PAMPA II Advanced Charting System

Project Management is the primary key to successful software development. In 1995 Caper Jones stated that the failure or cancellation rate of large software systems was over 20% in his article on patterns of large software systems. More than two thirds of the projects fail due to improper management of skills, activities, and personnel. One main reason is that software is not a tangible entity and is hard to visualize and hence to monitor. A manager has to be skilled in different CASE tools and technologies to track and manage a software development process successfully. The volume of results produced by these CASE tools is so huge that a high level manager cannot look into all the details. He has to get a high level picture of the project, to know where the project is heading, and if needed, then look into the finer level details by drilling down to locate and correct problems. The objective of this thesis is to build an Advanced Charting System (ACS), which would act as a companion to PAMPA 2 (Project Attribute Monitoring and Prediction Associate) and help a manager visualize the state of a software project over a standard World Wide Web browser. The PAMPA 2 ACS will be responsible for visualizing and tracking of resources, tasks, schedules and milestones of a software project described in the plan. PAMPA 2 ACS will have the ability to depict the status of the project through a variety of graphs and charts. PAMPA 2 ACS implements a novel charting technique called as DOT Chart to track the processes and activities of a software project. PAMPA 2 ACS provides a multilevel view of the project status. PAMPA 2 ACS will be able to track any arbitrary plan starting from a collapsed / concise view of a whole project. This can be further drilled down to the lowest level of detail. The status can be viewed at the project version level, plan and workbreakdown levels, process, sub process, and activity level. Among all the process models, the DOT charts can be applied effectively to spiral process model where each spiral represents a project version

Cognitive Activity Support Tools: Design of the Visual Interface

This dissertation is broadly concerned with interactive computational tools that support the performance of complex cognitive activities, examples of which are analytical reasoning, decision making, problem solving, sense making, forecasting, and learning. Examples of tools that support such activities are visualization-based tools in the areas of: education, information visualization, personal information management, statistics, and health informatics. Such tools enable access to information and data and, through interaction, enable a human-information discourse. In a more specific sense, this dissertation is concerned with the design of the visual interface of these tools. This dissertation presents a large and comprehensive theoretical framework to support research and design. Issues treated herein include interaction design and patterns of interaction for cognitive and epistemic support; analysis of the essential properties of interactive visual representations and their influences on cognitive and perceptual processes; an analysis of the structural components of interaction and how different operational forms of interaction components affect the performance of cognitive activities; an examination of how the information-processing load should be distributed between humans and tools during the performance of complex cognitive activities; and a categorization of common visualizations according to their structure and function, and a discussion of the cognitive utility of each category. This dissertation also includes a chapter that describes the design of a cognitive activity support tool, as guided by the theoretical contributions that comprise the rest of the dissertation. Those that may find this dissertation useful include researchers and practitioners in the areas of data and information visualization, visual analytics, medical and health informatics, data science, journalism, educational technology, and digital games

Learners' self-assessment and metacognition when using an open learner model with drill down

Metacognition is ‘thinking on thinking’. It is important to educational practices for learners/teachers, and in activities such as formative-assessment and self-directed learning. The ability to perform metacognition is not innate and requires fostering, and self-assessment contributes to this. Literature suggests proven practices for promoting metacognitive opportunities and ongoing enquiry about how technology best supports these. This thesis considers an open learner model (OLM) with a drill-down approach as a method to investigate support for metacognition and self-assessment. Measuring aspects of metacognition without unduly influencing it is challenging. Direct measures (e.g. learners ‘thinking-aloud’) could distort/disrupt/encourage/effect metacognition. The thesis develops methods to evaluate aspects of metacognition without directly affecting it, relevant to future learning-analytics research/OLM design. It proposes a technology specification/implementation for supporting metacognition research and highlights the relevance of using a drill-down approach. Using measures that correspond to post-hoc learner accounts, this thesis identifies a baseline of student activity that is consistent with important regulation of cognition tasks and students’ specific interest in problems. Whilst this does not always influence self-assessment accuracy, students indicating their self-assessment ability can be used as a proxy measure to identify those who will improve. Evidence supports claims that OLMs remain relevant in metacognition research