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While AI technologies have transformed the processes adopted by language learners to produce and revise academic writing, more approaches are needed to promote understanding of text patterns and linguistic features of GenAI texts so learners can engage with language skill development and maintain control as novice authors of academic texts. The current study presents a fusion of corpus methods (embedded in a free Windows/macOS tool), facilitating researchers, teachers and students in hands-on, interactive, comparative analysis of essays created by students and essays on the same topics created through GenAI tools. To demonstrate the feasibility of the approach, we analysed 2003 university level argumentative essays on 26 topics, alongside 546 AI-generated essays (21 essays per topic), focussing on four essays from one randomly selected topic for exemplification. The methods highlight notable strengths of AI-generated texts, including broad vocabulary profiles, balance between maintaining lexical focus and avoiding repetition, and rich collocational relations. By visually representing the roles of vocabulary items in text-level contexts, the tool provides a new approach for English for Academic Purposes teachers and students to engage with data patterns in the texts they have produced with and without GenAI, with potential to aid detection, identification, reflection and ultimately production.

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A Study on the Creativity of Creators Using GenAI Tools in Game UGC - Focusing on Roblox

손백존, 조동민

[NRF 연계] 한국전시산업융합연구원 한국과학예술융합학회 Vol.42 No.3 2024.06 pp.135-151

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This study began in December 2023 and analyzes the creativity of creators using generative artificial intelligence (GenAI) tools in game user-generated content (UGC), particularly focusing on the Roblox platform. The aim of this study is to explore how these tools affect creators' creativity. Therefore, the research methods implemented in this study include a literature review and quantitative analysis to assess the creativity levels of creators.The research findings and content are as follows. First, through a literature review, the main findings and theoretical frameworks in existing studies were identified and summarized. Second, using quantitative analysis methods, statistical analysis was conducted on actual usage data from creators to evaluate the impact of GenAI tools on their creativity. Based on these research results, we found that the use of GenAI tools can significantly enhance creators' innovation capabilities and the quality of their works. Based on these findings, we anticipate that further research is necessary to more comprehensively understand the application effects of GenAI tools on other UGC platforms.

 
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