Instruments for visualization of self, co, and socially shared regulation of learning using multimodal analytics:a systematic review

Abstract. This thesis presents a systematic literature review in the intersection of multimodal learning analytics, regulation theories of learning, and visual analytics literature of the last decade (2011- 2021). This review is to collect existing research-based instruments designed to visualize Self-Regulation of Learning (SRL), Co-Regulation of learning (CoRL), and Socially Shared Regulation of learning (SSRL) using dashboards and multimodal data. The inclusion and exclusion criteria used in this review addressed two main aims. First, to distil settings, instruments, constructs, and audiences. Second, to identify visualization used for targets (i.e., cognition, motivation, and emotion), phases (i.e., forethought, performance, and reflection), and types of regulation (i.e., SRL, CoRL, and SSRL). By following the Preferred Reporting Items for Systematic Reviews and MetaAnalyses (PRISMA) guidelines, this thesis included 23 peer-reviewed articles out of 383 articles retrieved from 5 different databases searched in April 2021. The main findings from this literature review are (a) the included articles used theoretical grounding of SRL in all articles while CoRL is used only in 3 articles and SSRL only in 2 articles; (b) most articles used both teachers and students as the audience for visual feedback and operated in online learning settings; (c) selected articles focused mainly on visualizing cognition and motivation (17 articles each) as targets of regulation, while emotion as the target was applied only in 6 articles; (d) The performance phase was common to most of the articles and used various visualizations followed by reflection and forethought phases respectively. Simple visualizations, i.e., progress bar chart, line chart, color coding, are used more frequently than bubble chart, stacked column chart, funnel chart, heat maps, and Sankey diagram. Most of the dashboard instruments identified in the review are still improving their designs. Therefore, the results of this review should be put into the context of future studies to be utilized by researchers and teachers in recognizing the missing targets and phases of SRL, CoRL, and SSRL in visualized feedback. Addressing these could also assist them in giving timely feedback on students’ learning strategies to improve their regulatory skills

Enterprise dashboards for waterproofing systems in wood construction

O ato de tomar decisões em gestão pode ser complexo. Todas as indústrias têm os seus próprios atores e campos de intervenção muito específicos. Por esse motivo, as informações visuais podem ser um aliado poderoso quando adaptadas corretamente ao seu ponto de foco. Os dashboards, em particular, reúnem toda a quantidade de dados gerados todos os dias e convertem em informação visual que ajudam o usuário a monitorar o projeto de uma forma mais dinâmica e com muito mais controle dos processos nos quais ele deve tomar decisões. A construção em madeira é muito comum nos países escandinavos e especialmente em edifícios residenciais, nos quais é necessário instalar sistemas de impermeabilização para as chamadas “divisões húmidas”, em constante contato com água ou humidade. Este estudo tem como objetivo desenvolver um modelo visual que possibilite a análise, criação e avaliação de dashboards que darão suporte ao processo de tomada de decisão do project manager, com foco no lado gerencial do produto e não na produção. Isso é composto por vários estágios de desenvolvimento que resultam em um protótipo de alta definição. O usuário desempenhou um papel importante neste trabalho ao longo de pesquisas e observação direta de testes, para avaliar o potencial do sistema a ser usado com frequência. Seis participantes fizeram parte das sessões de teste da primeira versão do protótipo que teve média de 74,6 no System Usability Scale, com o protótipo sendo considerado Bom.The act of decision-making in the management field can be complex. All the several industries have their own actors and very specific fields of intervention. For that reason, visual information can be a powerful ally when correctly adapted to its focused point. Dashboards in particular, gather all the amount of data that’s been generated every day and translate that into visual information that helps the user to monitor the project in a more dynamic and with much more control of the processes it is supposed to make decisions on. Within the construction industry exist many sub-industries that contribute for the thousands of components that comprises a structure, a building, a final product. The wood construction is very common in Scandinavian countries and specially in residential buildings, in which it is necessary to install waterproofing systems for the so called “wet rooms”, in constant contact with moist or water. This study aims to develop a visual model that make possible the analysis, creation and the evaluation of dashboards that will support the decision-making process of the project manager, focusing on the management side of the product rather than the production. This is comprised by several stages of development which results in a high-definition prototype. The user played an important role in this work throughout surveys and direct observation of testing, so it could evaluate the potential of the system to be used frequently. For the focus group, 6 participants were part of the testing sessions for the first version of the prototype. The score average was 74,6 in the System Usability Scale, with the prototype being considered as Good

User-Centered Visual Design of Alarms in Manufacturing Dashboards: Insights on Comprehensibility and Preferences

The digitization of the manufacturing domain results in an enormous amount of available data decision-makers are continuously exposed to. Consequently, critical alarm information must be easily comprehensible and suit decision-makers’ preferences to facilitate timely reactions and thus prevent harm to production processes and employees. However, despite its importance, academia and practice show little consensus regarding alarm design in manufacturing dashboards. Against this background, the purpose of our study is twofold. First, we identified 5 factors for visual alarm design with overall 12 design options in a structured literature review. Second, we investigated the effect these design options have on users’ comprehension and preferences in a conjoint study and a best-worst scaling approach with 98 participants with experience working in manufacturing. Our results show that alarm description and their visual integration are the most important factors for alarm design. In this regard, a cluster analysis reveals more nuanced and more stable preferences in more experienced users. Further, we find that color-coding-based content classification entails best performance in recognizing alarms. We contribute to academia and practice by providing actionable insights that may support improving alarm design in manufacturing

Saliency Prediction in the Data Visualization Design Process

L'abstract è presente nell'allegato / the abstract is in the attachmen

Systematic Variation of Preattentive Attributes to Highlight Relevant Data in Information Visualization

In information visualization (InfoVis), the Visualizers (graph designers and creators) have to consider multiple parameters, such as colors and graphic symbols, to obtain a chart that correctly represents a data set. Along with this, visualizers must adequately select the combination of these range of parameters to drive the observers’ attention to the relevant data. When a visualizer drives the attention to relevant aspects of the information, she is providing a starting point to read the graph; this focus point might help the observer to complete the task faster and more efficiently, minimizing distraction from unimportant information. Contemporary tools for InfoVis help visualizers to a certain extent, but most of them currently do not provide insights or suggestions about the modifications needed to drive data attention. This article presents the preliminary results of an exploratory approach to draw the attention to some specific data subset selected by the graph creator, through a systematic variation of some preattentive attributes (i.e., color, texture and orientation). As a first simple method to validate the feasibility of the approach, a set of charts is created from the same source data, with exhaustive variations on preattentive attributes. All generated charts are then automatically evaluated using a salience map algorithm for data analysis images, to identify their focus attention point. After that, the algorithm chooses the chart that best emphasizes the data subset initially specified by the visualizer. To validate our approach, we have implemented a prototype tool, and preliminary results confirm that it is possible to systematically change the attention area of a chart

The Role of Cognitive Effort in Decision Performance Using Data Representations :;a Cognitive Fit Perspective

A major goal of Decision Support (DSS) and Business Intelligence (BI) systems is to aid decision makers in their decision performance by reducing effort. One critical part of those systems is their data representation component of visually intensive applications such as dashboards and data visualization. The existing research led to a number of theoretical approaches that explain decision performance through data representation\u27s impact on users\u27 cognitive effort, with Cognitive Fit Theory (CFT) being the most influential theoretical lens. However, available CFT-based literature findings are inconclusive and there is a lack of research that actually attempts to measure cognitive effort, the mechanism underlying CFT and CFT-based literature. This research is the first one to directly measure cognitive effort in Cognitive Fit and Business Information Visualization context and the first one to evaluate both self-reported and physiological measures of cognitive effort. The research provides partial support for CFT by confirming that task characteristics and data representation do influence cognitive effort. This influence is pronounced for physiological measures of cognitive effort while it minimal for self-reported measure of cognitive effort. While cognitive effort was found to have an impact on decision time, this research suggests caution is assuming that task-representation fit is influencing decision accuracy. Furthermore, this level of impact varies between self-reported and physiological cognitive effort and is influenced by task complexity. Research provides extensive cognitive fit theory, business information visualization and cognitive effort literature review along with implications of the findings for both research and practic

The Role of Cognitive Effort in Decision Performance Using Data Representations :;a Cognitive Fit Perspective

A major goal of Decision Support (DSS) and Business Intelligence (BI) systems is to aid decision makers in their decision performance by reducing effort. One critical part of those systems is their data representation component of visually intensive applications such as dashboards and data visualization. The existing research led to a number of theoretical approaches that explain decision performance through data representation\u27s impact on users\u27 cognitive effort, with Cognitive Fit Theory (CFT) being the most influential theoretical lens. However, available CFT-based literature findings are inconclusive and there is a lack of research that actually attempts to measure cognitive effort, the mechanism underlying CFT and CFT-based literature. This research is the first one to directly measure cognitive effort in Cognitive Fit and Business Information Visualization context and the first one to evaluate both self-reported and physiological measures of cognitive effort. The research provides partial support for CFT by confirming that task characteristics and data representation do influence cognitive effort. This influence is pronounced for physiological measures of cognitive effort while it minimal for self-reported measure of cognitive effort. While cognitive effort was found to have an impact on decision time, this research suggests caution is assuming that task-representation fit is influencing decision accuracy. Furthermore, this level of impact varies between self-reported and physiological cognitive effort and is influenced by task complexity. Research provides extensive cognitive fit theory, business information visualization and cognitive effort literature review along with implications of the findings for both research and practic

Triangulum City Dashboard: An Interactive Data Analytic Platform for Visualizing Smart City Performance

Cities are becoming smarter by incorporating hardware technology, software systems, and network infrastructure that provide Information Technology (IT) systems with real-time awareness of the real world. What makes a “smart city” functional is the combined use of advanced infrastructure technologies to deliver its core services to the public in a remarkably efficient manner. City dashboards have drawn increasing interest from both city operators and citizens. Dashboards can gather, visualize, analyze, and inform regional performance to support the sustainable development of smart cities. They provide useful tools for evaluating and facilitating urban infrastructure components and services. This work proposes an interactive web-based data visualization and data analytics toolkit supported by big data aggregation tools. The system proposed is a cloud-based prototype that supports visualization and real-time monitoring of city trends while processing and displaying large data sets on a standard web browser. However, it is capable of supporting online analysis processing by answering analytical queries and producing graphics from multiple resources. The aim of this platform is to improve communication between users and urban service providers and to give citizens an overall view of the city’s state. The conceptual framework and architecture of the proposed platform are explored, highlighting design challenges and providing insight into the development of smart cities. Moreover, results and the potential statistical analysis of important city services offered by the system are introduced. Finally, we present some challenges and opportunities identified through the development of the city data platform.publishedVersio

Interactive visualisation of electricity usage in smart environments

Saving electricity is a trending topic due to the electricity challenges that are being faced globally. Smart environments are environments that are equipped with physical objects, which include computers, sensors, actuators, smartphones, and wearable devices interconnected together through the Internet of Things. The Internet of Things provides a network to achieve communication, and computation abilities to provide individuals with smart services anytime, and anywhere. Rapid developments in information technology have increased the number of smart appliances being used, leading to increased electricity usage. Devices and appliances in Smart Environments continue to consume electricity even when not in use, because of the standby function. The problems arise as the electricity consumption of the standby function accumulates to large amounts. Effective communication through visualisation of the electricity consumption in a Smart Environment provides a viable solution to reducing the consumption of electricity. This research aimed to design and developed a visualisation system that successfully communicates electricity consumption to the user using a variety of visualisation techniques. The Design Science Research Methodology was used to address the research questions and was used to iteratively design and develop an energy usage visualisation system. The visualisation system was created for the Smart Lab at the Nelson Mandela University's Department of Computing Sciences. A usability study was conducted to assess the usability and efficacy of the system. The system was found to be usable and effective in communicating power usage to potential customers, since the participants were able to complete the tasks in a short amount of time. The positive results show that visualisation can aid in communicating electricity usage to customers, resulting in a possible reduction in electricity consumption and improved decision-making.Thesis (MSc) -- Faculty of Science, School of Computer Science, Mathematics, Physics and Statistics, 202