Developing Learning Analytics for Epistemic Commitments in a Collaborative Information Seeking Environment

Learning analytics sits at the confluence of learning, information, and computer sciences. Using a distinctive account of learning analytics as a form of assessment, I first argue for its potential in pedagogically motivated learning design, suggesting a particular construct – epistemic cognition in literacy contexts – to probe using learning analytics. I argue for a recasting of epistemic cognition as ‘epistemic commitments’ in collaborative information tasks drawing a novel alignment between information seeking and multiple document processing (MDP) models, with empirical and theoretical grounding given for a focus on collaboration and dialogue in such activities. Thus, epistemic commitments are seen in the ways students seek, select, and integrate claims from multiple sources, and the ways in which their collaborative dialogue is brought to bear in this activity. Accordingly, the empirical element of the thesis develops two pedagogically grounded literacy based tasks: a MDP task, in which pre-selected documents were provided to students; and a collaborative information seeking task (CIS), in which students could search the web. These tasks were deployed at scale (n > 500) and involved writing an evaluative review, followed by a pedagogically supported peer assessment task. Assessment outcomes were analysed in the context of a new epistemic commitments-oriented set of trace data, and psychometric data regarding the participants’ epistemic cognition. Demonstrating the value of the methodological and conceptual approach taken, qualitative analyses indicate clear epistemic activity, and stark differences in behaviour between groups, the complexity of which is challenging to model computationally. Despite this complexity, quantitative analyses indicate that up to 30% of variance in output scores can be modelled using behavioural indicators. The explanatory potential of behaviourally-oriented models of epistemic commitments grounded in tool-interaction and collaborative dialogue is demonstrated. The thesis provides an exemplification of theoretically positioned analytic development, drawing on interdisciplinary literatures in addressing complex learning contexts

Knowledge visualization: From theory to practice

Visualizations have been known as efficient tools that can help users analyze com- plex data. However, understanding the displayed data and finding underlying knowl- edge is still difficult. In this work, a new approach is proposed based on understanding the definition of knowledge. Although there are many definitions used in different ar- eas, this work focuses on representing knowledge as a part of a visualization and showing the benefit of adopting knowledge representation. Specifically, this work be- gins with understanding interaction and reasoning in visual analytics systems, then a new definition of knowledge visualization and its underlying knowledge conversion processes are proposed. The definition of knowledge is differentiated as either explicit or tacit knowledge. Instead of directly representing data, the value of the explicit knowledge associated with the data is determined based on a cost/benefit analysis. In accordance to its importance, the knowledge is displayed to help the user under- stand the complex data through visual analytical reasoning and discovery

Immersive Insights: A Hybrid Analytics System for Collaborative Exploratory Data Analysis

In the past few years, augmented reality (AR) and virtual reality (VR) technologies have experienced terrific improvements in both accessibility and hardware capabilities, encouraging the application of these devices across various domains. While researchers have demonstrated the possible advantages of AR and VR for certain data science tasks, it is still unclear how these technologies would perform in the context of exploratory data analysis (EDA) at large. In particular, we believe it is important to better understand which level of immersion EDA would concretely benefit from, and to quantify the contribution of AR and VR with respect to standard analysis workflows. In this work, we leverage a Dataspace reconfigurable hybrid reality environment to study how data scientists might perform EDA in a co-located, collaborative context. Specifically, we propose the design and implementation of Immersive Insights, a hybrid analytics system combining high-resolution displays, table projections, and augmented reality (AR) visualizations of the data. We conducted a two-part user study with twelve data scientists, in which we evaluated how different levels of data immersion affect the EDA process and compared the performance of Immersive Insights with a state-of-the-art, non-immersive data analysis system.Comment: VRST 201

Proceedings of the 5th Workshop on Awareness and Reflection in Technology Enhanced Learning

Awareness and reflection are viewed differently across the disciplines informing Technology Enhanced Learning (CSCW, psychology, educational sciences, computer science and others). The ARTEL workshop series brings together researchers and professionals from different backgrounds to provide a forum for discussing the multi-faceted area of awareness and reflection. Through the last ARTEL workshops at EC-TEL the addressed topics are converging towards the usage of awareness and reflection in practice, its implementation in modern organisations, its impact on learners and questions of feasibility and sustainability for awareness and reflection in education and work. To reflect the growing maturity of research in ARTEL over the years the workshop particularly invited contributions that dealt with the application of awareness and reflection in practice. This is encapsulated in the workshop motto: 'Awareness and Reflection in Practice: How can awareness and reflection technology become common in work practice and how does it change work practices?

Tools and Methods to Analyze Multimodal Data in Collaborative Design Ideation

Collaborative design ideation is typically characterized by informal acts of sketching, annotation, and discussion. Designers have always used the pencil-and-paper medium for this activity, partly because of the flexibility of the medium, and partly because the ambiguous and ill-defined nature of conceptual design cannot easily be supported by computers. However, recent computational tools for conceptual design have leveraged the availability of hand-held computing devices for creating and sharing ideas. In order to provide computer support for collaborative ideation in a way that augments traditional media rather than imitates it, it is necessary to study the affordances made available by digital media for this process, and to study designers\u27 cognitive and collaborative processes when using such media. In this thesis, we present tools and methods to help make sense of unstructured verbal and sketch data generated during collaborative design, with a view to better understand these collaborative and cognitive processes. This thesis has three main contributions