Home / News / CIC@LAK18

CIC@LAK18

 

The International Conference on Learning Analytics & Knowledge (LAK) is the premier research conference in the field of Learning Analytics. Acceptance rates are 30%, double-blind peer reviewed, with archival proceedings in the ACM Digital Library. After a year’s planning, for the first time, LAK comes to the southern hemisphere, right on our doorstep in Sydney CBD.

CIC’s Director Simon Buckingham Shum is a scientific Program Co-Chair, and all of CIC’s researchers including PhD students are active, chairing workshops, sessions, and presenting research papers and demonstrations. In addition, UTS DVC & Vice President (Education & Students) Shirley Alexander is an invited speaker at the Leadership Summit on the Wednesday.

Here’s where you can find us through the week of March 5-9 …

Monday 5th March (Workshops)

Learning Analytics in Schools

CIC: Simon Buckingham Shum

The Fourth LAK Hackathon: Benefiting Learning through novel data sources, standards and infrastructure

CIC: Kirsty Kitto

Turning the TAP on Writing Analytics

CIC: Antonette Shibani, Sophie Abel, Andrew Gibson and Simon Knight

Participatory Design of Learning Analytics (PD-LAK)

CIC: Carlos Gerardo Prieto Alvarez, Theresa Anderson, Roberto Martinez Maldonado, Kirsty Kitto

Orchestrating Learning Analytics: Learning Analytics Adoption at the Classroom Level

CIC: Roberto Martinez-Maldonado

Personalising feedback at scale: approaches and practicalities

CIC: Roberto Martinez-Maldonado 

Tuesday 6th March (Workshops)

The Fourth LAK Hackathon: Benefiting Learning through novel data sources, standards and infrastructure

CIC: Kirsty Kitto

CrossMMLA: Multimodal Learning Analytics Across Physical and Digital Spaces

CIC: Roberto Martinez-Maldonado,  Vanessa Echeverria 

Wednesday 7th March

Leadership Panel: How can Learning Analytics contribute to a wider notion of student success? 

Room: Grand Lodge • 11:00 – 12:00. Session 1A2

UTS: Shirley Alexander

Driving Data Storytelling from Learning Design

Room: Corinthian • Dashboards, Learning Design & Video. Session 2C • 13:00 – 13:30. Session 2C1

CIC: Vanessa Echeverria, Roberto Martinez-Maldonado & Simon Buckingham Shum

Data science is now impacting the education sector, with a growing number of commercial products and research prototypes providing learning dashboards. From a human-centred computing perspective, the end-user’s interpretation of these visualisations is a critical challenge to design for, with empirical evidence already showing that ‘usable’ visualisations are not necessarily effective from a learning perspective. Since an educator’s interpretation of visualised data is essentially the construction of a narrative about student progress, we draw on the growing body of work on Data Storytelling (DS) as the inspiration for a set of enhancements that could be applied to data visualisations to improve their communicative power. We present a pilot study that explores the effectiveness of these DS elements based on educators’ responses to paper prototypes. The dual purpose is understanding the contribution of each visual element for data storytelling, and the effectiveness of the enhancements when combined.

Vanessa Echeverria, Roberto Martinez-Maldonado, Roger Granda, Katherine Chiluiza, Cristina Conati and Simon Buckingham Shum. 2018. Driving Data Storytelling from Learning Design. In LAK’18: International Conference on Learning Analytics and Knowledge, March 7–9, 2018, Sydney, NSW, Australia. ACM, New York, NY, USA, 10 pages. https://doi.org/10.1145/3170358.3170380 

Leadership Summit

Invitational 1-5pm

UTS: Shirley Alexander & Simon Buckingham Shum

Friday 9th March

Room: Doric • Multimodal Analytics. Session 6B • 11:45 – 12:00. Session 6B5

Physical Learning Analytics: A Multimodal Perspective

CIC: Roberto Martinez-Maldonado & Vanessa Echeverria

The increasing progress in ubiquitous technology makes it easier and cheaper to track students’ physical actions unobtrusively, making it possible to consider such data for supporting research, educator interventions, and provision of feedback to students. In this paper, we reflect on the underexplored, yet important area of learning analytics applied to physical/motor learning tasks and to the physicality aspects of ‘traditional’ intellectual tasks that often occur in physical learning spaces. Based on Distributed Cognition theory, the concept of Internet of Things and multimodal learning analytics, this paper introduces a theoretical perspective for bringing learning analytics into physical spaces. We present three prototypes that serve to illustrate the potential of physical analytics for teaching and learning. These studies illustrate advances in proximity, motion and location analytics in collaborative learning, dance education and healthcare training.

Martinez-Maldonado, V. Echeverria, O. C. Santos, A. D. P. Santos and K. Yacef. 2018. Physical Learning Analytics: A multimodal Perspective. In LAK’18: International Conference on Learning Analytics and Knowledge, March 7–9, 2018, Sydney, NSW, Australia. ACM, New York, NY, USA, 10 pages. https://doi.org/10.1145/3170358.3170379

Grand Hall • User-Centered Design II. Session 7A • 13:30 – 14:00. Session 7A2

Analytics-Enabled Teaching as Design: Reconceptualisation and Call for Research

CIC: Simon Knight

As a human-centred educational practice and field of research, learning analytics must account for key stakeholders in teaching and learning. The focus of this paper is on the role of institutions to support teachers to incorporate learning analytics into their practice by understanding the confluence of internal and external factors that influence what they do. In this paper, we reconceptualise ‘teaching as design’ for ‘analytics-enabled teaching as design’ to shape this discussion to allow for the consideration of external factors, such as professional learning or ethical considerations of student data, as well as personal considerations, such as data literacy and teacher beliefs and identities. In order to address the real-world challenges of progressing teachers’ efficacy and capacity toward analytics- enabled teaching as design, we have placed the teacher – as a cognitive, social, and emotional being – at the center. In so doing, we discuss potential directions towards research for practice in elucidating underpinning factors of teacher inquiry in the process of authentic design.

S.S.J. Alhadad, K. Thompson, S. Knight. M. Lewis, & J.M. Lodge. 2018. Analytics-enabled teaching as design: Reconceptualisation and call for research. In LAK’18: International Conference on Learning Analytics and Knowledge, March 7–9, 2018, Sydney, NSW, Australia. ACM, New York, NY, USA, 7 pages. https://doi.org/10.1145/3170358.3170390

Room: Corinthian • Theory. Session 7C • 13:00 – 13:30. Session 7C1

Embracing Imperfection in Learning Analytics

CIC: Kirsty Kitto, Simon Buckingham Shum & Andrew Gibson

Learning Analytics (LA) sits at the confluence of many contributing disciplines, which brings the risk of hidden assumptions inherited from those fields. Here, we consider a hidden assumption derived from computer science, namely, that improving computational accuracy in classification is always a worthy goal. We demonstrate that this assumption is unlikely to hold in some important educational contexts, and argue that embracing computational “imperfection” can improve outcomes for those scenarios. Specifically, we show that learner-facing approaches aimed at “learning how to learn” require more holistic validation strategies. We consider what information must be provided in order to reasonably evaluate algorithmic tools in LA, to facilitate transparency and realistic performance comparisons.

Kirsty Kitto, Simon Buckingham Shum, and Andrew Gibson. 2018. Embracing Imperfection in Learning Analytics. In LAK’18: International Conference on Learning Analytics and Knowledge, March 7–9, 2018, Sydney, NSW, Australia. ACM, New York, NY, USA, 10 pages. https://doi.org/10.1145/3170358. 3170413

The Pragmatic Maxim as Learning Analytics Research Method

CIC: Andrew Gibson

It is arguable that the chief aim of Learning Analytics is to use analytics for meaningful purposes in learning and teaching contexts, and that research in the field should advance this cause. However the field does not present a single clear understanding of what constitutes quality in Learning Analytics research. In this paper we present the Pragmatic Inquiry for Learning Analytics Research (PILAR) method as one approach to conducting Learning Analytics research. Rather than creating a new method, we reintroduce an old method to a new field, drawing on the Pragmatic Maxim, proposed by Charles Sanders Peirce as a principle for making ideas clear. Our instantiation of the Pragmatic Maxim re- quires the researcher to situate Learning Analytics research within a clearly defined learning context and to consider the analytics in terms of the practical effects on learning. We propose three essential elements and a five step process for addressing them in research. After presenting PILAR we address two potential limitations of the approach, and conclude with some implications for its future use in Learning Analytics research.

Andrew Gibson and Charles Lang. 2018. The Pragmatic Maxim as Learning Analytics Research Method. In LAK’18: International Conference on Learning Analytics and Knowledge, March 7–9, 2018, Sydney, NSW, Australia. ACM, New York, NY, USA, 5 pages. https://doi.org/10.1145/3170358.3170384

Leave a Reply

Your email address will not be published.

Top