Evaluating geovisualization for spatial learning analytics

Robinson, Anthony C.; Anderson, Cary L; Quinn, Sterling D.

doi:10.1080/23729333.2020.1735034

Cited by 4 publications

(3 citation statements)

References 40 publications

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“…Usability metrics were based on the system usability scale (Brooke 1996). Utility metrics followed a format similar to those designed by Pezanowski et al (2018) and Robinson et al (2020) but were adapted to explicitly evaluate the extent to which DataView facilitates better understanding of bicycling behavior at various spatial resolutions and could help city planners or Departments of Transportation make informed decisions on bicycle infrastructure design and implementation.…”

Section: Sum Mative Assessm Ent Methodology and Participantsmentioning

confidence: 99%

User-centered Design and Evaluation of a Geovisualization Application Leveraging Aggregated QS Data

Nelson¹,

MacEachren²

2020

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Individual movement traces recorded by users of activity tracking applications such as Strava provide opportunities that extend beyond delivering personal value or insight to the individual who engages in these “quantified-self” (QS) activities. The large volumes of data generated by these individuals, when aggregated and anonymized, can be used by city planners, Departments of Transportation, advocacy groups, and researchers to help make cities safer and more efficient. This opportunity, however, is constrained by the technical skills and resources available to those tasked with assessing bicycling behavior in urban centers. This paper aims to address the question of how to design cartographic interfaces to serve as mediated platforms for making large amounts of individual bicycling data more accessible, usable, and actionable. Principles of cartographic representation, geovisual analytics techniques, and best practices in user interface/experience design are employed to arrive at an effective visualization tool for a broad urban planning audience. We use scenario-based design methods to encapsulate knowledge of map use practice gleaned from the development process, and conduct a post-implementation two-part user study with seven domain experts to further assess the usability and utility of the interactive mapping tool.

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Section: Sum Mative Assessm Ent Methodology and Participantsmentioning

confidence: 99%

User-centered Design and Evaluation of a Geovisualization Application Leveraging Aggregated QS Data

Nelson¹,

MacEachren²

2020

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“…Moreover, creating an evaluation e-learning model aims to reduce the gap between the conceptual model of the user and the creator's experience. e relationship between user and device is the user's conceptual model [14,17,[19][20][21]. Cognitive science has typically influenced the science of human computer interface to better user experience.…”

Section: Literature Reviewmentioning

confidence: 99%

A Genetic Algorithm-Based Support Vector Machine Approach for Intelligent Usability Assessment of m-Learning Applications

Asghar

Bajwa

Ramzan

et al. 2022

Mobile Information Systems

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In the field of human computer interaction (HCI), the usability assessment of m-learning (mobile-learning) applications is a real challenge. Such assessment typically involves extraction of best features of an application like efficiency, effectiveness, learnability, cognition, memorability, etc., and further ranking of those features for overall assessment of the quality of the mobile application. In the previous literature, it is found that there is neither any theory nor any tool available to measure or assess a user’s perception and assessment of usability features of a m-learning application for the sake of ranking of the graphical user interface of a mobile application in terms of a user’s acceptance and satisfaction. In this paper, a novel approach is presented by performing a mobile application’s quantitative and qualitative analysis. Based on the user’s requirements and perception, a criterion is defined based on a set of important features. Afterwards, for the qualitative analysis, genetic algorithm (GA) is used to score prescribed features for usability assessment of a mobile application. The used approach assigns a score to each usability feature according to the user’s requirement and weight of each feature. GA performs the rank assessment process initially by performing feature selection and scoring the best features of the application. A comparison of assessment analysis of GA and various machine learning models, i.e., K-nearest neigbors, Naïve Bayes, and Random Forests is performed. It was found that GA-based support vector machine (SVM) provides more accuracy in the extraction of best features of a mobile application and further ranking of those features.

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“…Especificamente, os mapas digitais são elaborados para permitir a interação do usuário, e seus objetivos podem incluir tanto a análise visual exploratória em um ambiente interativo, quanto os usos mais tradicionais associados à comunicação, função primeira dos mapas (Robinson et al, 2020). Outro objetivo da geovisualização seria:…”

Section: 1-google Maps E a Popularização Da Cartografia No Século XXIunclassified

E Agora, Para Onde Vai? Proposta De Atividade De Ensino De Cartografia À Distância Para Alunos Do Ensino Médio

Morais¹,

Costa²,

Laudares³

2021

RGEO-UFJF

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Dado o contexto de excepcionalidade suscitado pela pandemia do vírus SARS-CoV-2, professores e alunos se reorganizaram para continuar seus estudos remotamente, o que implicou na reelaboração de metodologias de ensino e aprendizagem. Motivado pela necessidade de inovação das aulas de Geografia, este artigo tem como objetivo apresentar uma sequência didática para o ensino de cartografia a alunos do ensino médio em educação a distância e relatar seus principais resultados, tanto na perspectiva de sua capacidade de provocar aprendizagens significativas, quanto de sua capacidade de gerar engajamento. Desenvolvida a partir do Google Maps, Google Street View e Google Forms, e inspirada nas Corridas de Orientação, a atividade foi proposta para que os alunos pudessem vivenciar as lições aprendidas sobre a navegação em mapas em situações virtuais. Os resultados mostraram que a metodologia foi capaz de melhorar as habilidades de leitura e navegação de mapas dos alunos. Concluiu-se que os recursos de navegação virtual oferecidos pelas ferramentas de geovisualização podem ser apropriados como importantes aliados no ensino remoto de Geografia.

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Evaluating geovisualization for spatial learning analytics

Cited by 4 publications

References 40 publications

User-centered Design and Evaluation of a Geovisualization Application Leveraging Aggregated QS Data

User-centered Design and Evaluation of a Geovisualization Application Leveraging Aggregated QS Data

A Genetic Algorithm-Based Support Vector Machine Approach for Intelligent Usability Assessment of m-Learning Applications

E Agora, Para Onde Vai? Proposta De Atividade De Ensino De Cartografia À Distância Para Alunos Do Ensino Médio

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