Cross-Space UMAP’ 18 Tutorial

Designing for Cross-Space Learning Analytics and Personalised Support

Student’s learning happens where the learner is , rather than being constrained to a single physical or digital environment. In fact, students commonly interact at diverse physical spaces and with a variety of educational tools. In this tutorial, participants will explore the challenges of designing data-intensive solutions to support learning and provide feedback to students in blended learning scenarios through collaborative prototyping.  Specifically, this tutorial explores a number of design and prototyping issues such as defining the short-term future vision of ubiquitous and pervasive learning support, dealing with heterogeneous data, collecting multimodal sources of student’s data beyond clickstreams and acknowledging potential ethical issues that may arise. By bringing together researchers, practitioners, designers and makers in an intense but reflective day of prototyping cross-space learning analytics and adaptation experiences, we believe this tutorial will advance the development of a vision of the kind of work that needs to be done to make real progress in this interesting area of learning support.

This tutorial will take place on Sunday, July 9, 2017 at UMAP 2017 in Bratislava, Slovakia!


Planned Activities

The tutorial will be focused on applying fast prototyping techniques to design data-intensive initiatives to provide continued support to learning across digital and physical spaces (see Table below).

The tutorial will be run as a simplified version of a design sprint where participants will engage first in individually generating ideas (both optimistic and pessimistic – Tasks 1 & 2) about analytics and personalisation innovations and the learning scenarios where these can be applied. Then, quick prototyping techniques will be operationalised (including quick sketching, storyboarding and sharing – Tasks 3 & 4). The design activities will be highly collaborative, giving room to discussion, cross-pollination and collectively developing selected ideas. The critical topics of discussion will be elicited from the audience. From experience in previous sessions, some critical themes that have emerged are: multimodal emerging technologies, the challenges imposed by heterogeneous data sources and potential surveillance and ethical issues.

Tutorial Outline

Welcome- Set the Stage

Participants flash presentations

Task 1: Understanding the problem  – Individual Brainwriting (How Might We?) and thematic clustering

Task 2: Understanding the problem – Individual voting

Task 3: Cross-space solutions – (sketching)

Task 4: Cross-space solutions (rapid prototyping and sharing)

Expected Outcomes

As a result of the very hands-on design-based session, we expect that participants will:

1) Gain understanding about how rapid prototyping collaborative techniques from the design field could be used to envisage emerging applications of learner modelling and personalisation research; and

2) Contribute to the development of the vision for this emerging area of interest that considers the physicality of the learning environments into the design loop of analytics and personalisation innovations.

While this tutorial can be considered to be grounded on a consolidated line interest on the topic of learning across spaces, in this case, the focus is on the particular challenges to provide continued support to students by using learning analytics and adaptation techniques.


Roberto Martinez-Maldonado is an Educational Data Science Research Fellow in the Connected Intelligence Centre at University of Technology Sydney, Australia. He has done research grounded on principles of HCI, CSCL, Educational Data Mining and Learning Analytics. He has co-organised five international research workshops at ICLS 2012, CSCL 2013, ITS 2014 and AIED 2015.

Davinia Hernandez-Leo is Associate Professor, and head of her Teaching Support Unit at the Universitat Pompeu Fabra, Spain. Her research lies at the intersection of network and computer applications, HCI, and the learning sciences, with a special focus on CSCL, learning design and learning architectures.

Abelardo Pardo is Associate Professor in the Faculty of Engineering and IT at The University of Sydney, Australia . His areas of research are learning analytics, software tools for collaboration and personalized learning, and systems to improve teaching practice and student experience.