A Data-driven Approach Towards Human-robot Collaborative Problem Solving in a Shared Space

We are developing a system for human-robot communication that enables people to communicate with robots in a natural way and is focused on solving problems in a shared space. Our strategy for developing this system is fundamentally data-driven: we use data from multiple input sources and train key components with various machine learning techniques. We developed a web application that is collecting data on how two humans communicate to accomplish a task, as well as a mobile laboratory that is instrumented to collect data on how two humans communicate to accomplish a task in a physically shared space. The data from these systems will be used to train and fine-tune the second stage of our system, in which the robot will be simulated through software. A physical robot will be used in the final stage of our project. We describe these instruments, a test-suite and performance metrics designed to evaluate and automate the data gathering process as well as evaluate an initial data set.Comment: 2017 AAAI Fall Symposium on Natural Communication for Human-Robot Collaboratio

User-Friendly Locations of Error Messages in Web Forms: An Eye Tracking Study

Error messages presented to users are one of the most important elements of Web forms. Error messages are embedded in different parts of the forms available on the Internet and presented in various formats. One of the measures of a user-friendly error message design is the ability to easily capture users’ attention and facilitate fast error correction. In this empirical study, I tested four different locations of error messages frequently used in Web forms on 32 participants. In addition, I analysed the participants’ interactions with error messages through their eye movements. The results of the study showed that the participants spotted the error message fastest when it was displayed on the right side of the erroneous input field. When error messages displayed further the input field users have less saccades to and fixations on error messages compared to those located near to this field, suggesting that less effort has been spent to understand the given message. However, group mean dif-ferences were not statistically significant for form completion time, error recognition time, the number of saccades, and error correction time

Saliency Prediction for Mobile User Interfaces

We introduce models for saliency prediction for mobile user interfaces. A mobile interface may include elements like buttons, text, etc. in addition to natural images which enable performing a variety of tasks. Saliency in natural images is a well studied area. However, given the difference in what constitutes a mobile interface, and the usage context of these devices, we postulate that saliency prediction for mobile interface images requires a fresh approach. Mobile interface design involves operating on elements, the building blocks of the interface. We first collected eye-gaze data from mobile devices for free viewing task. Using this data, we develop a novel autoencoder based multi-scale deep learning model that provides saliency prediction at the mobile interface element level. Compared to saliency prediction approaches developed for natural images, we show that our approach performs significantly better on a range of established metrics.Comment: Paper accepted at WACV 201

Attention Allocation Aid for Visual Search

This paper outlines the development and testing of a novel, feedback-enabled attention allocation aid (AAAD), which uses real-time physiological data to improve human performance in a realistic sequential visual search task. Indeed, by optimizing over search duration, the aid improves efficiency, while preserving decision accuracy, as the operator identifies and classifies targets within simulated aerial imagery. Specifically, using experimental eye-tracking data and measurements about target detectability across the human visual field, we develop functional models of detection accuracy as a function of search time, number of eye movements, scan path, and image clutter. These models are then used by the AAAD in conjunction with real time eye position data to make probabilistic estimations of attained search accuracy and to recommend that the observer either move on to the next image or continue exploring the present image. An experimental evaluation in a scenario motivated from human supervisory control in surveillance missions confirms the benefits of the AAAD.Comment: To be presented at the ACM CHI conference in Denver, Colorado in May 201

Student-Centered Learning: Functional Requirements for Integrated Systems to Optimize Learning

The realities of the 21st-century learner require that schools and educators fundamentally change their practice. "Educators must produce college- and career-ready graduates that reflect the future these students will face. And, they must facilitate learning through means that align with the defining attributes of this generation of learners."Today, we know more than ever about how students learn, acknowledging that the process isn't the same for every student and doesn't remain the same for each individual, depending upon maturation and the content being learned. We know that students want to progress at a pace that allows them to master new concepts and skills, to access a variety of resources, to receive timely feedback on their progress, to demonstrate their knowledge in multiple ways and to get direction, support and feedback from—as well as collaborate with—experts, teachers, tutors and other students.The result is a growing demand for student-centered, transformative digital learning using competency education as an underpinning.iNACOL released this paper to illustrate the technical requirements and functionalities that learning management systems need to shift toward student-centered instructional models. This comprehensive framework will help districts and schools determine what systems to use and integrate as they being their journey toward student-centered learning, as well as how systems integration aligns with their organizational vision, educational goals and strategic plans.Educators can use this report to optimize student learning and promote innovation in their own student-centered learning environments. The report will help school leaders understand the complex technologies needed to optimize personalized learning and how to use data and analytics to improve practices, and can assist technology leaders in re-engineering systems to support the key nuances of student-centered learning

Form Feedback on the Web: A Comparison of Popup Alerts and In-Form Error Messages

acceptedVersio

Virtual training for assembly tasks: a framework for the analysis of the cognitive impact on operators

The importance of training for operators in industrial contexts is widely highlighted in literature. Virtual Reality (VR) technology is considered an efficient solution for training, since it provides immersive, realistic, and interactive simulations environments where the operator can learn-by-doing, far from the risks of the real field. Its efficacy has been demonstrated by several studies, but a proper assessment of the operator’s cognitive response in terms of stress and cognitive load, during the use of such technology, is still lacking. This paper proposes a comprehensive methodology for the analysis of user’s cognitive states, suitable for each kind of training in the industrial sector and beyond. Preliminary feasibility analysis refers to virtual training for assembly of agricultural vehicles. The proposed protocol analysis allowed understanding the operators’ loads to optimize the VR training application, considering the mental demand during the training, and thus avoiding stress, mental overload, improving the user performance

Improving Mobile Web Experience at Dyn Inc.

Recommendations were made to implement content and layout optimizations enabling pages to dynamically adapt to varying screen sizes. A mobile website design with logical content grouping, spacing and positioning appear to provide a more intuitive experience and may improve the overall usability of Dyn\u27s checkout process. This MQP report examines Dyn Inc.\u27s efforts to enhance mobile usability of their checkout process through the implementation of adaptive web design. Two eye-tracking user experience studies were conducted to identify and evaluate mobile-specific drivers of usability. Companies engaging in e-commerce stand to gain a significant competitive advantage through website optimizations resulting in increased mobile usability