Innovating Pedagogy 2015: Open University Innovation Report 4

This series of reports explores new forms of teaching, learning and assessment for an interactive world, to guide teachers and policy makers in productive innovation. This fourth report proposes ten innovations that are already in currency but have not yet had a profound influence on education. To produce it, a group of academics at the Institute of Educational Technology in The Open University collaborated with researchers from the Center for Technology in Learning at SRI International. We proposed a long list of new educational terms, theories, and practices. We then pared these down to ten that have the potential to provoke major shifts in educational practice, particularly in post-school education. Lastly, we drew on published and unpublished writings to compile the ten sketches of new pedagogies that might transform education. These are summarised below in an approximate order of immediacy and timescale to widespread implementation

From Visualization to Visually Enabled Reasoning

Interactive Visualization has been used to study scientific phenomena, analyze data, visualize information, and to explore large amounts of multi-variate data. It enables the human mind to gain novel insights by empowering the human visual system, encompassing the brain and the eyes, to discover properties that were previously unknown. While it is believed that the process of creating interactive visualizations is reasonably well understood, the process of stimulating and enabling human reasoning with the aid of interactive visualization tools is still a highly unexplored field. We hypothesize that visualizations make an impact if they successfully influence a thought process or a decision. Interacting with visualizations is part of this process. We present exemplary cases where visualization was successful in enabling human reasoning, and instances where the interaction with data helped in understanding the data and making a better informed decision. We suggest metrics that help in understanding the evolution of a decision making process. Such a metric would measure the efficiency of the reasoning process, rather than the performance of the visualization system or the user. We claim that the methodology of interactive visualization, which has been studied to a great extent, is now sufficiently mature, and we would like to provide some guidance regarding the evaluation of knowledge gain through visually enabled reasoning. It is our ambition to encourage the reader to take on the next step and move from information visualization to visually enabled reasoning

Information visualization: from petroglyphs to CoDe Graphs

2016 - 2017Data visualization concerns the communication of data through visual representations and techniques. It aims at enhancing perception and support data-driven decision making so enabling insights otherwise hard to achieve. A good visualization of data makes it possible to identify patterns and enables better understanding of phenomena. In other words, data visualization is related to an innate human ability to quickly comprehend, discern and convert patterns into useful and usable information. Humans have used visual graphical representations as early as 35.000 B.C., through cave drawings. Indeed, human ancestors already reasoned in terms of models or schemata: the visual representation of information is an ancient concept, as witnessed by the rock carvings found. Over the centuries, information visualization has evolved to take into account the changing human needs and its use has become more and more conscious. The first data visualization techniques have been developed to observe and represent physical quantities, geography and celestial positions. Successively, the combined use of euclidean geometry and algebra improved accuracy and complexity of information representation, in different fields, such as astronomy, physics and engineering. Finally, in the last century most modern forms of data representations were invented: starting from charts, histograms, and graphs up to high dimensional data, and dynamic and interactive visualizations of temporal data [41]. Nowadays, the huge amount of information enables more precise interpretation of phenomena so fostering the adoption of infographic techniques, in particular, for supporting managerial decision-making in the business area... [edited by author]XVI n.s

Supporting the sensemaking process in visual analytics

Visual analytics is the science of analytical reasoning facilitated by interactive visual interfaces. It involves interactive exploration of data using visualizations and automated data analysis to gain insight, and to ultimately make better decisions. It aims to support the sensemaking process in which information is collected, organized and analyzed to form new knowledge and inform further action. Interactive visual exploration of the data can lead to many discoveries in terms of relations, patterns, outliers and so on. It is difficult for the human working memory to keep track of all findings during a visual analysis. Also, synthesis of many different findings and relations between those findings increase the information overload and thereby hinders the sensemaking process further. The central theme of this dissertation is How to support users in their sensemaking process during interactive exploration of data? To support the sensemaking process in visual analytics, we mainly focus on how to support users to capture, reuse, review, share, and present the key aspects of interest concerning the analysis process and the findings during interactive exploration of data. For this, we have developed generic models and tools that enable users to capture findings with provenance, and construct arguments; and to review, revise and share their visual analysis. First, we present a sensemaking framework for visual analytics that contains three linked views: a data view, a navigation view and a knowledge view for supporting the sense-making process. The data view offers interactive data visualization tools. The navigation view automatically captures the interaction history using a semantically rich action model and provides an overview of the analysis structure. The knowledge view is a basic graphics editor that helps users to record findings with provenance and to organize findings into claims using diagramming techniques. Users can exploit automatically captured interaction history and manually recorded findings to review and revise their visual analysis. Thus, the analysis process can be archived and shared with others for collaborative visual analysis. Secondly, we enable analysts to capture data selections as semantic zones during an analysis, and to reuse these zones on different subsets of data. We present a Select & Slice table that helps analysts to capture, manipulate, and reuse these zones more explicitly during exploratory data analysis. Users can reuse zones, combine zones, and compare and trace items of interest across different semantic zones and data slices. Finally, exploration overviews and searching techniques based on keywords, content similarity, and context helped analysts to develop awareness over the key aspects of the exploration concerning the analysis process and findings. On one hand, they can proactively search analysis processes and findings for reviewing purposes. On the other hand, they can use the system to discover implicit connections between findings and the current line of inquiry, and recommend these related findings during an interactive data exploration. We implemented the models and tools described in this dissertation in Aruvi and HARVEST. Using Aruvi and HARVEST, we studied the implications of these models on a user’s sensemaking process. We adopted the short-term and long-term case studies approach to study support offered by these tools for the sensemaking process. The observations of the case studies were used to evaluate the models

Evaluating digital cultural heritage 'in the wild': The case for reflexivity

Digital heritage interpretation is often untethered from traditional museological techniques and environments. As museums and heritage sites explore the potentials of locative technologies and ever more sophisticated content-triggering mechanisms for use outdoors, the kinds of questions digital heritage researchers are able to explore have complexified. Researchers now find themselves in the realm of the immersive, the experiential, and the performative. Working closely with their research participants, they navigate ambiguous terrain including the often unpredictable affective resonances that are the direct consequences of interaction. This article creates a dialogue between two case studies which, taken together, help to unpack some key methodological and ethical questions emerging from these developments. Firstly, we introduce With New Eyes I See, an itinerant and immersive digital heritage encounter which collapsed boundaries between physical/digital, fact/fiction and past/present. Secondly, we detail Rock Art on Mobile Phones, a set of dialogic web apps that aimed to explore the potential of mobile devices in delivering heritage interpretation in the rural outdoors. Looking outward from these case studies, we reflect on how traditional evaluation frameworks are being stretched and strained given the kinds of questions digital heritage researchers are now exploring. Drawing on vignettes from experience-oriented qualitative studies with participants, we articulate specific common evaluative challenges related to the embodied, multimodal and transmedial nature of the digital heritage experiences under investigation. In doing so, we make the case for reflexivity as a central - and more collaborative - feature of research design within this field going forward; paying attention to, and advocating, the reciprocal relationship between researchers and the heritage experiences we stud

Conformity, deformity and reformity

In any given field of artistic practice, practitioners position themselves—or find themselves positioned—according to interests and allegiances with specific movements, genres, and traditions. Selecting particular frameworks through which to approach the development of new ideas, patterns and expressions, balance is invariably maintained between the desire to contribute towards and connect with a particular set of domain conventions, whilst at the same time developing distinction and recognition as a creative individual. Creativity through the constraints of artistic domain, discipline and style provides a basis for consideration of notions of originality in the context of activity primarily associated with reconfiguration, manipulation and reorganisation of existing elements and ideas. Drawing from postmodern and post-structuralist perspectives in the analysis of modern hybrid art forms and the emergence of virtual creative environments, the transition from traditional artistic practice and notions of craft and creation, to creative spaces in which elements are manipulated, mutated, combined and distorted with often frivolous or subversive intent are considered. This paper presents an educational and musically focused perspective of the relationship between the individual and domain-based creative practice. Drawing primarily from musical and audio-visual examples with particular interest in creative disruption of pre-existing elements, creative strategies of appropriation and recycling are explored in the context of music composition and production. Conclusions focus on the interpretation of creativity as essentially a process of recombination and manipulation and highlight how the relationship between artist and field of practice creates unique creative spaces through which new ideas emerge

Volume 33, Number 4, December 2013 OLAC Newsletter

Digitized December 2013 issue of the OLAC Newsletter

Imaging and visualization at the University of Missouri--Columbia

"The following group of faculty helped prepare this document for MU’s Cyberinfrastructure (CI) Council as part of the 2016 updates to MU’s CI Plan. ... Bimal Balakrishnan, Tommi White, Teresa Lever, David Larsen, Kannappan Palaniappan, Filiz Bunyak, and Chi-Ren ShyuThe document includes a long-term vision for a Show-Me Center for Imaging and Visualization (see page 7). For consistency, with the other parts of the CI Plan, one and three year objectives are provided. This document is designed to help update the CI Plan, and help advance the growing momentum for a imaging and visualization center to support faculty and students from a wide-variety of discipline, and advance a variety of innovative collaborations.Imaging and Visualization and the University of Missouri (MU) -- Return on Proposed Investment -- Imaging and Visualization Needs and Recommendations -- Cross connections with other areas of emphasis in the MU Cyberinfrastructure Plan -- One Year Objectives -- Three to Five Year Objectives -- The Big Picture: the Show-Me Center for Imaging and Visualization. Physical Space ; Where to Start and Why ; Visualization Related ; Infrastructure needed at MU ; Computation, Data Storage and Networking needs ; Management, Staffing, Training and Support ; Needed expertise -- Appendix A: Faculty Perspectives on the Importance of Visualization on Research and Teaching at MU -- Appendix B: Comparable Imaging Facilities -- Appendix C: Visualization Centers at Major Research Universities

Semantic enrichment for enhancing LAM data and supporting digital humanities. Review article

With the rapid development of the digital humanities (DH) field, demands for historical and cultural heritage data have generated deep interest in the data provided by libraries, archives, and museums (LAMs). In order to enhance LAM data’s quality and discoverability while enabling a self-sustaining ecosystem, “semantic enrichment” becomes a strategy increasingly used by LAMs during recent years. This article introduces a number of semantic enrichment methods and efforts that can be applied to LAM data at various levels, aiming to support deeper and wider exploration and use of LAM data in DH research. The real cases, research projects, experiments, and pilot studies shared in this article demonstrate endless potential for LAM data, whether they are structured, semi-structured, or unstructured, regardless of what types of original artifacts carry the data. Following their roadmaps would encourage more effective initiatives and strengthen this effort to maximize LAM data’s discoverability, use- and reuse-ability, and their value in the mainstream of DH and Semantic Web