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Ouhaichi, H., Spikol, D. & Vogel, B. (2023). Rethinking MMLA: Design Considerations for Multimodal Learning Analytics Systems. In: L@S '23: Proceedings of the Tenth ACM Conference on Learning @ Scale: . Paper presented at Conference on Learning @ Scale, Copenhagen, Denmark, July 20-22, 2023 (pp. 354-359). ACM Digital Library
Open this publication in new window or tab >>Rethinking MMLA: Design Considerations for Multimodal Learning Analytics Systems
2023 (English)In: L@S '23: Proceedings of the Tenth ACM Conference on Learning @ Scale, ACM Digital Library, 2023, p. 354-359Conference paper, Published paper (Refereed)
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.

Place, publisher, year, edition, pages
ACM Digital Library, 2023
Keywords
Multimodal Learning Analytics, System Design, Internet of Things, Scalability
National Category
Computer and Information Sciences
Identifiers
urn:nbn:se:mau:diva-63744 (URN)10.1145/3573051.3596186 (DOI)2-s2.0-85167870433 (Scopus ID)9798400700255 (ISBN)
Conference
Conference on Learning @ Scale, Copenhagen, Denmark, July 20-22, 2023
Available from: 2023-11-20 Created: 2023-11-20 Last updated: 2024-02-01Bibliographically approved
Schnaider, K., Schiavetto, S., Meier, F., Wasson, B., Allsopp, B. B. & Spikol, D. (2021). Governmental Response to the COVID-19 Pandemic: A Quantitative Ethnographic Comparison of Public Health Authorities’ Communication in Denmark, Norway, and Sweden. In: Advances in Quantitative Ethnography: Second International Conference, ICQE 2020, Malibu, CA, USA, February 1-3, 2021, Proceedings. Paper presented at International Conference on Quantitative Ethnography, ICQE 2020, Malibu, CA, USA, February 1-3, 2021 (pp. 406-421). Springer
Open this publication in new window or tab >>Governmental Response to the COVID-19 Pandemic: A Quantitative Ethnographic Comparison of Public Health Authorities’ Communication in Denmark, Norway, and Sweden
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2021 (English)In: Advances in Quantitative Ethnography: Second International Conference, ICQE 2020, Malibu, CA, USA, February 1-3, 2021, Proceedings, Springer, 2021, p. 406-421Conference paper, Published paper (Refereed)
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.

Place, publisher, year, edition, pages
Springer, 2021
Series
Communications in Computer and Information Science, ISSN 1865-0929, E-ISSN 1865-0937 ; 1312
Keywords
COVID-19, Crisis communication, Pandemic, Quantitative ethnography, Health, Information management, Public relations, Crisis communications, Denmark, Governmental response, Health systems, Press release, Scandinavian countries, Socio-economic impacts, Presses (machine tools)
National Category
Public Health, Global Health, Social Medicine and Epidemiology
Identifiers
urn:nbn:se:mau:diva-48967 (URN)10.1007/978-3-030-67788-6_28 (DOI)2-s2.0-85101372806 (Scopus ID)978-3-030-67787-9 (ISBN)978-3-030-67788-6 (ISBN)
Conference
International Conference on Quantitative Ethnography, ICQE 2020, Malibu, CA, USA, February 1-3, 2021
Available from: 2021-12-27 Created: 2021-12-27 Last updated: 2021-12-28Bibliographically approved
Ouhaichi, H., Spikol, D. & Vogel, B. (2021). MBOX: Designing a Flexible IoT Multimodal Learning Analytics System. In: Chang, M., Chen, NS., Sampson, DG., Tlili, A. (Ed.), IEEE 21st International Conferenceon Advanced Learning TechnologiesICALT 2021: . Paper presented at IEEE 21st International Conference on Advanced Learning Technologies, 12–15 July 2021 Online (pp. 122-126). IEEE
Open this publication in new window or tab >>MBOX: Designing a Flexible IoT Multimodal Learning Analytics System
2021 (English)In: IEEE 21st International Conferenceon Advanced Learning TechnologiesICALT 2021 / [ed] Chang, M., Chen, NS., Sampson, DG., Tlili, A., IEEE, 2021, p. 122-126Conference paper, Published paper (Refereed)
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.

Place, publisher, year, edition, pages
IEEE, 2021
Series
IEEE International Conference on Advanced Learning Technologies, ISSN 2161-3761
Keywords
Multimodal Learning Analytics, CSCL, IoT, Interaction Design, Human Social Signal Processing
National Category
Computer Sciences
Identifiers
urn:nbn:se:mau:diva-48140 (URN)10.1109/ICALT52272.2021.00044 (DOI)000719352000038 ()2-s2.0-85114887166 (Scopus ID)978-1-6654-4106-3 (ISBN)
Conference
IEEE 21st International Conference on Advanced Learning Technologies, 12–15 July 2021 Online
Available from: 2021-12-15 Created: 2021-12-15 Last updated: 2024-02-05Bibliographically approved
Davidsson, P., Langheinrich, M., Linde, P., Mayer, S., Casado-Mansilla, D., Spikol, D., . . . Russo, N. L. (Eds.). (2020). IoT '20 Companion: 10th International Conference on the Internet of Things Companion. Paper presented at IoT '20 Companion: 10th International Conference on the Internet of Things Companion Malmö Sweden October 6 - 9, 2020. ACM Digital Library
Open this publication in new window or tab >>IoT '20 Companion: 10th International Conference on the Internet of Things Companion
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2020 (English)Conference proceedings (editor) (Refereed)
Place, publisher, year, edition, pages
ACM Digital Library, 2020
National Category
Computer Sciences
Identifiers
urn:nbn:se:mau:diva-56831 (URN)10.1145/3423423 (DOI)978-1-4503-8820-7 (ISBN)
Conference
IoT '20 Companion: 10th International Conference on the Internet of Things Companion Malmö Sweden October 6 - 9, 2020
Available from: 2022-12-20 Created: 2022-12-20 Last updated: 2023-07-06Bibliographically approved
Cukurova, M., Zhou, Q., Spikol, D. & Landolfi, L. (2020). Modelling Collaborative Problem-solving Competence with Transparent Learning Analytics: Is Video Data Enough?. In: LAK20: THE TENTH INTERNATIONAL CONFERENCE ON LEARNING ANALYTICS & KNOWLEDGE. Paper presented at Tenth International Conference on Learning Analytics & Knowledge, March 2020 (pp. 270-275). Association for Computing Machinery (ACM)
Open this publication in new window or tab >>Modelling Collaborative Problem-solving Competence with Transparent Learning Analytics: Is Video Data Enough?
2020 (English)In: LAK20: THE TENTH INTERNATIONAL CONFERENCE ON LEARNING ANALYTICS & KNOWLEDGE, Association for Computing Machinery (ACM), 2020, p. 270-275Conference paper, Published paper (Refereed)
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.

Place, publisher, year, edition, pages
Association for Computing Machinery (ACM), 2020
Keywords
Multimodal learning analytics, physical learning analytics, collaborative problem-solving, decision trees, video analytics
National Category
Computer Sciences
Identifiers
urn:nbn:se:mau:diva-18667 (URN)10.1145/3375462.3375484 (DOI)000558753800036 ()2-s2.0-85082397681 (Scopus ID)
Conference
Tenth International Conference on Learning Analytics & Knowledge, March 2020
Available from: 2020-10-15 Created: 2020-10-15 Last updated: 2024-02-05Bibliographically approved
Vujovic, M., Hernandez-Leo, D., Tassani, S. & Spikol, D. (2020). Round or rectangular tables for collaborative problem solving?: A multimodal learning analytics study. British Journal of Educational Technology, 51(5), 1597-1614
Open this publication in new window or tab >>Round or rectangular tables for collaborative problem solving?: A multimodal learning analytics study
2020 (English)In: British Journal of Educational Technology, ISSN 0007-1013, E-ISSN 1467-8535, Vol. 51, no 5, p. 1597-1614Article in journal (Refereed) Published
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.

Place, publisher, year, edition, pages
John Wiley & Sons, 2020
National Category
Learning
Identifiers
urn:nbn:se:mau:diva-17825 (URN)10.1111/bjet.12988 (DOI)000544059400001 ()
Available from: 2020-07-21 Created: 2020-07-21 Last updated: 2021-10-28Bibliographically approved
Martinez-Maldonado, R., Echeverria, V., Prieto, L. P., Rodriguez-Triana, M. J., Spikol, D., Curukova, M., . . . Worsley, M. (Eds.). (2018). 2nd Crossmmla: Multimodal learning analytics across physical and digital spaces. Paper presented at Second Multimodal Learning Analytics Across (Physical and Digital) Spaces (CrossMMLA 2018), Sydney, Australia, March 06, 2018.. CEUR
Open this publication in new window or tab >>2nd Crossmmla: Multimodal learning analytics across physical and digital spaces
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2018 (English)Conference proceedings (editor) (Refereed)
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.

Place, publisher, year, edition, pages
CEUR, 2018
Series
CEUR Workshop Proceedings, E-ISSN 1613-0073 ; 2163
National Category
Information Systems, Social aspects
Identifiers
urn:nbn:se:mau:diva-45608 (URN)
Conference
Second Multimodal Learning Analytics Across (Physical and Digital) Spaces (CrossMMLA 2018), Sydney, Australia, March 06, 2018.
Available from: 2021-09-03 Created: 2021-09-03 Last updated: 2022-07-22Bibliographically approved
Dorthé, L., Olsson, A., Spikol, D., Spalazzese, R., Linde, P., Leckner, S., . . . Topgaard, R. (2018). Forskarnas galleri #5: People have the power: IOTAP on exhibit.
Open this publication in new window or tab >>Forskarnas galleri #5: People have the power: IOTAP on exhibit
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2018 (English)Artistic output (Unrefereed)
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"

Abstract [en]

All around us sensors collect data, which is analyzed to figure out how to save energy, how much insulin to inject, where the closest rental bike is located, how many people are still inside a building that is on fire… This fast-spreading technology is called the Internet of Things, or IoT for short. People have the power, or do we really? How much do we value our privacy? What internet connected gadgets will help us lead a healthy, sustainable life – and what gadgets will only increase our stress level? When does use become abuse? This exhibition explores how IoT affects people, society and industry. You are welcome to try out IoT through demos and hands-on experiences based on research projects at Malmö University. Research projects in the exhibition: Emergent Configuration for IoT Systems (ECOS+), Smart energy management and security (SEMS), Fair Data, Walk the ward, Dynamic Intelligent Sensor-Intensive Systems (DISS), PELARS project and Busrunner are presented in the "IOTAP-lab"

Keywords
IOTAP, Internet of things, technology, IoT
National Category
Engineering and Technology
Identifiers
urn:nbn:se:mau:diva-8207 (URN)28647 (Local ID)28647 (Archive number)28647 (OAI)
Note

People have the Power is a joint production by Malmö University Library and the research center Internet of Things and People (IOTAP) and have been supported by the Sten K Johnson Foundation.

Available from: 2020-02-28 Created: 2020-02-28 Last updated: 2023-12-28Bibliographically approved
Hwang, G.-J., Spikol, D. & Li, K.-C. (2018). Guest Editorial: Trends and Research Issues of Learning Analytics and Educational Big Data (ed.). Educational Technology & Society, 21(2), 134-136
Open this publication in new window or tab >>Guest Editorial: Trends and Research Issues of Learning Analytics and Educational Big Data
2018 (English)In: Educational Technology & Society, ISSN 1176-3647, E-ISSN 1436-4522, Vol. 21, no 2, p. 134-136Article in journal, Editorial material (Other academic) Published
Place, publisher, year, edition, pages
National Taiwan Normal University, Taiwan, 2018
Keywords
Education & Educational Research
National Category
Social Sciences
Identifiers
urn:nbn:se:mau:diva-16075 (URN)000429647500011 ()2-s2.0-85046096701 (Scopus ID)26684 (Local ID)26684 (Archive number)26684 (OAI)
Available from: 2020-03-30 Created: 2020-03-30 Last updated: 2023-12-22Bibliographically approved
Katterfeldt, E.-S., Cukurova, M., Spikol, D. & Cuartielles, D. (2018). Physical computing with plug-and-play toolkits: Key recommendations for collaborative learning implementations (ed.). International Journal of Child-Computer Interaction, 17, 72-82
Open this publication in new window or tab >>Physical computing with plug-and-play toolkits: Key recommendations for collaborative learning implementations
2018 (English)In: International Journal of Child-Computer Interaction, ISSN 2212-8689, E-ISSN 2212-8697, Vol. 17, p. 72-82Article in journal (Refereed) Published
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.

Place, publisher, year, edition, pages
Elsiever, 2018
Keywords
Collaborative learning, Education, Motivation, Physical computing, ProgrammingToolkit
National Category
Engineering and Technology
Identifiers
urn:nbn:se:mau:diva-2401 (URN)10.1016/j.ijcci.2018.03.002 (DOI)2-s2.0-85045182549 (Scopus ID)27163 (Local ID)27163 (Archive number)27163 (OAI)
Available from: 2020-02-27 Created: 2020-02-27 Last updated: 2024-02-06Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0001-9454-0793

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