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Wide-Scale Automatic Analysis of 20 Years of ITS Research

Hodgson, Ryan; Cristea, Alexandra; Shi, Lei; Graham, John; Cristea, Alexandra I.; Troussas, Christos

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Authors

Ryan Hodgson

Lei Shi

John Graham

Christos Troussas



Abstract

The analysis of literature within a research domain can provide significant value during preliminary research. While literature reviews may provide an in-depth understanding of current studies within an area, they are limited by the number of studies which they take into account. Importantly, whilst publications in hot areas abound, it is not feasible for an individual or team to analyse a large volume of publications within a reasonable amount of time. Additionally, major publications which have gained a large number of citations are more likely to be included in a review, with recent or fringe publications receiving less inclusion. We provide thus an automatic methodology for the large-scale analysis of literature within the Intelligent Tutoring Systems (ITS) domain, with the aim of identifying trends and areas of research from a corpus of publications which is significantly larger than is typically presented in conventional literature reviews. We illustrate this by a novel analysis of 20 years of ITS research. The resulting analysis indicates a significant shift of the status quo of research in recent years with the advent of novel neural network architectures and the introduction of MOOCs.

Citation

Hodgson, R., Cristea, A., Shi, L., Graham, J., Cristea, A. I., & Troussas, C. (2021). Wide-Scale Automatic Analysis of 20 Years of ITS Research. . https://doi.org/10.1007/978-3-030-80421-3_2

Conference Name Intelligent Tutoring Systems
Conference Location Athens, Greece / Virtual
Start Date Jun 7, 2021
End Date Jun 11, 2021
Acceptance Date Mar 13, 2021
Online Publication Date Jul 9, 2021
Publication Date 2021
Deposit Date Apr 12, 2021
Publicly Available Date Apr 13, 2021
Pages 8-21
Series Title Lecture Notes in Computer Science
DOI https://doi.org/10.1007/978-3-030-80421-3_2

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Copyright Statement
The final authenticated version is available online at https://doi.org/10.1007/978-3-030-80421-3_2







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