Demo Data from SIGIR 2026 / reviewers in the wild / expert
Qinyi Tao
dblp:429/0599
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2026
0009-0003-7979-747XORCID · reported
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 · 70% Human-AI interaction · 30% |
Topics — the 3 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Learning and educational technologies
language learning |
1.0 | 1 | 2026 | WordCraft: Scaffolding the Keyword Method for L2 Vocabulary Learning with Multimodal LLMs · CHI 2026 |
Human-AI interaction › large language models
multimodal large language models |
1.0 | 1 | 2026 | WordCraft: Scaffolding the Keyword Method for L2 Vocabulary Learning with Multimodal LLMs · CHI 2026 |
Learning and educational technologies › language learning
second-language vocabulary learning |
1.0 | 1 | 2026 | WordCraft: Scaffolding the Keyword Method for L2 Vocabulary Learning with Multimodal LLMs · CHI 2026 |
Methods — techniques the papers use, named apart from their topics
user study · 1.0multimodal large language model · 1.0formative study · 1.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | WordCraft: Scaffolding the Keyword Method for L2 Vocabulary Learning with Multimodal LLMsabstractApplying the keyword method for vocabulary memorization remains a significant challenge for L1 Chinese–L2 English learners. They frequently struggle to generate phonologically appropriate keywords, construct coherent associations, and create vivid mental imagery to aid long-term retention. Existing approaches, including fully automated keyword generation and outcome-oriented mnemonic aids, either compromise learner engagement or lack adequate process-oriented guidance. To address these limitations, we conducted a formative study with L1 Chinese-L2 English learners and educators (N=18), which revealed key difficulties and requirements in applying the keyword method to vocabulary learning. Building on these insights, we introduce WordCraft, a learner-centered interactive tool powered by Multimodal Large Language Models (MLLMs). WordCraft scaffolds the keyword method by guiding learners through keyword selection, association construction, and image formation, thereby enhancing the effectiveness of vocabulary memorization. Two user studies demonstrate that WordCraft not only preserves the generation effect but also achieves high levels of effectiveness and usability. Yuheng Shao, Chaoran Wu, Yang Ouyang, Qinyi Tao, Quan Li 0002 |
CHI | 7 |