Command line and version control skills are vital to computer science students during their education and as they enter the software industry. These skills are commonly taught to undergraduate students via traditional lecturing methods and brief hands-on activities. Many students struggle with learning the Git version control system because they are not familiar with the command line, or they do not understand how Git works internally. Recent research highlights the effectiveness of using interactive visualizations to teach computer science concepts. Thus, we developed novel command line and Git exercises with interactive visualizations. These exercises integrate with learning management systems to automate grading. We tested the effectiveness of the exercises in a CS2 course at a large research institution by conducting pre-assessments before and post-assessments after the students completed the exercises. We found that students performed significantly better on both the command line and Git post-assessments than on the pre-assessments. Furthermore, we found that students with less experience with the command line and Git achieved a significantly greater improvement from the pre-assessments to the post-assessments. Additionally, we found that students with different levels of command line and Git experience did not perform differently on the exercises. Therefore, the exercises provide a novel tool for teaching command line and Git concepts to undergraduate computer science students with any level of command line and Git experience. / Master of Science / Command line is a term used to refer to a text-based user interface that allows users to interact with their computers by inputting commands. Git is a version control system typically used to track the stages of development for a computer program. Command line and Git skills are vital to computer science students during their education and as they enter the software industry. These skills are commonly taught to undergraduate students via traditional lecturing methods and brief hands-on activities. Many students struggle with Git because they are not familiar with the command line, or they do not understand how Git works internally. Recent research highlights the effectiveness of using interactive visualizations to teach computer science concepts. Thus, we developed novel command line and Git exercises with interactive visualizations. These exercises integrate with learning management systems to automate grading. We tested the effectiveness of the exercises in a CS2 course at a large research institution by conducting pre-assessments before and post-assessments after the students completed the exercises. We found that students performed significantly better on the post-assessments than on the pre-assessments. Furthermore, we found that students with less experience with the command line and Git achieved a significantly greater improvement from the pre-assessments to the post-assessments. Therefore, the exercises provide a novel tool for teaching command line and Git concepts to undergraduate computer science students with any level of command line and Git experience.

This thesis will introduce the concept of collaboratively using freehand gestures to interact with visualizations. It could be problematic to work with data and visualizations together with others in the traditional desktop setting because of the limited screen size and a single user input device. Therefore this thesis suggests a solution by integrating computer vision and gestures with interactive visualizations. This integration resulted in a prototype where multiple users can interact with the same visualizations simultaneously. The prototype was evaluated and tested on ten potential users. The results from the tests show that using gestures have potential to support collaboration while working with interactive visualizations. It also shows what components are needed in order to enable gestural interaction with visualizations.

The large and ever-increasing amounts of multi-dimensional, multivariate, multi-source, spatio-temporal data represent a major challenge for the future. The need to analyse and make decisions based on these data streams, often in time-critical situations, demands integrated, automatic and sophisticated interactive tools that aid the user to manage, process, visualize and interact with large data spaces. The rise of `Web 2.0', which is undisputedly linked with developments such as blogs, wikis and social networking, and the internet usage explosion in the last decade represent another challenge for adapting these tools to the Internet to reach a broader user community. In this context, the research presented in this thesis introduces an effective web-enabled geovisual analytics framework implemented, applied and verified in Adobe Flash ActionScript and HTML5/JavaScript. It has been developed based on the principles behind Visual Analytics and designed to significantly reduce the time and effort needed to develop customized web-enabled applications for geovisual analytics tasks and to bring the benefits of visual analytics to the public. The framework has been developed based on a component architecture and includes a wide range of visualization techniques enhanced with various interaction techniques and interactive features to support better data exploration and analysis. The importance of multiple coordinated and linked views is emphasized and a number of effective techniques for linking views are introduced. Research has so far focused more on tools that explore and present data while tools that support capturing and sharing gained insight have not received the same attention. Therefore, this is one of the focuses of the research presented in this thesis. A snapshot technique is introduced, which supports capturing discoveries made during the exploratory data analysis process and can be used for sharing gained knowledge. The thesis also presents a number of applications developed to verify the usability and the overall performance of the framework for the visualization, exploration and analysis of data in different domains. Four application scenarios are presented introducing (1) the synergies among information visualization methods, geovisualization methods and volume data visualization methods for the exploration and correlation of spatio-temporal ocean data, (2) effective techniques for the visualization, exploration and analysis of self-organizing network data, (3) effective flow visualization techniques applied to the analysis of time-varying spatial interaction data such as migration data, commuting data and trade flow data, and (4) effective techniques for the visualization, exploration and analysis of flood data.

Project Meme Evolution Programme (Project MEP) is a research program directed by Raazesh Sainudiin, Uppsala University, Sweden, that collects and analyzes datasets from Twitter. Twitter can be used to understand how ideas spread in social media. This project aims to produce interactive visualizations for datasets collected in Project MEP. Such interactive visualizations will facilitate exploratory data analysis in Project MEP. Several technologies had to be learned to produce the visualizations, most notably JavaScript, D3, and Scala. Three interactive visualizations were produced; one that allows for exploration of a Twitter user timeline and two that allows for exploration and understanding of a Twitter retweet network. The interactive visualizations are accessible as Scala functions and in a website developed in this project and uploaded to GitHub. The interactive visulizations contain some known bugs but they still allow for useful exploratory data analysis of Project MEP datasets and the project goal is therefore considered met. / Project Meme Evolution Programme