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Junlei Du

Biographic Data

ID9589897
NAMEJunlei Du
GIVEN NAMESJunlei
FAMILY NAMEDu
SIGNATUREDU J
AFFILIATIONSBeijing Normal University
ORCID0000-0002-2881-5223
VERIFIEDYes
TOTAL WORKS7
TOTAL CITATIONS0
AUTHOR COUNT7
EDITOR COUNT0
FIRST PUBLICATION YEAR2022
LATEST PUBLICATION YEAR2026
H-INDEX0
  • Diversified social capital accumulation strategies for cMooc learners

    Open Access•Shuang Li, Xinpei Yu et al.•ARTICLE•Interactive Learning Environments•2026

    The analysis of learners’ social capital development strategies provides an important perspective for understanding the mechanisms and strategies of connectivist learning. This study employs community detection algorithms, social network analysis, and SIENA to explore the diverse strategies connectivist learners use to accumulate social capital and assess their effectiveness, based on longitudinal observation and analysis of subcommunity interact…

  • Dynamics of cMooc learner interactions in different social media

    Shuang Li, Junlei Du et al.•ARTICLE•Interactive Learning Environments•2025

    Social media may have an impact on people’s interaction patterns and social relationships. Investigating the interaction patterns of learners across various social media platforms can provide profound insights into the characteristics and mechanisms of connectivist learning. This study explores interaction network characteristics and the dynamic evolution of interaction patterns across multiple social media platforms within a cMOOC by using SNA a…

  • Automatic item generation for educational assessments

    Yishen Song, Junlei Du et al.•ARTICLE•Interactive Learning Environments•2025

    This study reviewed automatic item generation (AIG) applications for educational assessments from 2010 to 2024. The analysis included 71 articles and focused on examining types of generated items and assessments, technical approaches, and evaluation models. The results showed that most generated items related to multiple choice questions, and the generated assessments were mainly about computer and medical sciences at college and vocational level…

  • What participation types of learners are there in connectivist learning

    Yaqian Xu, Junlei Du•ARTICLE•Interactive Learning Environments•2023

    Learners in connectivist learning are diverse. It’s necessary to make a clear understanding of learners’ participation types and characteristics for optimizing the learning support service and learning evaluation in connectivist learning. This study aims to describe different types of learners in connectivist learning from two dimensions of social network and concept network characteristics. We analyzed 10598 collected data output during a 12-wee…

  • Diversified resource access paths in Moocs

    Open Access•Shuang Li, Junlei Du et al.•ARTICLE•Computers & Education•2023

  • Understanding the evolution of cognitive engagement with interaction levels in online learning environments

    Open Access•Liming Guo, Junlei Du et al.•ARTICLE•Journal of Computer Assisted…•2023

  • Mooc learners' time‐investment patterns and temporal‐learning characteristics

    Open Access•Shuang Li, Shuang Wang et al.•ARTICLE•Journal of Computer Assisted…•2022

No prominent works on this page.

  • Mooc learners' time‐investment patterns and temporal‐learning characteristics

    Open Access•Shuang Li, Shuang Wang et al.•ARTICLE•Journal of Computer Assisted…•2022

  • What participation types of learners are there in connectivist learning

    Yaqian Xu, Junlei Du•ARTICLE•Interactive Learning Environments•2023

    Learners in connectivist learning are diverse. It’s necessary to make a clear understanding of learners’ participation types and characteristics for optimizing the learning support service and learning evaluation in connectivist learning. This study aims to describe different types of learners in connectivist learning from two dimensions of social network and concept network characteristics. We analyzed 10598 collected data output during a 12-wee…

  • Diversified resource access paths in Moocs

    Open Access•Shuang Li, Junlei Du et al.•ARTICLE•Computers & Education•2023

  • Understanding the evolution of cognitive engagement with interaction levels in online learning environments

    Open Access•Liming Guo, Junlei Du et al.•ARTICLE•Journal of Computer Assisted…•2023

  • Dynamics of cMooc learner interactions in different social media

    Shuang Li, Junlei Du et al.•ARTICLE•Interactive Learning Environments•2025

    Social media may have an impact on people’s interaction patterns and social relationships. Investigating the interaction patterns of learners across various social media platforms can provide profound insights into the characteristics and mechanisms of connectivist learning. This study explores interaction network characteristics and the dynamic evolution of interaction patterns across multiple social media platforms within a cMOOC by using SNA a…

  • Automatic item generation for educational assessments

    Yishen Song, Junlei Du et al.•ARTICLE•Interactive Learning Environments•2025

    This study reviewed automatic item generation (AIG) applications for educational assessments from 2010 to 2024. The analysis included 71 articles and focused on examining types of generated items and assessments, technical approaches, and evaluation models. The results showed that most generated items related to multiple choice questions, and the generated assessments were mainly about computer and medical sciences at college and vocational level…

  • Diversified social capital accumulation strategies for cMooc learners

    Open Access•Shuang Li, Xinpei Yu et al.•ARTICLE•Interactive Learning Environments•2026

    The analysis of learners’ social capital development strategies provides an important perspective for understanding the mechanisms and strategies of connectivist learning. This study employs community detection algorithms, social network analysis, and SIENA to explore the diverse strategies connectivist learners use to accumulate social capital and assess their effectiveness, based on longitudinal observation and analysis of subcommunity interact…

Computer Science (7 works) · Online Learning and Analytics (7 works) · Psychology (7 works) · World Wide Web (5 works) · Innovative Teaching and Learning Methods (4 works) · Online and Blended Learning (4 works) · Mathematics education (3 works) · Artificial Intelligence (2 works) · Data science (2 works) · Knowledge management (2 works)

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