{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T02:03:38Z","timestamp":1760148218592,"version":"build-2065373602"},"reference-count":24,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2023,4,10]],"date-time":"2023-04-10T00:00:00Z","timestamp":1681084800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Technical University of Sofia","award":["\u041a\u041f-06-H47\/4"],"award-info":[{"award-number":["\u041a\u041f-06-H47\/4"]}]},{"name":"Bulgarian FNI","award":["\u041a\u041f-06-H47\/4"],"award-info":[{"award-number":["\u041a\u041f-06-H47\/4"]}]},{"name":"Modeling and Research of Intelligent Educational Systems and Sensor Networks (ISOSeM)","award":["\u041a\u041f-06-H47\/4"],"award-info":[{"award-number":["\u041a\u041f-06-H47\/4"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Informatics"],"abstract":"<jats:p>During the pandemic, universities were forced to convert their educational process online. Students had to adapt to new educational conditions and the proposed online environment. Now, we are back to the traditional blended learning environment and wish to understand the students\u2019 attitudes and perceptions of online learning, knowing that they are able to compare blended and online modes. The aim of this paper is to present the performed predictive analysis regarding the students\u2019 online learning performance taking into account their opinion. The predictive models are created through a supervised machine learning algorithm based on Artificial Neural Networks and are characterized with high accuracy. The analysis is based on generated synthetic datasets, ensuring a high level of students\u2019 privacy preservation.<\/jats:p>","DOI":"10.3390\/informatics10020037","type":"journal-article","created":{"date-parts":[[2023,4,10]],"date-time":"2023-04-10T03:24:18Z","timestamp":1681097058000},"page":"37","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Towards Independent Students\u2019 Activities, Online Environment and Learning Performance: An Investigation through Synthetic Data and Artificial Neural Networks"],"prefix":"10.3390","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8474-6226","authenticated-orcid":false,"given":"Malinka","family":"Ivanova","sequence":"first","affiliation":[{"name":"Department of Informatics, Faculty of Applied Mathematics and Informatics, Technical University of Sofia, Blvd. Kl. Ohridski 8, 1797 Sofia, Bulgaria"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8482-4792","authenticated-orcid":false,"given":"Tsvetelina","family":"Petrova","sequence":"additional","affiliation":[{"name":"Department of Energy and Mechanical Engineering, Technical College of Sofia, Technical University of Sofia, Blvd. Kl. Ohridski 8, 1797 Sofia, Bulgaria"}]}],"member":"1968","published-online":{"date-parts":[[2023,4,10]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Holzer, J., L\u00fcftenegger, M., Korlat, S., Pelikan, E., Salmela-Aro, K., Spiel, C., and Schober, B. (2021). Higher Education in Times of COVID-19: University Students\u2019 Basic Need Satisfaction, Self-Regulated Learning, and Well-Being. AERA Open, 7.","DOI":"10.1177\/23328584211003164"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"573590","DOI":"10.3389\/fpsyg.2021.573590","article-title":"The Empirical Study of College Students\u2019 E-Learning Effectiveness and Its Antecedents Toward the COVID-19 Epidemic Environment","volume":"12","author":"Wang","year":"2021","journal-title":"Front. Psychol. Sec. Educ. Psychol."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"10625","DOI":"10.1007\/s10639-022-11054-z","article-title":"Effectiveness of using E-learning systems during COVID-19 in Saudi Arabia: Experiences and perceptions analysis of engineering students","volume":"27","author":"Alkabaa","year":"2022","journal-title":"Educ. Inf. Technol."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"405","DOI":"10.1007\/s10758-021-09541-2","article-title":"Learning Analytics in Online Learning Environment: A Systematic Review on the Focuses and the Types of Student-Related Analytics Data","volume":"27","author":"Kew","year":"2022","journal-title":"Technol. Knowl. Learn."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Liu, B., Lu, J., Wang, P., Zhang, J., Zeng, D., Qian, Z., and Ge, S. (2022, January 26\u201328). Privacy-Preserving Student Learning with Differentially Private Data-Free Distillation. Proceedings of the 2022 IEEE 24th International Workshop on Multimedia Signal Processing (MMSP), Shanghai, China.","DOI":"10.1109\/MMSP55362.2022.9950001"},{"key":"ref_6","unstructured":"Wagner, P. (2022, November 17). Privacy Enhancing Technologies and Synthetic Data. Available online: https:\/\/ssrn.com\/abstract=3762686."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Wang, S., Sun, Z., and Chen, Y. (2022). Effects of higher education institutes\u2019 artificial intelligence capability on students\u2019 self-efficacy, creativity and learning performance. Educ. Inf. Technol.","DOI":"10.1007\/s10639-022-11338-4"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"835","DOI":"10.1016\/j.procs.2021.03.104","article-title":"Artificial Intelligence and Machine Learning to Predict Student Performance during the COVID-19","volume":"184","author":"Tarik","year":"2021","journal-title":"Procedia Comput. Sci."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"983","DOI":"10.1080\/08839514.2021.1922847","article-title":"Artificial Neural Networks for Educational Data Mining in Higher Education: A Systematic Literature Review","volume":"35","author":"Okewu","year":"2021","journal-title":"Appl. Artif. Intell."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Gudkova, Y., Reznikova, S., Samoletova, M., and Sytnikova, E. (2021, January 24\u201326). Effectiveness of Moodle in student\u2019s independent work. Proceedings of the E3S Web of Conferences, Rostov-on-Don, Russia.","DOI":"10.1051\/e3sconf\/202127312084"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"165","DOI":"10.1504\/IJIL.2017.081939","article-title":"An assessment of the effectiveness of Moodle e-learning system for undergraduate public administration education","volume":"21","author":"Umek","year":"2017","journal-title":"Int. J. Innov. Learn."},{"key":"ref_12","first-page":"1124","article-title":"Effectiveness of Moodle in the Learning of Introductory Physics During COVID-19 Pandemic: A Case Study at the University of Zambia","volume":"6","author":"Rajan","year":"2021","journal-title":"Int. J. Innov. Sci. Res. Technol."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Dyrek, N., Wikarek, A., Niemiec, M., Owczarek, A.J., Olszanecka-Glinianowicz, M., and Koce\u0142ak, P. (2022). The perception of e-learning during the SARS-CoV-2 pandemic by students of medical universities in Poland\u2014A survey-based study. BMC Med. Educ., 22.","DOI":"10.1186\/s12909-022-03600-7"},{"key":"ref_14","first-page":"383","article-title":"The Impact and Effectiveness of E-Learning on Teaching and Learning","volume":"5","author":"Encarnacion","year":"2020","journal-title":"Int. J. Comput. Sci. Res."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"410","DOI":"10.1119\/5.0028641","article-title":"Bringing Physical Physics Classroom Online\u2014Challenges of Online Teaching in the New Normal","volume":"59","author":"Tan","year":"2021","journal-title":"Phys. Teach."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Tan, D.Y., Kwan, W.L., Koh, L.L.A., Pee, G.-Y.M., Lur, K.T., and Yeo, Z.Y. (2022, January 28\u201331). Virtual Dissection Activities as a Strategy for Blended Synchronous Learning in the New Normal. Proceedings of the 2022 IEEE Global Engineering Education Conference (EDUCON), Tunis, Tunisia.","DOI":"10.1109\/EDUCON52537.2022.9766498"},{"key":"ref_17","first-page":"5416722","article-title":"Analysis of Artificial Neural Network: Architecture, Types, and Forecasting Applications","volume":"2022","author":"Madhiarasan","year":"2022","journal-title":"J. Electr. Comput. Eng."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Dharmasaroja, P., and Kingkaew, N. (2016, January 13\u201315). Application of artificial neural networks for prediction of learning performances. Proceedings of the 2016 12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD), Changsha, China.","DOI":"10.1109\/FSKD.2016.7603268"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Huang, C., Zhou, J., Chen, J., and Yang, J. (2021). A feature weighted support vector machine and artificial neural network algorithm for academic course performance prediction. Neural Comput. Appl., 1\u201313.","DOI":"10.1007\/s00521-021-05962-3"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Hamadneh, N.N., Atawneh, S., Khan, W.A., Almejalli, K.A., and Alhomoud, A. (2022). Using Artificial Intelligence to Predict Students\u2019 Academic Performance in Blended Learning. Sustainability, 14.","DOI":"10.3390\/su141811642"},{"key":"ref_21","unstructured":"Leelaluk, S., Minematsu, T., Taniguchi, Y., Okubo, F., and Shimada, A. (2022, January 21\u201322). Predicting student performance based on Lecture Materials data using Neural Network Models. Proceedings of the CEUR Workshop 4th Workshop on Predicting Performance Based on the Analysis of Reading Behavior, Online. Available online: https:\/\/sites.google.com\/view\/lak22datachallenge."},{"key":"ref_22","first-page":"157","article-title":"Prediction of Students\u2019 Academic Performance using Artificial Neural Network","volume":"40","author":"Ahmad","year":"2018","journal-title":"Bull. Educ. Res. Dec."},{"key":"ref_23","unstructured":"MOSTLY AI (2023, January 23). Available online: https:\/\/mostly.ai\/synthetic-data\/."},{"key":"ref_24","unstructured":"(2023, January 23). RapidMiner Studio Manual. Available online: https:\/\/docs.rapidminer.com\/downloads\/RapidMiner-v6-user-manual.pdf."}],"container-title":["Informatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2227-9709\/10\/2\/37\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T19:13:02Z","timestamp":1760123582000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2227-9709\/10\/2\/37"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,4,10]]},"references-count":24,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2023,6]]}},"alternative-id":["informatics10020037"],"URL":"https:\/\/doi.org\/10.3390\/informatics10020037","relation":{},"ISSN":["2227-9709"],"issn-type":[{"type":"electronic","value":"2227-9709"}],"subject":[],"published":{"date-parts":[[2023,4,10]]}}}