Tuesday 18th June 2019: “The Big Picture”
10:00-11:00 Welcome and Introductions
Professor Brian Norton (Principal, TU Dublin City Campus)
Pauline Rooney (Daltai Project Co-Lead) & Kevin O’Rourke (TU Dublin)
11:30-13:00 An introduction to learning analytics for higher education
Niall Sclater (Consultant and Director – Sclater Digital)
Chaired by: Geraldine Gray (Daltai Project co-Lead, TU Dublin)
Learning analytics is being used for a range of purposes in HE, such as adaptive learning, and identifying students who are at risk of attrition. However, many ethical issues have arisen in making predictions about students, and in using their data appropriately. Niall Sclater has researched the issues for Jisc and has coordinated the development of a Code of Practice for Learning Analytics. During this session he will outline the key issues and suggest how they can be addressed by institutions.
14:00-16:00 Artificial intelligence in higher education
Derek Carroll, IBM Watson
Chaired by James Doody (TU Dublin)
Wednesday 19th June 2019: “Big Data, Big Questions”
10:00-11:00 “Show Me Your Data And I’ll Tell You Who You Are” – an interactive presentation on the power of data analytics, machine learning and AI
Brian Mac Namee, University College Dublin
Chaired by Catherine Deegan (TU Dublin)
A huge amount of our daily activities now create a digital footprint – every phone call or SMS; every Facebook like or Tweet; every email; every online purchase; every Wi-Fi network joined, or every work-out session recorded. All of these little digital footprints combine to create a detailed picture of us that can be mined to determine our preferences, opinions, and desires. Whether we call it data science, machine learning, data mining, or big data, corporations and government organisations are using technologies to mine these digital footprints for insights to make predictions about the future behaviours of their customers and citizens. This interactive seminar will guide audiences on an exploration of the current state of the art data-driven prediction technology, its applications and likely consequences (good and bad).
11:30-13:00 Measuring your digital footprint
Kevin O’Rourke, TU Dublin
This workshop aims to build on previous sessions in order to help participants to discover their personal digital footprint. Looking at mobile devices and social media, as well as use of software and hardware within academic institutions, the session is designed to be interactive and to raise as many questions as it answers, both technical and ethical.
14:00-16:00 Building an analytics strategy for your module
Niall Minto (TU Dublin)
Chaired by Phelim Murnion (Galway-Mayo Institute of Technology)
The session will ask what learning and teaching can take from business analytics strategy. Participants will have the opportunity to workshop their own strategy in an interactive session following the talk.
Thursday 20th June 2019: “Feedback Footprints“
10:00-11:00 Using learning analytics to support student engagement with, and learning from, feedback
Naomi Winstone, University of Surrey, UK
Chaired by Jen Harvey, TU Dublin
Assessment feedback is often viewed as a product rather than a process, a model which minimises the role of the student in feedback. Maximising the impact of feedback on students’ learning is facilitated where students possess agency and motivation to implement feedback. In this talk, I will share the learning from the ‘Feedback Footprints’ project which sought to understand and enhance students’ engagement with feedback within the VLE. I will present data representing students’ views of the potential for learning technologies to enhance their engagement with feedback, and their perceptions of learning analytics in this context. I will share the Feedback Engagement and Tracking System, a feedback e-portfolio co-designed by students and staff, and present evaluation data from our implementation of the system. I will argue that student-facing analytics regarding engagement with feedback can transform students from passive receivers to proactive recipients of feedback.
Chaired by Tom Farrelly (Institute of Technology Tralee)
11.30: Using attendance monitoring to improve student retention
Heidi Kelly-Hogan TU Dublin
This session will briefly explore the operation of a system of attendance monitoring for first years in the School of Hospitality Management & Tourism, TU Dublin City Campus. It will address the rationale for adopting attendance monitoring, the operation of it, and overall reflections on using such a system.
11.40: Assessment analytics at DCU
Mark Glynn, Dublin City University
11.50: Using Peerwise
Emma Robinson, TU Dublin
Using PeerWise for peer assessment and learning can be a rewarding minefield. Through looking at a large (150) cohort of first year engineering students interactions with the platform, we will see how the leaderboard numbers can help…and hinder assessment. Click here for an overview of the process. The session itself will be focusing on the numbers!
12.00: Exploring VLE analytics
James Doody, TU Dublin
This exploratory research seeks to identify topics that learners find difficult on a third year Algorithms module. The research analyses learners’ Moodle activity logs which record their access to Moodle resources on specific topics. It then compares access levels against results in Moodle quizzes and the length of time taken to complete them. Based on the results, the lecturer can help learners to master difficult topics by allocating additional class time to them and/or providing additional materials.
12:10-12:20: Q&A/Open Forum
12.20: Learning analytics: policy, ethics and expectations
Geraldine Gray, Pauline Rooney, Catherine Deegan, TU Dublin
This session is informed by the DALTAI project that aims is to increase digital proficiencies amongst staff and students to enable more effective use of learning data to promote student success. The project objectives are firstly to review and identify specific professional development needs with regard to learning analytics skills for higher education staff; and secondly to develop open access professional development resources that scaffold and enable staff and students to interpret learning analytics outputs. This session reports on staff and student focus groups that have explored perceptions on: awareness of the data we collect; ethical and legal concerns regarding collecting and analysing educational data; views on appropriate use of data with regard to providing useful information to all stakeholders in education; the readiness of students and staff to engage with the outputs of learning analytics; and perceptions on the role of professional development training in data and digital literacy.
12.30: Accessible learning analytics
Geraldine Gray, Mohammed Ibrahim and Daniel McSweeney, TU Dublin
Although there is wide agreement on the benefits of Learning Analytics (LA), many institutes still struggle to operationalise their LA Strategy across campus for a number of reasons. Many stakeholders in the learning process generate data, but are unsure of how to derive actionable intelligence from their data. To maximise the benefit from analysis, data needs to be easily converted to well formatted, visualised output that is accessible and meaningful. This session outlines progress made towards an Accessible Learning Analytics environment based on Moodle data readily available to faculty, with the main goal of enabling faculty apply LA, moving LA toward more participatory and inclusive approaches.
12:40: Using big data to inform LEAF (Learning from and Engaging with Assessment and Feedback)
Ziene Mottiar, TU Dublin
This presentation will show how the TU Dublin Teaching Fellowship LEAF project used various big data sources including ISSE and staff and student surveys to inform the project and its recommendations. The data was used, in conjunction with qualitative data from key informant interviews and quality documentation, to identify key issues in relation to assessment and feedback in TU Dublin. Recommendations were then developed at the module, programme and institutional level. Thus the data is likely to affect considerable change in assessment and feedback strategies across the university.
12:50-13:00: Q&A/Open Forum
14:00-16:00 Can we improve student engagement through the use of learning analytics?
Ed Foster, Nottingham Trent University, UK
Chaired by Heidi Kelly-Hogan (TU Dublin)
Friday 21st June 2019: “Using Learning Analytics in Your VLEs”
10:00-11:00 Parallel Workshops
(1) Brightspace Learning Analytics for Beginners
Sophie McGown (Desire2Learn)
This session is an introduction to the analytics behind the scenes in Brightspace and how you can use them as an instructor. Starting from the beginning to look at what analytics you can make use of in Brightspace, and where these are, we will focus on viewing analytics through a pedagogical lens so you feel comfortable using the analytics and applying them in your practice. Going beyond where the data is and what it shows you, we will talk through how you can action the data and make impactful decisions with it to evaluate both how you are using Brightspace, but also how students are interacting with your course.
(2) Moodle Learning Analytics for Beginners
Mark Glynn, Dublin City University
(2) Harnessing Student Engagement Data in Moodle for Advanced Users
Cormac Quigley, Galway Mayo Institute of Technology
This workshop aims to provide participants with the ability to use learning analytics to create a holistic feedback cycle for their students. There are three aspects to this workshop;
- There will be an introductory section, exploring the information stored by Moodle and how it can be accessed. This will be followed by a demonstration of harnessing large data sets and transforming it into meaningful feedback.
- Participants will be provided with a sample data set and sample algorithms. They can modify these to make it suitable for use on their own data from their own VLE.
- If time allows the workshop will explore some of the additional data stored by certain types of Moodle quiz and how this can be used to create a more complete picture of student activity.
Participants will be able to complete each of the steps necessary to create personalised feedback. Acquiring these skills and tools will enable participants to use learning analytics within their own teaching practice and recognise the potential value it represents for their institutions. Where possible, participants will be invited to use their own data allowing them to immediately implement this technique.
11:30-13:00 Parallel Workshops continued……
13:00 Brown Bag Lunch & Close