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Correction to: Implementation and Assessment Methodologies of Teachers’ Training Courses for STEM Activities (Technology, Knowledge and Learning, (2019), 24, 2, (247-268), 10.1007/s10758-018-9356-1)
No full textThe article listed above was initially published with incorrect copyright information. Upon publication of this Correction, the copyright of this article has been changed to “The Author(s)”. The original article has been corrected
Machine learning for modelling and identification of educational robotics activities
No full textEducational Robotics (ER) is a powerful tool to help students learn school subjects, robotics, and developing cognitive skills and soft skills. Assessing the learning outcomes of ER activities requires the identification of the model that underly the process. Machine learning can be useful to identify such models and to interpret data. This paper aims to present a system that could help integrating Educational Data Mining and Learning Analytics techniques into the open-ended learning environment that characterizes the constructionist approach of ER. Both supervised and unsupervised learning methods could be applied to extract meaningful information. Students' approaches to learning as well as a prediction of their final performance could inform teachers' decision and facilitate the implementation of effective ER activities in formal and non-formal education. First results show good premises for a future broader implementation, but more research is needed to face all the open issues
Identification and Assessment of Educational Experiences: Utilizing Data Mining with Robotics
No full textThis article describes an example of data mining techniques applied to an open educational environment. These novel assessment methods in the educational robotics (ER) field provide empirical evidence of problem-solving styles behind the key tasks of proposed activities within real operative scenarios. A supervised, mixed machine learning (ML) approach was applied to data from seven Italian secondary schools (197 students), and four ML techniques [logistic regression (LR), support vector machine (SVM), k-nearest neighbors (KNN), and random forest (RF)] were explored to predict students' success
Analysis of Educational Robotics Activities Using a Machine Learning Approach
No full textThis paper presents the preliminary results of using machine learning techniques to analyze educational robotics activities. An experiment was conducted with 197 secondary school students in Italy: the authors updated Lego Mindstorms EV3 programming blocks to record log files with coding sequences students had designed in teams. The activities were part of a preliminary robotics exercise. We used four machine learning techniques—logistic regression, support-vector machine (SVM), K-nearest neighbors and random forests—to predict the students’ performance, comparing a supervised approach (using twelve indicators extracted from the log files as input for the algorithms) and a mixed approach (applying a k-means algorithm to calculate the machine learning features). The results showed that the mixed approach with SVM outperformed the other techniques, and that three predominant learning styles emerged from the data mining analysis
Identification of the Students Learning Process During Education Robotics Activities
Full text linkThis paper presents the design of an assessment process and its outcomes to investigate the impact of Educational Robotics activities on students' learning. Through data analytics techniques, the authors will explore the activities' output from a pedagogical and quantitative point of view. Sensors are utilized in the context of an Educational Robotics activity to obtain a more effective robot–environment interaction. Pupils work on specific exercises to make their robot smarter and to carry out more complex and inspirational projects: the integration of sensors on a robotic prototype is crucial, and learners have to comprehend how to use them. In the presented study, the potential of Educational Data Mining is used to investigate how a group of primary and secondary school students, using visual programming (Lego Mindstorms EV3 Education software), design programming sequences while they are solving an exercise related to an ultrasonic sensor mounted on their robotic artifact. For this purpose, a tracking system has been designed so that every programming attempt performed by students' teams is registered on a log file and stored in an SD card installed in the Lego Mindstorms EV3 brick. These log files are then analyzed using machine learning techniques (k-means clustering) in order to extract different patterns in the creation of the sequences and extract various problem-solving pathways performed by students. The difference between problem-solving pathways with respect to an indicator of early achievement is studied
Ten years of Educational Robotics in a Primary School
No full textMany researchers and teachers agree that the inclusion of science, technology, engineering, and mathematics in early education provides strong motivation and greatly improves the speed of learning. Most primary school curricula include a number of concepts that cover science and mathematics, but less effort is placed in teaching problem-solving, computer science, technology and robotics. The use of robotic systems and the introduction of robotics as a curriculum subject educates children in the basics of technology, and gives them additional human and organizational values. This paper presents a new program introduced in an Italian primary school, thanks to a collaboration with National Instruments and Università Politecnica delle Marche. Specifically, the project’s curricular aim was to improve logic, creativity, and the ability to focus, all of which are lacking in today’s generation of students. The subject of robotics will be part of the primary school’s curriculum for all five years. The program has delivered training to the teachers, and a complete program in which children have demonstrated great learning abilities, not only in technology, but also in collaboration and teamwork
Educational Robotics and Social Relationships in the Classroom
No full textIn a constructionist environment, robotics engagingly teaches traditional concepts, while applying them to compelling real-world problems. Educational robotics can help students develop soft skills, like teamwork, and improve the way they relate to each other. Researchers in different disciplines have devoted many efforts to exploring this dimension. One tool that may be useful for exploring the relational dimension of these activities is the sociogram. The case study reported in this paper presents findings from an experience which brought educational robotics, coding and tinkering to fourth graders in a primary school in Ancona (Italy). A questionnaire and a sociogram were administered to students, during curricular activities, before and after the project took place. The findings highlight some improvements in students’ relations, but more investigation is needed into the process of describing students’ relationships and their development in a project involving innovative methodologies and technology
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
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