A Review of Data Augmentation and Data Generation Using Artificial Intelligence in Education

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Technological advancement of artificial intelligence enhances the quality of education. Sufficient and high-quality data are important elements in building accurate artificial intelligence models. The real-world scenarios are often small-scale, attributable to various reasons, such as the high cost of data collection, low occurrence of events, protected data, privacy issues, and ethical issues. Data augmentation and generation provide additional training data to facilitate machine learning model construction. This paper reviewed 202 publications to analyze the methodologies, results, and applications of data synthesis approaches for educational research in 2010–2023 (up to August 2023). Basic characteristics were studied, including the number of annual publications, subject areas of publications, top ten publishers, and a word cloud of keywords. It was followed by an in-depth discussion of the top ten most cited publications. Several open challenges and suggestions for potential future research directions were considered.

Original languageEnglish
Title of host publicationTechnology in Education. Innovative Practices for the New Normal - 6th International Conference on Technology in Education, ICTE 2023, Proceedings
EditorsSimon K.S. Cheung, Fu Lee Wang, Kam Cheong Li, Naraphorn Paoprasert, Peerayuth Charnsethikul, Kongkiti Phusavat
Pages242-253
Number of pages12
DOIs
Publication statusPublished - 2024
Event6th International Conference on Technology in Education, ICTE 2023 - Hong Kong, China
Duration: 19 Dec 202321 Dec 2023

Publication series

NameCommunications in Computer and Information Science
Volume1974 CCIS
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937

Conference

Conference6th International Conference on Technology in Education, ICTE 2023
Country/TerritoryChina
CityHong Kong
Period19/12/2321/12/23

Keywords

  • artificial intelligence
  • data augmentation
  • data generation
  • small-scale dataset
  • smart education

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