Analysis of Adult Learners' Usage Preferences and Requirements for Agent-Based AI Teaching Assistants

With the rapid development of large language model technology, the applications of agent-based AI in various fields have received extensive attention. However, few studies have focused on the usage preferences and application requirements of adult learners regarding agent-based AI teaching assistants. In this study, direct-type and heuristic AI teaching assistant agents for the "Basic Computer Applications" course were developed based on the Coze platform, and applied in open education courses. The interaction data between adult learners and the AI teaching assistants are analyzed with inductive and statistical methods, and the research shows that these agents can provide students with continuous support for course knowledge anytime and anywhere. Findings indicate that adult learners primarily interact with the AI teaching assistants through WeChat, prefer direct-type AI teaching assistants for solving course test problems, and also express a need for emotional support. This study offers novel insights and recommendations for researchers and developers of AI teaching assistants for adult learners.

Authors

Institutions

Publication Details

Published
2025-04-18
DOI
https://doi.org/10.1109/cste64638.2025.11092169
Citations
1
Primary Topic
Education and Learning Interventions
Type
article
Field-Weighted Citation Impact
3.25

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Analysis of Adult Learners' Usage Preferences and Requirements for Agent-Based AI Teaching Assistants

Zhuoheng Wei, Yan Zhang, Liang Xiao-qi, Qi-jie Tang et al.
1 citations
Education and Learning Interventions
3.25
article

Analysis of Adult Learners' Usage Preferences and Requirements for Agent-Based AI Teaching Assistants

Zhuoheng Wei, Yan Zhang, Liang Xiao-qi, Qi-jie Tang, Richard Sun
article en
1 citations

Abstract

With the rapid development of large language model technology, the applications of agent-based AI in various fields have received extensive attention. However, few studies have focused on the usage preferences and application requirements of adult learners regarding agent-based AI teaching assistants. In this study, direct-type and heuristic AI teaching assistant agents for the "Basic Computer Applications" course were developed based on the Coze platform, and applied in open education courses. The interaction data between adult learners and the AI teaching assistants are analyzed with inductive and statistical methods, and the research shows that these agents can provide students with continuous support for course knowledge anytime and anywhere. Findings indicate that adult learners primarily interact with the AI teaching assistants through WeChat, prefer direct-type AI teaching assistants for solving course test problems, and also express a need for emotional support. This study offers novel insights and recommendations for researchers and developers of AI teaching assistants for adult learners.

Shanghai Open University (CN), Shanghai Municipal Education Commission (CN), Empire State University (US)
Open University
Quality Education
Openalex Percentile: Top 7%
Education and Learning Interventions
3.25
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Analysis of Adult Learners' Usage Preferences and Requirements for Agent-Based AI Teaching Assistants — Zhuoheng Wei, Yan Zhang, et al. · (2025) | TGRS Research Map | TGRS