AHCI RESEARCH GROUP
Publications
Papers published in international journals,
proceedings of conferences, workshops and books.
OUR RESEARCH
Scientific Publications
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2024
Khurana, A.; Chilana, P. K.
Understanding Novice Users' Mental Models of Gesture Discoverability and Designing Effective Onboarding Proceedings Article
In: UbiComp Companion - Companion ACM Int. Jt. Conf. Pervasive Ubiquitous Comput., pp. 290–295, Association for Computing Machinery, Inc, 2024, ISBN: 979-840071058-2 (ISBN).
Abstract | Links | BibTeX | Tags: Augmented Reality, Gesture discoverability, Gesture recognition, Help seeking, help-seeking, Immersive, Language Model, Large language model, large language models, Mental model, Mixed reality, Novice user, Onboarding, Prompt-based interaction, prompt-based interactions
@inproceedings{khurana_understanding_2024,
title = {Understanding Novice Users' Mental Models of Gesture Discoverability and Designing Effective Onboarding},
author = {A. Khurana and P. K. Chilana},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85206148797&doi=10.1145%2f3675094.3678370&partnerID=40&md5=e16aa1b52d2ccbe8bdf882be4ff57fd7},
doi = {10.1145/3675094.3678370},
isbn = {979-840071058-2 (ISBN)},
year = {2024},
date = {2024-01-01},
booktitle = {UbiComp Companion - Companion ACM Int. Jt. Conf. Pervasive Ubiquitous Comput.},
pages = {290–295},
publisher = {Association for Computing Machinery, Inc},
abstract = {A variety of consumer Augmented Reality (AR) applications have been released on mobile devices and novel immersive headsets over the last five years, creating a breadth of new AR-enabled experiences. However, these applications, particularly those designed for immersive headsets, require users to employ unfamiliar gestural input and adopt novel interaction paradigms. This leap forward intensifies the complexity of help-seeking and onboarding needs for the end-users. Recent emergence of artificial intelligence (AI)powered in-context help tools has become potential alternatives to onboarding and search methods. However, non-technical users struggle with prompt-based interactions within LLMs that offer human-like language capabilities, which is unique, but can also be unreliable. My doctoral research aims to (1) understand how novice users discover gestural interactions and classify the types of interaction challenges they face; (2) investigate the nuances in users' mental models of emerging technologies, such as LLMs and AR; and, (3) explore the design of onboarding that enhances gesture discoverability and their application within the AR environments. © 2024 Copyright held by the owner/author(s).},
keywords = {Augmented Reality, Gesture discoverability, Gesture recognition, Help seeking, help-seeking, Immersive, Language Model, Large language model, large language models, Mental model, Mixed reality, Novice user, Onboarding, Prompt-based interaction, prompt-based interactions},
pubstate = {published},
tppubtype = {inproceedings}
}
A variety of consumer Augmented Reality (AR) applications have been released on mobile devices and novel immersive headsets over the last five years, creating a breadth of new AR-enabled experiences. However, these applications, particularly those designed for immersive headsets, require users to employ unfamiliar gestural input and adopt novel interaction paradigms. This leap forward intensifies the complexity of help-seeking and onboarding needs for the end-users. Recent emergence of artificial intelligence (AI)powered in-context help tools has become potential alternatives to onboarding and search methods. However, non-technical users struggle with prompt-based interactions within LLMs that offer human-like language capabilities, which is unique, but can also be unreliable. My doctoral research aims to (1) understand how novice users discover gestural interactions and classify the types of interaction challenges they face; (2) investigate the nuances in users' mental models of emerging technologies, such as LLMs and AR; and, (3) explore the design of onboarding that enhances gesture discoverability and their application within the AR environments. © 2024 Copyright held by the owner/author(s).