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Jihong Ding

Biographic Data

ID9622967
NAMEJihong Ding
GIVEN NAMESJihong
FAMILY NAMEDing
SIGNATUREDING J
AFFILIATIONSZhejiang Normal University
ORCID0000-0002-2939-6171
VERIFIEDYes
TOTAL WORKS4
TOTAL CITATIONS0
WORKS AS AUTHOR4
WORKS AS EDITOR0
FIRST PUBLICATION YEAR2020
LATEST PUBLICATION YEAR2026
H-INDEX0
  • Pcca-Darts

    Open Access•Yuan Tian, Huazhong Liu et al.•ARTICLE•IEEE Transactions on Computational…•2026

  • Integrating AI-enhanced 4C/ID scaffolding into rural STEM education

    Jihong Ding, Huazhong Liu et al.•ARTICLE•Interactive Learning Environments•2026

    Rural students often face limited exposure to multidisciplinary knowledge and insufficient training in complex problem-solving (CPS) skills. To address this gap, this quasi-experimental study adopted a progressively integrated multidisciplinary STEM approach based on the Four-Component Instructional Design (4C/ID) model, with Large Language Models (LLMs) embedded as adaptive scaffolding in one experimental condition. A total of 120 Grade 6 studen…

  • The paradox of instrumental visibility

    Open Access•Jihong Ding, Huazhong Liu et al.•ARTICLE•Teaching and Teacher Education•2026

  • Scalable Tensor-Train-Based Tensor Computations for Cyber–Physical–Social Big Data

    Open Access•Huazhong Liu, Laurence T Yang et al.•ARTICLE•IEEE Transactions on Computational…•2020

    Tensor-based big data analysis approaches are effectively exploited to handle multisource and heterogeneous cyber-physical-social big data generated from diverse spaces. However, the curse of dimensionality seriously restricts their widespread exploitation, especially under edge/fog computing environments. To alleviate the dilemma, we attempt to present a set of tensor-train (TT)-based tensor operations with their scalable computations and then p…

No prominent works on this page.

  • Scalable Tensor-Train-Based Tensor Computations for Cyber–Physical–Social Big Data

    Open Access•Huazhong Liu, Laurence T Yang et al.•ARTICLE•IEEE Transactions on Computational…•2020

    Tensor-based big data analysis approaches are effectively exploited to handle multisource and heterogeneous cyber-physical-social big data generated from diverse spaces. However, the curse of dimensionality seriously restricts their widespread exploitation, especially under edge/fog computing environments. To alleviate the dilemma, we attempt to present a set of tensor-train (TT)-based tensor operations with their scalable computations and then p…

  • Pcca-Darts

    Open Access•Yuan Tian, Huazhong Liu et al.•ARTICLE•IEEE Transactions on Computational…•2026

  • Integrating AI-enhanced 4C/ID scaffolding into rural STEM education

    Jihong Ding, Huazhong Liu et al.•ARTICLE•Interactive Learning Environments•2026

    Rural students often face limited exposure to multidisciplinary knowledge and insufficient training in complex problem-solving (CPS) skills. To address this gap, this quasi-experimental study adopted a progressively integrated multidisciplinary STEM approach based on the Four-Component Instructional Design (4C/ID) model, with Large Language Models (LLMs) embedded as adaptive scaffolding in one experimental condition. A total of 120 Grade 6 studen…

  • The paradox of instrumental visibility

    Open Access•Jihong Ding, Huazhong Liu et al.•ARTICLE•Teaching and Teacher Education•2026

Advanced Neuroimaging Techniques and Applications (1 work) · Advanced Wireless Communication Techniques (1 work) · Algorithm (1 work) · Architecture (1 work) · Artificial Intelligence (1 work) · Big data (1 work) · Computation (1 work) · Computer Science (1 work) · Critical Race Theory in Education (1 work) · Curse of dimensionality (1 work)

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