Ching Chang

National Taiwan Normal University

Papers

3

Total Citations

46

H-Index

3

About

Ching Chang is an innovative education researcher whose work sits at the intersection of computational thinking, language learning, and technology-enhanced pedagogy. With a focus on interdisciplinary learning approaches, Chang has made significant contributions to understanding how emerging educational technologies — particularly educational robots and game-based learning platforms — can simultaneously develop students' computational thinking skills and foreign language acquisition, most notably in English as a Foreign Language (EFL) contexts. Chang's most influential work demonstrates that integrating computational thinking beyond traditional STEM boundaries into language learning environments yields meaningful academic gains. Their 2022 study on pair programming with educational robots (20 citations) challenged conventional disciplinary silos, while subsequent research employing sequential behavior analysis illuminated how game-based learning approaches shape interdisciplinary competencies. Notably, Chang has also foregrounded questions of equity in technology education, examining how gender dynamics influence computational thinking development and advocating for pedagogical designs that genuinely empower girls rather than simply emphasizing problem-solving metrics. Collectively accumulating over 46 citations across recent publications, Chang's research offers both practitioners and scholars a nuanced framework for designing inclusive, cross-disciplinary digital learning experiences that prepare diverse learners for an increasingly technology-driven world.

Research Focus

Key Achievements

3
H-Index
3
Papers
46
Total Citations
15
Avg Citations/Paper
🏆 Most Cited Paper
Effects of a Pair Programming Educational Robot-Based Approach on Students’ Interdisciplinary Learning of Computational Thinking and Language Learning
20 citations · 2022
📈 Most Prolific Year: 2022 (2 Papers)
🤝 Key Collaborators: 6
🏛 Institutions: National Taiwan Normal University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 15 days ago