Dataset: Artificial Intelligence in Education through Asian-affiliated Scholarship

Description

This dataset consists of two files. Dataset 1 contains bibliographic metadata exported from Scopus for journal articles on Artificial Intelligence (AI) in education involving Asian-affiliated scholarship. The metadata include information such as titles, abstracts, authors, affiliations, source titles, publication years, keywords, citation data, and cited references where available. Dataset 2 contains the abstract corpus extracted from the Scopus bibliographic metadata. This abstract dataset was prepared for supplementary text analysis using TALL. Bibliometric analysis of Dataset 1 was conducted using Biblioshiny, while text analysis of Dataset 2 was conducted using TALL. The outputs from both analyses are included to support transparency, reproducibility, and secondary analysis.

Steps to reproduce

The search strategy was developed by combining two groups of terms. The first group captured artificial intelligence-related technologies, while the second group captured educational contexts. The search was conducted in the Scopus “TITLE-ABS-KEY” field to retrieve publications in which the relevant concepts appeared in the title, abstract, or keywords. The artificial intelligence-related terms included general and specific AI technologies, such as artificial intelligence, machine learning, deep learning, natural language processing, intelligent tutoring systems, learning analytics, educational data mining, chatbots, generative AI, ChatGPT, and large language models. The education-related terms included education, learning, teaching, students, teachers, classrooms, schools, universities, higher education, online learning, and e-learning. The following query was used to retrieve the initial Scopus records: TITLE-ABS-KEY ("artificial intelligence" OR AI OR "machine learning" OR "deep learning" OR "natural language processing" OR "intelligent tutoring system*" OR "learning analytics" OR "educational data mining" OR chatbot* OR "generative AI" OR ChatGPT OR "large language model*") AND TITLE-ABS-KEY (education OR educational OR learning OR teaching OR student* OR teacher* OR classroom* OR school* OR universit* OR "higher education" OR "online learning" OR "e-learning") To reproduce the analysis, import Dataset 1 into Biblioshiny/bibliometrix and use the Scopus bibliographic metadata to run the bibliometric analyses, including publication growth, source, author, institution and country productivity, collaboration analysis, citation analysis, keyword co-occurrence, thematic mapping, and thematic evolution. Then import Dataset 2, which contains the abstract corpus extracted from the Scopus metadata, into TALL to conduct corpus diagnostics, frequency and keyness analysis, co-occurrence analysis, topic modelling, syntactic profiling, polarity and emotion analysis, and artefact checking. The generated outputs can be compared with the Biblioshiny and TALL output files included in this dataset. Exact replication may vary because Scopus indexing, affiliation metadata, and citation counts are updated over time.

Institutions

• Sekolah Tinggi Agama Islam Muhammadiyah Tulungagung

  East Java, Tulungagung
• Universitas Islam Negeri Sayyid Ali Rahmatullah Tulungagung

  East Java, Tulungagung

Categories

Licence