Author Archives: Duygu Bektik

Learning at Scale SIG: An Exclusive Session on Digital Badging

Please join us for the next Learning at Scale Special Interest Group on Tuesday 14th December (10:00-12:00):

Digital badging as a way of accrediting learning at scale

Title: Digital Badges in Context: Looking behind and beyond the digital badge

Speaker: Dr Simon Cross, Senior Lecturer and Associate Director at the Institute of Educational Technology (IET), The Open University

Abstract:

Digital badges possess affordances that position them well as an option for reward and recognition in digital learning and teaching at scale. However, the processes and structures required to issue and value badges may not be as compatible with such scaling. What are the factors that limit and enable their use at scale?  How can we better understand the application of digital badges in the digital and actual contexts in which they are employed? How can we strategically and practically exploit the constructive disruption that digital badges can cause to create a productive dissonance? Continue reading →

Celebrating Six Years of openTEL

openTEL is a strategic research area in Technology Enhanced Learning (TEL) created in 2015 at The Open University (OU). More precisely, this open research group forms part of the Institute of Educational Technology (IET). Professor Eileen Scanlon leads the group alongside the TEL community, with members from across the university who support the development of local and international TEL projects. OpenTEL is also the recipient of the 2017 Open Education Consortium award for Open Research. This award recognises excellence in research on open education and related studies that help advance our understanding and demonstrate effectiveness related to challenges in OER.

You may already know that information by heart if you are a loyal reader of the openTEL blog. But what makes this post different then? Well, today, we want to celebrate the trajectory of openTEL by highlighting the success, innovation and impact the group has had since its origins up till now. So, how has openTEL contributed to the field during these six years?  Continue reading →

Don’t be afraid to question information from the network

The Learning at Scale (L@S) Special Interest Group included presentations from two members of the Knowledge Media Institute at The Open University. Professor Anna De Liddo and Research associate Tracie Farrell shared their exciting work about  Contested Collective Intelligence and  Mis(sing) Information on Tuesday, October 12th.  Continue reading →

Are digital exams here to stay?

On Wednesday, October 6th, the Assessment and Feedback Special Interest Group welcomed José Luis Aznarte, associate professor at the Department of Artificial Intelligence of UNED University. In this session José talked about the experience of switching to online exams amidst the COVID-19 pandemic.

The National Distance Education University is the largest university in Spain that combines online with face-to-face learning through a hybrid methodology offered to more than 200,000 students. Exams at UNED were usually held in their local study centres or exam spots. Results were digitised and distributed to each course team using the software called ‘valija virtual’ (virtual pouch). However, the university had to consider alternatives to adjust the examination process and to guarantee fairness and rigour during the unprecedented circumstances of the coronavirus pandemic.  Continue reading →

First time OU students commented on their own learning analytics data in a research study – how did it go?

These days following a progressive move of Higher Education Institutions towards blended and online environments, accelerated by COVID-19, many universities have access to a greater variety of student data than before. Learning Analytics (LA) provides means for collecting and analysing such evidence. In order to make this analysis useful to the end user, LA data are aggregated in the form of a Learning Analytics Dashboard (LAD). LADs visualise and predict students’ learning progress based on demographics, performance, and digital learning footprints data and have a strong potential to provide useful insights into how teaching and learning may be improved. Continue reading →