Prateek hejmady thesis

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Prateek hejmady thesis

Intergraph Smart 3D Model Manipulations Design Challenge While manipulating a 3D model orientation, the disconnect between view orientation of the model, in relation to the direction that a user tried to manipulate the model was excessively frustrating.

Process Understanding user goals and challenges During contextual inquiries with end users, we were able to see exactly how and where they struggled. View cube static image did not change its orientation based on changes in model orientation.

Also, the availability Prateek hejmady thesis just one view cube for multiple graphic windows led to user frustrations. Based on observations, we then worked on capturing opportunities for improving the navigation experience. To further assist our design process, we sketched two user stories to help us understand end user scenarios better.

Sketching possible solutions Based on data from user research, we sketched six to seven possible solutions. Prototype and test two designs We selected two good ideas to prototype, based on the design challenge. Challenges High-stakes project β€” everyone wanted a say in the design! Prateek hejmady thesis for high fidelity prototypes vs.

Role Lead and brainstorm with 3 member design team Assist in usability evaluation and formulate recommendations Smart 3D QuickPick Design Challenge Plant designers when interacting with denser volumes of a 3D model, struggled with quick selection of desired objects.

Process We aggregated user issues from internal inventory of customer support tickets and stakeholder interviews. Contextual inquiries revealed that, the current implementation of QuickPick automatically popped up and interrupted user workflows.

In addition, from user interviews we found that, numerical representations on QuickPick conveyed no relationship with underlying objects or geometries that composed an object. Challenges Convincing stakeholders with new design ideas Need for quick turnaround with prototype testing Solution Objects present in the z-order of a 3D model were presented as a list with the composing geometries shown as flyouts for each object in the list.

N. Hari Narayanan: Advising

Given the high frequency of QuickPick usage, swift on demand display was facilitated with either a mouse gesture or keyboard shortcut. Results Iterative usability tests guided us on where we should make small tweaks to QuickPick layouts.

Prateek hejmady thesis

Process We sourced information by researching internal inventory of customer support tickets, user analytics, stakeholder interviews. This was followed by contextual inquiries with end users. This research helped us capture user frustrations around information architecture, application accessibility and lack of context sensitive user actions.

Based on product milestones, technical constraints and competitor research Ribbon Interface was used to implement the commanding interface for Smart 3D. Many tools were employed to determine the optimal Ribbon configuration.

Two stage card sorting exercise was conducted.

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Stage one, we discovered the higher level groups with an open sort. Followed by a closed sort to evaluate how users would bucket the panels of the Ribbon. The card sort was done via software so we could send it out to end users and get more data.

Although this information was not the sole driver for the solution.

Prateek hejmady thesis

Each item in the Ribbon had a number of parameters that had to be managed and specified: Patterns were documented with assistance from visual design team to share design knowledge with interaction designers and developers. Results Iterative usability tests guided us on where we should make small tweaks to individual panel layouts.

Project goals and methods In this project we focused on understanding the strength and weakness of property pages as implemented in the current Smart 3D.

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Various aspects of the property pages were identified based on task analysis for testing, leading up to user tasks for tests. Usability tests were conducted in our in house labs with twelve participants. Metrics measured A combination of both qualitative and quantitative data was collected, with quantitative data providing the crux of evidence for usability findings.

Performance metrics measured β€” time to complete tasks, success rates, number of attempts and mouse clicks. Perception metrics β€” ease of use, perceived time to complete tasks, satisfaction and feelings about the task before and after use.

Documenting findings Qualitative data was reported as issues and illustrations arranged by task. Quantitative data was predominantly reported as charts for every category of data, along with Summative Usability Metric SUM method for single-scoring and ranking usability.

The major roadblock to this initiative was lack of direct access to end users. I lead the charge on creating a Contextual Inquiry plan, and successfully convinced the executive management and stakeholders on ROI.

On approval, I led and conducted contextual inquiry at multiple customer sites in North America, Europe and South Asia.Prateek Hejmady.

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A Thesis Submitted to the Graduate Faculty of. Auburn University. in Partial Fulfillment of the. Requirements for the Degree of. Master of Science. for agreeing to be part of my thesis advisory committee and giving for me valuable advice during the course of this research.

Prateek Hejmady. A Thesis Submitted to the Graduate Faculty of. Auburn University. in Partial Fulfillment of the. Requirements for the Degree of. Master of Science. for agreeing to be part of my thesis advisory committee and giving for me valuable advice during the course of this research.

Prateek Hejmady Thesis. A Cognitive Model and Gaze-Based Evaluation of Multiple Prateek Hejmady. A Thesis Submitted to the Graduate Faculty of. Auburn University.

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