A Review of the Trends and Challenges in Adopting Natural Language Processing Methods for Education Feedback Analysis
Artificial Intelligence (AI) is a fast-growing area of study that stretching its presence to many business and research domains. Machine learning, deep learning, and natural language processing (NLP) are subsets of AI to tackle different areas of data processing and modelling. This review article pr...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2022-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9781308/ |
| _version_ | 1828318783747391488 |
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| author | Thanveer Shaik Xiaohui Tao Yan Li Christopher Dann Jacquie McDonald Petrea Redmond Linda Galligan |
| author_facet | Thanveer Shaik Xiaohui Tao Yan Li Christopher Dann Jacquie McDonald Petrea Redmond Linda Galligan |
| author_sort | Thanveer Shaik |
| collection | DOAJ |
| description | Artificial Intelligence (AI) is a fast-growing area of study that stretching its presence to many business and research domains. Machine learning, deep learning, and natural language processing (NLP) are subsets of AI to tackle different areas of data processing and modelling. This review article presents an overview of AI’s impact on education outlining with current opportunities. In the education domain, student feedback data is crucial to uncover the merits and demerits of existing services provided to students. AI can assist in identifying the areas of improvement in educational infrastructure, learning management systems, teaching practices and study environment. NLP techniques play a vital role in analyzing student feedback in textual format. This research focuses on existing NLP methodologies and applications that could be adapted to educational domain applications like sentiment annotations, entity annotations, text summarization, and topic modelling. Trends and challenges in adopting NLP in education were reviewed and explored. Context-based challenges in NLP like sarcasm, domain-specific language, ambiguity, and aspect-based sentiment analysis are explained with existing methodologies to overcome them. Research community approaches to extract the semantic meaning of emoticons and special characters in feedback which conveys user opinion and challenges in adopting NLP in education are explored. |
| first_indexed | 2024-04-13T17:47:14Z |
| format | Article |
| id | doaj.art-b463d794510d4b6086370114ef4fb2a2 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-04-13T17:47:14Z |
| publishDate | 2022-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-b463d794510d4b6086370114ef4fb2a22022-12-22T02:36:53ZengIEEEIEEE Access2169-35362022-01-0110567205673910.1109/ACCESS.2022.31777529781308A Review of the Trends and Challenges in Adopting Natural Language Processing Methods for Education Feedback AnalysisThanveer Shaik0https://orcid.org/0000-0002-9730-665XXiaohui Tao1https://orcid.org/0000-0002-0020-077XYan Li2https://orcid.org/0000-0002-4694-4926Christopher Dann3https://orcid.org/0000-0001-7477-0305Jacquie McDonald4Petrea Redmond5https://orcid.org/0000-0001-9674-1206Linda Galligan6https://orcid.org/0000-0001-8156-8690School of Mathematics and Physics and Computing, University of Southern Queensland, Toowoomba, QLD, AustraliaSchool of Mathematics and Physics and Computing, University of Southern Queensland, Toowoomba, QLD, AustraliaSchool of Mathematics and Physics and Computing, University of Southern Queensland, Toowoomba, QLD, AustraliaSchool of Education, University of Southern Queensland, Toowoomba, QLD, AustraliaAcademic Development, University of Southern Queensland, Toowoomba, QLD, AustraliaSchool of Education, University of Southern Queensland, Toowoomba, QLD, AustraliaSchool of Mathematics and Physics and Computing, University of Southern Queensland, Toowoomba, QLD, AustraliaArtificial Intelligence (AI) is a fast-growing area of study that stretching its presence to many business and research domains. Machine learning, deep learning, and natural language processing (NLP) are subsets of AI to tackle different areas of data processing and modelling. This review article presents an overview of AI’s impact on education outlining with current opportunities. In the education domain, student feedback data is crucial to uncover the merits and demerits of existing services provided to students. AI can assist in identifying the areas of improvement in educational infrastructure, learning management systems, teaching practices and study environment. NLP techniques play a vital role in analyzing student feedback in textual format. This research focuses on existing NLP methodologies and applications that could be adapted to educational domain applications like sentiment annotations, entity annotations, text summarization, and topic modelling. Trends and challenges in adopting NLP in education were reviewed and explored. Context-based challenges in NLP like sarcasm, domain-specific language, ambiguity, and aspect-based sentiment analysis are explained with existing methodologies to overcome them. Research community approaches to extract the semantic meaning of emoticons and special characters in feedback which conveys user opinion and challenges in adopting NLP in education are explored.https://ieeexplore.ieee.org/document/9781308/Artificial Intelligencenatural language processingeducationdeep learning |
| spellingShingle | Thanveer Shaik Xiaohui Tao Yan Li Christopher Dann Jacquie McDonald Petrea Redmond Linda Galligan A Review of the Trends and Challenges in Adopting Natural Language Processing Methods for Education Feedback Analysis IEEE Access Artificial Intelligence natural language processing education deep learning |
| title | A Review of the Trends and Challenges in Adopting Natural Language Processing Methods for Education Feedback Analysis |
| title_full | A Review of the Trends and Challenges in Adopting Natural Language Processing Methods for Education Feedback Analysis |
| title_fullStr | A Review of the Trends and Challenges in Adopting Natural Language Processing Methods for Education Feedback Analysis |
| title_full_unstemmed | A Review of the Trends and Challenges in Adopting Natural Language Processing Methods for Education Feedback Analysis |
| title_short | A Review of the Trends and Challenges in Adopting Natural Language Processing Methods for Education Feedback Analysis |
| title_sort | review of the trends and challenges in adopting natural language processing methods for education feedback analysis |
| topic | Artificial Intelligence natural language processing education deep learning |
| url | https://ieeexplore.ieee.org/document/9781308/ |
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