{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,18]],"date-time":"2026-03-18T00:52:25Z","timestamp":1773795145689,"version":"3.50.1"},"reference-count":15,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2021,11,2]],"date-time":"2021-11-02T00:00:00Z","timestamp":1635811200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,11,2]],"date-time":"2021-11-02T00:00:00Z","timestamp":1635811200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["SN COMPUT. SCI."],"published-print":{"date-parts":[[2022,1]]},"DOI":"10.1007\/s42979-021-00944-7","type":"journal-article","created":{"date-parts":[[2021,11,2]],"date-time":"2021-11-02T17:23:17Z","timestamp":1635873797000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["Computational Intelligence Enabled Student Performance Estimation in the Age of COVID-19"],"prefix":"10.1007","volume":"3","author":[{"given":"Vipul","family":"Bansal","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3679-3498","authenticated-orcid":false,"given":"Himanshu","family":"Buckchash","sequence":"additional","affiliation":[]},{"given":"Balasubramanian","family":"Raman","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,11,2]]},"reference":[{"key":"944_CR1","doi-asserted-by":"crossref","unstructured":"Al-Shehri H, Al-Qarni A, Al-Saati L, Batoaq A, Badukhen H, Alrashed S, Alhiyafi J, Olatunji SO. Student performance prediction using support vector machine and k-nearest neighbor. In: 2017 IEEE 30th Canadian conference on electrical and computer engineering (CCECE). IEEE; 2017, p. 1\u20134.","DOI":"10.1109\/CCECE.2017.7946847"},{"key":"944_CR2","doi-asserted-by":"publisher","first-page":"67822","DOI":"10.1109\/ACCESS.2020.2985318","volume":"8","author":"H Buckchash","year":"2020","unstructured":"Buckchash H, Raman B. Variational conditioning of deep recurrent networks for modeling complex motion dynamics. IEEE Access. 2020;8:67822\u201334.","journal-title":"IEEE Access"},{"key":"944_CR3","doi-asserted-by":"publisher","first-page":"112934","DOI":"10.1016\/j.psychres.2020.112934","volume":"5","author":"W Cao","year":"2020","unstructured":"Cao W, Fang Z, Hou G, Han M, Xu X, Dong J, Zheng J. The psychological impact of the Covid-19 epidemic on college students in China. Psychiatry Res. 2020;5:112934.","journal-title":"Psychiatry Res"},{"issue":"01","key":"944_CR4","doi-asserted-by":"publisher","first-page":"1450005","DOI":"10.1142\/S1469026814500059","volume":"13","author":"JF Chen","year":"2014","unstructured":"Chen JF, Do QH. Training neural networks to predict student academic performance: a comparison of cuckoo search and gravitational search algorithms. Int J Comput Intell Appl. 2014;13(01):1450005.","journal-title":"Int J Comput Intell Appl"},{"key":"944_CR5","doi-asserted-by":"publisher","first-page":"100313","DOI":"10.1016\/j.edurev.2020.100313","volume":"29","author":"LE Delnoij","year":"2020","unstructured":"Delnoij LE, Dirkx KJ, Janssen JP, Martens RL. Predicting and resolving non-completion in higher (online) education\u2014a literature review. Educ Res Rev. 2020;29:100313.","journal-title":"Educ Res Rev"},{"issue":"7","key":"944_CR6","doi-asserted-by":"publisher","first-page":"749","DOI":"10.1057\/palgrave.jors.2601717","volume":"55","author":"F Duckworth","year":"2004","unstructured":"Duckworth F, Lewis A. A successful operational research intervention in one-day cricket. J Oper Res Soc. 2004;55(7):749\u201359.","journal-title":"J Oper Res Soc"},{"key":"944_CR7","doi-asserted-by":"crossref","unstructured":"Harvey JL, Kumar SA. A practical model for educators to predict student performance in k-12 education using machine learning. In: 2019 IEEE symposium series on computational intelligence (SSCI). IEEE; 2019. p. 3004\u201311.","DOI":"10.1109\/SSCI44817.2019.9003147"},{"key":"944_CR8","doi-asserted-by":"crossref","unstructured":"Hellas A, Ihantola P, Petersen A, Ajanovski VV, Gutica M, Hynninen T, Knutas A, Leinonen J, Messom C, Liao SN. Predicting academic performance: a systematic literature review. In: Proceedings companion of the 23rd annual ACM conference on innovation and technology in computer science education. 2018. p. 175\u201399.","DOI":"10.1145\/3293881.3295783"},{"key":"944_CR9","doi-asserted-by":"crossref","unstructured":"Li Z, Shang C, Shen Q. Fuzzy-clustering embedded regression for predicting student academic performance. In: 2016 IEEE international conference on fuzzy systems (FUZZ-IEEE). IEEE; 2016. p. 344\u201351.","DOI":"10.1109\/FUZZ-IEEE.2016.7737707"},{"issue":"1","key":"944_CR10","first-page":"43","volume":"9","author":"I Livieris","year":"2016","unstructured":"Livieris I, Mikropoulos T, Pintelas P. A decision support system for predicting students\u2019 performance. Themes Sci Technol Educ. 2016;9(1):43\u201357.","journal-title":"Themes Sci Technol Educ"},{"issue":"2","key":"944_CR11","first-page":"171","volume":"12","author":"DM Olive","year":"2019","unstructured":"Olive DM, Huynh DQ, Reynolds M, Dougiamas M, Wiese D. A quest for a one-size-fits-all neural network: early prediction of students at risk in online courses. IEEE Transa LearnTechnol. 2019;12(2):171\u201383.","journal-title":"IEEE Transa LearnTechnol"},{"key":"944_CR12","doi-asserted-by":"crossref","unstructured":"Patil AP, Ganesan K, Kanavalli A. Effective deep learning model to predict student grade point averages. In: 2017 IEEE international conference on computational intelligence and computing research (ICCIC). IEEE; 2017. p. 1\u20136.","DOI":"10.1109\/ICCIC.2017.8524317"},{"key":"944_CR13","doi-asserted-by":"publisher","unstructured":"Sahu P. Closure of universities due to coronavirus disease 2019 (Covid-19): impact on education and mental health of students and academic staff. Cureus. 2020;12(4). https:\/\/doi.org\/10.7759\/cureus.7541.","DOI":"10.7759\/cureus.7541"},{"key":"944_CR14","doi-asserted-by":"crossref","unstructured":"Spinelli A, Pellino G. Covid-19 pandemic: perspectives on an unfolding crisis. The British journal of surgery. 2020; 107(7):785\u2013787.","DOI":"10.1002\/bjs.11627"},{"issue":"1","key":"944_CR15","doi-asserted-by":"publisher","first-page":"39","DOI":"10.1186\/s41239-019-0171-0","volume":"16","author":"O Zawacki-Richter","year":"2019","unstructured":"Zawacki-Richter O, Mar\u00edn VI, Bond M, Gouverneur F. Systematic review of research on artificial intelligence applications in higher education\u2014where are the educators? Int J Educ Technol Higher Educ. 2019;16(1):39.","journal-title":"Int J Educ Technol Higher Educ"}],"container-title":["SN Computer Science"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s42979-021-00944-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s42979-021-00944-7\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s42979-021-00944-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,1,10]],"date-time":"2022-01-10T18:38:24Z","timestamp":1641839904000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s42979-021-00944-7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,11,2]]},"references-count":15,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2022,1]]}},"alternative-id":["944"],"URL":"https:\/\/doi.org\/10.1007\/s42979-021-00944-7","relation":{},"ISSN":["2662-995X","2661-8907"],"issn-type":[{"value":"2662-995X","type":"print"},{"value":"2661-8907","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,11,2]]},"assertion":[{"value":"3 November 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"18 October 2021","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"2 November 2021","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"On behalf of all authors, the corresponding author states that there is no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"This content has been made available to all.","name":"free","label":"Free to read"}],"article-number":"41"}}