{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,31]],"date-time":"2025-12-31T12:11:25Z","timestamp":1767183085007,"version":"build-2065373602"},"reference-count":78,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2025,9,2]],"date-time":"2025-09-02T00:00:00Z","timestamp":1756771200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Universitas Indonesia (UI)","award":["PKS-318\/UN2.RST\/HKP.05.00\/2025"],"award-info":[{"award-number":["PKS-318\/UN2.RST\/HKP.05.00\/2025"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["BDCC"],"abstract":"<jats:p>Assessing e-learning students\u2019 satisfaction with lecturers\u2019 interactions in asynchronous forums is essential for enhancing teaching and learning processes. The discussion forum allows students to share comments and ideas with peers or lecturers, stimulating diverse perspectives and improving learning efficacy. However, lecturers\u2019 responses are often similar or redundant to previous students\u2019 comments, limiting feedback depth and potentially reducing students\u2019 perceived value of the interaction. Machine learning classifiers have been widely used to assess satisfaction based on sentiment or semantic similarity. However, integrating sentiment and semantic similarity between students\u2019 comments or opinions and lecturers\u2019 responses in asynchronous online discussion forums has received limited attention and may be improved. Through this research, we propose a novel model called E-learning Satisfaction Assessment using Textual Neural Network (E-SATNet). The E-SATNet model has two main sub-networks. The first sub-network employs a Convolutional Neural Network (CNN) to extract sentiment-related features from students\u2019 reactions to lecturers\u2019 responses. The second sub-network utilizes a Bidirectional Long Short-Term Memory (BiLSTM) to extract semantic features from lecturers\u2019 responses and compute their similarity with the overall discussion content. Evaluation results show that E-SATNet effectively assesses satisfaction, achieving an average F1-score of 88.12.<\/jats:p>","DOI":"10.3390\/bdcc9090228","type":"journal-article","created":{"date-parts":[[2025,9,2]],"date-time":"2025-09-02T09:24:41Z","timestamp":1756805081000},"page":"228","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["E-SATNet: Evaluating Student Satisfaction with Lecturer Responses in Asynchronous Online Discussions Using Sentiment and Semantic Similarity Analysis"],"prefix":"10.3390","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3370-4541","authenticated-orcid":false,"given":"Sulis","family":"Sandiwarno","sequence":"first","affiliation":[{"name":"Faculty of Computer Science, Universitas Indonesia, Depok 16424, Indonesia"},{"name":"Faculty of Computer Science, Universitas Mercu Buana, West Jakarta 11650, Indonesia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0012-8552","authenticated-orcid":false,"given":"Dana Indra","family":"Sensuse","sequence":"additional","affiliation":[{"name":"Faculty of Computer Science, Universitas Indonesia, Depok 16424, Indonesia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0459-0493","authenticated-orcid":false,"given":"Harry Budi","family":"Santoso","sequence":"additional","affiliation":[{"name":"Faculty of Computer Science, Universitas Indonesia, Depok 16424, Indonesia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1847-8665","authenticated-orcid":false,"given":"Deden Sumirat","family":"Hidayat","sequence":"additional","affiliation":[{"name":"National Research and Innovation Agency (BRIN), Jakarta 10340, Indonesia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5210-259X","authenticated-orcid":false,"given":"Ally S.","family":"Nyamawe","sequence":"additional","affiliation":[{"name":"United Nations University Institute in Macau, Macau SAR, China"},{"name":"Department of Computer Science and Engineering, The University of Dodoma, P.O. Box 490, Dodoma 41218, Tanzania"}]},{"given":"Abdallah","family":"Yousif","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Sudan University of Science and Technology, P.O. Box 407, Khartoum 11111, Sudan"}]}],"member":"1968","published-online":{"date-parts":[[2025,9,2]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1509","DOI":"10.1108\/ITP-09-2021-0687","article-title":"Online listening responses and e-learning performance","volume":"36","author":"Du","year":"2023","journal-title":"Inf. Technol. People"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"805","DOI":"10.1007\/s11135-020-01028-z","article-title":"Effects of COVID-19 in E-learning on higher education institution students: The group comparison between male and female","volume":"55","author":"Shahzad","year":"2021","journal-title":"Qual. 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