practical applications in educational settings.

The typical way to learn programming is using different high-level programming languages and a simple text editor, in order to compose and compile programs, usually to solve simple computational problems. Nowadays, an alternative method for the introduction of lower secondary school students into programming is through educational robotics. In this work, we design, organize and implement a teaching model in the context of flipped classroom learning, using educational robotics and an asynchronous tele-education environment for courses with limited weekly school time. Such a model must include learning independent of time and place, a more efficient use of classroom time and a cooperative teaching technique in cross-curricular subjects. The whole process is evaluated by the lower secondary school students themselves through a data collection tool and the relevant results are presented.

Programming, most recently in the form of Computational Thinking (CT), is emerging as a new subject in primary schools worldwide. By data-based decision making, teachers, as learning designers, make decisions on instruction design based on a broad range of evidence, such as student assessment scores and classroom teaching observations. Given the current limitations on conclusive, field-proven teaching practices and an underlying “culture” to use as a basis, we turn to pertinent empirical studies that the growing scientific interest on introducing programming in primary school curricula has produced. The hypothesis is that we may overcome the lack of extensive experience in designing a programming course by reviewing the above evidence, in order to frame learning situations and methods.

Popular interest in robotics has increased significantly over the last years. It has been claimed that robotics can provide new benefits to the learning process at all levels of education. The main ideas of the present study adhered to the constructionist theory, according to which the learning process is not only transmitted from teacher to pupil, but rather constructed in the mind of the pupil in the form of active learning. The purpose of the present study was to implement a robotic toy (Lego Mindstorms NXTTM) in a Greek primary school, in order to teach twelve year-old children some of the basic concepts of geometry. The main hypothesis of the present study was that children who used the Lego Mindstorms NXT platform would score higher on an evaluation questionnaire than children who formed the control group. Descriptive statistical analysis was performed in order to evaluate the correct answers of the questionnaires. Statistical analysis revealed that children who participated in the experimental group performed better in the 21 items of the questionnaire. Moreover, they mentioned that the geometry course became more interesting and drew their attention in comparison to the courses that were taught through the standard teaching process. It is apparent that the present study follows the line of inquiries that supports that robotics can make a significant impact to education. Robots can be a tool that can enhance the skills of children.

Dyscalculia is a neurodevelopmental disorder that affects the ability of a child to learn arithmetic. Dyscalculia appears despite normal intelligence, proper schooling, adequate environment, socioeconomic status and motivation. The first aim of the present research protocol was to construct a battery of tests that can be delivered by computer in order to screen children's arithmetic skills. Our second aim was to develop a web application screener for dyscalculia that assesses children aged from 8–11 years old and that, to the best of our knowledge, does not exist. The hypothesis of the present study was that Greek students that are already diagnosed by paper-and-pencil tests as dyscalculic, will present lower performance and higher time latencies in the tasks of the aforementioned web application screener. A total of sixty, right handed children (30 male and 30 female, age range 8–11 years old) participated in this study. The students with disorders in mathematics (N=30, 15 male and 15 female) had a statement of dyscalculia issued after assessment at a Centre of Diagnosis, Assessment and Support, as required by Greek Law. The comparison group (N=30) was formed by pupils who attended the same classes with dyscalculics, presented typical academic performance according to their teachers' ratings and had been matched for age and gender with the children with disorder in mathematics. Three tasks were used for evaluating children's arithmetic ability: a calculation task, a task that evaluated their skills in understanding mathematical terminology, and an arithmetic problem solving task. Statistical analysis revealed that children with dyscalculia had statistically significant lower mean scores of correct answers and larger time latencies in all tasks compared to their average peers that participated in the comparison group. In conclusion, it must be highlighted that the web application screener for dyscalculia used in this study was found to be a feasible instrument for first-pass screening services and referral.