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anubhav kumar singh n.
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Geometrix PowerPoint Presentation

Geometrix

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Geometrix

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  1. Anubhav Kumar Singh Geometrix

  2. Geometrix • A GUI based Interface for the Triangle/Showme Software Suite • Replace existing Command Line interface with a smarter Direct manipulation Interface

  3. Motivation • Problems with Old Interface • CLI – Hard to remember commands, counter-intuitive • Direct Manipulation – Easy to grasp and use • Smart Menu System – Context aware menus that allow many different task combinations.

  4. Screenshots (Old UI) Triangle Showme

  5. Screenshots (New UI) Geometrix: Point Set Mode Geometrix: Triangulation Mode (Polygonal)

  6. User Study Conditions • Number of Users: 38 • Within Subjects Study – Minimize Individual skill factor skewing data • Possible – Biases • Experimenter Bias : Tasks might be better for new UI • Systematic Bias: Bash Shell support for Old UI

  7. Analysis & Results • Hypothesis 1 : “The Geometrix Interface is easier to learn than the old Interface” • Null Hypothesis: “The Geometrix Interface is not easier to learn than the old Interface” • Metric 1: Ease of Learning – Subjective

  8. Hypothesis - 1 • Metric 2: Number of Errors for Final Proficiency Task • t-value: 11.34335, p-value: 1.3252E-13 From above and survey response, we can accept Hypothesis-1.

  9. Hypothesis – 2 • Hypothesis 2: The new Geometrix Interface provides a better understanding of Computational Geometry algorithms than the previous system • Metric: Subjective Questions 9,10 in Questionnaire • Based on survey data, we can accept Hypothesis 2.

  10. Observation • Error and Time’s fall unexpectedly for old Command-Line UI on similar/repetitive tasks • Explanation: Similar commands easy to re-use using command-memory of Modern Shells like Bash

  11. Observation • If we remove bias • Matches with expectations now. • % improvement agrees with Hypothesis – 1.

  12. Conclusions • Feedback makes learning easier • Do-not underestimate/discount exterior factors. • Study Conduction Insights • Pilot Study • Recruit with bigger sample size than required • Incentives can greatly improve recruitment and sample quality. • Guidelines • Integration of Output and Processing/Input • Working with users • Informative help can quickly resolve small problems