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Jennifer Hoffman

Publications and source records attributed to Jennifer Hoffman.

4 recordsLinked to original sources
arXiv2024

Nanoscale Conducting and Insulating Domains on YbB$_6$

YbB$_6$ is a predicted topological insulator, with experimental evidence for conducting surface states of yet-unproven origin. However, its lack of a natural cleavage plane, and resultant surface-dependent polarity, has obscured its study. We use scanning tunneling microscopy to image the cleaved surface of YbB$_6$, exhibiting several coexisting terminations with distinct atomic structures. Our spectroscopic measurements show band-bending between the terminations, resulting in both conducting and fully-gapped regions. In the conductive regions, we observe spectral peaks that are suggestive of van Hove singularities arising from Rashba spin-split quantum well states. The insulating regions rule out the possibility that YbB$_6$ is a strong topological insulator, while the spin-polarized conducting regions suggest possible utility for spintronic devices.

cond-mat.mes-hall↗
arXiv2023

Envisioning an Inclusive Metaverse: Student Perspectives on Accessible and Empowering Metaverse-Enabled Learning

The emergence of the metaverse is being widely viewed as a revolutionary technology owing to a myriad of factors, particularly the potential to increase the accessibility of learning for students with disabilities. However, not much is yet known about the views and expectations of disabled students in this regard. The fact that the metaverse is still in its nascent stage exemplifies the need for such timely discourse. To bridge this important gap, we conducted a series of semi-structured interviews with 56 university students with disabilities in the United States and Hong Kong to understand their views and expectations concerning the future of metaverse-driven education. We have distilled student expectations into five thematic categories, referred to as the REEPS framework: Recognition, Empowerment, Engagement, Privacy, and Safety. Additionally, we have summarized the main design considerations in eight concise points. This paper is aimed at helping technology developers and policymakers plan ahead of time and improving the experiences of students with disabilities.

cs.CY↗
arXiv2023

Your Favorite Gameplay Speaks Volumes about You: Predicting User Behavior and Hexad Type

In recent years, the gamification research community has widely and frequently questioned the effectiveness of one-size-fits-all gamification schemes. In consequence, personalization seems to be an important part of any successful gamification design. Personalization can be improved by understanding user behavior and Hexad player/user type. This paper comes with an original research idea: It investigates whether users' game-related data (collected via various gamer-archetype surveys) can be used to predict their behavioral characteristics and Hexad user types in non-game (but gamified) contexts. The affinity that exists between the concepts of gamification and gaming provided us with the impetus for running this exploratory research. We conducted an initial survey study with 67 Stack Exchange users (as a case study). We discovered that users' gameplay information could reveal valuable and helpful information about their behavioral characteristics and Hexad user types in a non-gaming (but gamified) environment. The results of testing three gamer archetypes (i.e., Bartle, Big Five, and BrainHex) show that they can all help predict users' most dominant Stack Exchange behavioral characteristics and Hexad user type better than a random labeler's baseline. That said, of all the gamer archetypes analyzed in this paper, BrainHex performs the best. In the end, we introduce a research agenda for future work.

cs.HC↗