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Bhagya Maheshi

Dados Biográficos

ID6509750
NOMEBhagya Maheshi
PRENOMESBhagya
SOBRENOMEMaheshi
ASSINATURAMAHESHI B
AFILIAÇÕESMonash University
ORCID0009-0000-3268-0627
VERIFICADOSim
TOTAL DE OBRAS4
TOTAL DE CITAÇÕES0
TOTAL COMO AUTOR4
TOTAL COMO EDITOR0
PRIMEIRO ANO DE PUBLICAÇÃO2024
ANO MAIS RECENTE DE PUBLICAÇÃO2026
ÍNDICE H0
  • Design Thinking and Learning Analytics: Involving Students in Designing a Feedback Tool From Ideation to Deployment

    Open Access•Bhagya Maheshi, Flora Ji-Yoon Jin et al.•ARTICLE•Journal of Computer Assisted…•2026

  • Enhancing learner-centered feedback with AI: Teachers’ practices and perceptions

    Open Access•Ahmad Ari Aldino, Bhagya Maheshi et al.•ARTICLE•Assessment & Evaluation in Higher…•2026

    Learner-centered feedback, emphasising future improvement, sensemaking, and student agency, has been increasingly recognised as effective, yet remains challenging for educators to offer in large classes with diverse learner needs. Recent advances in generative artificial intelligence (GenAI) offer new ways to support feedback practice, but limited research has examined how teachers use and perceive GenAI in real-world feedback practices, particul…

  • Feedback in K-12 and higher education: Educators’ perspectives

    Open Access•Flora Ji-Yoon Jin, Flora Jin et al.•ARTICLE•Teaching and Teacher Education•2025•Referências: 4

    Feedback is essential in education, yet often studied within isolated educational sectors. This study investigates feedback practices across K-12 and higher education by surveying 254 educators to explore perceptions of effective feedback, student barriers, and methods for tracking feedback impact. Our findings reveal that higher education educators prioritise cognitive and structural feedback elements, emphasising actionable suggestions and time…

  • Dialogic feedback at scale: Recommendations for learning analytics design

    Open Access•Bhagya Maheshi, Wei Dai et al.•ARTICLE•Journal of Computer Assisted…•2024

Sem obras proeminentes nesta página.

  • Dialogic feedback at scale: Recommendations for learning analytics design

    Open Access•Bhagya Maheshi, Wei Dai et al.•ARTICLE•Journal of Computer Assisted…•2024

  • Feedback in K-12 and higher education: Educators’ perspectives

    Open Access•Flora Ji-Yoon Jin, Flora Jin et al.•ARTICLE•Teaching and Teacher Education•2025•Referências: 4

    Feedback is essential in education, yet often studied within isolated educational sectors. This study investigates feedback practices across K-12 and higher education by surveying 254 educators to explore perceptions of effective feedback, student barriers, and methods for tracking feedback impact. Our findings reveal that higher education educators prioritise cognitive and structural feedback elements, emphasising actionable suggestions and time…

  • Design Thinking and Learning Analytics: Involving Students in Designing a Feedback Tool From Ideation to Deployment

    Open Access•Bhagya Maheshi, Flora Ji-Yoon Jin et al.•ARTICLE•Journal of Computer Assisted…•2026

  • Enhancing learner-centered feedback with AI: Teachers’ practices and perceptions

    Open Access•Ahmad Ari Aldino, Bhagya Maheshi et al.•ARTICLE•Assessment & Evaluation in Higher…•2026

    Learner-centered feedback, emphasising future improvement, sensemaking, and student agency, has been increasingly recognised as effective, yet remains challenging for educators to offer in large classes with diverse learner needs. Recent advances in generative artificial intelligence (GenAI) offer new ways to support feedback practice, but limited research has examined how teachers use and perceive GenAI in real-world feedback practices, particul…

Student Assessment and Feedback (3 obras) · Analytics (2 obras) · Higher education (2 obras) · Learning analytics (2 obras) · Mathematics education (2 obras) · Pedagogy (2 obras) · Psychology (2 obras) · Computer Science (1 obras) · Data science (1 obras) · Design Thinking (1 obras)

Ethnos_APP • Projeto Open Source • Licença MIT • Frontend v2.0.0 • Privacidade e Cookies • Documentação da API: api.ethnos.app/docs • Código da API: GitHub • DOI: 10.5281/zenodo.17049435 • Código do Frontend: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae