Evaluating the Quality of AI-Generated Digital Educational Resources for University Teaching and Learning DOI Creative Commons
Qian Huang,

Chunlan Lv,

Lu Li

и другие.

Systems, Год журнала: 2025, Номер 13(3), С. 174 - 174

Опубликована: Март 3, 2025

With the proliferation of artificial intelligence in education, AI-generated digital educational resources are increasingly being employed as supplements for university teaching and learning. However, this raises concerns about quality content produced. To conduct a comprehensive assessment, paper presents an evaluation index system by combining Delphi method Analytic Hierarchy Process. The initial indicators across dimensions content, expression, user technical aspects identified through systematic literature review recent research. Then, is utilized to modify according experts’ opinions two rounds questionnaire surveys. Subsequently, weight coefficients calculated using Finally, indicator evaluating developed, which comprises four twenty indicators. findings reveal that characteristics critical importance assessing resources, followed expression second most significant factor, with also recognized. Among second-level indicators, “authenticity”, “accuracy”, “legitimacy”, “relevance” accorded greater relative other proposed equips relevant stakeholders framework selecting high-quality AIGDERs steering AI tools line standards. some implications provided support selection guidance on aligning these

Язык: Английский

Fine-tuning diffusion model to generate new kite designs for the revitalization and innovation of intangible cultural heritage DOI Creative Commons
Yaqin Zhou, Yu Liu, Yongbo Shao

и другие.

Scientific Reports, Год журнала: 2025, Номер 15(1)

Опубликована: Март 4, 2025

Язык: Английский

Процитировано

0

Evaluating the Quality of AI-Generated Digital Educational Resources for University Teaching and Learning DOI Creative Commons
Qian Huang,

Chunlan Lv,

Lu Li

и другие.

Systems, Год журнала: 2025, Номер 13(3), С. 174 - 174

Опубликована: Март 3, 2025

With the proliferation of artificial intelligence in education, AI-generated digital educational resources are increasingly being employed as supplements for university teaching and learning. However, this raises concerns about quality content produced. To conduct a comprehensive assessment, paper presents an evaluation index system by combining Delphi method Analytic Hierarchy Process. The initial indicators across dimensions content, expression, user technical aspects identified through systematic literature review recent research. Then, is utilized to modify according experts’ opinions two rounds questionnaire surveys. Subsequently, weight coefficients calculated using Finally, indicator evaluating developed, which comprises four twenty indicators. findings reveal that characteristics critical importance assessing resources, followed expression second most significant factor, with also recognized. Among second-level indicators, “authenticity”, “accuracy”, “legitimacy”, “relevance” accorded greater relative other proposed equips relevant stakeholders framework selecting high-quality AIGDERs steering AI tools line standards. some implications provided support selection guidance on aligning these

Язык: Английский

Процитировано

0