Digital learning – Page 2

Civil society fishbowl on digital learning

Posted on 06/04/2017by Daniele Di Mitri

Here is the digital #FishBowl: a new perspective for Lifelong Learning #LLLPAC17 pic.twitter.com/FjosIqrDHX

— LLLPlatform (@lllplatform) June 1, 2017

In the beautiful hall of Tallinna Ülikool took place the annual conference of the Lifelong Learning Platform <Education in the Digital World> a flipped e-discussion taking place also on Twitter with the #LLLPAC17 hashtag.

The digital Fishbowl gathered Civil Society representatives of European NGOs active in the Lifelong learning field and was coordinated by the Lifelong Learning Platform.

The Fishbowl touched upon the most burning issues around Digital Technologies in Education like neutrality, handwriting vs keyboard, BYOD and GAFAM.

Digital learning Education Learning Pulse

#LAK17 - it's all about multimodality

Posted on 03/26/2017by Daniele Di Mitri

Originally posted on lilab.eu

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%.

Submission stats #lak17 well done to our phds to be part of it with full papers @m_a_s_c @dimstudi0 pic.twitter.com/Uqb5qJP4ci

— HDrachsler (@HDrachsler) March 15, 2017

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.

Digital learning

Digital Learning and Media Literacy - #LLLWeek16

Posted on 10/16/2016by Daniele Di Mitri

During the Lifelong Learning Week 2016 organised by the Lifelong Learning Platform, the second Digital Learning working group meeting took place at MundoJ, 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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When talking about - digital - technology in education people seem polarised between two opposite standpoints. On one side there are the cyber-optimists who believe that technology is the quick-fix for all the problems education is facing in 21st Century. On the other side, the cyber-frightened who perceive technology as highly dangerous and rather prefer to stick to the traditional practices that are widely tested and recognised.

Digital learning Events

#JTELSS16 summer school in 10 tweets

Posted on 07/05/2016by Daniele Di Mitri

Knowledge exchange among researchers not necessarily should happen in formal scientific conferences but can also include less formal and more fun moments. It is in this spirit that the Joint Technology Enhanced Learning Summer School was ideated, to give a space to PhDs and young researchers for peer learning, to exchange views, practices and receive feedback. And of course also have a break from work and have fun. This is what JTEL was about, and I admit I really liked it as it foster cooperation and knowledge sharing for the researcher working in the technology enhanced learning field.

This year's JTEL took place in Estonia from the 19th to the 24th of June, close to the cold Baltic sea. As usual on dimstudio.org, this post wraps up the highlights of with 10 tweets.

Digital learning Education

Big Data in Education - Learning Outcomes

Posted on 07/05/2016by Daniele Di Mitri

Written for Lilab.eu

BigDatainEducation

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 consists in model or pattern discovering, through which is possible to perform automatic predictions or classifications.

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