An official website of the United States government
Tolerance for Ambiguity (TA) is the ability to seek out, enjoy, and excel in ambiguous tasks. This is a skill or mindset that today’s engineering graduates must possess in order to address the problems they must be prepared to solve—problems that are complex, fraught with uncertainty, and given to conflicting interpretations by varying constituents. It can be argued that students with a higher tolerance for ambiguity will be better suited to proactively engage in, enjoy, and excel in finding solutions to the contemporary problems faced by 21st-century engineers. In contrast, students with a lower tolerance for ambiguity may be unmotivated in the modern engineering work environment and struggle to perform well. Given this reality, pedagogical innovations shown to increase students’ tolerance for ambiguity have the potential to better prepare the future engineering workforce. However, there are few examples of how to do this in engineering and/or how to measure the effectiveness of our efforts. This paper briefly describes the development of a pedagogical intervention designed to increase sophomore engineering students’ tolerance for ambiguity. The context of this study is an undergraduate engineering statistics course offered by the Industrial Engineering department at a large university located in the southeast. Students will be given a large hypothetical data set that mimics real data the undergraduate student experience (e.g., GPAs, course completion rates), and asked to use the engineering design process to identify and solve a data-rich problem using statistical techniques they have learned in the course. Two well-established measures of TA were adapted for this study; the result of the face validity check will also be discussed. This paper closes with insights on how these measures will be used to evaluate the impact of the intervention. The findings of this study will not only advance our understanding of pedagogical strategies for fostering the development of this 21st century skill, but also give us meaningful ways to measure the effectiveness of our efforts.
more »
« less
Collaborative Interaction in Large Explorative Environments
Building collaborative VR applications for exploring and interacting with large or abstract spaces presents several problems. Given a large space and a potentially large number of possible interactions, it is expected that users will need a tool selection menu that will be easily accessible at any point in the environment. Given the collaborative nature, users will also want to be able to maintain awareness of each other within the environment and communicate about what they are seeing or doing. We present a demo that shows solutions to these problems developed in the context of a collaborative geological dataset viewer.
more »
« less
- Award ID(s):
- 1815976
- PAR ID:
- 10168893
- Date Published:
- Journal Name:
- ACM Symposium on Spatial User Interaction (SUI) 2019
- Page Range / eLocation ID:
- 1 to 2
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
During active shooter events or emergencies, the ability of security personnel to respond appropriately to the situation is driven by pre-existing knowledge and skills, but also depends upon their state of mind and familiarity with similar scenarios. Human behavior becomes unpredictable when it comes to making a decision in emergency situations. The cost and risk of determining these human behavior characteristics in emergency situations is very high. This paper presents an immersive collaborative virtual reality (VR) environment for performing virtual building evacuation drills and active shooter training scenarios using Oculus Rift head mounted displays. The collaborative immersive environment is implemented in Unity 3D and is based on run, hide, and fight mode for emergency response. The immersive collaborative VR environment also offers a unique method for training in emergencies for campus safety. The participant can enter the collaborative VR environment setup on the cloud and participate in the active shooter response training environment, which leads to considerable cost advantages over large-scale real-life exercises. A presence questionnaire in the user study was used to evaluate the effectiveness of our immersive training module. The results show that a majority of users agreed that their sense of presence was increased when using the immersive emergencymore » « less
-
Narrative and collaboration are two core features of rich interactive learning. Narrative-centered learning environments offer significant potential for supporting student learning. By contextualizing learning within interactive narratives, these environments leverage students’ innate facilities for developing understandings through stories. Computer-supported collaborative learning environments offer students rich, collaborative learning experiences in which small groups of students engage in constructing artifacts, addressing disciplinary challenges, and solving problems. Narrative and collaboration have distinct affordances for learning, but combining them poses significant challenges. In this paper, we present initial work on solving this problem by introducing collaborative narrative-centered learning environments. These environments will enable small groups of students to collaboratively solve problems in rich multi-participant storyworlds. We propose a novel framework for designing and developing these environments, which we are using to create a collaborative narrative-centered learning environment for middle school ecosystems education. In the learning environment, students work on problem-solving scenarios centered on how to support optimal fish health in aquatic environments. Results from pilot testing the learning environment with 45 students suggest it supports the creation of engaging and effective collaborative narrative-centered learning experiences.more » « less
-
Current collaborative augmented reality (AR) systems establish a common localization coordinate frame among users by exchanging and comparing maps comprised of feature points. However, relative positioning through map sharing struggles in dynamic or feature-sparse environments. It also requires that users exchange identical regions of the map, which may not be possible if they are separated by walls or facing different directions. In this paper, we present Cappella11Like its musical inspiration, Cappella utilizes collaboration among agents to forgo the need for instrumentation, an infrastructure-free 6-degrees-of-freedom (6DOF) positioning system for multi-user AR applications that uses motion estimates and range measurements between users to establish an accurate relative coordinate system. Cappella uses visual-inertial odometry (VIO) in conjunction with ultra-wideband (UWB) ranging radios to estimate the relative position of each device in an ad hoc manner. The system leverages a collaborative particle filtering formulation that operates on sporadic messages exchanged between nearby users. Unlike visual landmark sharing approaches, this allows for collaborative AR sessions even if users do not share the same field of view, or if the environment is too dynamic for feature matching to be reliable. We show that not only is it possible to perform collaborative positioning without infrastructure or global coordinates, but that our approach provides nearly the same level of accuracy as fixed infrastructure approaches for AR teaming applications. Cappella consists of an open source UWB firmware and reference mobile phone application that can display the location of team members in real time using mobile AR. We evaluate Cappella across mul-tiple buildings under a wide variety of conditions, including a contiguous 30,000 square foot region spanning multiple floors, and find that it achieves median geometric error in 3D of less than 1 meter.more » « less
-
null (Ed.)Mobile Augmented Reality (AR) provides immersive experiences by aligning virtual content (holograms) with a view of the real world. When a user places a hologram it is usually expected that like a real object, it remains in the same place. However, positional errors frequently occur due to inaccurate environment mapping and device localization, to a large extent determined by the properties of natural visual features in the scene. In this demonstration we present SceneIt, the first visual environment rating system for mobile AR based on predictions of hologram positional error magnitude. SceneIt allows users to determine if virtual content placed in their environment will drift noticeably out of position, without requiring them to place that content. It shows that the severity of positional error for a given visual environment is predictable, and that this prediction can be calculated with sufficiently high accuracy and low latency to be useful in mobile AR applications.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1145/3357251.3360017
