Table 6.

Most locally and globally cited documents

DocumentTitleLocal citations (LC)Global citations (GC)LC/GC ratio (%)
Chan (2023) The AI generation gap: Are Gen Z students more interested in adopting generative AI such as ChatGPT in teaching and learning than their Gen X and millennial generation teachers?82400
de Winter (2023) Can ChatGPT pass high school exams on English Language Comprehension?55100
Chan (2023) Students’ voices on generative AI: Perceptions, benefits, and challenges in higher education42416.67
Chan (2023) A comprehensive AI policy education framework for university teaching and learning3329.38
Pursnani et al. (2023) Performance of ChatGPT on the US fundamentals of engineering exam: Comprehensive assessment of proficiency and potential implications for professional environmental engineering practice21200
Impact of ChatGPT on learners in an L2 writing practicum: An exploratory investigation1462.17
Herbold et al. (2023) A large-scale comparison of human-written versus ChatGPT-generated essays1250
Jeon and Lee (2023) Large language models in education: a focus on the complementary relationship between human teachers and ChatGPT1382.63
Rudolph (2023a, 2023b) War of the chatbots: Bard, bing chat, ChatGPT, ernie and beyond. The new AI gold rush and its impact on higher education11160.86
Source(s): Table by authors

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