Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page

Taichang Zhou

dblp:319/4225 · DBLP profile ↗
← Back
1ranked-venue papers
0as first author
1since 2021 · last 2022
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Human-computer interaction and ubiquitous computing · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Human-computer interaction and pervasive computing
1 paper
Learning and educational technologies · 44% User interface design and tools · 44% Ubiquitous computing and smart environments · 13%

Topics — the 1 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Learning and educational technologies › online learning
virtual classroom
0.612022
Glancee: An Adaptable System for Instructors to Grasp Student Learning Status in Synchronous Online Classes · CHI 2022

Methods — techniques the papers use, named apart from their topics

within-subject user study · 0.6needfinding survey · 0.6learning status detection algorithms · 0.6
YearPublicationVenuePosition
2022 Glancee: An Adaptable System for Instructors to Grasp Student Learning Status in Synchronous Online Classes
abstract
Synchronous online learning has become a trend in recent years. However, instructors often face the challenge of inferring audiences’ reactions and learning status without seeing their faces in video feeds, which prevents instructors from establishing connections with students. To solve this problem, based on a need-finding survey with 67 college instructors, we propose Glancee, a real-time interactive system with adaptable configurations, sidebar-based visual displays, and comprehensive learning status detection algorithms. Then, we conduct a within-subject user study in which 18 college instructors deliver lectures online with Glancee and two baselines, EngageClass and ZoomOnly. Results show that Glancee can effectively support online teaching and is perceived to be significantly more helpful than the baselines. We further investigate how instructors’ emotions, behaviors, attention, cognitive load, and trust are affected during the class. Finally, we offer design recommendations for future online teaching assistant systems.
Shuai Ma 0005, Taichang Zhou, Fei Nie, Xiaojuan Ma
CHI2