International Conference: Connecting technologies and didactics - The IDEA project experience

10th-11th February 2020

T-Hotel, Via dei Giudicati, 66 - Cagliari

Organized by the Educational Technology Program of
Center for Advanced Studies Research and Development in Sardinia - CRS4

Conference programme

8:30 - Welcome and Registration

9:15 - Institutional greetings and project presentation
Sessions are introduced and moderated by: Alessandro Bogliolo

Institutional greetings:
Cristian Solinas, President of the Autonomous Region of Sardinia (ARS)
Andrea Biancareddu, Regional Councillor for Education, Cultural Heritage, Information, Entertainment and Sport, (ARS)
Giuseppe Fasolino, Regional Councillor for Planning, Budget, Credit and Town and Country Planning, (ARS)
Maria Assunta Serra, Special Administrator, Sardegna Ricerche
Annalisa Bonfiglio, President of CRS4

Project presentation:
Carole Salis, Head of the IDEA Project - funded with "Plan of Action and Cohesion" - and Head of the Educational Technology program, CRS4

10:30 - COFFEE BREAK
ARTIFICIAL INTELLIGENCE

11:00 - Donald Clark, Ed Tech Entrepreneur, Visiting Professor, University of Derby, United Kingdom
Talk: AI changes everything

11:40 - Teachers give testimony of their experience
Interdisciplinarità con Intelligenza Artificiale - Un caso d’uso (Cross-curricular activities with an Artificial Intelligence module – a use case)
Talk: IA con le scienze (Artificial Intelligence and sciences)
School Principal: Giovanni Carmelo Marras - Istituto Comprensivo “S.Satta-A.Fais”, Perfugas, Italy
Teacher: Silvana Pinna
Didactic Tutor: Pier Luigi Lai
Technological Tutor: Alessandro Costantino
Introduced by: Davide Zedda, CRS4 and Istituto di Istruzione Superiore Statale “Michele Giua”, Cagliari, Italy

LEARNING ANALYTICS

12:20 - Barbara Wasson, Director, Centre for the Science of Learning & Technology (SLATE), Professor, University of Bergen, Norway
Talk: Learning Analytics

13:00 - STANDING BUFFET
COMPUTATIONAL THINKING

14:10 - Daniel Schneider, Professor, University of Geneva, Switzerland
Talk: Computational Thinking and Making

14:50 -  Teachers give testimony of their experience
Pensiero Computazionale con coding, robotica educativa o Internet delle Cose – un caso d’uso (Computational Thinking with coding, robotics or Internet of Things – a use case)
Talk: Geometria IoT (IoT geometry)
School Principal: Gian Battista Usai – Istituto Tecnico Professionale IANAS, Tortolì, Italy
Teachers: Anna Marongiu, Orietta Scattu
Didactic Tutor: Scilla Contu
Technological Tutor: Mauro Mereu
Introduced by: Giuliana Brunetti, CRS4

PLATFORM AND ITS EVOLUTION

15:30 - Francesco Cabras, Head, Platform Development, CRS4 and Radix, Italy
Talk: Piattaforma IDEA, il cloud al servizio della didattica (The IDEA Platform, the cloud at the service of didactics)

16:10 - Davide Zedda, CRS4 and Istituto di Istruzione Superiore Statale “Michele Giua”, Cagliari, Italy
Talk: Accesso Remoto Intelligente ad Esperienze di Laboratorio - RIALE (Remote Intelligent Access to Lab Experiment) (Remote Intelligent Access to Lab Experiment - RIALE)

16:50 - Closing remarks and information on next day’s activities
Carole Salis, Head of the IDEA Project - funded with "Plan of Action and Cohesion" - and Head of the Educational Technology program, CRS4

9:00 - Welcome and Registration

9:15 - Sessions are introduced and moderated by: Alessandro Bogliolo

REGIONAL POLICIES FOR EDUCATION

Luca Galassi, Director of the School Policy Service - Regional Department of Education, Cultural Heritage, Information, Entertainment and Sport, Autonomous Region of Sardinia (ARS)
Francesco Feliziani, General Director Regional School Office for Sardinia (MIUR)
Alessandro Corrias, Director, Policy Service for Tertiary Education and Youth

10:30 - COFFEE BREAK
MOBILE LEARNING

11:00 - Kevin Burden, Professor, University of Hull, United Kingdom
Talk: What does Innovative Mobile Learning Look Like?

11:40 -  Teachers give testimony of their experience
Mobile Learning - Un caso d’uso – Scuola Senza Pareti (Mobile Learning – a use case – School Without Walls)
Talk: Uomo e ambiente (Mankind and environment)
School Principal: Gian Battista Usai – Istituto Tecnico Professionale IANAS, Tortolì, Italy
Teachers: Claudia Moi, Laura Piazza, Rosa Deidda, Cristina Bini
Didactic Tutor: Scilla Contu
Technological Tutor: Anna Costa
Introduced by: Stefano Leone Monni, CRS4 and Liceo Scientifico ”Michelangelo”, Cagliari, Italy

PEDAGOGICAL DESIGN

12:20 - Valéry Psyché, Professor, University Teluq, Quebec, Canada
Talk: Instructional design for Intelligent Adaptive Learning 

13:00 -  Teachers give testimony of their experience
Design Pedagogico – Un caso d’uso (Pedagogical Design – a use case)
Talk: Tris Box
School Principal: Giovanni Carmelo Marras - Istituto Comprensivo “S.Satta-A.Fais”, Perfugas, Italy
Teacher: Giovannica Cosso
Didactic Tutor: Barbara Letteri
Technological Tutor: Vittorio Padiglia
Introduced by: Carole Salis, Head of the IDEA Project - funded with "Plan of Action and Cohesion" - and Head of the Educational Technology program, CRS4

13:40 - STANDING BUFFET
ARTIFICIAL INTELLIGENCE AND EDUCATION

14:50 - Kaska Porayska-Pomsta, Professor, University College London, United Kingdom
Talk: Scaffolding learners’ socio-emotional self-regulation through AI-enhanced learning environments

15:30 -  Teachers give testimony of their experience
Interdisciplinarità con Intelligenza Artificiale - Un caso d’uso (Cross-curricular activities with an Artificial Intelligence Module – a use case)
Talk: Viaggio nello spazio sonoro (Journey across sound space)
School Principal: Maria Romina Lai - I.I.S. Minerario "Giorgio Asproni" - I.T.C.G. "Enrico Fermi", Iglesias, Italy
Teachers: Stefania Anna Russo, Riccardo Bachis
Didactic Tutors: Roberta Aru, Emanuela Nioi
Technological Tutors: Santiago Garrido Rua, Giulio Lai
Introduced by: Davide Zedda, CRS4 and Istituto di Istruzione Superiore Statale “Michele Giua”, Cagliari, Italy

16:10 - Closing remarks and Future developements
Carole Salis, Head of the IDEA Project - funded with "Plan of Action and Cohesion" - and Head of the Educational Technology program, CRS4

Conference speakers

Dr Kevin Burden

Kevin Burden, Professor, University of Hull, United Kingdom

Dr. Kevin Burden is Professor of Digital Education in the Faculty of Arts, Cultures and Education (FACE) at the University of Hull where he leads a team investigating the impact and pedagogical potential of digital technologies on learning and in education more generally. His research area explores the affordances of mobile and pervasive computing with a particular focus on teacher education and professional learning. He is currently leading several international research projects focusing on the use of mobile technologies in schools and colleges and recently completed a major Erasmus+ project to create a mobile learning toolkit for teacher educators (www.mobilelearningtoolkit.com). His current research focuses on the nature of innovation and transformation in mobile learning and includes an Erasmus+ Key Action 2 project to develop a professional learning app and associated MOOC to support educators in designing innovative mobile learning activities (see www.deimpeu.com)

Dr. Burden is a Distinguished Visiting Scholar at the University of Technology, Sydney and has previously been invited to Hong Kong University, the University of Macau and Universidad del Norte in Barranquilla, Colombia. Kevin has attracted over £1.5m in competitive grants and awards and was made a National Teaching Fellow by the UK Higher Education Academy (HEA) for his work in supporting students and staff in the innovative use of digital technologies. He is the author of over fifty peer-reviewed articles, chapters and publications and, along with colleagues at UTS and the University of Cambridge he has recently co-authored the book ‘Uncertainty in Teacher Education Futures: Scenarios, Politics and STEM’ (http://www.springer.com/gp/book/9789811082450

What does Innovative Mobile Learning Look Like?

Keywords: innovation; mobile learning; design

Context
Since the emergence of mobile technologies in the early part of the 21st century, numerous studies have demonstrated how, when used effectively, m-learning can support, enhance and in some cases, transform teaching and learning, bringing about significant gains for students (Pegrum, Howitt, & Striepe, 2013; Wu, Wu, Chen, Kao, Lin, & Huang, 2012; Kearney, Burden, & Rai, 2015; Mifsud, 2014). However, despite these demonstrable opportunities to enhance and transform how students learn, educators have been slow to harness mobile technologies and this includes both teachers in schools and teacher educators in universities with responsibility for preparing the next generation of teachers (Burden & Kearney, 2017). Research undertaken by the presenter indicates this is a ‘wicked problem’ and at its heart is the lack of effective professional development, suitable resources and exemplars to convince educators that mobile learning is worth investing in.

Purpose/Goal
In response to this challenge the presenter has led two Erasmus+ projects aimed at supporting teachers and teacher educators in using mobile technologies more effectively and more innovatively. The first of these projects – Mobilising and Transforming Teacher Educators’ Pedagogies (MTTEP) ran from 2014-2017 involving five partners from five universities and four schools (www.mttep.eu ). The second project - Designing and Evaluating Innovative Mobile Pedagogies (DEIMP) – is ongoing, and will be the basis of this presentation. Both projects are underpinned by a bespoke mobile learning framework called iPAC (Kearney, Schuck, Burden & Aubusson, 2012)

Actual or anticipated outcomes
The MTTEP project has resulted in a freely available, online mobile learning toolkit (www.mobilelearningtoolkit.com ) that schools and educators can use, modify and adapt. The DEIMP project is currently developing an original mobile app and complementary MOOC that supports educators in designing and evaluating innovative mobile learning scenarios (see www.deimpeu.com). The websites for these projects have been accessed in excess of 100,000 times and up to twenty institutions have used or adopted the resources for professional development purposes.

Conclusions/recommendations/summary
These projects demonstrate the value of how sustained and practical professional development activities can encourage educators to engage with mobile technologies in ways that overcome many of the barriers and challenges that have been highlighted in the literature (Burden & Hopkins, 2016). The presentation will encourage participants to join the m-learning network which has been established and to take part in the forthcoming trials and research scheduled for 2019-2020.

Francesco Cabras

Francesco Cabras, Consultant CRS4, Radix, Italy
Francesco Cabras is an entrepreneur who works in cloud-based software development. He is also a consultant with over 20 years of experience in the field of ICT. Before working freelance, he worked for about 10 years as researcher at CRS4 where he dealt with data management and data presentation in multimedia, health information technology and telemedicine. He is now part of the IDEA team as responsible for the creation and the usage of technological platform.
The IDEA Platform, the cloud at the service of didactics.

Keywords: IDEA platform, data management

Speed, scalability and iterative development were the main requirements to be respected to create a technological platform such as that of the IDEA project. In this talk, I shall first describe the system and its components, then illustrate how cloud technologies have made it possible to reach the expected results reducing time and costs of development and optimizing system reuse, evolutions and reliability.

Donald Clark

Donald Clark, Ed Tech Entrepreneur, Visiting Professor, University of Derby, United Kingdom
Donald Clark is an EdTech Entrepreneur, CEO, Professor, Researcher, Blogger and Speaker. He was CEO and one of the original founders of Epic Group plc, which established itself as the leading company in the UK online learning market, floated on the Stock Market in 1996 and sold in 2005. As well as being the CEO of Wildfire an AI-driven learning company, he also invests in, and advises, EdTech companies.
Describing himself as 'free from the tyranny of employment', he is a board member of AI focussed companies Cogbooks and LearningPool. He is also a Visiting Professor and involved in research into AI in learning. He has worked in schools, vocational, higher, corporate and adult learning, delivering real projects to real learners.
Donald has over 30 years experience in online learning, games, simulations, semantic, adaptive, chatbot, social media, mobile learning, virtual reality and AI projects. He has designed, delivered and advised on online learning for many global, public and private organisations. He is an evangelist for the use of technology in learning and has won many awards, including the first 'Outstanding Achievement in E-learning Award' and 'Best AIM Stock Market Company', 'Most Innovative Online Product' (for WildFire), 'Best Online Learning Project (for WildFire)' and 'JISC EdTech Award' (for WildFire).
An award winning speaker at national and international conferences, he has delivered keynotes in Europe. US, Africa, Australia, Middle and Far East... also a regular blogger (10 years+) on learning technology, His series on learning theorists, as well as 500 researched, online design tips, are valuable open resources. His book on AI for learning is in production.
AI changes everything

Keywords: Artificial Intelligence

Almost everything you do online is mediated by AI - Google, social media, Amazon, Netflix. This has come to education. Donald will define AI then go through the learning journey from learner engagement, learner support, delivery, assessment and well being showing real examples of how AI can aid teachers in education.

Kaśka Porayska-Pomsta

Kaśka Porayska-Pomsta, Professor, University College London, United Kingdom
Kaśka Porayska-Pomsta is a Professor of Artificial Intelligence in Education at the University College London (UCL), Knowledge Lab. Her research focuses on Artificial Intelligence in Education, with the specific emphasis on developing adaptive interactive environments for learning. She has over 20 years of experience in working with different learners, including with children and adults with and without special needs, and in developing AI systems for front line education. After completing her PhD in computational linguistics at the University of Edinburgh, she transitioned fully into AI in Education research and focused on modelling emotions in learning interactions, knowledge elicitation and knowledge engineering methodologies, and AI for social inclusion. She has been a principal investigator as well as co-investigator of a number of large interdisciplinary grants focusing on the application of AI to a variety of formal and informal educational contexts in the UK, the EU, India and the Philippines. Kaśka is an active participant in the recent debates and a contributor to evidence for parliamentary hearings on the role of Artificial Intelligence in human development and learning. In this she seeks to help harness AI for human benefit. She is Head of Research for the Department of Culture, Communication and Media at the UCL Institute of Education, member of the management committee for the Bloomsbury Centre for Educational Neuroscience, the steering committee for the UCL Institute of Digital Health, and of the Executive Board for the International Society for Artificial Intelligence in Education.
Scaffolding learners’ socio-emotional self-regulation through AI-enhanced learning environments

Keywords: Artificial Intelligence, Pedagogical Agents, Intelligent Learning Environments

The use of Artificial Intelligence in supporting social skills development is an emerging area of interest in education and broader teaching and learning practices. While the relationship between social communication skills and learning is well documented in diverse research disciplines that are cognate with educational research and practices (e.g. developmental and educational psychology, cognitive neuroscience), there is also a growing emphasis on those skills in formal learning contexts, where collaborative, self-regulated and project-based learning are becoming increasingly part of such contexts. However, despite the importance of social interaction to human everyday functioning, including learning, social skills require substantial training, socio-cultural conditioning and highly developed metacognitive competencies, involving ongoing, targeted self-monitoring and regulation. Social interaction and emotional self-regulation skills cannot be supported merely through showing or telling people how to feel or behave. Instead, they require access to (i) repeatable embodied experiences in contexts that credibly approximate real-life scenarios, and (ii) opportunities for situated recall and guided scrutiny of the behaviours enacted first-hand by the learners. Socially plausible interactions that are supported by AI agents and open learner modelling (OLM) provide a useful enhancement to the practices presently available. They also enable a systematic study of social interactions and of learning support needed to nurture learners’ self-regulation competencies.
In this talk I will present work conducted as part of two projects. The first project focused on supporting the development of social communication skills of the so-called low functioning children with Autism Spectrum Disorders diagnoses through the application of AI agents in blended AI-human learning contexts. The second project focused on creating an AI-enhanced situated experience and open learner modelling for 16-18 years old learners who were deemed at risk of social exclusion through unemployment during job interviews with AI recruiters, and on evaluating the impact of this environment on their verbal and non-verbal behaviours and on their self-efficacy. Using those two examples, I will discuss the applicability of AI-based education for supporting self-regulation competencies and more broadly social and educational inclusion. To conclude, I will draw a link between the approaches used in both of these projects and their relevance to formal and informal learning and teaching contexts, highlighting their critical emphasis on higher-level cognitive skills of importance to learning across domains

Valéry Psyché

Valéry Psyché, Professor, University Teluq, Quebec, Canada
Valéry Psyché is a full professor at TELUQ University and is a regular researcher at the LICEF research centre. She is specialized in technology enhanced learning, in instructional design, and Artificial Intelligence applied to education. She holds a PhD in cognitive informatics from the University of Quebec at Montreal (UQAM).
She did a postdoctoral fellowship on virtual communities of practice, at TELUQ University at TELUQ University, a doctoral internship in knowledge engineering at the Laboratoire d’informatique, de robotique et de microélectronique (LIRMM) at the University of Montpellier (France), and a doctoral internship in ontological engineering at the Institute of Scientific and Industrial Research (ISIR) at Osaka University (Japan). She holds a master’s degree in physics from UQAM, and a French degree in physics from the University Grenoble-Alpes (France). She also holds a Specialized Graduate Diploma in Educational Technology from TELUQ University and a certificate in Software Technology from McGill University. Before becoming a professor, she worked for many years as an instructional designer, independent researcher and faculty coordinator.
Her work focuses on ontological engineering, virtual communities of practice or learning, intelligent tutorial systems and more generally artificial intelligence in education.
Instructional design for Intelligent Adaptive Learning

Keywords: Instructional Design, Theories of teaching and learning, Adaptive learning environments, Learning Styles , structure of adaptive learning environments

“Apprentissage Adaptatif” is a literal translation of “Adaptive Learning”, which is best interpreted as “Adaptive Teaching” since the digital learning environment adapts to the learner and not the other way around. Adaptive learning is the process of “building a model of the learner’s objectives, preferences and knowledge, and using it throughout his or her interaction with the environment to provide personalized feedback or adapt content and interface to his or her learning needs” (Brusilovsky & Peylo, 2003). The adaptation is performed in real time using algorithms (machine) that make inferences from the learner’s actions in the learning session. An example of inference is the diagnosis of their errors. The more the machine simulates the behaviour of a human tutor, the more “intelligent” it is. This is referred to as an intelligent tutor and intelligent adaptive learning.
The “intelligent” nature of a digital learning environment lies in the fact that it can adapt to the learner. Adaptability refers to the ability of the learning environment to modify its behaviour based on inferences made based on the updated content of a learner’s model, whether on his or her cognitive, metacognitive or emotional state. Adaptive learning is the paradigm associated with learning environments and intelligent tutorial systems (Carbonnell, 1970; Sleeman and Brown, 1981; Wenger, 1987). Since Bloom’s (1984) demonstration, we know that tutoring is twice as effective as any other form of conventional teaching. This has encouraged its implementation in environments with an intelligent tutor or, more generally, in adaptive e-learning platforms, either intelligent or not. The adaptability of an intelligent learning environment (ILE) is implemented through the educational data collected. They generally correspond to information:

  • on the learner’s profile, pedagogical strategy and learning areas;
  • from the learner’s interactions with the ILE interface;

These data are generally used for (Nkambou, Mizoguchi and Bourdeau, 2010):

  • Dynamically plan learning objectives and activities in the ILE;
  • Configure its interface, presentation and sequence of activities;
  • Guide the learner through an activity or;
  • Establish a cognitive diagnosis of the learner.

How to integrate adaptive learning into your teaching?
Obviously, an instructional design method must be applied in order to define the level of possible adaptation according to the human and technological resources available to an institution. During this conference, we will discuss the parameters and the steps on which the teacher and the techno pedagogical team can intervene in order to achieve a minimum integration of adaptive learning in an online course according to a learning design approach.

Daniel Schneider

Daniel Schneider, Professor, University of Geneva, Switzerland
Daniel K. Schneider is an associate professor of educational technology at TECFA, a research and teaching unit in the Faculty of Psychology and Educational Sciences, University of Geneva. Holding a PhD in political science, he has been working in educational technology since 1988 and participated in various innovative pedagogical and technological projects. His long-term R&D interests focus on modular, flexible and open Internet architectures supporting rich and effective educational designs. His current interests include digital design and fabrication in education, student monitoring, e-learning competence, computational thinking and informal learning in developing countries. within TECFA's "blended" master program in educational technology (MALTT), he teaches educational information and communication systems, digital design and fabrication, foundations of educational technology, and research methodology. His personal homepage is at http://tecfa.unige.ch/DKS and he coordinates EduTechWiki (http://edutechwiki.unige.ch).
Computational Thinking and making

Keywords: Computational Thinking, Problem Solving, Making

The younger generation is neither born with built-in ICT skills nor exposed to much computational thinking. They seem to have little control over professional software. Few have basic coding skills and few are involved in the creation of shared technical artifacts. Digital design and fabrication (most often referred to as "making"), associated with design thinking, appears as a relevant solution to raise younger people's interest in digital subjects. It embodies human nature as a "hand in action" shaping the environment and addressing challenges that require creativity and technical skills. Associated with design thinking, "making" could develop 21st century skills such as numerical competence, problem-solving strategies and self-regulation. "Making" has several roots. It has been formalized by Gershenfeld in his "how to make almost anything" course at M.I.T. Characterized by project-based pedagogy, a just-in-time organization and a strong collaboration between students, this course served as a model for creating emancipatory and pedagogic "fab labs." At the same time, Do It Yourself (DYI) and crafts have experienced a revival through the evolution and the omnipresence of digital devices. A new generation of open source hardware allowed to build low-cost computer-controlled fabrication devices, in particular 3D printers. This led to the creation of so-called "maker-spaces". A new generation of websites allows easy sharing of digital designs and brought some new life to online involvement. So-called "hack labs" brought together people interested in electronics, e.g., taking things apart, understanding, repairing and repurposing them. The literature addresses four reasons for promoting "making" in education:

  1. It's a medium to teach programming, vector drawing, mathematics, environmental and societal issues.
  2. "Making" teaches planning, cooperation, and develops metacognitive skills.
  3. Design skills are essential for the future economy.
  4. Teachers can create or adapt constructive learning objects.

According to Blikstein, educators who introduce "making" refer to Papert's constructionism, as well as the libertarian pedagogies of Freire or Freinet. As such, "making" also is a tool for educational change, if desired. In this contribution we will focus on using "making" as a medium to teach computational thinking principles and some technical ICT fundamentals. We define computational thinking as a set of skills, competencies and procedures that facilitate problem solving based on principles from computer science. In that spirit, computational literacy can be broken down into three components:

  1. the ability to formulate a broader issue,
  2. solving a problem using information and communication technologies, and
  3. sharing the solution through online platforms.

We will present an overview of the so far sparse literature on making and computational thinking. We will present details of a few environments to teach basic programming, e.g. BlockSCAD, OpenSCAD and TurtleStitch, and discuss their didactic affordances to teach both basic programming constructs and some problem solving. We will then look at a larger picture, i.e. how to engage learners into creating meaningful objects that teach computational and other thinking skills beyond basic programming. To finish we will also discuss the possibility to create tools to teach computer science principles unplugged, since teachers who learn how to create objects that are meaningful for their own teaching also may consider teaching making to their own students.

Barbara Wasson

Barbara Wasson, Director, Centre for the Science of Learning & Technology (SLATE), University of Bergen, Norway
Barbara Wasson, Director of the Centre for The Science of Learning & Technology (SLATE), University of Bergen, Norway is a full Professor in the Department of Information Science & Media Studies. She was one of the founders of Kaleidoscope, a European Network of Excellence on Technology Enhanced Learning, sat on the executive committee, and was leader of its CSCL SIG with over 400 members, and is often used as an Expert evaluator by the European Commission. Wasson has been involved in research on technology enhanced learning since her Masters research starting in 1983. While a Ph.D student in Canada she was involved in the design of pedagogical agents for content planning in Intelligent Tutoring Systems. Before moving to Norway in 1991, Wasson was an advanced educational research specialist on Marlene Scardamalia and Carl Bereiter's Computer Supported Intentional Learning Environment (CSILE) Project at the University of Toronto, Canada, the first funded research project in the area of networked learning in the classroom. Subsequent to moving to Norway, Wasson’s research has focused on collaborative learning in distributed settings, mobile learning, interaction design, computer support for collaborative learning (CSCL), learning games, intelligent tutoring systems, e-assessment, teacher inquiry, learning analytics, and pedagogical agents. In 2003 Wasson obtained the contract for her previous research centre, InterMedia, to develop the ICT-based system to deliver the Norwegian National Tests in English for the Norwegian Ministry of Education (BITE-IT project). Wasson is/has been PI for numerous national and international projects and has over 120 publications in the field of Technology Enhanced Learning.
Learning Analytics

Keywords: Learning Analytics

Learning Analytics (LA) has emerged over the past 9 years as a promising field of research and domain of practice. The LA field comprises research into the challenges of collecting, managing, analysing, and reporting of data with the specific intent to improve learning and the contexts in which it occurs.
Since the term “learning analytics” first started appearing in 2010, there has been an increasing number of publications in the area, a growing number of implementations of learning analytics, emerging research Centres with learning analytics as a focus, and a growing interest from different stakeholders and policy makers. Learning analytics research draws on research fields that emerged in the 1970s and 1980s such as educational data mining, artificial intelligence in education, decision-support systems, intelligent tutoring systems, and new fields such as learning sciences, big data and business analytics.
In this talk I will first give an overview of the field of learning analytics and reflect on its role in education. Then I will present three SLATE projects that address learning analytics in the school sector.
First, in the Adaptive Learning in Mathematics (ALMAT) project, we carried out an empirical study of the use of an adapting learning tool, Multi Smart Øving (MSØ). MSØ is the only learning analytics tool being used in primary and secondary schools in Norway. Empirical data was collected on how teachers use and experience the tool, how the vendor experiences their own product, and how MSØ is presented commercially (Egelandsdal et al., 2019).
The second project, Activity Data for Assessment and Adaptivity (AVT), aimed to investigate the possibilities for the integration of activity data between vendors of digital tools used in schools, in order to provide learning tasks/items that are better adapted to a learner’s needs (Morlandstø et al., 2019; Wasson et al., 2019). In AVT we developed a framework for learning analytics that structures the data generated by learners working with the digital tools, provides an infrastructure that handles secure data exchange between vendors, and enables the recommendation of relevant tasks/items for learners. The AVT LA Framework provides a foundation for future work with learning analytics in primary and lower secondary education.
The insurgence of the use of technology for learning has increased the amount and types of data available in technology- and information-rich classrooms, and tools to handle this data are emerging. In our research on data literacy and use for teaching (Wasson & Hansen, 2016) we suggest that conceptions of digital competence need to be expanded to include the understanding of how to use this data, i.e., data literacy.
In a third project, Teacher Inquiry into Student Learning (TISL), the perspective of the teacher is central. TISL is an approach that investigates how teachers use student learning data to improve own teaching practice. Teacher inquiry, can be seen both as a way to improve day-to-day teaching in the classroom and as professional development for teachers.

Davide Zedda

Davide Zedda, Consultant CRS4, IISS Michele Giua, Italy
By training, Davide is a physicist and works as IT teacher at high school level. He presently teaches in IISS Giua, Cagliari. He has always worked in the area of Information Technology (IBM, University of Cagliari, Hydrocontrol), with a strong interest towards research. This aspiration is fulfilled with the collaboration with the Edutech group of CRS4, especially collaborating to the IDEA project. He acted as a bridge between schools and the IDEA project, the objective of which is to help teachers use technologies having a good potential to enhance didactic paths.
Current educational topics studied are: Computational thinking, robotics, IoT, databases, web apps, mobile applications, Artificial Intelligence, OOP mainly developed using Microsoft and Arduino platforms.
Remote Intelligent Access to Lab Experiment

Keywords: Artificial Intelligence, Remote Labs

RIALE is a multimodal learning approach proposal for science subjects, augmented by video, audio, text, external links tagged with the support of Artificial Intelligence (AI). Experimental data is remotely collected through IoT channels. The AI tagged contents are placed in a timeline that allows users to live and relive the experiment and that provides for a visual support that helps users identify cause and effect relationships between the different experiment steps. RIALE is designed not only to supplement traditional laboratory activities but also as an opportunity for the student to experience first-hand how a real college-level scientific experiment is carried out, with technologies and tools that school laboratories cannot afford. RIALE offers a space in which teachers can share the created contents and scenarios, and tailor them to match their specific teaching and educational objectives. The RIALE platform is based on an as a service cloud infrastructure (PaaS) accessible from both Web browsers and mobile devices.

Questo sito utilizza cookie tecnici e assimilati. Possono essere presenti anche cookie profilazione di terze parti. Se vuoi saperne di più o negare il consenso a tutti o ad alcuni cookie leggi l'informativa completa. Proseguendo nella navigazione (anche con il semplice scrolling) acconsenti all'uso dei cookie. This site uses technical and anonymized analytics cookies only. There may also be profiling third-party cookies. Please read the cookie information page to learn more about how we use cookies or blocking them. more information

The cookie settings on this website are set to "allow cookies" to give you the best browsing experience possible. If you continue to use this website without changing your cookie settings or you click "Accept" below then you are consenting to this.

Close