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  • 1. Cerratto Pargman, Teresa
    et al.
    Otero, Nuno
    Milrad, Marcelo
    Spikol, Daniel
    Malmö högskola, Fakulteten för lärande och samhälle (LS), Institutionen för natur, miljö, samhälle (NMS).
    Knutsson, Ola
    Ramberg, Robert
    Purposeful Learning Across Collaborative Educational Spaces2014Inngår i: Learning and becoming in practice: the international conference of the learning sciences (ICLS) 2014: proceedings volume 3, International Society of the Learning Sciences, 2014, s. 1597-1598Konferansepaper (Annet vitenskapelig)
    Abstract [en]

    This paper presents the overall goals and preliminary results of an on-going research project that aims at: understanding the intricacies and complexities of introducing mobile technologies into schools’ curriculum and accepted teaching practices; analyzing actual transformations that the use of mobile technologies in schools brings to contemporary forms of learning. The results of the project will contribute to a better understanding of new media literacies and their implications for curriculum design and everyday educational practices.

    Fulltekst (pdf)
    FULLTEXT01
  • 2. Cerratto-Pargman, Teresa
    et al.
    Knuttsson, Ola
    Spikol, Daniel
    Malmö högskola, Teknik och samhälle (TS).
    Milrad, Marcelo
    Exploring Teachers’ perspectives on the use of Mobile devices for Math and Language Learning2014Inngår i: Conference proceedings - 4th international Designs for Learning conference 6-9th May 2014, Stockholm University, 2014Konferansepaper (Annet vitenskapelig)
    Abstract [en]

    “Digital competence” and practices such as “social networking” are today seen as central skills that citizens of the 21st century should have (Lucas and Moreira, 2009). In spite of these developments, recent studies have shown that most of the innovations related to the use of ICT in schools have not impacted pedagogical or school development (Buckinghamn & Willett, 2006; Coiro et al., 2008; Snyder et al., 2010). The problem is far from being trivial since online communication and interaction are not longer a separate phenomenon from children’s daily lives. In this socio‐technological configuration, schools in particular are deeply challenged as they are confronted with questions such as: What kinds of learning strategies and skills are kids developing outside schools? What are they learning in their interaction with digital tools? Which opportunities for learning and work do digital tools really afford? How are schools aligned to the conditions for learning and teaching that the use of digital tools promotes today?

    Fulltekst (pdf)
    FULLTEXT01
  • 3. Cojocaru, Dorian
    et al.
    Friesel, Anna
    Spikol, Daniel
    Malmö högskola, Fakulteten för teknik och samhälle (TS). Malmö högskola, Internet of Things and People (IOTAP).
    Supporting STEM knowledge and skills in engineering education: PELARS project2016Inngår i: Proceedings of the 2016 ASEE Annual Conference & Exposition, The American Society for Engineering Education, 2016, artikkel-id 17572Konferansepaper (Fagfellevurdert)
    Abstract [en]

    In this paper we present our proposal for improving education with hands-on, project-based and experimental scenarios for engineering students with the use of learning analytics. We accomplish this through teacher and learner engagement, user studies and evaluated trials, performed at UCV (University of Craiova, Romania) and DTU (Technical University of Denmark). The PELARS project (Practice-based Experiential Learning Analytics Research And Support) provides technological tools and ICT-based methods for collecting activity data (moving image-based and embedded sensing) for learning analytics (data-mining and reasoning) of practice-based and experiential STEM. This data is used to create analytics support tools for teachers, learners and administrators, providing frameworks for evidence-based curriculum design and learning systems. The PELARS project creates behavioral recording inputs, proving a new learning analytic that is scalable in application, and bridge qualitative and quantitative methods through reasoning and feedback from input data. The project serves to better understand learners' knowledge in physical activities in laboratory and workshop environments, as well as informal learning scenarios. PELARS traces and helps assess learner progress through technology enhancement, in novel ways building upon current research. The project results in learning analytics tools for practice-based STEM learning that are appropriate for real-world learning environments.

    Fulltekst (pdf)
    FULLTEXT01
  • 4.
    Cojocaru, Dorian
    et al.
    Univ Craiova, Fac Automat Comp & Elect, Craiova, Romania.
    Spikol, Daniel
    Malmö högskola, Fakulteten för teknik och samhälle (TS).
    Friesel, Anna
    Tech Univ Denmark, DTU Ballerup Campus DTU Diplom, Lyngby, Denmark.
    Cukurova, Mutlu
    UCL, London Knowledge Lab, Inst Educ, London WC1E 6BT, England.
    Valkanova, Nina
    Copenhagen Inst Interact Design, Copenhagen, Denmark.
    Rovida, Raffaella
    Copenhagen Inst Interact Design, Copenhagen, Denmark.
    Tanasie, Razvan Tudor
    Univ Craiova, Fac Automat Comp & Elect, Craiova, Romania.
    Prototyping Feedback for Technology Enhanced Learning2016Inngår i: INTERNATIONAL JOURNAL OF EDUCATION AND INFORMATION TECHNOLOGIES, ISSN 2074-1316, Vol. 10, s. 144-151Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    The development of new educational technologies, in the area of practical activities is the main aim of the FP7 PELARS project. As part of the constructivist learning scenarios, according to the project proposal, the development and evaluation of technology designs are envisaged, for analytic data generation for Science, Technology, Engineering and Mathematics (STEM) subjects, such as: technology solutions, infrastructure, activities, assessment, curricula, and classroom furniture and environment designs. Inside four EU national settings, three separate learning contexts are being dealt with - from secondary-level high school STEM learning environments to post-secondary level engineering classes and design studios. Given this experience and framework, the present paper provides a perspective on the importance of using such research experience and iterative prototyping in real learning environments for engineering students.

  • 5.
    Cukurova, Mutlu
    et al.
    London Knowledge Lab, UCL Institute of Education, University College London, London, United Kingdom.
    Avramides, Katerina
    London Knowledge Lab, UCL Institute of Education, University College London, London, United Kingdom.
    Spikol, Daniel
    Malmö högskola, Fakulteten för teknik och samhälle (TS). Malmö högskola, Internet of Things and People (IOTAP).
    Luckin, Rose
    London Knowledge Lab, UCL Institute of Education, University College London, London, United Kingdom.
    Mavrikis, Manolis
    London Knowledge Lab, UCL Institute of Education, University College London, London, United Kingdom.
    An analysis framework for collaborative problem solving in practice-based learning activities: A mixed-method approach2016Inngår i: Proceedings of LAK '16 6th International Conference on Learning Analytics and Knowledge, ACM Digital Library, 2016, s. 84-88Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Systematic investigation of the collaborative problem solving process in open-ended, hands-on, physical computing design tasks requires a framework that highlights the main process features, stages and actions that then can be used to provide 'meaningful' learning analytics data. This paper presents an analysis framework that can be used to identify crucial aspects of the collaborative problem solving process in practice-based learning activities. We deployed a mixed-methods approach that allowed us to generate an analysis framework that is theoretically robust, and generalizable. Additionally, the framework is grounded in data and hence applicable to real-life learning contexts. This paper presents how our framework was developed and how it can be used to analyse data. We argue for the value of effective analysis frameworks in the generation and presentation of learning analytics for practice-based learning activities.

  • 6.
    Cukurova, Mutlu
    et al.
    UCL, UCL Knowledge Lab, London, England.
    Luckin, Rose
    UCL, UCL Knowledge Lab, London, England.
    Millán, Eva
    Univ Malaga, Malaga, Spain.
    Mavrikis, Manolis
    UCL, UCL Knowledge Lab, London, England.
    Spikol, Daniel
    Malmö högskola, Fakulteten för teknik och samhälle (TS).
    Diagnosing collaboration in practice-based learning: Equality and Intra-individual variability of physical interactivity2017Inngår i: Data Driven Approaches in Digital Education: Proceedings of the 12 th European Conference on Technology Enhanced Learning, Springer, 2017, s. 30-42Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Collaborative problem solving (CPS), as a teaching and learning approach, is considered to have the potential to improve some of the most important skills to prepare students for their future. CPS often differs in its nature, practice, and learning outcomes from other kinds of peer learning approaches, including peer tutoring and cooperation; and it is important to establish what identifies collaboration in problem-solving situations. The identification of indicators of collaboration is a challenging task. However, students physical interactivity can hold clues of such indicators. In this paper, we investigate two non-verbal indexes of student physical interactivity to interpret collaboration in practice-based learning environments: equality and intra-individual variability. Our data was generated from twelve groups of three Engineering students working on open-ended tasks using a learning analytics system. The results show that high collaboration groups have member students who present high and equal amounts of physical interactivity and low and equal amounts of intra-individual variability.

  • 7.
    Cukurova, Mutlu
    et al.
    University College London, UK.
    Zhou, Qi
    University College London, UK.
    Spikol, Daniel
    Malmö universitet, Internet of Things and People (IOTAP). Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT).
    Landolfi, Lorenzo
    Scuola Superiore Sant'Anna, Italy.
    Modelling Collaborative Problem-solving Competence with Transparent Learning Analytics: Is Video Data Enough?2020Inngår i: LAK20: THE TENTH INTERNATIONAL CONFERENCE ON LEARNING ANALYTICS & KNOWLEDGE, Association for Computing Machinery (ACM), 2020, s. 270-275Konferansepaper (Fagfellevurdert)
    Abstract [en]

    In this study, we describe the results of our research to model collaborative problem-solving (CPS) competence based on analytics generated from video data. We have collected similar to 500 mins video data from 15 groups of 3 students working to solve design problems collaboratively. Initially, with the help of OpenPose, we automatically generated frequency metrics such as the number of the face-in-the-screen; and distance metrics such as the distance between bodies. Based on these metrics, we built decision trees to predict students' listening, watching, making, and speaking behaviours as well as predicting the students' CPS competence. Our results provide useful decision rules mined from analytics of video data which can be used to inform teacher dashboards. Although, the accuracy and recall values of the models built are inferior to previous machine learning work that utilizes multimodal data, the transparent nature of the decision trees provides opportunities for explainable analytics for teachers and learners. This can lead to more agency of teachers and learners, therefore can lead to easier adoption. We conclude the paper with a discussion on the value and limitations of our approach.

  • 8.
    Dabisias, Giacomo
    et al.
    Scuola Superiore Sant’Anna, Italy.
    Spikol, Daniel
    Malmö högskola, Fakulteten för teknik och samhälle (TS).
    Ruffaldi, Emanuele
    Scuola Superiore Sant’Anna, Italy.
    A Learning Analytics Framework for Practice-Based Learning2015Inngår i: Exploring the Material Conditions of Learning: Computer Supported Collaborative Learning (CSCL) Conference 2015;2, International Society of the Learning Sciences, 2015, s. 740-742Konferansepaper (Fagfellevurdert)
    Abstract [en]

    The role of the PELARS Learning Analytics System (LAS) system is to collect information from students performing project-based tasks, reason on such information and provide visualization to teachers and students, that is usable for understanding the learning process. The information collected by the LAS comprises pieces of information collected directly by the Students, and other collected by the System automatically. In this work we will provide a comprehensive description of the framework and the motivations behind the various decisions. The software framework will be described starting from the broad vision of the context and then the different components will be described in detail.

  • 9.
    Davidsson, Paul
    et al.
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Internet of Things and People (IOTAP).
    Langheinrich, MarcUniversità della Svizzera italiana, Lugano, Switzerland.Linde, PerMalmö universitet, Fakulteten för kultur och samhälle (KS), Institutionen för konst, kultur och kommunikation (K3). Malmö universitet, Internet of Things and People (IOTAP).Mayer, SimonUniversity of St. Gallen, Switzerland.Casado-Mansilla, DiegoUniversity of Deusto, Spain.Spikol, DanielMalmö universitet, Internet of Things and People (IOTAP). Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT).Kraemer, Frank AlexanderNorwegian University of Science and Technology, Norway.Russo, Nancy LMalmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Internet of Things and People (IOTAP).
    IoT '20 Companion: 10th International Conference on the Internet of Things Companion2020Konferanseproceedings (Fagfellevurdert)
  • 10. Eliasson, Johan
    et al.
    Pargmann, Teresa Cerratto
    Nouri, Jalal
    Spikol, Daniel
    Malmö högskola, Teknik och samhälle (TS).
    Ramberg, Robert
    Mobile devices as support rather than distraction for mobile learners: evaluating guidelines for design2013Inngår i: Innovations in mobile educational technologies and applications / [ed] David Parsons, IGI Global, 2013, s. 61-76Kapittel i bok, del av antologi (Fagfellevurdert)
    Abstract [en]

    This article questions the design of mobile learning activities that lead students to spend time focusing on the mobile devices at the expense of interacting with other students or exploring the environment. This problem is approached from an interaction design perspective, designing and analysing geometry-learning activities. The authors present six guidelines for designing mobile learning activities, where mobile devices support rather than distract students from contents and contexts relevant to the learning goals. The guidelines are developed through video analysis of groups of middle school students doing learning activities outdoors and evaluated using the task model. The guidelines suggest that students (1) assume roles based on a different functionality of each device, (2) use devices as contextual tools, that the activities, (3) include physical interaction with the environment, (4) let teachers assume roles, (5) encourage face-to-face communication, and (6) introduce students to the mobile devices.

  • 11.
    Friesel, Anna
    et al.
    Section for Electrical Technology, Technical University of Denmark, Denmark.
    Spikol, Daniel
    Malmö högskola, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT).
    Cojocaru, Dorian
    Department of Automation, Electronics and Mechatronics, University of Craiova, Craiova, Romania.
    Technologies designed and developed in PELARS project: the way to enhance STEM education2017Inngår i: 2017 27TH EAEEIE Annual Conference (EAEEIE), IEEE, 2017Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Practice-based Experiential Learning Analytics Research and Support (PELARS) is a project about learning and making. The PELARS project finds ways of generating "analytics" (data about the learning process and analysis of this data), which helps learners and teachers by providing feedback from hands-on, project-based and experiential learning situations. In this paper, we present our proposal for improving analytics education with hands-on, project-based and experimental scenarios for engineering students. This is done through teacher and learner engagement, user studies and evaluated trials, performed at UCV (University of Craiova, Romania) and DTU Diplom (Technical University of Denmark, Campus Ballerup, Denmark). The PELARS project provides technological tools and ICT-based methods for collecting activity data ( moving image-based and embedded sensing) for learning analytics (data-mining and reasoning) of practice-based and experiential STEM.

  • 12. Healion, Daniel
    et al.
    Russell, Sam
    Cukurova, Mutlu
    Spikol, Daniel
    Malmö högskola, Fakulteten för teknik och samhälle (TS). Malmö högskola, Internet of Things and People (IOTAP).
    Designing Spaces for Collaboration in Practice-Based Learning2017Inngår i: CSCL’17 : The 12th International Conference on Computer Supported Collaborative Learning, International Society of the Learning Sciences. , 2017, s. 565-568Konferansepaper (Fagfellevurdert)
    Abstract [en]

    In order to support equity and access in collaborative learning, it is important to understand the nature of collaborative learning itself. One approach is to look at the physical aspects of how students collaborate while engaged in open-ended group-work during Practice-Based Learning (PBL) activities. By analysing how students and teachers move and interact in relation to each other, the space they are in and the objects within it, we can gain a greater understanding of the physical nature of collaborative group-work. This understanding can help us to create a learning environment that intrinsically but unobtrusively supports access by all user profiles who seek to engage with it, thus promoting equity of engagement and participation. Using the example of the design of a Learning Analytics System (LAS) and the educational furniture in which it is implemented, we will show how the physical design of a CSCL implementation can support increased collaboration.

  • 13.
    Healion, Donal
    et al.
    National College of Art and Design, Dublin, Ireland.
    Russell, Sam
    National College of Art and Design, Dublin, Ireland.
    Cukurova, Mutlu
    UCL Knowledge Lab, University College, London, United Kingdom.
    Spikol, Daniel
    Malmö högskola, Fakulteten för teknik och samhälle (TS).
    Tracing physical movement during practice-based learning through Multimodal Learning Analytics2017Inngår i: Proceedings of the Seventh International Learning Analytics & Knowledge Conference, ACM Digital Library, 2017, s. 588-598Konferansepaper (Fagfellevurdert)
    Abstract [en]

    In this paper, we pose the question, can the tracking and analysis of the physical movements of students and teachers within a Practice-Based Learning (PBL) environment reveal information about the learning process that is relevant and informative to Learning Analytics (LA) implementations? Using the example of trials conducted in the design of a LA system, we aim to show how the analysis of physical movement from a macro level can help to enrich our understanding of what is happening in the classroom. The results suggest that Multimodal Learning Analytics (MMLA) could be used to generate valuable information about the human factors of the collaborative learning process and we propose how this information could assist in the provision of relevant supports for small group work. More research is needed to confirm the initial findings with larger sample sizes and refine the data capture and analysis methodology to allow automation.

  • 14.
    Hwang, Gwo-Jen
    et al.
    National Taiwan University of Science and Technology, Taiwan.
    Spikol, Daniel
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Disciplinary literacy and inclusive teaching.
    Li, Kam-Cheong
    Open University of Hong Kong, China.
    Guest Editorial: Trends and Research Issues of Learning Analytics and Educational Big Data2018Inngår i: Educational Technology & Society, ISSN 1176-3647, E-ISSN 1436-4522, Vol. 21, nr 2, s. 134-136Artikkel i tidsskrift (Annet vitenskapelig)
    Fulltekst (pdf)
    FULLTEXT01
  • 15.
    Jönsson, Per
    et al.
    Malmö högskola, Teknik och samhälle (TS).
    Spikol, Daniel
    Malmö högskola, Teknik och samhälle (TS).
    Svingby, Gunilla
    Malmö högskola, Fakulteten för lärande och samhälle (LS), Institutionen för natur, miljö, samhälle (NMS).
    Peterson, Anders
    Pendrill, Ann-Marie
    Nationell implementeringsplan för IKT i matematikundervisningen2013Inngår i: Datorn i utbildningen, ISSN 1100-3650, Vol. 4, s. 30-33Artikkel i tidsskrift (Annet (populærvitenskap, debatt, mm))
    Fulltekst (pdf)
    FULLTEXT01
  • 16.
    Katterfeldt, Eva-Sophie
    et al.
    University of Bremen, Bremen, Germany.
    Cuartielles, David
    Arduino Verkstad AB, Malmö, Sweden.
    Spikol, Daniel
    Malmö högskola, Fakulteten för teknik och samhälle (TS). Malmö högskola, Internet of Things and People (IOTAP).
    Ehrenberg, Nils
    Malmö högskola, Fakulteten för teknik och samhälle (TS). Malmö högskola, Internet of Things and People (IOTAP).
    Talkoo: A new paradigm for physical computing at school2016Inngår i: Proceedings of IDC2016: The 15th International Conference on INteraction Design and Children, ACM Digital Library, 2016, s. 512-517Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Introducing physical computing into regular school classes is challenged by constraints of schedules and curricula structures, which do not allow for time-consuming electronics prototyping. We present a novel approach to prototyping with physical computing components with the Arduino-based TALKOO kit: It comprises hardware modules, a visual IDE and prototyping material. Sensor and actuator modules are pluggable and do not require soldering and prior knowledge in electronics. The components have the ability to "talk" back to the visual IDE and to a learning analytics system. A new paradigm for visual programming maps physical modules onto virtual representations on screen making programming more intuitive. The TALKOO kit expands the field of application of physical computing for children in regular school contexts. Preliminary evaluation results show that children were able to build elaborative prototypes within an hour.

  • 17.
    Katterfeldt, Eva-Sophie
    et al.
    University of Bremen, Germany.
    Cukurova, Mutlu
    University College London, United Kingdom.
    Spikol, Daniel
    Malmö universitet, Internet of Things and People (IOTAP). Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Disciplinary literacy and inclusive teaching.
    Cuartielles, David
    Arduino Verkstad AB.
    Physical computing with plug-and-play toolkits: Key recommendations for collaborative learning implementations2018Inngår i: International Journal of Child-Computer Interaction, ISSN 2212-8689, E-ISSN 2212-8697, Vol. 17, s. 72-82Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Physical computing toolkits have long been used in educational contexts to learn about computational concepts by engaging in the making of interactive projects. This paper presents a comprehensive toolkit that can help educators teach programming with an emphasis on collaboration, and provides suggestions for its effective pedagogical implementation. The toolkit comprises the Talkoo kit with physical computing plug-and-play modules and a visual programming environment. The key suggestions are inspired by the results of the evaluation studies which show that children (aged 14–18 in a sample group of 34 students) are well motivated when working with the toolkit but lack confidence in the kit’s support for collaborative learning. If the intention is to move beyond tools and code in computer education to community and context, thus encouraging computational participation, collaboration should be considered as a key aspect of physical computing activities. Our approach expands the field of programming with physical computing for teenage children with a focus on empowering teachers and students with not only a kit but also its appropriate classroom implementation for collaborative learning.

  • 18.
    Leckner, Sara
    et al.
    Malmö högskola, Fakulteten för teknik och samhälle (TS). Malmö högskola, Fakulteten för kultur och samhälle (KS), Medea.
    Packmohr, Sven
    Malmö högskola, Fakulteten för teknik och samhälle (TS). Malmö högskola, Fakulteten för kultur och samhälle (KS), Medea.
    Spikol, Daniel
    Malmö högskola, Fakulteten för teknik och samhälle (TS). Malmö högskola, Fakulteten för kultur och samhälle (KS), Medea.
    Creating innovation: reflecting on the MEDEA studio at Malmö University2015Inngår i: eLearning Papers, E-ISSN 1887-1542, Vol. 41, s. 61-65Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    The MEDEA Studio was a research centre founded at Malmö University. It focused on collaborative media and design to promote research and practice in connection with its surrounding environment for better innovation and outreach. During its history, MEDEA has undergone several changes leading to diverse challenges. This field report examines MEDEA’s development from the perspectives of knowledge acquisition and learning with the aim to analyse factors for success and failures. As society and especially academia struggle with understanding how to innovate and connect, reflecting on the different instantiations of the MEDEA studio can bring insights for researchers, practitioners, administrators and the studio’s future development.

    Fulltekst (pdf)
    FULLTEXT01
  • 19.
    Luckin, Rose
    et al.
    UCL, London, England.
    Mavrikis, Manolis
    UCL, London, England.
    Cukurova, Mutlu
    UCL, London, England.
    Porayska-Pomsta, Kaska
    UCL, London, England.
    Holmes, Wayne
    Open Univ, Milton Keynes, Bucks, England.
    Rienties, Bart
    Open Univ, Milton Keynes, Bucks, England.
    Spikol, Daniel
    Malmö högskola, Fakulteten för teknik och samhälle (TS).
    Aleven, Vincent
    Carnegie Mellon Univ, Pittsburgh, PA 15213 USA.
    Forcier, Laurie
    Pearson, London, England.
    How Do We Unleash AIEd at Scale to Benefit All Teachers and Learners?2017Inngår i: Artificial Intelligence in Education: Back matter: Tutorials and workshops / [ed] André, Elisabeth; Baker, Ryan; Hu, Xiangen; Ma, Mercedes T. Rodrigo, du Boulay, Benedict, Springer, 2017, s. 665-667Konferansepaper (Fagfellevurdert)
    Abstract [en]

    The application of artificial intelligence to education (AIEd) has been the subject of academic research for more than 30 years, a period during which much technical progress has been made, but few in-roads into mainstream education have been achieved. With the upsurge of interest in AI in general and increasingly in AI for education in particular, what role could and should the AIED research community play?

  • 20. Luckin, Rose
    et al.
    Mavrikis, Manolis
    Spikol, Daniel
    Malmö högskola, Fakulteten för teknik och samhälle (TS).
    Learning Analytics for Project Based and Experiential Learning Scenarios2015Inngår i: Artificial Intelligence in Education: 17th International Conference, AIED 2015, Madrid, Spain, June 22-26, 2015. Proceedings, Springer, 2015, s. 886-886Konferansepaper (Annet vitenskapelig)
  • 21.
    Martinez-Maldonado, Roberto
    et al.
    University of Technology, Sydney, Australia.
    Echeverria, VanessaUniversity of Technology, Sydney, Australia.Prieto, Luis P.School of Educational Sciences, Tallin University, Estonia.Rodriguez-Triana, Maria JesusÉcole Polytechnique Fédérale de Lausanne & Tallinn University, Estonia.Spikol, DanielMalmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Disciplinary literacy and inclusive teaching.Curukova, MutluUCL Knowledge Lab, United Kingdom.Mavrikis, ManolisUCL Knowledge Lab, United Kingdom.Ochoa, XavierEscuela Superior Politécnica del Litoral, ESPOL, Ecuador.Worsley, MarceloNorthwestern University, United States.
    2nd Crossmmla: Multimodal learning analytics across physical and digital spaces2018Konferanseproceedings (Fagfellevurdert)
    Abstract [en]

    Students’ learning is ubiquitous. It happens wherever the learner is rather than being constrained to a specific physical or digital learning space (e.g. the classroom or the institutional LMS respectively). A critical question is: how to integrate and coordinate learning analytics to provide continued support to learning across physical and digital spaces? CrossMMLA is the successor to the Learning Analytics Across Spaces (CrossLAK) and MultiModal Learning Analytics (MMLA) series of workshops that were merged in 2017 after successful cross-pollination between the two communities. Although it may be said that CrossLAK and MMLA perspectives follow different philosophical and practical approaches, they both share a common aim. This aim is: deploying learning analytics innovations that can be used across diverse authentic learning environments whilst learners feature various modalities of interaction or behaviour.

    Fulltekst (pdf)
    Preface
  • 22. Mehanovic, Sanela
    et al.
    Spikol, Daniel
    Malmö högskola, Teknik och samhälle (TS).
    Investigating how to design interactive learning environments to support students’ learning of upper secondary and university math2012Inngår i: Proceedings of the 20th International Conference on Computers in Education ICCE2012, National Institute of Education, Nanyang Technological University, Singapore , 2012, s. 782-786Konferansepaper (Annet vitenskapelig)
    Abstract [en]

    Students’ difficulties in learning of mathematics have for a long time, been investigated by researchers in different fields. Within educational research there are claims that technological tools appropriately integrated in students’ mathematical work can support their understanding of a wide range of concepts in mathematics. This paper reports on the initial investigation for the design of Interactive Learning Environments (ILE) to support students’ learning of mathematics. The project is guided by the notion of Design Based Research (DBR) and aims to explore how to design ILE that support students’ understanding of integrals in particular. The initial study was conducted at a Swedish university with 10 students in 4 groups. The study confirmed difficulties in students’ understanding of integrals as reported in educational literature and provides a set of design aims for the next iteration of the ILE to support the learning.

    Fulltekst (pdf)
    FULLTEXT01
  • 23. Nouri, Jalal
    et al.
    Spikol, Daniel
    Malmö högskola, Fakulteten för teknik och samhälle (TS). Malmö högskola, Internet of Things and People (IOTAP).
    Pargman Cerratto, Teresa
    The Learning Activity Design Framework to Support Mobile Learning in Primary School2016Inngår i: Designs for Learning, ISSN 1654-7608, Vol. 8, nr 1, s. 1-12Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    This article introduces the Learning Activity Design (LEAD) framework for the development and implementation of mobile learning activities in primary schools. The LEAD framework is grounded in 4 design projects conducted over a period of 6 years. It contributes with a new understanding of the intricacies and multifaceted aspects of the design-process characterizing the development and implementation of mobile devices (i.e. smart phones and tablets) into curricular activities conducted in Swedish primary schools. The LEAD framework draws on methodological perspectives suggested by design-based research and interaction design, in the specific field of Technology-Enhanced Learning (TEL). This framework intends to provide both designers and researchers with methodological tools that take account of pedagogical foundations of technologically-based educational interventions, usability issues related to the interaction with the mobile application developed, multiple data streams generated during the design project, multiple stakeholders involved in the design process, and sustainability aspects of the mobile learning activities implemented in the school classroom.

    Fulltekst (pdf)
    FULLTEXT01
  • 24.
    Ouhaichi, Hamza
    et al.
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT).
    Spikol, Daniel
    Univ Copenhagen, Dept Sci Educ, Copenhagen, Denmark..
    Vogel, Bahtijar
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT).
    MBOX: Designing a Flexible IoT Multimodal Learning Analytics System2021Inngår i: IEEE 21st International Conferenceon Advanced Learning TechnologiesICALT 2021 / [ed] Chang, M., Chen, NS., Sampson, DG., Tlili, A., IEEE, 2021, s. 122-126Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Multimodal Learning Analytics (MMLA) provides opportunities for understanding and supporting collaborative problem-solving. However, the implementation of MMLA systems is challenging due to the lack of scalable technologies and limited solutions for collecting data from group work. This paper proposes the Multimodal Box (MBOX), an IoT-based system for MMLA, allowing the collection and processing of multimodal data from collaborative learning tasks. MBOX investigates the development and design for an IoT focusing on small group work in real-world settings. Moreover, MBOX promotes adaptation to different learning environments and enables a better scaling of computational resources used within the learning context.

  • 25.
    Ouhaichi, Hamza
    et al.
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Internet of Things and People (IOTAP).
    Spikol, Daniel
    Malmö universitet, Internet of Things and People (IOTAP). Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Disciplinary literacy and inclusive teaching.
    Vogel, Bahtijar
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Internet of Things and People (IOTAP).
    Rethinking MMLA: Design Considerations for Multimodal Learning Analytics Systems2023Inngår i: L@S '23: Proceedings of the Tenth ACM Conference on Learning @ Scale, ACM Digital Library, 2023, s. 354-359Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Designing MMLA systems is a complex task requiring a wide range of considerations. In this paper, we identify key considerations that are essential for designing MMLA systems. These considerations include data management, human factors, sensors and modalities, learning scenarios, privacy and ethics, interpretation and feedback, and data collection. The implications of these considerations are twofold: 1) The need for flexibility in MMLA systems to adapt to different learning contexts and scales, and 2) The need for a researcher-centered approach to designing MMLA systems. Unfortunately, the sheer number of considerations can lead to a state of "analysis paralysis," where deciding where to begin and how to proceed becomes overwhelming. This synthesis paper asks researchers to rethink the design of MMLA systems and aims to provide guidance for developers and practitioners in the field of MMLA.

    Fulltekst (pdf)
    fulltext
  • 26.
    Ruffaldi, Emanuele
    et al.
    Scuola Superiore Sant’ Anna, Pisa, Italy.
    Dabisias, Giacomo
    Scuola Superiore Sant’ Anna, Pisa, Italy.
    Landolfi, Lorenzo
    Scuola Superiore Sant’ Anna, Pisa, Italy.
    Spikol, Daniel
    Malmö högskola, Fakulteten för teknik och samhälle (TS). Malmö högskola, Internet of Things and People (IOTAP).
    Data collection and processing for a multimodal learning analytic system2016Inngår i: Proceedings of 2016 SAI Computing Conference (SAI), IEEE, 2016, s. 858-863Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Learning Analytic (LA) systems are aimed at supporting teachers in understanding the learning process by analyzing the information and the interaction of students with computer systems. In the case of a project-based learning process there is a need of introducing measure the student’ activity as acquired via multiple modalities and then processed. The acquisition and processing needs to take into account the specificities of the learning context and deployment at schools, in particular in terms of system architecture. The paper proposes an architecture for the acquisition and processing of data for project-based LA designed to be interoperable and scalable. System design, details of the solutions and brief examples of acquired data are presented.

  • 27.
    Schnaider, K.
    et al.
    Umeå University.
    Schiavetto, S.
    State University of Campinas.
    Meier, F.
    Aalborg University, Denmark.
    Wasson, B.
    University of Bergen, Norway.
    Allsopp, B. B.
    Aalborg University, Denmark.
    Spikol, Daniel
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT).
    Governmental Response to the COVID-19 Pandemic: A Quantitative Ethnographic Comparison of Public Health Authorities’ Communication in Denmark, Norway, and Sweden2021Inngår i: Advances in Quantitative Ethnography: Second International Conference, ICQE 2020, Malibu, CA, USA, February 1-3, 2021, Proceedings, Springer, 2021, s. 406-421Konferansepaper (Fagfellevurdert)
    Abstract [en]

    The Scandinavian countries are often seen as a unity. However, during the COVID-19 pandemic striking differences on how the countries approached the crisis became evident. This quantitative-ethnographic (QE) study aimed to understand political and cultural similarities and differences between the three Scandinavian countries – Denmark, Norway and Sweden – through their crisis communications during the COVID-19 pandemic. Specifically, we focused on how the health authorities of the three countries, in their press releases, treated information about COVID-19 and acted in four fields: reorganization of population behavior, containment of viral transmission, preparation of health systems, and management of socioeconomic impacts. As a methodology, the QE tools nCoder and ENA were applied, respectively: to code the press releases and to correlate the treatment of information with the four fields of action. © 2021, Springer Nature Switzerland AG.

  • 28.
    Spikol, Daniel
    Malmö högskola, Fakulteten för teknik och samhälle (TS).
    The Design of Learning2016Inngår i: The Wiley handbook of learning technology / [ed] Nick Rushby, Daniel Surry, John Wiley & Sons, 2016, s. 372-389Kapittel i bok, del av antologi (Annet vitenskapelig)
    Abstract [en]

    This chapter introduces the notion of design for learning sciences that broaden the idea of design in research. Inspired by the different design processes the differences of scientific and design problems and the role of design as a membrane between research and practice, a condensed process can be developed to bridge design-based research (DBR) and interaction design. One of things that differentiates designing for learning and other design activities are the learners. An important way of thinking about learning is learner-centered design (LCD). The chapter then examines design challenges and dilemmas across different research projects and offers insights on how to address them. Next, it looks at different design research and methods that can be applied to research projects. The chapter ends with a discussion on how to proceed in the design of learning sciences.

  • 29.
    Spikol, Daniel
    et al.
    Malmö högskola, Fakulteten för teknik och samhälle (TS). Malmö högskola, Internet of Things and People (IOTAP).
    Avramides, Katerina
    UCL Institute of Education, London, UK.
    Cukurova, Mutlu
    UCL Institute of Education, London, UK.
    Vogel, Bahtijar
    Malmö högskola, Fakulteten för teknik och samhälle (TS). Malmö högskola, Internet of Things and People (IOTAP).
    Luckin, Rose
    UCL Institute of Education, London, UK.
    Ruffaldi, Emanuele
    Scuola Superiore Sant'Anna.
    Mavrikis, Manolis
    UCL Institute of Education, London, UK.
    Exploring the interplay between human and machine annotated multimodal learning analytics in hands-on STEM Activities2016Inngår i: Proceedings of LAK '16 6th International Conference on Learning Analytics and Knowledge, ACM Digital Library, 2016, s. 522-523Konferansepaper (Fagfellevurdert)
    Abstract [en]

    This poster explores how to develop a working framework for STEM education that uses both human annotated and machine data across a purpose-built learning environment. Our dual approach is to develop a robust framework for analysis and investigate how to design a learning analytics system to support hands-on engineering design tasks. Data from the first user tests are presented along with the framework for discussion.

  • 30.
    Spikol, Daniel
    et al.
    Malmö högskola, Fakulteten för teknik och samhälle (TS). Malmö högskola, Internet of Things and People (IOTAP).
    Avramides, Katerina
    Katterfeldt, Eva-Sophie
    Ruffaldi, Emanuele
    Cuartielles, David
    Malmö högskola, Fakulteten för kultur och samhälle (KS), Institutionen för konst, kultur och kommunikation (K3).
    CSCL Opportunities with Digital Fabrication through Learning Analytics2015Inngår i: Exploring the Material Conditions of Learning: Computer Supported Collaborative Learning (CSCL) Conference 2015;2, International Society of the Learning Sciences, 2015, s. 697-698Konferansepaper (Annet vitenskapelig)
    Abstract [en]

    This paper presents a recently started research project that aims to generate, analyze, use, and provide feedback for analytics derived from hands-on, project-based and experiential learning scenarios. The project draws heavy influence from digital fabrication activities and related inquiry-based learning. The intention of the poster is to raise the discussion about how learning analytics from the project can be used to support and enhance learning for tangible technologies, These activities include physical computing and other lab work for small group work in higher education and high school settings.

  • 31.
    Spikol, Daniel
    et al.
    Malmö högskola, Fakulteten för teknik och samhälle (TS). Malmö högskola, Internet of Things and People (IOTAP).
    Ehrenberg, Nils
    Malmö högskola, Fakulteten för teknik och samhälle (TS). Malmö högskola, Internet of Things and People (IOTAP).
    Cuartielles, David
    Zbick, Janosch
    Design Strategies for developing a Visual Platform for Physical Computing with Mobile Tools for Project Documentation and Reflection2015Inngår i: AIED 2015: 17th International Conference on Artificial Intelligence in Education;2, CEUR-WS.org , 2015, s. 57-62Konferansepaper (Fagfellevurdert)
    Abstract [en]

    This poster discusses work on the design of a visual-based programming language for physical computing and mobile tools for the learners to actively document and reflect on their projects. These are parts of a European project that is investigating how to generate, analyze, use and provide feedback from analytics derived from hands-on learning activities. Our aim is to raise a discussion about how learning analytics, intelligence, and the role of learners’ documenting their work can provide richer opportunities for supporting learning and teaching.

    Fulltekst (pdf)
    FULLTEXT01
  • 32.
    Spikol, Daniel
    et al.
    Malmö högskola, Fakulteten för teknik och samhälle (TS), Institutionen för materialvetenskap och tillämpad matematik (MTM).
    Ehrenberg, Nils
    Malmö högskola, Fakulteten för teknik och samhälle (TS), Institutionen för materialvetenskap och tillämpad matematik (MTM).
    Njor Nielsen, Miklas
    Vogel, Bahtijar
    Malmö högskola, Fakulteten för teknik och samhälle (TS), Institutionen för materialvetenskap och tillämpad matematik (MTM).
    Persson, Mats
    Malmö högskola, Fakulteten för teknik och samhälle (TS), Institutionen för materialvetenskap och tillämpad matematik (MTM).
    Kunskapsbaserad teknik för kompetensutveckling i byggsektorn: en forskningsrapport från Sveriges Byggindustrier2017Rapport (Annet vitenskapelig)
    Abstract [sv]

    Syftet med rapporten är att undersöka kunskapsförsörjningen inom byggsektorn på tre nivåer, gymnasium, yrkeshögskola och universitet/högskola samt en industriell partner. Projektet genomfördes med intervjuer, workshops och enkäter styrda av en grundlig litteraturstudie som tittat på aktuell forskning inom utbildning och pedagogik. Resultaten från projektet visar att lärare och elever/studenter har digitala kompetensen, men det finns utrymme för förbättringar av lärandematerial och processer. Dessutom visar resultaten från industrin ett starkt intresse för bättre utnyttja informationsteknik för kompetensutveckling. Betänkandet pekar på att det krävs fortsatt utveckling för en förbättra utbildning inom byggbranschen.

    Fulltekst (pdf)
    FULLTEXT01
  • 33.
    Spikol, Daniel
    et al.
    Malmö högskola, Fakulteten för teknik och samhälle (TS).
    Nouri, Jalal
    Stockholm University, Sweden.
    Pargman, Teresa Cerratto
    Stockholm University, Sweden.
    Milrad, Marcelo
    Linnaeus University, Sweden.
    Emerging Design: Transforming the STEAM Learning Landscape with the Support of Digital Technologies (Preface)2017Inngår i: IxD&A: Interaction Design and Architecture(s), ISSN 1826-9745, E-ISSN 2283-2998, nr 34, s. 5-6Artikkel i tidsskrift (Annet vitenskapelig)
    Fulltekst (pdf)
    FULLTEXT01
  • 34.
    Spikol, Daniel
    et al.
    Malmö högskola, Fakulteten för teknik och samhälle (TS).
    Prieto, Luis P.
    Tallinn University, Tallinn, Estonia.
    Rodriguez-Triana, M. J.
    REACT Group, EPFL, Lausanne, Switzerland.
    Worsley, Marcelo
    Northwestern University, Evanston, IL, United States.
    Ochoa, Xavier
    ESPOL, Guayaquil, Ecuador.
    Cukurova, Mutlu
    UCL Knowledge Lab, London, United Kingdom.
    Vogel, Bahtijar
    Malmö högskola, Fakulteten för teknik och samhälle (TS).
    Ruffaldi, Emanuele
    Scuola Superiore Sant'Anna, Italy.
    Ringtved, Ulla Lunde
    University College Nordjylland.
    Current and Future Multimodal Learning Analytics Data Challenges2017Inngår i: Seventh International Learning Analytics & Knowledge Conference (LAK'17), ACM Digital Library, 2017, s. 518-519Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Multimodal Learning Analytics (MMLA) captures, integrates and analyzes learning traces from different sources in order to obtain a more holistic understanding of the learning process, wherever it happens. MMLA leverages the increasingly widespread availability of diverse sensors, high-frequency data collection technologies and sophisticated machine learning and artificial intelligence techniques. The aim of this workshop is twofold: first, to expose participants to, and develop, different multimodal datasets that reflect how MMLA can bring new insights and opportunities to investigate complex learning processes and environments; second, to collaboratively identify a set of grand challenges for further MMLA research, built upon the foundations of previous workshops on the topic.

  • 35.
    Spikol, Daniel
    et al.
    Malmö högskola, Fakulteten för teknik och samhälle (TS).
    Ruffaldi, Emanuele
    Scuola Superiore Sant'Anna, Italy.
    Cukurova, Mutlu
    University College London, UK.
    Using Multimodal Learning Analytics to Identify Aspects of Collaboration in Project-Based Learning2017Inngår i: Making aDifference: Prioritizing Equity and Access in CSCL, 12th International Conference onComputer Supported Collaborative Learning (CSCL), International Society of the Learning Sciences. , 2017, Vol. 1, s. 263-270Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Collaborative learning activities are a key part of education and are part of many common teaching approaches including problem-based learning, inquiry-based learning, and project-based learning. However, in open-ended collaborative small group work where learners make unique solutions to tasks that involve robotics, electronics, programming, and design artefacts evidence on the effectiveness of using these learning activities are hard to find. The paper argues that multimodal learning analytics (MMLA) can offer novel methods that can generate unique information about what happens when students are engaged in collaborative, project-based learning activities. Through the use of multimodal learning analytics platform, we collected various streams of data, processed and extracted multimodal interactions to answer the following question: which features of MMLA are good predictors of collaborative problem-solving in open-ended tasks in project-based learning? Manual entered scores of CPS were regressed using machine-learning methods. The answer to the question provides potential ways to automatically identify aspects of collaboration in project-based learning.

    Fulltekst (pdf)
    fulltext
  • 36.
    Spikol, Daniel
    et al.
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Disciplinary literacy and inclusive teaching.
    Ruffaldi, Emanuele
    Scuola Superiore Sant'Anna, Italy.
    Dabisias, Giacomo
    Scuola Superiore Sant'Anna, Italy.
    Cukurova, Mutlu
    UCL Knowledge Lab, University College London, United Kingdom.
    Supervised machine learning in multimodal learning analytics for estimating success in project-based learning2018Inngår i: Journal of Computer Assisted Learning, ISSN 0266-4909, E-ISSN 1365-2729, Vol. 34, nr 4, s. 366-377Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Multimodal learning analytics provides researchers new tools and techniques to capture different types of data from complex learning activities in dynamic learning environments. This paper investigates the use of diverse sensors, including computer vision, user-generated content, and data from the learning objects (physical computing components), to record high-fidelity synchronised multimodal recordings of small groups of learners interacting. We processed and extracted different aspects of the students' interactions to answer the following question: Which features of student group work are good predictors of team success in open-ended tasks with physical computing? To answer this question, we have explored different supervised machine learning approaches (traditional and deep learning techniques) to analyse the data coming from multiple sources. The results illustrate that state-of-the-art computational techniques can be used to generate insights into the "black box" of learning in students' project-based activities. The features identified from the analysis show that distance between learners' hands and faces is a strong predictor of students' artefact quality, which can indicate the value of student collaboration. Our research shows that new and promising approaches such as neural networks, and more traditional regression approaches can both be used to classify multimodal learning analytics data, and both have advantages and disadvantages depending on the research questions and contexts being investigated. The work presented here is a significant contribution towards developing techniques to automatically identify the key aspects of students success in project-based learning environments, and to ultimately help teachers provide appropriate and timely support to students in these fundamental aspects.

  • 37.
    Spikol, Daniel
    et al.
    Malmö högskola, Fakulteten för teknik och samhälle (TS). Malmö högskola, Internet of Things and People (IOTAP).
    Ruffaldi, Emanuele
    PERCRO, Scuola Superiore sant'Anna, Italy.
    Landolfi, Lorenzo
    PERCRO, Scuola Superiore sant'Anna, Italy.
    Cukurova, Mutlu
    UCL Knowledge Lab, University College London, United Kingdom.
    Estimation of Success in Collaborative Learning Based on Multimodal Learning Analytics Features2017Inngår i: Proceedings 17th International Conference on Advanced Learning Technologies - ICALT 2017, IEEE, 2017, s. 269-273Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Abstract: Multimodal learning analytics provides researchers new tools and techniques to capture different types of data from complex learning activities in dynamic learning environments. This paper investigates high-fidelity synchronised multimodal recordings of small groups of learners interacting from diverse sensors that include computer vision, user generated content, and data from the learning objects (like physical computing components or laboratory equipment). We processed and extracted different aspects of the students' interactions to answer the following question: which features of student group work are good predictors of team success in open-ended tasks with physical computing? The answer to the question provides ways to automatically identify the students' performance during the learning activities.

  • 38.
    Vujovic, Milica
    et al.
    Univ Pompeu Fabra, ICT Dept, TIDE Res Grp, Barcelona, Spain.
    Hernandez-Leo, Davinia
    TIDE Res Grp, Barcelona, Spain; Univ Pompeu Fabra, ICT Dept, Barcelona, Spain.
    Tassani, Simone
    SIMBiosys Grp, Multiscale & Computat Biomech & Mechanobiol Team, Barcelona, Spain.
    Spikol, Daniel
    Malmö universitet, Internet of Things and People (IOTAP). Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Internet Things Res Ctr, Smart Learning, Madison, WI USA.
    Round or rectangular tables for collaborative problem solving?: A multimodal learning analytics study2020Inngår i: British Journal of Educational Technology, ISSN 0007-1013, E-ISSN 1467-8535, Vol. 51, nr 5, s. 1597-1614Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    The current knowledge of the effects of the physical environment on learners' behaviour in collaborative problem-solving tasks is underexplored. This paper aims to critically examine the potential of multimodal learning analytics, using new data sets, in studying how the shapes of shared tables affect the learners' behaviour when collaborating in terms of patterns of participation and indicators related to physical social interactions. The research presented in this paper investigates this question considering the potential interplay with contextual aspects (level of education) and learning design decisions (group size). Three dependent variables (distance between students, range of movement and level of participation) are tested using quantitative and qualitative analyses of data collected using a motion capture system and video recordings. Results show that the use of round tables (vs rectangular tables) leads to higher levels of on-task participation in the case of elementary school students. For university students, different table shapes seem to have a limited impact on their levels of participation in collaborative problem solving. The analysis shows significant differences regarding the relationship between group size and the distance between students, but there is no substantial evidence that group size affects the level of participation. The findings support previous research highlighting the importance of studying the role of the physical environment as an element of learning design and the potential of multimodal learning analytics in approaching these studies.

  • 39. Zbick, Janosch
    et al.
    Vogel, Bahtijar
    Malmö högskola, Fakulteten för teknik och samhälle (TS). Malmö högskola, Internet of Things and People (IOTAP).
    Spikol, Daniel
    Malmö högskola, Fakulteten för teknik och samhälle (TS). Malmö högskola, Internet of Things and People (IOTAP).
    Jansen, Marc
    Milrad, Marcelo
    Toward an Adaptive and Adaptable Architecture to Support Ubiquitous Learning Activities2015Inngår i: Mobile, Ubiquitous, and Pervasive Learning: Fundaments, Applications, and Trends / [ed] Alejandro Peña-Ayala, Springer, 2015, s. 193-222Kapittel i bok, del av antologi (Annet vitenskapelig)
    Abstract [en]

    The continuous evolution of learning technologies combined with the changes within ubiquitous learning environments in which they operate result in dynamic and complex requirements that are challenging to meet. The fact that these systems evolve over time makes it difficult to adapt to the constant changing requirements. Existing approaches in the field of Technology Enhanced Learning (TEL) are generally not addressing those issues and they fail to adapt to those dynamic situations. In this chapter, we investigate the notion of an adaptive and adaptable architecture as a possible solution to address these challenges. We conduct a literature survey upon the state-of-the-art and state-of-practice in this area. The outcomes of those efforts result in an initial model of a Domain Specific Architecture to tackle the issues of adaptability and adaptiveness. To illustrate these ideas, we provide a number of scenarios where this architecture can be applied or is already applied. Our proposed approach serves as a foundation for addressing future ubiquitous learning applications where new technologies constantly emerge and new requirements evolve.

  • 40.
    Dorthé, Lotti ()
    Malmö universitet, Malmö universitetsbibliotek.
    Olsson, Annsofie ()
    Malmö universitet, Malmö universitetsbibliotek.
    Spikol, Daniel (, )
    Malmö universitet, Fakulteten för teknik och samhälle (TS). Malmö universitet, Internet of Things and People (IOTAP).
    Spalazzese, Romina (, )
    Malmö universitet, Fakulteten för teknik och samhälle (TS). Malmö universitet, Internet of Things and People (IOTAP).
    Linde, Per (, )
    Malmö universitet, Fakulteten för kultur och samhälle (KS), Institutionen för konst, kultur och kommunikation (K3). Malmö universitet, Internet of Things and People (IOTAP).
    Leckner, Sara (, )
    Malmö universitet, Fakulteten för teknik och samhälle (TS). Malmö universitet, Internet of Things and People (IOTAP).
    Russo, Nancy (, )
    Malmö universitet, Fakulteten för teknik och samhälle (TS). Malmö universitet, Internet of Things and People (IOTAP).
    Eriksson, Jeanette (, )
    Malmö universitet, Fakulteten för teknik och samhälle (TS). Malmö universitet, Internet of Things and People (IOTAP).
    Persson, Jan (, )
    Malmö universitet, Fakulteten för teknik och samhälle (TS). Malmö universitet, Internet of Things and People (IOTAP).
    Holmberg, Johan (, )
    Malmö universitet, Fakulteten för teknik och samhälle (TS). Malmö universitet, Internet of Things and People (IOTAP).
    Olsson, Carl Magnus (, )
    Malmö universitet, Fakulteten för teknik och samhälle (TS). Malmö universitet, Internet of Things and People (IOTAP).
    Brandström, Maria ()
    Malmö universitet, Malmö universitetsbibliotek.
    Tosting, Åsa ()
    Malmö universitet, Malmö universitetsbibliotek.
    Egevad, Per ()
    Malmö universitet, Malmö universitetsbibliotek.
    Svensson, Anneli ()
    Malmö universitet, Malmö universitetsbibliotek.
    Topgaard, Richard ()
    Malmö universitet, Gemensamt verksamhetsstöd. Malmö universitet, Internet of Things and People (IOTAP).
    Forskarnas galleri #5: People have the power: IOTAP on exhibit2018Kunstnerisk output (Ogranskad)
    Abstract [sv]

    Överallt samlar sensorer data som analyseras för att räkna ut hur man sparar energi, hur mycket insulin som ska injiceras, var den närmaste hyrbilen finns, hur många människor som fortfarande är kvar inne i en brinnande byggnad... Denna snabba spridning av teknik kallas för Sakernas Internet, eller IoT. Människor har makten, eller har vi verkligen det? Hur mycket värderar vi vår integritet? Vilka internetanslutna gadgets hjälper oss att leva ett hälsosamt och hållbart liv - och vilka prylar kommer bara att öka vår stressnivå? När blir användningen missbruk? Utställningen undersöker hur IoT påverkar människor, samhälle och industri. Forskningsprojekt i utställningen: Emergent Configuration for IoT Systems (ECOS+), Smart energy management and security (SEMS), Fair Data, Walk the ward, Dynamic Intelligent Sensor-Intensive Systems (DISS), PELARS-projektet och Busrunner presenteras i "IOTAP-labbet"

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