{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,21]],"date-time":"2026-05-21T16:57:20Z","timestamp":1779382640008,"version":"3.53.1"},"publisher-location":"Cham","reference-count":28,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031935664","type":"print"},{"value":"9783031935671","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025]]},"DOI":"10.1007\/978-3-031-93567-1_19","type":"book-chapter","created":{"date-parts":[[2025,5,31]],"date-time":"2025-05-31T04:47:07Z","timestamp":1748666827000},"page":"271-283","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Hybrid Deep Learning-Based Framework for Students\u2019 Cognitive Analysis in Online Learning"],"prefix":"10.1007","author":[{"given":"Kavya","family":"Kannan","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"M. Ali Akber","family":"Dewan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mahbub","family":"Murshed","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,5,25]]},"reference":[{"key":"19_CR1","doi-asserted-by":"publisher","first-page":"275","DOI":"10.1016\/j.susoc.2022.05.004","volume":"3","author":"A Haleem","year":"2022","unstructured":"Haleem, A., Javaid, M., Qadri, M.A., Suman, R.: Understanding the role of digital technologies in education: a review. Sustainable Operat. Comput. 3, 275\u2013285 (2022)","journal-title":"Sustainable Operat. Comput."},{"issue":"6","key":"19_CR2","doi-asserted-by":"publisher","first-page":"8265","DOI":"10.1007\/s10639-022-10943-7","volume":"27","author":"Z Liu","year":"2022","unstructured":"Liu, Z., Kong, X., Liu, S., Yang, Z., Zhang, C.: Looking at MOOC discussion data to uncover the relationship between discussion pacings, learners\u2019 cognitive presence and learning achievements. Educ. Inform. Technol. 27(6), 8265\u20138288 (2022)","journal-title":"Educ. Inform. Technol."},{"key":"19_CR3","doi-asserted-by":"publisher","first-page":"1111","DOI":"10.1016\/j.compedu.2007.11.002","volume":"51","author":"K Hew","year":"2008","unstructured":"Hew, K., Cheung, W.: Attracting student participation in asynchronous online discussions: a case study of peer facilitation. Comput. Educ. 51, 1111\u20131124 (2008)","journal-title":"Comput. Educ."},{"key":"19_CR4","doi-asserted-by":"crossref","unstructured":"Parmar, D., Dewan, M.A.A., Wen,\u00a0D., Lin, F.: Cognitive engagement detection of online learners using GloVe embedding and hybrid LSTM. In: International Conference on Intelligent Tutoring Systems, Thessaloniki, Greece (2024)","DOI":"10.1007\/978-3-031-63031-6_2"},{"issue":"3","key":"19_CR5","doi-asserted-by":"publisher","first-page":"219","DOI":"10.1080\/00461520.2014.965823","volume":"49","author":"MT Chi","year":"2014","unstructured":"Chi, M.T., Wylie, R.: The ICAP framework: Linking cognitive engagement to active learning outcomes. Educ. Psychol. 49(3), 219\u2013243 (2014)","journal-title":"Educ. Psychol."},{"key":"19_CR6","first-page":"993","volume":"3","author":"DMB Blei","year":"2003","unstructured":"Blei, D.M.B., Ng, A.Y., Jordan, M.I.: Latent dirichlet allocation. J. Mach. Learn. Res. 3, 993\u20131022 (2003)","journal-title":"J. Mach. Learn. Res."},{"key":"19_CR7","doi-asserted-by":"crossref","unstructured":"Atapattu, T., Thilakaratne, M., Vivian,\u00a0R.,\u00a0 Falkner,\u00a0 K.: Detecting cognitive engagement using word embeddings within an online teacher professional development community. Comput. Educ. 140, 103594 (2019)","DOI":"10.1016\/j.compedu.2019.05.020"},{"issue":"3","key":"19_CR8","first-page":"416","volume":"29","author":"L Chen","year":"2024","unstructured":"Chen, L.: Integrating deep learning-based educational technologies in biotechnology training: an effectiveness evaluation from a hybrid education perspective. J. Commer. Biotechnol. 29(3), 416\u2013426 (2024)","journal-title":"J. Commer. Biotechnol."},{"issue":"1","key":"19_CR9","doi-asserted-by":"publisher","first-page":"188","DOI":"10.46328\/ijres.3081","volume":"9","author":"EK Essa","year":"2023","unstructured":"Essa, E.K.: The effectiveness of hybrid learning in enhancing academic mindfulness and deeper learning of university students. Inter. J. Res. Educ. Sci. 9(1), 188\u2013202 (2023)","journal-title":"Inter. J. Res. Educ. Sci."},{"key":"19_CR10","doi-asserted-by":"crossref","unstructured":"Bayan Alnasyan, M.B.M.A.:\u00a0 The power of Deep Learning techniques for predicting student performance in Virtual Learning Environments: A systematic literature review. Comput. Educ. Artifi. Intell. 6, 100231 (2024)","DOI":"10.1016\/j.caeai.2024.100231"},{"key":"19_CR11","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1371\/journal.pone.0308607","volume":"19","author":"S Tahir","year":"2024","unstructured":"Tahir, S., Hafeez, Y., Humayun, M., Ahmad, F., Khan, M., Shaheen, M.: Harnessing hybrid deep learning approach for personalized retrieval in e-learning,\u201d. PLoS ONE 19, 1\u201321 (2024)","journal-title":"PLoS ONE"},{"key":"19_CR12","doi-asserted-by":"crossref","unstructured":"Subha, S, Sankaralingam, B.P., Gurusamy, A., Sehar, S., Bavirisetti, .DP.: Personalization-based deep hybrid E-learning model for online course recommendation system.\u00a0 PeerJ Comput. Sci. 9, e1670 (2023)","DOI":"10.7717\/peerj-cs.1670"},{"key":"19_CR13","doi-asserted-by":"crossref","unstructured":"Jawed, S.,\u00a0 \u00a0Faye, I., Malik, A.S.: Deep Learning-Based Assessment Model for Real-Time Identification of Visual Learners Using Raw EEG. IEEE Trans. Neural Syst. Rehabilit. Eng. 32, 378\u2013390 (2024)","DOI":"10.1109\/TNSRE.2024.3351694"},{"key":"19_CR14","doi-asserted-by":"crossref","unstructured":"Alzahab, N.A., et al.: Hybrid deep learning (hDL)-based brain-computer interface (BCI) systems: a systematic review. Brain Sci. 11(1) (2021)","DOI":"10.3390\/brainsci11010075"},{"key":"19_CR15","doi-asserted-by":"crossref","unstructured":"Hussain, T.,\u00a0 \u00a0Yu, L.,\u00a0 \u00a0Asim, M., Ahmed, A., Wani, M.A.: Enhancing E-learning adaptability with automated learning style identification and sentiment analysis: a hybrid deep learning approach for smart education.\u00a0 Information 15(5) (2024)","DOI":"10.3390\/info15050277"},{"key":"19_CR16","doi-asserted-by":"publisher","first-page":"103687","DOI":"10.1109\/ACCESS.2024.3434644","volume":"12","author":"JAIS Masood","year":"2024","unstructured":"Masood, J.A.I.S., Chakravarthy, N.S.K., Asirvatham, D., Marjani, M., Shafiq, D.A., Nidamanuri, S.: A hybrid deep learning model to predict high-risk students in virtual learning environments. IEEE Access 12, 103687\u2013103703 (2024)","journal-title":"IEEE Access"},{"key":"19_CR17","doi-asserted-by":"crossref","unstructured":"Min Zhao, J.S., et al.: An attention-based hybrid deep learning framework integrating brain connectivity and activity of resting-state functional MRI data. Medical Image Anal. 78,\u00a0 102413, (2022)","DOI":"10.1016\/j.media.2022.102413"},{"key":"19_CR18","doi-asserted-by":"crossref","unstructured":"Kowsher, M., et al.: LSTM-ANN & BiLSTM-ANN: hybrid deep learning models for enhanced classification accuracy. Proc. Comput. Sci. 193, 131\u2013140 (2021)","DOI":"10.1016\/j.procs.2021.10.013"},{"key":"19_CR19","doi-asserted-by":"crossref","unstructured":"Altaf, S., Asad, R., Ahmad, S., Ahmed, I., Abdollahian, M., Zaindin, M.: A hybrid framework of deep learning techniques to predict online performance of learners during COVID-19 pandemic.\u00a0 Sustainability\u00a0 15 (2023)","DOI":"10.3390\/su151511731"},{"key":"19_CR20","unstructured":"spaCy: Industrial-Strength Natural Language Processing in Python.\u00a0\u00a0https:\/\/spacy.io\/. Accessed 30 12 2024"},{"key":"19_CR21","unstructured":"BERT base model (uncased). https:\/\/huggingface.co\/google-bert\/bert-base-uncased. Accessed 30 12 2024]"},{"key":"19_CR22","doi-asserted-by":"crossref","unstructured":"Dai, Z., Wang, X., Pin Ni, P.,\u00a0 Li, Y.,\u00a0 Li,\u00a0G.,\u00a0 Bai, X.:\u00a0 Named Entity Recognition Using BERT BiLSTM CRF for Chinese Electronic Health Records. In: International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, Suzhou, China (2019)","DOI":"10.1109\/CISP-BMEI48845.2019.8965823"},{"key":"19_CR23","volume-title":"BERT-BiLSTM Model for entity recognition in clinical text,\u201d in CEUR Workshop Proceedings","author":"Z Zhu","year":"2022","unstructured":"Zhu, Z., Wang, L.: BERT-BiLSTM Model for entity recognition in clinical text,\u201d in CEUR Workshop Proceedings. A Coruna, Spain (2022)"},{"issue":"42","key":"19_CR24","first-page":"1","volume":"56","author":"HK Maragheh","year":"2024","unstructured":"Maragheh, H.K., Gharehchopogh, F.S., Majidzadeh, K., Sangar, A.B.: A hybrid model based on convolutional neural network and long short-term memory for multi-label text. Neural. Process. Lett. 56(42), 1\u201331 (2024)","journal-title":"Neural. Process. Lett."},{"key":"19_CR25","unstructured":"Topic modeling for humans. https:\/\/radimrehurek.com\/gensim\/. Accessed 30 12 2024"},{"key":"19_CR26","unstructured":"Agrawal,\u00a0A., Paepcke, A.: The Stanford MOOCPosts Data Set. https:\/\/datastage.stanford.edu\/StanfordMoocPosts\/. Accessed 12 February 2024"},{"key":"19_CR27","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.knosys.2017.04.006","volume":"126","author":"C Chen","year":"2017","unstructured":"Chen, C., Ren, J.: Forum latent Dirichlet allocation for user interest discovery. Knowl.-Based Syst. 126, 1\u20137 (2017)","journal-title":"Knowl.-Based Syst."},{"key":"19_CR28","unstructured":"pyLDAvis. https:\/\/github.com\/bmabey\/pyLDAvis\/blob\/master\/notebooks\/pyLDAvis_overview.ipynb. Accessed 21 12 2024"}],"container-title":["Lecture Notes in Computer Science","Learning and Collaboration Technologies"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-93567-1_19","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,5,31]],"date-time":"2025-05-31T04:47:20Z","timestamp":1748666840000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-93567-1_19"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"ISBN":["9783031935664","9783031935671"],"references-count":28,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-93567-1_19","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"25 May 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"HCII","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Human-Computer Interaction","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Gothenburg","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Sweden","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22 June 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27 June 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"hcii2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/2025.hci.international\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}