The comparison of two automated feedback approaches based on automated analysis of the online asynchronous interaction
A case of massive online teacher training
Bibliographic Data
| ID | 21632250 |
|---|---|
| Authors | Ning Ma (0000-0002-9503-3192, Beijing Normal University, corresponding author), Yan-Ling Zhang (0000-0003-4802-4346, Beijing Normal University), Zhang Yan-ling (Shenzhen University), Chunping Liu (0009-0008-1495-5138, Beijing Normal University), Chun-Ping Liu (Beijing Normal University), Lei Du (0000-0002-8548-9997, Beijing Normal University) |
| Year | 2023 |
| Pages | 1-22 |
| Publication date | 2023-04-01 |
| Peer Reviewed | Yes |
| Open Access | No |
| Type | ARTICLE |
| Venue | Interactive Learning Environments (JOURNAL) |
| Journal identifiers | ISSN: 1049-4820 • E-ISSN: 1744-5191 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/10494820.2023.2191252 |
| OpenAlex | W4362509390 |
| Language | EN |
| Citations received | 3 |
| References cited | 66 |
Online asynchronous interaction is considered a core part of online teacher training, which has an important impact on learners' learning experience and learning outcomes. How to provide immediate and effective feedback through technical support based on the learners' interactive content and enhance interactive connection has become a key issue in massive online teacher training. This study designed an automated feedback framework from feedback strategy, feedback way, and feedback type. Then, we designed an emotional-cognitive feedback approach and an emotional-cognitive-metacognitive feedback approach based on automated analysis of online asynchronous interactions. A massive online teacher training course was conducted to provide automated feedback to 1438 learners in the online asynchronous interaction. Results showed that the two approaches enabled learners to interact more positively, slow down the growth of the dropout rate, and help learners adjust their emotional state and cognitive level. Particularly, the emotional-cognitive-metacognitive feedback approach could facilitate learners' self-regulation and improve feedback quality. Through questionnaires and semi-structured interviews, we found that learners were obsessed by automated emotional-cognitive-metacognitive feedback approach and they believed that it was helpful for their learning. This study is of great significance and application value to widely carry out high-quality, massive and personalized online learning
Asynchronous communication · Asynchronous learning · Cognition · Cooperative learning · Human–computer interaction · Mathematics education · Metacognition · Multimedia · Synchronous learning · Teaching method · Computer Science · Innovative Teaching and Learning Methods · Intelligent Tutoring Systems and Adaptive Learning · Online Learning and Analytics · Psychology
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| Unique citing works | 3 |
|---|---|
| Citations per year | 3 |
| Citation span | 2025 - 2026 (2) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 3 |