Evaluation of the Implementation Effectiveness of Digital Scenario-based Teaching in University-level English Conversation Instruction: A Study Based on Artificial Intelligence Generated Content (AIGC) DOI
Qilin Xuan

Published: April 18, 2025

Abstract In recent years, the rapid development of artificial intelligence (AI) technology has highlighted growing potential Artificial Intelligence Generated Content (AIGC) in field education. university-level English instruction, traditional teaching models often fail to meet increasing demand for oral practice and contextual communication skills among students. This study, grounded theoretical framework digital scenario-based leveraging AIGC technology, designed implemented a model tailored conversation instruction higher Through an empirical investigation into outcomes—including dimensions such as student learning performance, communicative competence improvement, instructional satisfaction—the findings demonstrate that AIGC-driven significantly enhances students' comprehensive language application while stimulating their interest active engagement learning. Moreover, this study identifies technical bottlenecks pedagogical challenges encountered during implementation, proposing optimization strategies providing valuable insights intelligent evolution university teaching.

Language: Английский

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

Chunlan Lv,

Lu Li

et al.

Systems, Journal Year: 2025, Volume and Issue: 13(3), P. 174 - 174

Published: March 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

Language: Английский

Citations

0
Empowering music education with technology: a bibliometric perspective DOI Creative Commons
Yidi Ma, Chengliang Wang

Humanities and Social Sciences Communications, Journal Year: 2025, Volume and Issue: 12(1)

Published: March 8, 2025

Language: Английский

Citations

0
Impact of AI-agent-supported collaborative learning on the learning outcomes of University programming courses DOI
Haoming Wang, Chengliang Wang, Zhan Chen

et al.

Education and Information Technologies, Journal Year: 2025, Volume and Issue: unknown

Published: March 13, 2025

Language: Английский

Citations

0
Transforming Education in the AI Era: A Technology–Organization–Environment Framework Inquiry into Public Discourse DOI Creative Commons
Jinqiao Zhou, Hongfeng Zhang

Applied Sciences, Journal Year: 2025, Volume and Issue: 15(7), P. 3886 - 3886

Published: April 2, 2025

The advent of generative artificial intelligence (GAI) technologies has significantly influenced the educational landscape. However, public perceptions and underlying emotions toward intelligence-generated content (AIGC) applications in education remain complex issues. To address this issue, study employs LDA network opinion topic mining SnowNLP sentiment analysis to comprehensively analyze over 40,000 comments collected from multiple social media platforms China. Through a detailed data, examines distribution positive negative identifies six topics. further utilizes visual tools such as word clouds heatmaps present research findings. results indicate that emotional polarity across all topics is characterized by predominance ones. Moreover, an keywords reveals each its own emphasis, yet there are overlaps between them. Therefore, study, through quantitative methods, also reflects interconnections among elements within ecosystem. Additionally, integrates identified with Technology–Organization–Environment (TOE) framework explore broad impact AIGC on perspectives technology, organization, environment. This provides novel perspective attitudes key concerns Chinese regarding use education.

Language: Английский

Citations

0
Evaluation of the Implementation Effectiveness of Digital Scenario-based Teaching in University-level English Conversation Instruction: A Study Based on Artificial Intelligence Generated Content (AIGC) DOI
Qilin Xuan

Published: April 18, 2025

Abstract In recent years, the rapid development of artificial intelligence (AI) technology has highlighted growing potential Artificial Intelligence Generated Content (AIGC) in field education. university-level English instruction, traditional teaching models often fail to meet increasing demand for oral practice and contextual communication skills among students. This study, grounded theoretical framework digital scenario-based leveraging AIGC technology, designed implemented a model tailored conversation instruction higher Through an empirical investigation into outcomes—including dimensions such as student learning performance, communicative competence improvement, instructional satisfaction—the findings demonstrate that AIGC-driven significantly enhances students' comprehensive language application while stimulating their interest active engagement learning. Moreover, this study identifies technical bottlenecks pedagogical challenges encountered during implementation, proposing optimization strategies providing valuable insights intelligent evolution university teaching.

Language: Английский

Citations

0