Designing Augmented Reality Applications for Personal Health Decision-Making

Augmented reality (AR) is a technology that can assist with our daily decision-making tasks by presenting information that extends the physical world. However, little work has been done to understand the effect of the layout of AR interfaces on decision-making. In this paper, we present PHARA, an AR-based personal assistant that supports decision-making for healthier food products. In a controlled user study (n=28), we explored the use of four different AR layouts on two different devices: Microsoft HoloLens and smartphone. Using subjective and objective means, we measured their effects on decision-making tasks that occur when people hold food products in their hands. We found that pie and grid layouts perform better on the smartphone, whereas a stacked layout works better on the reduced field-of-view of the Microsoft HoloLens, potentially at the cost of some affordances such as time spent and actions

Tracking Data in Open Learning Environments

The collection and management of learning traces, metadata about actions that students perform while they learn, is a core topic in the domain of Learning Analytics. In this paper, we present a simple architecture for collecting and managing learning traces. We describe requirements, different components of the architecture, and our experiences with the successful deployment of the architecture in two different case studies: a blended learning university course and an enquiry based learning secondary school course. The architecture relies on trackers, collecting agents that fetch data from external services, for flexibility and configurability. In addition, we discuss how our architecture meets the requirements of different learning environments, critical reflections and remarks on future work

Contextual Inquiry Reflection Tools

Contextual Inquiry Reflection Tools, Deliverable 5.3, weSPOT ProjectweSPOT Project IST (FP7/2007-2013) under grant agreement N° 318499

Designing and Evaluating Student-facing Learning Dashboards: Lessons Learnt

Through the rise of on-line education, an abundance of learner data is generated and gathered. While Educational Data Mining provides insights algorithmically to better understand students, Learning Analytics (LA) attempts to leverage these traces to empower learners by increasing motivation, autonomy, effectiveness, and efficiency. One method to achieve this empowerment is that of Learning Dashboards, a personal informatics or Quantified Self approach, helping learners self-reflect and gain self-knowledge through the visualisation of these traces. Learning Dashboards are a welcome and much needed topic that shifts the research focus towards, and actively involves, teachers, advisers, and students, providing them with insights into behaviour of learners at both individual (a student) and group level (peer activities in courses, study programs, institutions). Investigating the potential impact of visualising these traces is important, but such research demands long-term deployments in realistic settings. Such an endeavour is challenging, as it requires commitment from institutions, teachers, and learners of (usually) unproven technology during sensitive, life-impacting situations, as well as running the risk of discovering problems with the dashboard designs after commitment, which raises ethical issues. Our research attempts to provide some leverage for such deployments by i) providing evidence of the perceived benefits and ii) providing design guidelines required to create useful and meaningful dashboards. To explore the required design choices, we take an iterative, design-based research approach, in close collaboration with experts, teachers, and students. The work starts by tackling following research questions: "How should we visualise learner data to support students to explore the path from effort to outcomes? (RQ1)", and "How can we promote students, inside and outside the classroom, to actively explore this effort to outcomes path? (RQ2)." To explore these questions, we have designed, deployed, and evaluated five learning dashboards in blended learning environments. This research resulted in several guidelines on how to visualise the LA data and how to promote exploration of students' efforts to outcomes. These lessons cover topics such as abstraction to deal with the abundance of data, facilitating easy access to learner artefacts and feedback, and integrating Learning Dashboards into the work-flow for better user acceptance. From our research, we noticed potential in the design of collaborative Learning Dashboards, and further explored possible scenarios that could benefit from this approach in two case studies: live dashboards to orchestrate feedback activities in the classroom, and support of the dialogue during advising sessions with students. The first case study focuses on the following questions: "What are the design challenges for ambient Learning Dashboards to promote balanced group participation in classrooms, and how can they be met? (RQ3)", and "Are ambient Learning Dashboards effective means for creating balanced group participation in classroom settings? (RQ4)". Exploring these questions resulted in a Learning Dashboard that raises activity awareness, activates students, and assists with classroom orchestration. We learn that it is important to visualise the data in a neutral way, toning down over-participators to leave room for under-participators. The second case study explores how a collaborative Learning Dashboard can assist both student and study adviser during advising session, and addresses the following research questions: "What are the design challenges for creating a Learning Dashboard to support study advice sessions, and how can they be met? (RQ5)", and "How does such a Learning Dashboard contribute to the role of the adviser, student, and dialogue? (RQ6)". Our design and evaluation process reveal that a passive, supportive dashboard can assist in guiding the student-study adviser conversation, provide further insights and new perspectives, and help convince students of taking specific actions.nrpages: 131status: publishe

Exploring inquiry-based learning analytics through interactive surfaces

Learning Analytics is about collecting traces that learners leave behind and using those traces to improve learning. Dashboard applications can visualize these traces to present learners and teachers with useful information. The work in this paper is based on traces from an inquiry-based learning (IBL) environment, where learners create hypotheses, discuss findings and collect data in the field using mobile devices. We present a work-in-progress that enables teachers and learners to gather around an interactive tabletop to explore the abundance of learning traces an IBL environment generates, and help collaboratively make sense of them, so as to facilitate insights.status: publishe

Learning dashboards

This article explores how information visualization techniques can be applied to learning analytics data to help teachers and students deal with the abundance of learner traces. We also investigate how the affordances of large interactive surfaces can facilitate a collaborative sense-making environment for multiple students and teachers to explore these learner traces together.status: publishe

Improving awareness and reflection through collaborative, interactive visualizations of badges

This paper introduces novel ways of improving awareness and reflection through visualizations of badges as an abstraction of learning analytics data. We report initial findings with both a personal dashboard approach, Navi Badgeboard, that provides details on student and class progress, and a collaborative, interactive tabletop visualization, Navi Surface, to promote group reflection. We evaluate both approaches to find improvements among students regarding awareness and reflection on course activities. Our results indicate that Navi Badgeboard helps with awareness of personal activity while Navi Surface improves collaboration resulting in better reflection.status: publishe

Improving teacher awareness through activity, badge and content visualizations

This paper introduces LARAe (Learning Analytics Reflection & Awareness environment), a teacher-oriented dashboard that visualizes learning traces from students, badges and course content. We also present an evaluation of the dashboard in a course on Human-Computer Interaction. The LARAe teacher dashboard provides a detailed overview of group and individual activities, achievements and course outcomes. To help visualize the abundance of traces, badges are used to abstract essential aspects of the course such as course goals and social activity. This paper reports our work on LARAe, presents the course in which we evaluated our approach with students and teachers, and analyses our first results that indicate that such an environment can help with teacher awareness.status: publishe

Faceted search on coordinated tablets and tabletop: a comparison

Large interactive displays and surfaces are useful modalities for visualizing big multi-dimensional data sets. They can offer simultaneous views on different facets of the data which lead to an efficient and effective environment for data exploration and analysis. While every data analyst and enthusiast can benefit from these advantages, large interactive systems are not yet available to everyone. Meanwhile, tablets have become ubiquitous and relatively cheap. Combining multiple tablets to replicate a single, large display has therefore become an affordable option. This paper compares the difference in search performance and user perception of a faceted search system for Cultural Heritage data on a single large interactive tabletop with a system composed of multiple coordinated tablet devices. We conclude that, while users generally prefer the tabletop system, there is no negative impact on search performance using tablets. This makes coordinated tablets a viable and portable solution in the absence of interactive tabletops.status: publishe