Tingru Cui
Biographic Data
| ID | 6628741 |
|---|---|
| NAME | Tingru Cui |
| GIVEN NAMES | Tingru |
| FAMILY NAME | Cui |
| SIGNATURE | CUI T |
| AFFILIATIONS | The University of Melbourne |
| ORCID | 0000-0002-7899-1372 |
| VERIFIED | Yes |
| TOTAL WORKS | 4 |
| TOTAL CITATIONS | 1 |
| AUTHOR COUNT | 4 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2018 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 1 |
Apologizing artificial intelligence
Artificial intelligence (AI) tools have become increasingly accurate, but still occasionally err. While research started examining AI erring and the efficacy of trust repair attempts in such cases, there is a need to (1) benchmark trust repair attempts by AI against the trust repair dynamics when humans make the same errors, and (2) examine contextual nuances of trust repair dynamics. Using two experiments, we found that users were less forgiving…
Adapting New Learners and New Resources to Micro Open Learning via Online Computation
Since the outbreak of COVID-19, an alternative way to keep students on the track, meanwhile, prevent them from being at the risk of infection is in highly demand. Many education providers had made a move in trial of delivering knowledge and learning materials remotely. Along with this trend, learning management systems, open educational resources (OERs) and OER platforms, mini applications in social media and video-conference software were combin…
Refinement and augmentation for data in micro open learning activities with an evolutionary rule generator
Improving both the quantity and quality of existing data are placed at the center of research for adaptive micro open learning. To cover this research gap, our work targets on the current scarcity of both data and rules that represent open learning activities. An evolutionary rule generator is constructed, which consists of an outer loop and an inner loop. The outer loop runs a genetic algorithm (GA) to produce association rules that can be effec…
Demystifying continuous participation in game applications at social networking sites
Purpose Drawn from the social playfulness literature and the elaboration likelihood model, the purpose of this paper is to propose and test a research model to examine users’ continuous participation in SNS game applications. Design/methodology/approach A field survey with 133 subjects was conducted to test the research model. Findings Two identified design features, symbolic physicality and inherent sociability, are found to influence users’ per…
Demystifying continuous participation in game applications at social networking sites
Purpose Drawn from the social playfulness literature and the elaboration likelihood model, the purpose of this paper is to propose and test a research model to examine users’ continuous participation in SNS game applications. Design/methodology/approach A field survey with 133 subjects was conducted to test the research model. Findings Two identified design features, symbolic physicality and inherent sociability, are found to influence users’ per…
Demystifying continuous participation in game applications at social networking sites
Purpose Drawn from the social playfulness literature and the elaboration likelihood model, the purpose of this paper is to propose and test a research model to examine users’ continuous participation in SNS game applications. Design/methodology/approach A field survey with 133 subjects was conducted to test the research model. Findings Two identified design features, symbolic physicality and inherent sociability, are found to influence users’ per…
Refinement and augmentation for data in micro open learning activities with an evolutionary rule generator
Improving both the quantity and quality of existing data are placed at the center of research for adaptive micro open learning. To cover this research gap, our work targets on the current scarcity of both data and rules that represent open learning activities. An evolutionary rule generator is constructed, which consists of an outer loop and an inner loop. The outer loop runs a genetic algorithm (GA) to produce association rules that can be effec…
Adapting New Learners and New Resources to Micro Open Learning via Online Computation
Since the outbreak of COVID-19, an alternative way to keep students on the track, meanwhile, prevent them from being at the risk of infection is in highly demand. Many education providers had made a move in trial of delivering knowledge and learning materials remotely. Along with this trend, learning management systems, open educational resources (OERs) and OER platforms, mini applications in social media and video-conference software were combin…
Apologizing artificial intelligence
Artificial intelligence (AI) tools have become increasingly accurate, but still occasionally err. While research started examining AI erring and the efficacy of trust repair attempts in such cases, there is a need to (1) benchmark trust repair attempts by AI against the trust repair dynamics when humans make the same errors, and (2) examine contextual nuances of trust repair dynamics. Using two experiments, we found that users were less forgiving…
Computer Science (3 works) · Multimedia (2 works) · Online Learning and Analytics (2 works) · World Wide Web (2 works) · AI in Service Interactions (1 work) · Artificial Intelligence (1 work) · Artificial Intelligence (1 work) · Association rule learning (1 work) · Attribution (1 work) · Benchmark (surveying) (1 work)