Chengjiu Yin
Biographic Data
| ID | 9456760 |
|---|---|
| NAME | Chengjiu Yin |
| GIVEN NAMES | Chengjiu |
| FAMILY NAME | Yin |
| SIGNATURE | YIN C |
| AFFILIATIONS | Kobe University |
| ORCID | 0000-0003-1492-5250 |
| VERIFIED | Yes |
| TOTAL WORKS | 6 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 6 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2020 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
Building a scaffolding framework with field environment digest system in high school agricultural education
The effective integration of practical skills with theoretical knowledge remains a significant challenge in high school agricultural education. Traditional teaching methods often emphasize the transmission of theoretical knowledge, while neglecting the cultivation of practical skills. This imbalance hinders students’ ability to apply classroom learning to real-world agricultural activities. With technological advancements, mobile devices have cre…
Precisely identifying and mitigating shallow reading behaviors through online reading data
Online learning has become a part of daily life. However, it has fostered a tendency to shallow reading. Notably, little attention has been paid to precisely identifying shallow reading behaviors using quantified education big data in favor of methods such as conceptual descriptions, opinions, and questionnaires, resulting in an imprecise analysis of its impact on learning and a lack of strategies to mitigate its causative factors. This study add…
Understanding students’ backtracking behaviors in digital textbooks
The purpose of this study is to explore students’ backtracking patterns in using a digital textbook, reveal the relationship between backtracking behaviors and academic performance as well as learning styles. This study was carried out for 2 semesters on 102 university students and they are required to use a digital textbook system called DITeL to review courseware. Students’ backtracking behaviors are characterized by seven backtracking features…
Understanding the relationship between computational thinking and computational participation
Computer ‐supported collaboration and written communication
Educational big data
Contemporary education, at all levels, is unbounded by time and space and learning can occur both in physical and virtual environments and with the assistance of countless technologies and pedagogi
No prominent works on this page.
Educational big data
Contemporary education, at all levels, is unbounded by time and space and learning can occur both in physical and virtual environments and with the assistance of countless technologies and pedagogi
Understanding the relationship between computational thinking and computational participation
Computer ‐supported collaboration and written communication
Precisely identifying and mitigating shallow reading behaviors through online reading data
Online learning has become a part of daily life. However, it has fostered a tendency to shallow reading. Notably, little attention has been paid to precisely identifying shallow reading behaviors using quantified education big data in favor of methods such as conceptual descriptions, opinions, and questionnaires, resulting in an imprecise analysis of its impact on learning and a lack of strategies to mitigate its causative factors. This study add…
Understanding students’ backtracking behaviors in digital textbooks
The purpose of this study is to explore students’ backtracking patterns in using a digital textbook, reveal the relationship between backtracking behaviors and academic performance as well as learning styles. This study was carried out for 2 semesters on 102 university students and they are required to use a digital textbook system called DITeL to review courseware. Students’ backtracking behaviors are characterized by seven backtracking features…
Building a scaffolding framework with field environment digest system in high school agricultural education
The effective integration of practical skills with theoretical knowledge remains a significant challenge in high school agricultural education. Traditional teaching methods often emphasize the transmission of theoretical knowledge, while neglecting the cultivation of practical skills. This imbalance hinders students’ ability to apply classroom learning to real-world agricultural activities. With technological advancements, mobile devices have cre…
Computer Science (5 works) · Psychology (5 works) · Mathematics education (4 works) · Multimedia (4 works) · Artificial Intelligence (3 works) · Educational technology (3 works) · Human–computer interaction (3 works) · Online Learning and Analytics (3 works) · Innovative Teaching and Learning Methods (2 works) · Agricultural education (1 work)