Inclusive & open learning analytics
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The document discusses inclusive and open learning analytics and challenges in the field. It addresses how learning analytics are currently seen, risks of benchmarks and recommendations, valuing individual experiences both formal and informal, empowering learners and communities, and ensuring learning analytics works for all types of learners to prevent disengagement and support lifelong learning. It concludes by introducing Daniele Di Mitri and his background supporting education technology and rights-based education.
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The final presentation of the master thesis project Visual Learning Pulse: Flow Prediction and Feedback in Self-Regulated Learning, a project collaboration between the Department of Data Science and Knowledge Engineering of the Univeristy of Maastricht and the Welten Institute of the Open University in the Netherlands.
TITLE:
Visual Learning Pulse: Flow Prediction and Feedback in Self-regulated Learning
ABSTRACT:
Visual Learning Pulse is a Master thesis research project developed in cooperation with the Welten Institute, the Research Centre for Learning, Teaching and Technology at the Open University of the Netherlands, and partially nanced by the European project Learning Analytics Community Exchange (LACE). Visual Learning Pulse explores whether physiological and physical data such as heart rate, step count and weather data if correlated with learning activity data can be used to predict learning success in self-regulated learning settings.
To verify this hypothesis an experiment was opportunely designed, consisting of three phases, lasting six weeks and involving nine participants, each of them wearing a Fitbit HR wrist band and having their application usage recorded during their learning and working activities throughout the day. An ad-hoc infrastructure for longitudinal and multi-modal data was designed and implemented. The data from di erent sources were stored using the Experience API (xAPI) data standard in a cloud distributed database called Learning Record Store.
The participants (doctoral students at the Open Universiteit) - were asked to rate their learning experience through an Activity Rating Tool indicating their perceived level of productivity, stress, challenge and abilities. These self-reported performance indicators were used as training labels for the two algorithms employed for prediction of time series data: the Vector Autoregression and Linear Mixed E ect Model.
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Zaal: Rotterdam Hall
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My presentation for the JISC-funded Strategy Cascade: Taking forward change in technology-enhanced education workshop, run by Mark Johnson [University of Bolton] and Keith Smythe [Edinburgh Napier University]. See: http://strategycascade.wordpress.com/
Taking forward change in technology-enhanced education
My presentation for the JISC-funded Strategy Cascade: Taking forward change in technology-enhanced education workshop, run by Mark Johnson [University of Bolton] and Keith Smythe [Edinburgh Napier University]. See: http://strategycascade.wordpress.com/
Supporting autistic students at university - academically, socially and throu...
Speaker: Dr. Marc Fabri, senior lecturer, Leeds Beckett University.
This talk will introduce the challenges and opportunities many young autistic students encounter during their higher education journey. Details and findings will be presented from two EU-funded research projects: Autism&Uni which focused on the transition into university, and IMAGE which is currently ongoing and focuses on the transition out of university, into the workplace. Both projects have a strong digital angle with the design of online toolkits specifically aimed at autistic students.
Through a participatory design approach, students were directly involved in conception and production of these digital tools. Leeds- Beckett University have learnt a lot about the skills and preferences autistic students have, and how technology can help them fulfil their aspirations. Along the way pre-conceptions were thoroughly challenged.
Both projects champion two important principles: Firstly, a strength-based view of autism that focuses on skills and abilities rather than deficits. And secondly a universal design approach to learning that provides choices, depending on an individual's preferences and abilities. This puts the onus on universities to consider how established practices and technologies must change to fully support autistic students in an inclusive way - and any other group of students.
Understanding Networked Scholars: Experiences and practices in online social ...
Slides from an invited talk given to the The 4th International Conference on E-learning and Distance Education located in Riyadh, Kingdom of Saudi Arabia: Online journals, online forums, and social media such as Facebook, Twitter, and YouTube are an integral part of open and digital scholarship, which is often seen as a major breakthrough in radically rethinking the ways in which knowledge is created and shared. In this presentation I situate networked practices in open/digital scholarship and explain what scholars and professors do online, and, why they do the things that the do. I conclude by describing 3 themes pervasive in scholarly networks: identify networks, networks of conflict, and networks of disclosure.
Leading and Learning in 21st Century Schools
This document summarizes Sheryl Nussbaum-Beach's keynote presentation on connected learning. Some of the main points included:
- Connected learning occurs through interactions and conversations between learners. Learning is collaborative and based on networking.
- Connected learning focuses on engaging learners and solving complex problems, rather than just content delivery. It involves skills like sharing, cooperating, collaborating and collective action.
- For schools to be relevant in the 21st century, they need to transform and redefine themselves, not just reform at the edges. This requires changing beliefs, values and the school culture to support innovation.
LLT as a community of practice
LLT - Lifelong Learning Teachers Workshop presentation, Laura Maffei - eTwinning Conference 2010, Seville
Critical questions for OEP
ODLAA launch webinar 15 /16 June 2020
Distance Education 41(2) SI
https://doi.org/10.1080/01587919.2020.1775341
Full Issue:
https://www.tandfonline.com/toc/cdie20/current
Critical Questions for Open Educational Practices
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More from Daniele Di Mitri
SenseTheClassroom Live at EC-TEL 2022
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 these cues poses a challenge for the teachers and hinders them in giving adequate, timely feedback in online educational settings. This can lead to learners not receiving proper guidance and may cause them to be demotivated. This paper proposes a pragmatic approach to detecting student affect in online synchronized learning classrooms. Our approach consists of a method and a privacy-preserving prototype that only collects data that is absolutely necessary to compute action units and is highly scalable by design to run on multiple devices without specialized hardware. We evaluated our prototype using a benchmark for the system performance. Our results confirm the feasibility and the applicability of the proposed approach.
Guest Lecture: Restoring Context in Distance Learning with Artificial Intelli...
Presentation given on the February 1st, 2022 at the "Brown Bag" presentation series organised by the Faculty of NYU Educational Communication and Technology which is part of the Steinhardt School of Culture, Education, and Human Development.
https://www.ectstudent.info/news-events/brown-bag-dr-daniele-di-mitri
Presentation Abstract:
The COVID-19 pandemic forced more than 1.6 billion learners out of school, becoming the most challenging disruption ever endured by the global education systems. In many countries, education institutions decided to move their regular activities online, opting for remote teaching as an emergency solution to continue their education. Meanwhile, physical distancing and learning in isolation heavily challenge learners and hinder their study success. There is a compelling need to make education systems more resilient and less vulnerable to future disruptions in such a critical landscape. In particular, we have to reconsider how digital technologies can support online and hybrid teaching. If digital education technologies such as video conferencing tools and learning management systems have improved to make educational resources more available and education more flexible, the modes of interaction they implement remain essentially unnatural for the learner due to a substantial lack of context. Modern sensor-enabled computer systems allow extending the standard human-computer interfaces and facilitate richer multimodal interaction. Furthermore, advances in AI allow interpreting the data collected from multimodal and multi-sensor devices. These insights can be used to support online teaching and learning in isolation with personalised feedback and adaptation through Multimodal Learning Experiences (MLX). This guest lecture elaborates on existing approaches, architectures, and methodologies. I illustrate use cases that employ multimodal learning analytics applications that can shape the online teaching of the future.
SITE Interactive kenyote 2021
I was invited to deliver a keynote at the SITE Interactive online conference 2021 Keynote on “Restoring Context in Online Teaching with Artificial Intelligence and Multimodal Learning Experiences”. The keynote paper to be published in the proceedings of the conference on the Learning & Technology Library
Abstract: The COVID-19 pandemic forced more than 1.6 billion learners out of school, becoming the most challenging disruption ever endured by the global education systems. In many countries, education institutions decided to move their regular activities online, opting for remote teaching as an emergency solution to continue their education. Meanwhile, physical distancing and learning in isolation are heavily challenging learners and hindering their study success. There is a compelling need to make education systems more resilient and less vulnerable to future disruptions in such a critical landscape. In particular, we have to reconsider how digital technologies can support online and hybrid teaching. In recent years, video conferencing tools and learning management systems have improved to make educational resources more available and education more flexible. However, the modes of interaction they implement remain essentially unnatural for the learner due to a substantial lack of context. Modern sensor-enabled computer systems allow extending the standard human-computer interface for multimodal communication. The advances in Artificial Intelligence allow interpreting the data collected from multimodal and multi-sensor devices. These insights can be used to support online teaching and learning in isolation with personalised feedback and adaptation through Multimodal Learning Experiences (MLX). In this keynote paper, I analyse the benefits and caveats of MLX and Multimodal Learning Analytics (MMLA) for online teaching. I describe three existing MLX systems to illustrate the possible ways of how these technologies can support online teaching.
MOBIUS: Smart Mobility Tracking with Smartphone Sensors
Presentation for the 11th EAI International Conference Sensor System and Software (S-Cube) taking place on the 3rd December 2020.
This paper received the *Best Paper Award* at the S-Cube conference https://www.dimstudio.org/best-paper-award-at-eai-s-cube-conference/
Abstract
In this paper, we introduce MOBIUS, a smartphone-based system for remote tracking of citizens' movements. By collecting smartphone's sensor data such as accelerometer and gyroscope, along with self-report data, the MOBIUS system allows to classify the users' mode of transportation. With the MOBIUS app the users can also activate GPS tracking to visualise their journeys and travelling speed on a map. The MOBIUS app is an example of a tracing app which can provide more insights into how people move around in an urban area. In this paper, we introduce the motivation, the architectural design and development of the MOBIUS app. To further test its validity, we run a user study collecting data from multiple users. The collected data are used to train a deep convolutional neural network architecture which classifies the transportation modes using with a mean accuracy of 89%.
Video of the presentation
https://youtu.be/tBXtxcHFyMs
To appear in the Springer proceedings Science and Technologies for Smart Cities 6th EAI International Summit, SmartCity360, online December 2-4 December 2020, Proceedings
The Multimodal Tutor - Presentation PhD defence
This is the final presentation of my PhD defence which took place on the 4th September 2020 at the Open University of The Netherlands.
Abstract
This doctoral thesis describes the journey of ideation, prototyping and empirical testing of the Multimodal Tutor}, a system designed for providing digital feedback that supports psychomotor skills acquisition using learning and multimodal data capturing. The feedback is given in real-time with a machine-driven assessment of the learner's task execution. The predictions are tailored by supervised machine learning models trained with human-annotated samples. The main contributions of this thesis are a literature survey on multimodal data for learning, a conceptual model (the Multimodal Learning Analytics Model), a technological framework (the Multimodal Pipeline), a data annotation tool (the Visual Inspection Tool) and a case study in Cardiopulmonary Resuscitation training (CPR Tutor). The CPR Tutor generates real-time, adaptive feedback using kinematic and myographic data and neural networks.
Link to youtube presentation
https://youtu.be/b1kDSORpV8A
Link to the PhD Thesis manuscript
https://research.ou.nl/en/publications/the-multimodal-tutor-adaptive-feedback-from-multimodal-experience
Real-time Multimodal Feedback with the CPR Tutor
My presentation at the International Conference in Artificial Intelligence in Education (AIED’2020)
8th July 2020
Di Mitri D., Schneider J., Trebing K., Sopka S., Specht M., Drachsler H. (2020) Real-Time Multimodal Feedback with the CPR Tutor. In: Bittencourt I., Cukurova M., Muldner K., Luckin R., Millán E. (eds) Artificial Intelligence in Education. AIED 2020. Lecture Notes in Computer Science, vol 12163. Springer, Cham
https://link.springer.com/chapter/10.1007/978-3-030-52237-7_12
Multimodal Tutor for CPR presented at AIME'19
Doctoral consortium presentation at the 17th Conference in Artificial Intelligence in Education in Poznań, Poland 2019
Abstract: In this doctoral consortium paper, we introduce the CPR Tutor, an intelligent tutoring system for cardiopulmonary resuscitation (CPR) training based on the analysis of multimodal data. Using a multi-sensor setup, the CPR Tutor tracks the CPR execution of the trainee and generates automatic adaptive feedback to improve the trainee's performance. This research work is part of a PhD project entitled ``Multimodal Tutor: adaptive feedback from multimodal experience capturing'', a project which investigates how to use multimodal and multi-sensor data to generate personalised feedback for training psycho-motor skills at the workplace or during medical simulations. In the CPR Tutor, we use Microsoft Kinect and Myo to track trainee's body position and the ResusciAnne QCPR manikin to get correct CPR performance metrics. We then use a validated approach, the Multimodal Pipeline, for the collection, storage, processing, annotation of multimodal data. This paper describes the preliminary results obtained in the first design of the CPR Tutor.
The Multimodal Learning Analytics Pipeline
Presented the 25th May 2019 at the conference Artificial Intelligence and Adaptive Education (AIAED'19) Beijing, China.
Abstract: We introduce the Multimodal Learning Analytics Pipeline, a generic approach for collecting and exploiting multimodal data to support learning activities across physical and digital spaces. The MMLA Pipeline facilitates researchers in setting up their multimodal experiments, reducing setup and configuration time required for collecting meaningful datasets. Using the MMLA Pipeline, researchers can decide to use a set of custom sensors to track different modalities, including behavioural cues or affective states. Hence, researchers can quickly obtain multimodal sessions consisting of synchronised sensor data and video recordings. They can analyse and annotate the sessions recorded and train machine learning algorithms to classify or predict the patterns investigated.
Workshop: Multimodal Tutor
Workshop slides presented at the Learning Analytics event in Delft, The Netheralnds organised the 8th April 2019
Read Between The Lines: an Annotation Tool for Multimodal Data
This is the presentation of Read Between The Lines, the paper which we published at the Learning Analytics & Knowledge Conference 2019 in Tempe, Arizona (#LAK19).
Link to the paper available in Open Access ACM library https://dl.acm.org/citation.cfm?id=3303776
Abstract:
This paper introduces the Visual Inspection Tool (VIT) which supports researchers in the annotation of multimodal data as well as the processing and exploitation for learning purposes. While most of the existing Multimodal Learning Analytics (MMLA) solutions are tailor-made for specific learning tasks and sensors, the VIT addresses the data annotation for different types of learning tasks that can be captured with a customisable set of sensors in a flexible way. The VIT supports MMLA researchers in 1) triangulating multimodal data with video recordings; 2) segmenting the multimodal data into time-intervals and adding annotations to the time-intervals; 3) downloading the annotated dataset and using it for multimodal data analysis. The VIT is a crucial component that was so far missing in the available tools for MMLA research. By filling this gap we also identified an integrated workflow that characterises current MMLA research. We call this workflow the Multimodal Learning Analytics Pipeline, a toolkit for orchestration, the use and application of various MMLA tools.
The Multimodal Tutor - short pitch presentation at JTELSS 2018 in Durrës, Alb...
Multimodal data from video recordings, sensor data, and human annotations can be collected and processed to generate feedback for learning. This data is analyzed to develop a multimodal tutor that provides digital support for learning across physical spaces. The paper explores how to use multimodal data to create a tutor that gives feedback.
Sensors for Learning workshop
Practical skills training, co-located group interactions, and tasks alternative to the classic desktop-based learning scenario represent still a big set of learning activities taking place in the classroom and at the workplace.
Physical interactions are most of the time offline moments, not captured by the data collection therefore not included in the datasets used for data analysis.
Bringing these moments into account requires extending the data collection from conventional data sources (LMS, MOOC data etc.) to data “beyond user-computer interaction” coming from multiple modalities.
ShareAlike 4.0 International (CC BY-SA 4.0)
Multimodal Machines #JTELSS17 workshop
Here the slides of the workshop "Multimodal Machines" presented at the JTEL Summer School 2017 in Aveiro, Portugal. For more info about it
http://www.prolearn-academy.org/Events/summer-school-2017/index_html
Multimodal Tutor - Adaptive feedback from multimodal experience capturing
This is my 5 minutes presentation at the Doctoral Consortium of the 18th Artificial Intelligence in Education conference held the 30th June 2017 in Wuhan, China
Obessu’s inputs on «opening up education»
1) OBESSU represents over 23 school student organizations from across Europe and welcomes the European Commission's Opening Up Education initiative to modernize education through technology.
2) However, OBESSU sees challenges in implementing the initiative due to education budget cuts across Europe. Successful digital transformation requires large investments, not just cost savings.
3) OBESSU is concerned the initiative focuses too much on adapting education to labor market needs rather than learner needs, and that technology not be used just to increase assessment but to personalize learning.
European politicaldebates presentation
Presentation used to describe the European political debates in the field of Education and Training.
Created by Daniele Di Mitri
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The Multimodal Tutor - short pitch presentation at JTELSS 2018 in Durrës, Alb...
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Inclusive & open learning analytics
- 1. Inclusive & Open Learning Analytics AMSTERDAM – 01/12/2014 DANIELE DI MITRI 1
- 2. How LA are seen right now? 2
- 3. What is the actual bigger risk? 3
- 4. Challenge: from benchmarks to suggestions & recommendations 4
- 5. Valuing the role of individuals Empower learners Foster communities Trust teachers 5
- 6. Valuing experiences Challenge 2: Non-formal LA How to give bigger value to non- formal and informal learning? 6
- 7. LA for everyone Not everyone is a self-regulated learner QuantifiedSelf approach: wrong direction! How to prevent disengagement? How to train for LLL? 7
- 8. Daniele Di Mitri Student activist for many year OBESSU network Vice president of EUCIS-LLL Artificial Intelligence student Right based Education supporter Education Technology enthusiast … d.dimitri@student.maastrichtuniversity.nl 8