Name
Abstract | ||
|---|---|---|
Assessment feedback is an essential part of learners’ learning experiences. Personalized feedback in learning is a useful and common strategy for assisting learners to optimize their learning. With the increasing need to provide learners with high quality, immediate, and personalized feedback, a large number of studies had been conducted to investigate how to provide students with personalized feedback effectively. In this study, bibliometric analysis and word cloud techniques were applied to identify research trends and status related to personalized feedback in teaching and learning, based on 276 publications retrieved from the Web of Science database. To be specific, the data were analyzed in terms of annual numbers of publications and citations, important publication sources, countries/regions, and institutions, as well as important research issues and concerns. The findings of this study provided scholars as well as instructors with a general picture of the personalized feedback research. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1007/978-3-030-59413-8_10 | DASFAA |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
0 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xieling Chen | 1 | 17 | 9.41 |
| Di Zou | 2 | 38 | 12.11 |
| Gary Cheng | 3 | 0 | 0.34 |
| Haoran Xie | 4 | 450 | 71.21 |
| Fu Lee Wang | 5 | 926 | 118.55 |
| Leung Pun Wong | 6 | 0 | 0.34 |