All Posts By

Daniele Di Mitri

Guest lecture at Zuyd Hogeschool

By | English, Learning Analytics, Presentations | No Comments

Today was rather special. I was invited to give a lecture at Zuyd Hogeschool in the minor of the Internet of Things (IoT). This minor is coordinated by my fellow colleague Marcel Schimtz (see 5 student teams working on classroom IoT). My lecture today was entitled “Multimodal Learning Analytics: 
an IoT approach for social signals”. I presented the theoretical background of social signals and multimodality in learning and human behaviour. I talked about the five main challenges of the multimodal learning analytics cycle, namely the data collection, data storing, data processing, data annotation and data exploitation.

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Purpose Pyramid for Multimodal Data

By | Conferences, English, Learning Analytics | No Comments

Last week the European Conference on Technology Enhanced Learning (#ECTEL2017) took place in Tallinn University with an overarching theme: “data-driven approaches in education“. This year’s conference focused on the role of data and learning analytics as means for deciphering and improving learning and teaching practices. This year, also in ECTEL17 great focus was given to multimodal data, i.e. the data sources like as sensors and wearables which aim to capture the learning behavior in the offline physical space, rather than in the online virtual environments. For instance, a new workshop was initiated merging two existing ones: the Cross Multimodal Learning Analytics Workshop…

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#LAK17 – it’s all about multimodality

By | English, Learning Analytics | One Comment

The 2017 edition of the Learning Analytics & Knowledge conference beat all the previous records with 344 submissions from 1000 authors and 415 participants, the acceptance rate of the full paper was 34%. Multimodality is the main focus The trending topic of #LAK17 is undoubtedly multimodality. Two keynotes out of three Sanna Jarvela and Sydney D’Mello focus on multimodal data for learning. The topic is also reflected in many studies presented during the parallel presentations. The 3 keynote speakers in #LAK17 seem to be embracing #multimodallity in different ways! #CrossLAK and #MMLA more relevant than ever? — Roberto Martinez (@RobertoResearch) 15…

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Digital Learning and Media Literacy – notes from #LLLWeek16

By | English, Event | 2 Comments

During the Lifelong Learning Week 2016 organised by the Lifelong Learning Platform, the second Digital Learning and Media Literacy working group meeting took place in Brussels, bringing representatives of the European Commission, Digital Europe and a number of other NGOs to discuss and share experience on the topic of Digital Learning. The objective of this discussion was to find a common ground and find possible project ideas. I was asked to make an introduction and overview on the topic: this was my contribution.

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Big Data in Education – Learning Outcomes

By | English | No Comments

The first episode in of Big Data in Education introduced the opportunities arising by programmatically collecting and analysing educational data. The second episode detailed the Dimensions of Education Data, the so-called input space of the Big Data in Education. As anticipated before, this session talks about learning outcomes measurement, or namely how to transform learning performance and assessment indicators to take into account when deploying Big Data techniques in Education. But if we now know where to collect data, why bother about the output at all? The output space is as important as the input as most of the supervised Big Data techniques…

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Big Data in Education – First episode

By | English | No Comments

Like in many other fields like healthcare, retail, telecommunications and natural science, Big Data and Analytics have become a new hype in Education and Learning under the umbrella name of “Learning Analytics”. As technology becomes ubiquitous and more accessible, as most of  the learning time is now spent on Massive Online Open Courses, vast quantities of data are continuously generated and stored in IT systems. These data offer unprecedented opportunities for researchers to analyse and understand several different aspects of learning and education. This data-driven approach is shaking the traditional paradigms of educational research:

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