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Robotics for soft skills training

Authors:
Franco Rubinacci at University of Naples Federico II
Franco Rubinacci
Michela Ponticorvo at University of Naples Federico II
Michela Ponticorvo
Rosa Passariello
Rosa Passariello
Rosa Passariello
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Orazio Miglino at University of Naples Federico II
Orazio Miglino
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Abstract and Figures

Robotics is a powerful tool in education and it has gained a notable impact in the field of teaching computer science, engineering, math, physics and similar. As educational robotics laboratories stimulate many different abilities in students, such as problem solving and group working, it is possible to use robotics to promote soft skills as well. Soft skills are necessary to complement hard skills to build the 21st century professionalism, so it seems relevant to start promoting these skills as soon as possible. In this paper, we describe a lab for primary and first grade secondary schools in which robotics is employed to train soft skills in an informal context.
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REM - Research on Education and Media
Vol. 10, N. 2, Year 2017
ISSN: 2037-0830 – DOI: 10.1515/rem-2017-0010

Robotics for soft skills training
Franco Rubinacci,a Michela Ponticorvo,b Rosa Passariello,c Orazio Miglino d
a University of Naples ‘Federico II’, Naples, Italy, franco.rubinacci@unina.it
b University of Naples ‘Federico II’, Naples, Italy, michela.ponticorvo@unina.it, ORCID 0000-0003-2451-
9539
c University of Naples ‘Federico II’, Naples, Italy
d University of Naples ‘Federico II’, Naples, Italy, orazio.miglino@unina.it
Abstract
Robotics is a powerful tool in education and it has gained a notable impact in the field of teaching computer science,
engineering, math, physics and similar. As educational robotics laboratories stimulate many different abilities in
students, such as problem solving and group working, it is possible to use robotics to promote soft skills as well.
Soft skills are necessary to complement hard skills to build the 21st century professionalism, so it seems relevant to
start promoting these skills as soon as possible. In this paper, we describe a lab for primary and first grade secondary
schools in which robotics is employed to train soft skills in an informal context.
Keywords: primary school; laboratory
Introduction
Robotics is a powerful tool to educate, and in recent years, it has gained a primary role in informal and formal
education contexts. Many researches have been devoted to this issue and new practices have been proposed to exploit
educational robotics potentialities, especially in STEM education (Merdan et al., 2016).
From an interesting review on this theme (Benitti, 2012), which analysed ten relevant articles extracted from
bibliographic databases, it emerges that the content to be taught employing robotics is mostly related to the fields of
physics and mathematics (80%), but it is worth noting that these experiences report teaching distances, angles,
kinematics, graphs, fractions, and geospatial concepts together with problem solving, logic and scientific methodology
– skills that can be promoted through robotics.
Moreover, some studies apply robotics to teaching the basic principles of evolution (Whittier and Robinson, 2007;
Author et al., 1999; Author et al., 2004; Author et al., 2007), developing social communication skills (Owens et al.,
2008) and learning to manage complex systems (Author et al., 2008; Author et al., 2016).
In the last few years, Educational Robotics has indeed experienced a new explosion for the training of STEM that are
crucial for competitiveness, but, for the goal of our work, it is useful to highlight that, together with this main vein,
some steps have been taken in the direction of using robotics to promote other skills, such as communication.
Communication, problem solving, and system management belong to soft skills, a concept widely used in training
and vocational context, which refers to the personal skills in opposition with the hard, technical skills (Bacolod et al.,
2009; Caudron, 1999). It is indeed a multiform concept that includes different dimensions of the personal sphere on
emotional, behavioural, and cognitive side.
In the last years, it has become evident that these skills are important in almost every context: for students along their
career, for working people at every level, for professionals which interact with other people and so on.
Robotics for soft skills training
Rubinacci, Pontecorvo, Passariello, Miglino
 
For their crucial role in the business field, many expensive and time-demanding programs are proposed, but it is also
possible to impart training on soft skills with less conventional methods, such as serious games (Dell’Aquila et al.,
2017) and the training can start much before the work world entrance.
We believe that educational robotics can open itself to the challenging field of soft-skills, especially in the case of
children and adolescents. For this reason, in this paper, we describe an experience in which robotics has been employed
to promote soft skills in primary and first level secondary school children very precociously as compared to the other
program that are mainly addressed to workers or university students. In the following sections, we will describe this
educational robotics example in detail.
1. The robotic lab for Soft Skills training with children
In this section, we describe a successful laboratory experience that was held in Naples, at Città della Scienza. This is
a cultural initiative to promote and popularize scientific knowledge. Città della Scienza has a multifunctional structure
with an interactive scientific museum and a training centre. In this training centre, many initiatives allow children to
take part in the laboratories in an informal context. The Soft Skills lab employed the well-known Lego Mindstorms kit.
This lab started from the hypothesis that Educational Robotics could be effectively applied to soft-skills training and
the first step was to investigate the teachers’ and students’ expectations about this issue, as a useful premise to the
consequent research.
1.1. Lab scheduling
The Soft Skills lab was arranged as follows: first, a pre-lab questionnaire was administered both to teachers and
students to assess their expectations about the laboratory, mainly about hard skills and soft skills.
Then the lab conductor introduced the robotic kit, educational robotics goals and the task to be accomplished.
After this general introduction, the group, usually a classroom of about 20 students, is divided into 4 sub-groups and
start building their robot. Some parts are pre-assembled to facilitate the task in a reduced amount of time. When the
building phase is over, the groups must conceive and implement the code to accomplish the task which can be path-
following, navigation task, or a competition between groups. The groups can try their solution once and then fix any
problem in the code.
At the end the feedback is delivered by the lab conductor and the post-lab questionnaire is administered. The whole
procedure lasts 75 minutes.
1.2. Participants and robot
The Soft Skills lab lasted from February 2016 to May 2016 and involved students accompanied by teachers: it was
attended by 278 children, who were either studying in the last year of primary school or the second year of first level
secondary school. The average age of the participating students was 11.65 years. The classrooms were accompanied
with 42 teachers.
The robot was built using the LEGO Mindstorms kit, which is widely used in education (Klassner and Anderson,
2003). The basic LEGO Mindstorms kit contains 750 building block pieces and the programmable control unit, the
RCX. It includes sensors for touch, light, angle (rotation), and temperature and actuator motor and light.
In this lab, the students used the tool for programming the RCX provided by LEGO. It is a development environment
with an interface that models programming as a process of dragging puzzle pieces together to build a chain. The pieces
are the program steps whereas the chain is the complete program. It is possible to use the basic programming concepts
such as loops and subroutines. The robot morphology that was used in Soft Skills lab is depicted in Figure 1.
Robotics for soft skills training
Rubinacci, Pontecorvo, Passariello, Miglino
 
Fig. 1 The robot morphology used for the Soft Skills Lab together with a screenshot from the Lego software
1.3. Questionnaires
Four questionnaires were used for data collection, 2 questionnaires for students and 2 questionnaires for teachers.
They were administered before (pre-test) and after (post-test) the lab experience in the same room where the lab took
place. It was compiled individually and in an anonymous manner. The researchers indicated a code to match the pre-
and post-lab questionnaires for each participant.
The participants could reply to the questionnaires items using a 5-point Likert scale, where 1 indicated complete
disagreement and 5 indicated complete agreement with the proposed sentence.
The questionnaire for students investigated their expectations (pre-lab) and their opinion (post-lab) about the lab’s
efficacy to stimulate their interest in science, robotics, technology, maths, coding, robot construction, robot
programming, team work, and problem solving.
The questionnaire for teachers investigated their expectation (pre-lab) and opinion (post-lab) about the lab’s efficacy
to stimulate students’ interest in the same fields.
2. Results
In this section, some data about the Soft Skills lab experience at Città della Scienza are reported. Students evaluated
the laboratory very positively on the technical skills promotion.
Regarding soft skills enhancing, it emerges that students have high expectations about team work, problem
understanding, and problem solving.
Robotics for soft skills training
Rubinacci, Pontecorvo, Passariello, Miglino
 
Fig. 2 The graph represents the average for the item regarding the soft skills for the students. The data for pre-lab questionnaire is represented by the
blue bar and the data for post-lab questionnaire is represented by the red bar. TW stands for team work, PU for problem understanding and PS for
problem solving.
In the case of problem understanding and problem solving, the students’ opinion is better than expectations whereas
the opposite happens for team work. The Pearson correlation values between the pre-lab and post-lab questionnaires are
reported in Table 1.
Table 1. Correlation between pre-lab and post-lab for students. Data in italics indicate values with probability under 0.05
TW pre PU pre PS pre
TW post 0.429 0.162 0.121
PU post 0.096 0.428 0.359
PS post 0.111 0.409 0.381
Regarding the teachers, the lab experience improved their consideration of lab effectiveness for promoting soft
skills.
Robotics for soft skills training
Rubinacci, Pontecorvo, Passariello, Miglino
 
Fig. 3 The graph represents the average for the item regarding soft skills for teachers. The data for pre-lab questionnaire is represented by the blue bar
and the data for post-lab questionnaire is represented by the red bar. TW stands for team work, PU for problem understanding and PS for problem
solving.
Also, for the teachers, the Pearson correlation was calculated for the soft skills parameters. The data are reported in
table 2.
Table 1. Correlation between pre-lab and post-lab for teachers. Data in italics indicate values with probability under 0.05
TW pre PU pre PS pre
TW post 0.350 0.154 0.300
PU post 0.500 0.250 0.345
PS post 0.534 0.225 0.301
Conclusions
Data indicates that the students and teachers were confident about the lab effectiveness in promoting soft skills. Also,
the teachers agreed that it was a good chance to stimulate collaboration, group working and enhanced communication
abilities in students.
The feedback from the teachers has confirmed that it stimulated students interest in STEM and coding as well as
their skills in group work, mediation and negotiation, problem definition and solving.
Also, the students evaluated the lab very positively, both about hard skills and soft skills.
This lab allowed the students to start acquiring very precociously the knowledge that transforms into skills and
competencies, which is crucial for their future in academic and working careers. Even though this experience can be
considered as just the first step in the lengthy process to widen the application of robotics to non-technical skills
acquisition, there is no doubt that there is a promising premise for the effectiveness of this challenging issue.
Robotics for soft skills training
Rubinacci, Pontecorvo, Passariello, Miglino
 
In fact, the users’ perception of robotics as a tool to promote soft skills confirms the opportunity to apply robotics in
the wider educational contexts. Moreover, starting from this observation, we have formulated the hypothesis that using
educational robotics is fit for soft-skills training, as it exploits the mediation of new relationships that are established
and kept alive in the children/adolescents group, by promoting everyone’s participation in a context that is very
different from everyday classroom activities, foresees interaction with tangible materials, and proposes challenging and
always changing tasks. Moreover, it is necessary to verify if the peculiarities of robotics are crucial to impact on soft-
skills; in other words, if soft-skills are promoted by the educational robotics side or by the laboratory side. The next step
will be verifying this hypothesis in this emerging field.
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... (Table 2). Creativity (Valko & Osadchyi, 2021) Critical thinking skills (Zhong et al., 2022;Tsoy et al., 2018;Valko & Osadchyi, 2021) Analytical thinking skills (Amo et al., 2021) Computational thinking skills (Anwar et al., 2019;Chaudhary et al., 2016;Kopcha et al., 2017;Pou et al., 2022;Sáez López et al., 2021;Wong & Jiang, 2019) Programming skills (Pou et al., 2022;Scaradozzi et al., 2015) Project-based learning skills (Pou et al., 2022;Zdešar et al., 2017) Scenario-based learning skills (Demir Kaçan & Kaçan, 2022) Problem-solving skills (Kopcha et al., 2017;Sáez López et al., 2021;Valko & Osadchyi, 2021;Chaudhary et al., 2016;Karaahmetoğlu & Korkmaz, 2019) Algorithmic skills (Karaahmetoglu, 2019), (Karaahmetoğlu & Korkmaz, 2019) Reasoning skills (Papadakis, 2020) Communication skills, social skills (Rubinacci et al., 2017) Teamwork skills, self-confidence, collaboration skills (Zhong et al., 2022) Motivation (Kaloti-Hallak et al., 2015;Mohr-Schroeder et al., 2014;Julià & Antolí, 2019) Logical thinking skills (Sáez López et al., 2021;Karaahmetoğlu & Korkmaz, 2019) Cognitive and learning skills (Kubilinskiene et al., 2017;Valko & Osadchyi, 2021) Process-oriented learning skills (Jung & Won, 2018) Intellectual-mega cognitive skills (Sáez López et al., 2021) Independent learning skills (Abidin et al., 2021) STEM skills (Dochshanov & Lapina, 2019;Amo et al., 2021) Soft skills (Rubinacci et al., 2017) Inquiry-based learning skills (Smyrnova-Trybulska et al., 2016) Positive attitude (Kaloti-Hallak et al., 2015;Smyrnova-Trybulska et al., 2016) Engineering skills (Chaudhary et al., 2016) It should be noted that creativity, analytical thinking skills, scenario-based learning skills, algorithmic skills, reasoning skills, communication and social skills, teamwork and self-confidence skills, process-oriented skills, intellectual megacognitive skills, soft skills, inquiry-based learning skills, engineering skills are only mentioned once in our literature review. Two studies mention programming skills, project-based learning skills, cognitive and learning skills, logical thinking skills, motivation, STEM skills, and positive attitude skills. ...
... (Table 2). Creativity (Valko & Osadchyi, 2021) Critical thinking skills (Zhong et al., 2022;Tsoy et al., 2018;Valko & Osadchyi, 2021) Analytical thinking skills (Amo et al., 2021) Computational thinking skills (Anwar et al., 2019;Chaudhary et al., 2016;Kopcha et al., 2017;Pou et al., 2022;Sáez López et al., 2021;Wong & Jiang, 2019) Programming skills (Pou et al., 2022;Scaradozzi et al., 2015) Project-based learning skills (Pou et al., 2022;Zdešar et al., 2017) Scenario-based learning skills (Demir Kaçan & Kaçan, 2022) Problem-solving skills (Kopcha et al., 2017;Sáez López et al., 2021;Valko & Osadchyi, 2021;Chaudhary et al., 2016;Karaahmetoğlu & Korkmaz, 2019) Algorithmic skills (Karaahmetoglu, 2019), (Karaahmetoğlu & Korkmaz, 2019) Reasoning skills (Papadakis, 2020) Communication skills, social skills (Rubinacci et al., 2017) Teamwork skills, self-confidence, collaboration skills (Zhong et al., 2022) Motivation (Kaloti-Hallak et al., 2015;Mohr-Schroeder et al., 2014;Julià & Antolí, 2019) Logical thinking skills (Sáez López et al., 2021;Karaahmetoğlu & Korkmaz, 2019) Cognitive and learning skills (Kubilinskiene et al., 2017;Valko & Osadchyi, 2021) Process-oriented learning skills (Jung & Won, 2018) Intellectual-mega cognitive skills (Sáez López et al., 2021) Independent learning skills (Abidin et al., 2021) STEM skills (Dochshanov & Lapina, 2019;Amo et al., 2021) Soft skills (Rubinacci et al., 2017) Inquiry-based learning skills (Smyrnova-Trybulska et al., 2016) Positive attitude (Kaloti-Hallak et al., 2015;Smyrnova-Trybulska et al., 2016) Engineering skills (Chaudhary et al., 2016) It should be noted that creativity, analytical thinking skills, scenario-based learning skills, algorithmic skills, reasoning skills, communication and social skills, teamwork and self-confidence skills, process-oriented skills, intellectual megacognitive skills, soft skills, inquiry-based learning skills, engineering skills are only mentioned once in our literature review. Two studies mention programming skills, project-based learning skills, cognitive and learning skills, logical thinking skills, motivation, STEM skills, and positive attitude skills. ...
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Full-text available
  • Nov 2022
Using robot programming activities for learning in the classroom is one way to drive interest and engagement in the STEM field among students, especially girls. And this is a field that is particularly characterized by an underrepresentation of women. Accordingly, many countries are increasingly integrating activities related to computer science concepts into their education systems. The EU also sets the goal of considering the connections between STEM disciplines in schools and having students gain experience with robots as well. The use of robots for teaching purposes creates opportunities for motivating and meaningful mathematics lessons that are linked to the fundamental concepts of computer science. Mathematics teaching in such a context offers possibilities for an experimental and problem-oriented approach to the content and a deep insight into mathematical concepts. Research in this area shows that the use of robots can promote understanding of mathematical concepts, change attitudes and motivation, and develop metacognitive and problem-solving skills. However, as for gender differences in this context, little is known to date. Addressing this gap, for this work, we investigated learners' performance, mathematical and computational ideas and experiences, problem-solving strategies, and help used in an ER (Educational Robotics) activity. In addition, the learners’ mathematical competence and computational thinking skills as well as possible correlations of these measures with the learners’ performance on an ER activity were examined. For these purposes, an ER activity on the topic of plane geometric figures was designed, which was carried out in a 6th grade (11-12 years) class (n=24) of an Austrian middle school in the city of Salzburg using the TI-Innovator Rover. The comparison of six female and six male student groups, each consisting of two students, made it possible to address the above research questions. For this purpose, a mixed-methods approach was chosen. Qualitative data, consisting of the audio recordings of the student groups' conversations during the ER activity, the constructions made on the posters, the student notes, and the saved programs, form the basis for thematic analysis. The quantitative data include the number of tasks solved during the ER activity by the student groups, the mathematics grade of the last school year by the students, and the results of a test on the students' computational thinking skills with the related self-assessments. Appropriate quantitative methods for analysis include the Wilcoxon rank-sum test (Mann-Whitney test), the Welch Two Sample t-test, and Kendall's tau and Pearson's correlation coefficient to test for differences and correlations. The main results indicate that groups with female students perform better while showing high engagement in the activity, exhibit a more systematic approach to problem-solving and at the same time use less intensive help from the teachers than their male counterparts in this class. The paper concludes by giving future directions for research and the limits of the present work.
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... Educational studies related to robotics are usually related to programming, robot building or mechatronics. It is used not only in the teaching of technical subjects but also in the teaching of the soft skills that are fundamental to twenty-first century skills such as problem solving and group work (Rubinacci et al., 2017). There are also studies in the literature that aim to provide students with various skills through in-school and out-of-school courses or competitions (Aksu, 2019;Benitti, 2012;Sonmez, 2019). ...
A systematic review of educational robotics studies for the period 2010–2021
Article
Full-text available
  • Dec 2022
The aim of this research is to systematically review the theses on educational robotics applications produced in Turkey between the years 2010–2021. The aim is to provide a broad perspective on current studies by revealing the existing situation in the literature. For this purpose, 124 postgraduate theses in the national thesis database were examined within the scope of the research. The theses were analysed using the content analysis method and the educational robotics publication classification form. According to the results of the research, most theses were carried out in 2019 and educational robotics was mostly studied in the master's theses. Experimental design with the quantitative method and the quasi‐experimental pre‐test post‐test control group was widely used as research methods. Research in the theses was mostly conducted in secondary schools. The implementations lasted between 1 and 2 months (6–8 weeks). The size of the study groups were 31–100 and the sample selection was appropriate for its purpose. Lego sets and Arduino sets were used the most in information technologies and software and science courses. The proposals sections of the theses suggest that future research should carry out studies with longer‐term implementations and larger sample groups. For practitioners, the theses suggest that robotics‐based activities should be added to the curriculum in every age group. They emphasize the need for a STEM‐based robotics course for teachers as an in‐service training course and that it would be beneficial to have robotics workshops in schools. The results obtained from the study are discussed in detail. The video abstracts for this article are available at https://youtu.be/rv9xiGxF4Uc and https://youtu.be/lXctWfpey5E.
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... Several studies have documented the usefulness and effectiveness of ER in the education of typical students in general (Benitti, 2012;Mubin et al., 2013;Beltrametti et al., 2017;Athanasiou et al., 2018;Talan, 2021), but only a few have already explored the use of ER with special needs students (Damiani et al., 2013;Businaro et al., 2014;Agatolio et al., 2016). ER can be utilised as a tool to promote individual development, creativity, teamwork, and communication, as well as problem-solving and computational reasoning (Kandlhofer & Steinbauer, 2016;Rubinacci et al., 2017). ...
Educational Robotics for Special Needs Students: Teachers’ Perspectives on Pre-service TrainingEducational Robotics for Special Needs Students: Teachers’ Perspectives on Pre-service Training
Article
Full-text available
  • Dec 2022
Since the introduction of LOGO by Seymour Papert in 1980 and the constructivist theories, after the teaching machines of Skinner, technology, robots and robotics activities have been viewed as effective educational tools. Multiple studies have demonstrated that robotics is a valuable device for special education students too. The present study is part of a particularly novel and challenging trend of research that intends to fill a knowledge gap regarding the perspectives and concerns of learning support teachers on educational robotics. Particularly by questioning teachers who have not received training in the use of educational robotics. In this exploratory study, 125 Italian pre-service learning support teachers were surveyed at the end or during their course specialization to determine their awareness and comprehension of educational robotics usage with students with special needs. The survey reveals that support teachers are not adequately trained to use educational robotics and that they are generally unfamiliar with it and they rarely employ it.
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An Investigation of Research on the Use of Robotics in Education: A Content Analysis Study
Article
Full-text available
  • Aug 2022
Programlama becerilerinin güvenlik, eğitim, sağlık, iletişim, üretim, finans gibi farklı alanlarda kullanılabilir olmasıyla küçük yaşlarda eğitim süreçlerinde kodlama ve programlama becerilerine yönelik araştırmalar önemli hale gelmiştir. Bu çalışmada eğitimde robotik uygulamalar araştırma konusu olarak seçilmiştir. Çalışma kapsamında eğitimde robotiğin kullanımı, ortaya çıkışı, tarihi ve güncel durumu hakkında bilgi verildikten sonra, 2015 ile 2020 yılları arasında Dergipark, ERIC ve ScienceDirect veritabanlarında yayınlanan 204 makale incelenmiştir. Makaleler örneklem düzeyleri, örneklem büyüklükleri, araştırmaların yapıldığı alanlar, tercih edilen araştırma yöntemleri gibi farklı başlıklarda derinlemesine analiz edilmiştir. Yapılan analizler sonucunda araştırmaların daha çok ilkokul ve ortaokul kademelerinde yoğunlaştığı, örneklem büyüklüğü olarak 11-30 arası katılımcının daha fazla tercih edildiği sonucuna ulaşılmıştır. Araştırmalarda yöntem olarak daha çok nitel araştırma yöntemlerinin kullanıldığı görülmüştür. Araştırmalarda tutum ve görüş değişkenlerinin sıklıkla incelendiği tespit edilmiştir. Çalışma sonucunda okul öncesi ve lise kademelerinde yapılacak araştırmaların artırılması, araştırmalarda dil öğrenimi ile ilgili çalışmaların yapılması önerilmektedir.
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Educational robotics studies in Italian scientific journals: A systematic review
Article
Full-text available
  • Oct 2022
In recent years, there has been increasing attention to applying educational robotics (ER) in learning settings and, consequently, it has concerned and involved the entire pedagogical field, giving rise to a large amount of experimentation and research. Educational robots are used within the school curriculum and in extra-curricular activities to improve student interest, engagement and academic achievement in various fields, such as STEM and digital literacy, and in many other ways, for example fostering specific cognitive and socio-relational skills. In Italy, as in many other countries, an increasing number of publications are featuring this subject. While there are also some reviews, none of them has been interested in reviewing studies published in Italian journals. The aim of this work is to provide a systematic review of the literature regarding studies investigating educational robotics and provide suggestions for further research and teaching practices. To do this we used the PRISMA statement process. In total, 28 studies published between 2011 and 2021 in 49 Italian journals were analyzed. The main findings from this review provide the current state of the art on research in ER. Furthermore, the paper discusses trends and the vision toward the future and opportunities for further research.
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Le nuove macchine per apprendere: Simulazioni al computer, robot e videogiochi multi-utente. Alcuni prototipi
Article
Full-text available
  • Jan 2007
1. INTRODUZIONE In questo scritto presenteremo e descriveremo alcuni prototipi di videogiochi ludici/didattici realizzati e usati in ambiti formativi ben circoscritti1. In particolare, tratteremo di sistemi hardware e software da noi sviluppati e adoperati nella formazione professionale sulla legge 626 (sicurezza nei luoghi di lavoro), nell'insegnamento della Biologia Evoluzionistica a degli studenti di un liceo scientifico napoletano, in un corso introduttivo di Psicologia Sociale dei piccoli gruppi; all'addestramento di insegnanti, amministratori pubblici, manager aziendali nella conduzione di un negoziato; alla divulgazione di nozioni e concetti relativi alle politiche fiscali adottate da uno stato. Tutti i prototipi presentati condividono due principi di base: a) sono stati pensati, progettati e realizzati come dei laboratori dove 1 La maggior parte degli applicativi sono scaricabili presso il sito web del Laboratorio di Sistemi Intelligenti dell'Università Federico II di Napoli al seguente link: www.isl.unina.it/EduGames. I software sono essenzialmente dei prototipi da utilizzare in contesti molto delimitati, quindi si potrebbero presentare dei problemi di configurazione e/o istallazione. Gli eventuali utenti possono richiedere assistenza e segnalare i malfunzionamenti al webmaster del suddetto sito.
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Using artificial life to teach evolutionary biology
Article
Full-text available
  • Jan 2004
This paper presents a pilot study on the use of artificial life software in an educational setting. Two groups of high school students received a standard lesson in evolutionary biology followed by a software session. The experimental group used the suite of artificial life software presented in this paper; the control group used a commercial multimedia hypertext. At the end of the software session both groups were asked to fill in a simple multiple-choice questionnaire testing the students knowledge of various aspects of evolutionary biology. The results show that the group using the artificial life software performed significantly better than the control group. We argue that the experimental group may learn more effectively because the artificial life makes it possible for students to perform experiments, a possibility not available to the control group.
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Breedbot: An evolutionary robotics application in digital content
Article
Full-text available
  • Jun 2008
  • ELECTRON LIBR
Purpose – This paper aims to describe an integrated hardware/software system based on evolutionary robotics and its application in an edutainment context. Design/methodology/approach – The system is based on a wide variety of artificial life techniques (artificial neural networks, genetic algorithms, user-guided evolutionary design and evolutionary robotics). A user without any computer programming skill can determine the robot's behavior in two different ways: artificial breeding or artificial evolution. Breedbot has been used as a didactic tool in teaching evolutionary biology and as a “futuristic” toy by several science centers. The digital side of Breedbot can be downloaded on the web site: www.isl.unina.it/breedbot Findings – The results in this pilot study suggest that using Breedbot in an educational context can be useful to improve learning in biology. Research limitations/implications – As this is a pilot study, one limitation is the small sample considered. The issue will be investigated further with a wider population and subject-matter, which will also improve the Breedbot system. Practical implications – These results suggest that tools like Breedbot could be introduced into biology curricula at schools. Originality/value – The paper describes an original application in digital content and shows the importance of using such a tool in an Edutainment context. It is therefore interesting for teachers, vocational trainers and anyone involved in educational activities.
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Urban Interactions: Soft Skills Versus Specialization
Article
Full-text available
  • Feb 2009
  • J ECON GEOGR
This article considers the role of soft skills in cities and industry clusters. It begins by specifying a model of agglomeration economies where soft skills allow agents to interact more productively. The model exposes two conflicting forces: agglomeration allows opportunities to interact, but it also produces thick, specialized markets, and this specialization can be a substitute for interaction. In order to empirically evaluate the soft skills—agglomeration relationship, the article matches data on the interaction requirements of occupations from the Dictionary of Occupational Titles to Census data. The within-industry average level of soft skills is found to be higher in cities but not in industry clusters. Workers at the top of the skill distribution in large cities typically have higher levels of soft skills than in small cities, while the least skilled workers are less skilled in large cities than in small cities. This pattern is reversed for industry clusters.
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LEGO((R)) Therapy and the Social Use of Language Programme: An Evaluation of Two Social Skills Interventions for Children with High Functioning Autism and Asperger Syndrome
Article
Full-text available
  • Jul 2008
LEGO therapy and the Social Use of Language Programme (SULP) were evaluated as social skills interventions for 6-11 year olds with high functioning autism and Asperger Syndrome. Children were matched on CA, IQ, and autistic symptoms before being randomly assigned to LEGO or SULP. Therapy occurred for 1 h/week over 18 weeks. A no-intervention control group was also assessed. Results showed that the LEGO therapy group improved more than the other groups on autism-specific social interaction scores (Gilliam Autism Rating Scale). Maladaptive behaviour decreased significantly more in the LEGO and SULP groups compared to the control group. There was a non-significant trend for SULP and LEGO groups to improve more than the no-intervention group in communication and socialisation skills.
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Breeding Robots to Learn How to Rule Complex Systems
Chapter
  • Oct 2017
Educational robotics has been extensively used to teach hard skills such as computer science, computational thinking and coding because traditional robotics is the outcome of analysis, design and programming. Other approaches to robotics, namely evolutionary robotics, open the way to reflection on emergence, self-organization, dynamical systems. As these issues are relevant in present days society, we propose a robotic laboratory where children are trained to rule complex systems. In particular, the integrated hardware/software system BrainFarm, that allows to evolve and train virtual robots and then test them in physical environments, is employed to train these skills and a successful experience in informal context is described.
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The Hard Case for Soft Skills
Article
  • Jan 1999
  • Workforce
About five years ago, Annie McKee, managing director of the Center for Professional Development at the University of Pennsylvania in Philadelphia, was meeting with the executive board of a Fortune 50 financial-services firm. The topic? A proposed leadership-development program for the company's senior executives. Just as McKee finished explaining how the program would work and what skills would be developed, one board member jumped to his feet and started pounding his fists on the table. "This program sounds fine," he said. "But how do we teach our executives to trust one another?" McKee was startled. "This wasn't the kind of place where you'd expect to find much tolerance for any discussion about emotion, but that was exactly what was happening," she says. Intuitively, this board member recognized that if the company were to be successful, its most senior leaders would not only need the right knowledge and experience, but they'd also have to be skilled at the softer side of management. Since that time, McKee has seen a dramatic change in the response of corporate executives to the notion of soft skills. "They're starting to get it," she says --and it's about time. Companies have offered soft-skills training to employees for years. But as every battle-scarred trainer knows, these programs are typically the first to go when budgets are cut. Given a choice between funding a course on computer skills or a course on active listening, corporate bean counters more willingly sign off on the computer course. Why? Because until recently, there had been no hard evidence that soft skills make a difference.
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Teaching Evolution to Non-English Proficient Students by Using Lego Robotics.
Article
  • Jan 2007
This article describes a teaching unit that used Lego Robotics to address state science standards for teaching basic principles of evolution in two middle school life science classes. All but two of 29 students in these classes were native Spanish speakers from Mexico. Both classes were taught using Sheltered Instruction Observation Protocol (SIOP). The evolutionary robots (Evobots) unit was comprised of twelve 60 minute classes. The students worked in cooperative groups to build and test Evobots that could either be the best at one thing (a specialist) or second best at everything (a generalist). After building the Evobots, the teams of students competed in four events: climbing, hauling, speed, and strength. Students then compared the different bots and proposed ideas explaining why each bot either won or lost the various competitions. Students used this information to write final papers summarizing the unit and their knowledge of concepts such as natural selection, adaptation, and niche specialization. Average knowledge gains were sizeable with the mean scores of the pretest and posttest of 26.9% and 42.3%.
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Exploring the educational potential of robotics in schools: A systematic review
Article
  • Apr 2012
  • COMPUT EDUC
This study reviews recently published scientific literature on the use of robotics in schools, in order to: (a) identify the potential contribution of the incorporation of robotics as educational tool in schools, (b) present a synthesis of the available empirical evidence on the educational effectiveness of robotics as an educational tool in schools, and (c) define future research perspectives concerning educational robotics. After systematically searching online bibliographic databases, ten relevant articles were located and included in the study. For each article, we analyze the purpose of the study, the content to be taught with the aid of robotics, the type of robot used, the research method used, and the sample characteristics (sample size, age range of students and/or level of education) and the results observed. The articles reviewed suggest that educational robotics usually acts as an element that enhances learning, however, this is not always the case, as there are studies that have reported situations in which there was no improvement in learning. The outcomes of the literature review are discussed in terms of their implications for future research, and can provide useful guidance for educators, practitioners and researchers in the area.
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