Multimodal Learning Analytics

Nov82022 by Daniele Di MitriNo Comments

New CfP: CROSSMMLA @ LAK 2023 Workshop

Call for Papers: CROSSMMLA @ LAK 2023 Workshop: Leveraging Multimodal Data for Generating Meaningful Feedback To be held face-to-face on March 13, 2023, in Arlington, Texas, United States, in conjunction with the LAK 2023 conference. The CROSSMMLA workshop series has focused on collecting and analysing multimodal data across the physical and virtual spaces for understanding and optimising learning processes. (more…)

Sep142022 by Daniele Di MitriNo Comments

New Pub: Actionable Components of a Model for Augmented Feedback

Feedback, Higher Education, Multimodal Learning Analytics, Workshop

A new workshop paper was presented at the MILeS 2022 workshop written by Daniele Di Mitri, Sebastian Gombert, Onur Karademir entitled: Reflecting on the Actionable Components of a Model for Augmented Feedback. The MILeS 2022 – Multimodal Immersive Learning Systems workshop took place on the 13th of September at EC-TEL 2022 conference taking place in Toulouse, France. The paper will appear in the CEUR proceedings. Abstract. In this paper, we introduce the concept of "Augmented feedback'' as an enhanced version of traditional educational feedback enriched by digital data and artificial intelligence. To provide an operational definition of augmented feedback, we acknowledge previous research in the fields of technology-enhanced learning and learning analytics. We argue why augmented feedback constitutes a promising research direction for the future of learning. We define the…

Sep142022 by Daniele Di MitriNo Comments

New Pub: Privacy-Preserving and Scalable Affect Detection in Online Synchronous Learning

Artificial Intelligence, Conference, Multimodal Learning Analytics, Publication, Research topic

A full research paper entitled "Privacy-Preserving and Scalable Affect Detection in Online Synchronous Learning" written by Felix Böttger, Ufuk Cetinkaya, Daniele Di Mitri, Sebastian Gombert, Krist Shingjergji, Deniz Iren & Roland Klemke was accepted at the Seventeenth European Conference on Technology Enhanced Learning (EC-TEL 2022) Educating for a new future: Making sense of technology-enhanced learning adoption - Toulouse, France, 12-16 September 2022 The paper reports on a research prototype which stems from the cooperation between DIPF and the Open University of the Netherlands. Abstract The recent pandemic has forced most educational institutions to shift to distance learning. Teachers can perceive various non-verbal cues in face-to-face classrooms and thus notice when students are distracted, confused, or tired. However, the students’ non-verbal cues are not observable in online classrooms. The lack of…

Sep112022 by Daniele Di MitriNo Comments

New pub: The Rise of Multimodal Tutors in Education

Artificial Intelligence, Book chapter, Further Education, Higher Education, Multimodal Learning Analytics, Open access, Publication

A book chapter entitled "The Rise of Multimodal Tutors in Education" written by Daniele Di Mitri, Jan Schneider & Hendrik Drachsler was published open access in the "Handbook of Open, Distance and Digital Education" edited by Olaf Zawacki-Richter and Insung Jung. Abstract This chapter describes the insights derived from the design and development of the Multimodal Tutor, a system that uses artificial intelligence to provide digital feedback and support psychomotor skills acquisition. In this chapter, we discuss the insights which we gained from eight studies: (1) an exploratory study combining physiological data and learning performance (Learning Pulse); (2) a literature survey on multimodal data for learning and a conceptual model (the Multimodal Learning Analytics Model); (3) an analysis of the technical challenges of Multimodal Learning Analytics (the Big Five Challenges);…

Jun52022 by Fernando P. Cardenas-HernandezNo Comments

Workshop – Learning Psychomotor Skills with AI & AR/VR considering Technical and Mental Aspects

Artificial Intelligence, Augmented Reality, Event, Multimodal Learning Analytics, Project, Research topic, Summer School, Workshop

From May 21 to 28, the 16th version of the EATEL Summer School on Technology-Enhanced Learning (JTELSS 2022) was held in the city of Halkidiki, Greece, whose purpose is to promote the dissemination of research in the area of Technology Enhanced Learning and encourage international cooperation between researchers, students and people interested in this topic. As members of the MILKI-PSY project, Dr. Daniele Di Mitri, Fernando P. Cardenas Hernandez, Gianluca Romano and Dr. Jan Schneider attended JTELSS 2022. Additionally, Fernando P. Cardenas Hernandez and Gianluca Romano, as active participants in the summer school, presented the workshop entitled "Learning Psychomotor Skills with AI & AR/VR considering Technical and Mental Aspects". This workshop started with a theoretical introduction given by both exponents where the participants were able to identify some of the…

Mar232022 by Prof. Dr. Hendrik DrachslerNo Comments

New Pub: Towards Collaborative Convergence: Quantifying Collaboration Quality with Automated Co-located Collaboration Analytics

Conference, Conference, Event, Higher Education, Learning Design, Multimodal Learning Analytics, Publication

Collaboration is one of the four important 21st-century skills. With the pervasive use of sensors, interest on co-located collaboration (CC) has increased lately. Most related literature used the audio modality to detect indicators of collaboration (such as total speaking time and turn taking). CC takes place in physical spaces where group members share their social (i.e., non-verbal audio indicators like speaking time, gestures) and epistemic space (i.e., verbal audio indicators like the content of the conversation). Past literature has mostly focused on the social space to detect the quality of collaboration. In this study, we focus on both social and epistemic space with an emphasis on the epistemic space to understand different evolving collaboration patterns and collaborative convergence and quantify collaboration quality. We conduct field trials by collecting audio recordings…

Mar112022 by Prof. Dr. Hendrik DrachslerNo Comments

PhD defense: Measuring the Unmeasurable? Towards Automatic Co-located Collaboration Analytics

Artificial Intelligence, Book, Higher Education, Learning Analytics, Multimodal Learning Analytics, PhD defense, Press

Collaboration is one of the most important skills in the 21st century. Education, therefore, focuses on learning to cooperate, both in online and face-to-face settings. Learning Analytics is increasingly being used to analyse collaborations. Can face-to-face collaborations be analysed automatically by means of sensor technology? And what is the quality of the analyses generated by this? Sambit Praharaj developed a technical prototype to achieve automated collaboration analytics. On Friday 11 March 2022 at 1.30 pm Sambit defended his thesis 'Measuring the Unmeasurable? Towards Automatic Co-located Collaboration Analytics' at the Open University in Heerlen. Collaboration analytics using sensor technology Sambit Praharaj investigated the possibilities of automating collaboration analytics in face-to-face settings. He developed a prototype that measures the quality of collaboration. Praharaj also developed a dashboard that visualises the data and…

Nov112021 by Daniele Di MitriNo Comments

Milky-Psy first face-to-face meeting

Artificial Intelligence, General education, Multimodal Learning Analytics, Project meeting

On November 9, 2021, the first face-to-face meeting of the BMBF funded project “Multimodal Immersive Learning with Artificial Intelligence for Psychomotor Skills” (Milki-Psy) consortium took place in the city of Cologne where the DIPF, as an active member, was represented by Dr Daniele Di Mitri, Dr Jan Schneider, Gianluca Romano and Fernando P. Cardenas-Hernandez. The purpose of this meeting was to present the progress of each project partner as well as to propose and discuss possible solutions for the two case studies of this project, which are running case and robot case. (more…)

Oct192021 by George-Petru Ciordas-HertelNo Comments

New Pub: Mobile Sensing with Smart Wearables of the Physical Context of Distance Learning Students to Consider Its Effects on Learning

General education, Journal, Learning Analytics, Lifelong Learning, Multimodal Learning Analytics, Open access, Project, Publication, Research topic, Target group, Technical paper

Research shows that various contextual factors can have an impact on learning. Some of these factors can originate from the physical learning environment (PLE) in this regard. When learning from home, learners have to organize their PLE by themselves. This paper is concerned with identifying, measuring, and collecting factors from the PLE that may affect learning using mobile sensing. More specifically, this paper first investigates which factors from the PLE can affect distance learning. The results identify nine types of factors from the PLE associated with cognitive, physiological, and affective effects on learning. Subsequently, this paper examines which instruments can be used to measure the investigated factors. The results highlight several methods involving smart wearables (SWs) to measure these factors from PLEs successfully. Third, this paper explores how software infrastructure…

Oct122021 by Jan SchneiderNo Comments

New Pub: Analysis of the “D’oh!” moments.

Artificial Intelligence, Conference, Conference, Further Education, Higher Education, Lifelong Learning, Multimodal Learning Analytics, Publication

“Soul and body, I suggest reacting sympathetically upon each other. A change in the state of the soul produces a change in the shape of the body and conversely, a change in the shape of the body produces a change in the state of the soul.” To test this hypothesis proposed by Aristotle, our bachelor student Tetiana Buraha investigated the physiology of students performing task-switching exercises. The physiological data were collected using an Empatica E4 band. The performances of the students were compared against the physiological data using descriptive statistics and machine learning techniques. The analysis of Tetiana enabled the identification of interesting correlations between galvanic skin response and performance, and models to predict performance based on the physiological data. Results of her excellent thesis were published and presented at…