Rhizome is an information-centric model that uses different interaction methods than traditional desktop systems. I built Rhizome with the specific use case of sharing a photo to observe people using the Rhizome operating system (OS) shell and modern OS shells. The purpose of this is to measure the cognitive load...
This project report presents an implementation of a GenderMag Recorder's Assistant from a semi-working state to a fully working Chrome web store application. In addition, this project report also discusses the persona customization option and limitations and how the persona tool eases the process of persona customization. For results, we...
Most software systems today do not support cognitive diversity. Further, because of differences in problem-solving styles that cluster by gender, software that poorly supports cognitive diversity can also embed gender biases. To help software professionals fix gender bias “bugs” related to people’s problem-solving styles for information processing and learning of...
To users, mobile touchscreen devices have appealing characteristics; among these characteristics is intuitiveness, which leads to mobile devices being used almost everywhere by almost everyone to accomplish almost anything. This statement, to some degree, holds for children too. Despite touchscreen devices’ intuitiveness and popularity, we don’t know much about how...
3D volume segmentation is a fundamental process in many scientific and medical applications. Producing accurate segmentations, in an efficient way, is challenging, in part due to low imaging data quality (e.g., noise and low image resolution), and ambiguity in the data that can only be resolved with higher-level knowledge of...
This research proposes a Human Fallibility Identification and Remediation Methodology (HFIRM) that supports the systematic identification and remediation of potential human errors. The objective of this research was to develop and test a prototype framework that supports the practical application of human factors knowledge to the analysis and design of...
"Explaining Reinforcement Learning to Mere Mortals: An Empirical Study
This is the dataset for replicating our study, which was accepted to IJCAI '19.
We present a user study to investigate the impact of explanations on non-experts’ understanding of reinforcement learning (RL) agents. We investigate both a common RL visualization, saliency...
Although machine learning is becoming commonly used in today's software, there has been little research into how end users might interact with machine learning systems, beyond communicating simple "right/wrong" judgments. If the users themselves could somehow work hand-in-hand with machine learning systems, the accuracy of learning systems could be improved...
This paper focuses on mining the strategies of problem solving software users by observing their actions. Our application domain is an HCI study aimed at discovering general strategies employed by software users and understanding how such strategies relate to gender and success. We cast this problem as a sequential pattern...
Windows Exploratory Testing (WET) is examined to determine whether testers working in pairs produce higher quality results, are more productive, or exhibit greater confidence and job satisfaction than testers working alone. WET is a form of application testing where a tester (or testers) explores an unknown application to determine the...
