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Force}}, title = {Computing Curricula 2020: Paradigms for Global Computing Education}, year = {2020}, isbn = {9781450390590}, publisher = {Association for Computing Machinery}, address = {New York, NY, USA}, pages={19, 20} } # Estudios primarios (new) # Scopus # EXPORT DATE: 10 April 2023 @ARTICLE{Shilbayeh2021562, author={Shilbayeh, S. and Abonamah, A.}, title={Predicting student enrolments and attrition patterns in higher educational institutions using machine learning}, journal={International Arab Journal of Information Technology}, year={2021}, volume={18}, number={4}, pages={562-567}, doi={10.34028/18/4/8}, note={cited By 4}, url={https://www.scopus.com/inward/record.uri?eid=2-s2.0-85110631056&doi=10.34028%2f18%2f4%2f8&partnerID=40&md5=df6ca88561c04dc1b9a2b670dbfd7939}, publisher={Zarka Private University}, document_type={Article}, source={Scopus}, } @ARTICLE{Perez202157, author={Perez, J.G. and Perez, E.S.}, title={Predicting Student Program Completion Using Naïve Bayes Classification Algorithm}, journal={International Journal of Modern Education and Computer Science}, year={2021}, volume={13}, number={3}, pages={57-67}, doi={10.5815/IJMECS.2021.03.05}, note={cited By 5}, url={https://www.scopus.com/inward/record.uri?eid=2-s2.0-85126148117&doi=10.5815%2fIJMECS.2021.03.05&partnerID=40&md5=4b2a1120d172ab019073da333d6b3b38}, publisher={Modern Education and Computer Science Press}, document_type={Article}, source={Scopus}, } @ARTICLE{Alwarthan2022107649, author={Alwarthan, S. and Aslam, N. and Khan, I.U.}, title={An Explainable Model for Identifying At-Risk Student at Higher Education}, journal={IEEE Access}, year={2022}, volume={10}, pages={107649-107668}, doi={10.1109/ACCESS.2022.3211070}, note={cited By 1}, url={https://www.scopus.com/inward/record.uri?eid=2-s2.0-85139451582&doi=10.1109%2fACCESS.2022.3211070&partnerID=40&md5=e57c9f6d41059efe172d9a82d5ab4747}, publisher={Institute of Electrical and Electronics Engineers Inc.}, document_type={Article}, source={Scopus}, } @ARTICLE{Khan2021, author={Khan, I. and Ahmad, A.R. and Jabeur, N. and Mahdi, M.N.}, title={An artificial intelligence approach to monitor student performance and devise preventive measures}, journal={Smart Learning Environments}, year={2021}, volume={8}, number={1}, doi={10.1186/s40561-021-00161-y}, art_number={17}, note={cited By 6}, url={https://www.scopus.com/inward/record.uri?eid=2-s2.0-85114501475&doi=10.1186%2fs40561-021-00161-y&partnerID=40&md5=c57ce71f62d6094a3bfd9f3196600e0b}, publisher={Springer}, document_type={Article}, source={Scopus}, } @ARTICLE{Sahlaoui2021152688, author={Sahlaoui, H. and Alaoui, E.A.A. and Nayyar, A. and Agoujil, S. and Jaber, M.M.}, title={Predicting and Interpreting Student Performance Using Ensemble Models and Shapley Additive Explanations}, journal={IEEE Access}, year={2021}, volume={9}, pages={152688-152703}, doi={10.1109/ACCESS.2021.3124270}, note={cited By 4}, url={https://www.scopus.com/inward/record.uri?eid=2-s2.0-85118542795&doi=10.1109%2fACCESS.2021.3124270&partnerID=40&md5=a74d7ccee09d0dd0051f1bb714a4aef9}, publisher={Institute of Electrical and Electronics Engineers Inc.}, document_type={Article}, source={Scopus}, } @ARTICLE{Segura2022, author={Segura, M. and Mello, J. and Hernández, A.}, title={Machine Learning Prediction of University Student Dropout: Does Preference Play a Key Role?}, journal={Mathematics}, year={2022}, volume={10}, number={18}, doi={10.3390/math10183359}, art_number={3359}, note={cited By 2}, url={https://www.scopus.com/inward/record.uri?eid=2-s2.0-85138658944&doi=10.3390%2fmath10183359&partnerID=40&md5=714776e99fdd4866906ed0bd946e2859}, publisher={MDPI}, document_type={Article}, source={Scopus}, } @ARTICLE{Latif20221051, author={Latif, G. and Alghazo, R. and Pilotti, M.A.E. and Ben Brahim, G.}, title={Identifying "At-Risk" Students: An AI-based Prediction Approach}, journal={International Journal of Computing and Digital Systems}, year={2022}, volume={11}, number={1}, pages={1051-1059}, doi={10.12785/ijcds/110184}, note={cited By 3}, url={https://www.scopus.com/inward/record.uri?eid=2-s2.0-85129619369&doi=10.12785%2fijcds%2f110184&partnerID=40&md5=d9c778ef345bc44eeb1d2ce088ea07ef}, publisher={University of Bahrain}, document_type={Article}, source={Scopus}, } @ARTICLE{Balaji2021, author={Balaji, P. and Alelyani, S. and Qahmash, A. and Mohana, M.}, title={Contributions of machine learning models towards student academic performance prediction: A systematic review}, journal={Applied Sciences (Switzerland)}, year={2021}, volume={11}, number={21}, doi={10.3390/app112110007}, art_number={10007}, note={cited By 8}, url={https://www.scopus.com/inward/record.uri?eid=2-s2.0-85118180499&doi=10.3390%2fapp112110007&partnerID=40&md5=fe4637a240b2d35b24e90439cc932a3c}, publisher={MDPI}, document_type={Article}, source={Scopus}, } @ARTICLE{Suhaimi20191, author={Suhaimi, N.M. and Abdul-Rahman, S. and Mutalib, S. and Hamid, N.H.A. and Malik, A.M.A.}, title={Review on Predicting Students’ Graduation Time Using Machine Learning Algorithms}, journal={International Journal of Modern Education and Computer Science}, year={2019}, volume={11}, number={7}, pages={1-13}, doi={10.5815/ijmecs.2019.07.01}, note={cited By 18}, url={https://www.scopus.com/inward/record.uri?eid=2-s2.0-85075745553&doi=10.5815%2fijmecs.2019.07.01&partnerID=40&md5=379a14480656e38f4b677cbd0557d3a2}, publisher={Modern Education and Computer Science Press}, document_type={Article}, source={Scopus}, } @ARTICLE{Yağcı2022, author={Yağcı, M.}, title={Educational data mining: prediction of students' academic performance using machine learning algorithms}, journal={Smart Learning Environments}, year={2022}, volume={9}, number={1}, doi={10.1186/s40561-022-00192-z}, art_number={11}, note={cited By 23}, url={https://www.scopus.com/inward/record.uri?eid=2-s2.0-85126250565&doi=10.1186%2fs40561-022-00192-z&partnerID=40&md5=d7222b249dc6c3ad747777bc12596884}, publisher={Springer}, document_type={Article}, source={Scopus}, } @ARTICLE{Fernandez-Garcia2021133076, author={Fernandez-Garcia, A.J. and Preciado, J.C. and Melchor, F. and Rodriguez-Echeverria, R. and Conejero, J.M. and Sanchez-Figueroa, F.}, title={A real-life machine learning experience for predicting university dropout at different stages using academic data}, journal={IEEE Access}, year={2021}, volume={9}, pages={133076-133090}, doi={10.1109/ACCESS.2021.3115851}, note={cited By 7}, url={https://www.scopus.com/inward/record.uri?eid=2-s2.0-85117054399&doi=10.1109%2fACCESS.2021.3115851&partnerID=40&md5=26a3796f13998d88470e95a739ba8ee6}, publisher={Institute of Electrical and Electronics Engineers Inc.}, document_type={Article}, source={Scopus}, } @ARTICLE{Guzmán2022, author={Guzmán, A. and Barragán, S. and Cala-Vitery, F.}, title={Comparative Analysis of Dropout and Student Permanence in Rural Higher Education}, journal={Sustainability (Switzerland)}, year={2022}, volume={14}, number={14}, doi={10.3390/su14148871}, art_number={8871}, note={cited By 1}, url={https://www.scopus.com/inward/record.uri?eid=2-s2.0-85136408686&doi=10.3390%2fsu14148871&partnerID=40&md5=cb934fb25c47d243ba6aaa039bb73d45}, publisher={MDPI}, document_type={Article}, source={Scopus}, } # IEEE @INPROCEEDINGS{8820813, author={de O. Santos, Kelly J. and Menezes, Angelo G. and de Carvalho, Andre B. and Montesco, Carlos A. E.}, booktitle={2019 IEEE 19th International Conference on Advanced Learning Technologies (ICALT)}, title={Supervised Learning in the Context of Educational Data Mining to Avoid University Students Dropout}, year={2019}, volume={2161-377X}, number={}, pages={207-208}, doi={10.1109/ICALT.2019.00068} } @INPROCEEDINGS{8484847, author={Perez, Boris and Castellanos, Camilo and Correal, Dario}, booktitle={2018 IEEE 1st Colombian Conference on Applications in Computational Intelligence (ColCACI)}, title={Applying Data Mining Techniques to Predict Student Dropout: A Case Study}, year={2018}, volume={}, number={}, pages={1-6}, doi={10.1109/ColCACI.2018.8484847} } @INPROCEEDINGS{9450735, author={Chitti, Manjari and Chitti, Padmini and Jayabalan, Manoj}, booktitle={2020 13th International Conference on Developments in eSystems Engineering (DeSE)}, title={Need for Interpretable Student Performance Prediction}, year={2020}, volume={}, number={}, pages={269-272}, doi={10.1109/DeSE51703.2020.9450735} } # Estudios primarios (old) # ================== @article{Bedregal2020, author = {Norka Bedregal-Alpaca and Víctor Cornejo-Aparicio and Joshua Zárate-Valderrama and Pedro Yanque-Churo}, title = {Classification Models for Determining Types of Academic Risk and Predicting Dropout in University Students}, journal = {International Journal of Advanced Computer Science and Applications}, doi = {10.14569/IJACSA.2020.0110133}, url = {http://dx.doi.org/10.14569/IJACSA.2020.0110133}, year = {2020}, publisher = {The Science and Information Organization}, volume = {11}, number = {1} } @Article{Aldowah2020, author={Aldowah, Hanan and Al-Samarraie, Hosam and Alzahrani, Ahmed Ibrahim and Alalwan, Nasser}, title={Factors affecting student dropout in MOOCs: a cause and effect decision‐making model}, journal={Journal of Computing in Higher Education}, year={2020}, month={08}, day={01}, volume={32}, number={2}, pages={429-454}, issn={1867-1233}, doi={10.1007/s12528-019-09241-y}, url={https://doi.org/10.1007/s12528-019-09241-y} } @article{Alvarez2020, author = {Niurys Lázaro Alvarez and Zoraida Callejas and David Griol}, title = {Predicting Computer Engineering students' dropout in Cuban Higher Education with pre-enrollment and early performance data}, journal = {Journal of Technology and Science Education}, volume = {10}, number = {2}, year = {2020}, keywords = {Dropout, retention, promotion, higher education, data analysis, computer engineering, automatic classification}, issn = {2013-6374}, pages = {241--258}, doi = {10.3926/jotse.922}, url = {https://www.jotse.org/index.php/jotse/article/view/922} } @Article{Flores2022, AUTHOR = {Flores, Vaneza and Heras, Stella and Julian, Vicente}, TITLE = {Comparison of Predictive Models with Balanced Classes Using the SMOTE Method for the Forecast of Student Dropout in Higher Education}, JOURNAL = {Electronics}, VOLUME = {11}, YEAR = {2022}, NUMBER = {3}, ARTICLE-NUMBER = {457}, URL = {https://www.mdpi.com/2079-9292/11/3/457}, ISSN = {2079-9292}, DOI = {10.3390/electronics11030457} } @Article{Moreira2022, AUTHOR = {Moreira da Silva, Diogo E. and Solteiro Pires, Eduardo J. and Reis, Arsénio and de Moura Oliveira, Paulo B. and Barroso, João}, TITLE = {Forecasting Students Dropout: A UTAD University Study}, JOURNAL = {Future Internet}, VOLUME = {14}, YEAR = {2022}, NUMBER = {3}, ARTICLE-NUMBER = {76}, URL = {https://www.mdpi.com/1999-5903/14/3/76}, ISSN = {1999-5903}, DOI = {10.3390/fi14030076} } # bad bibtex and encoding @article{Zarate2021, author={Zárate-Valderrama, Joshua AND Bedregal-Alpaca, Norka AND Cornejo-Aparicio, Víctor}, title = {Modelos de clasificación para reconocer patrones de deserción en estudiantes universitarios}, ISSN = {0718-3305}, journal = {Ingeniare. Revista chilena de ingeniería}, language = {es}, volume = {29}, year = {2021}, month = {03}, pages = {168 - 177}, publisher = {scielocl}, crossref = {10.4067/S0718-33052021000100168}, } # Alban2019 @article{Alban2019, author = {Mayra Alban and David Mauricio}, title = {Neural Networks to Predict Dropout at the Universities}, journal = {International Journal of Machine Learning and Computing}, volume = {9}, number = {2}, pages = {149-153}, year = {2019}, doi = {10.18178/ijmlc.2019.9.2.779}, } # Fernandez2019 @article{Fernandez2019, author={Fernández-Martín, Tatiana and Solís-Salazar, Martín and Hernández-Jiménez, María and Moreira-Mora, Tania}, title={A Multinomial and Predictive Analysis of Factors Associated with University Dropout}, volume={23}, url={https://www.revistas.una.ac.cr/index.php/EDUCARE/article/view/9038}, DOI={10.15359/ree.23-1.5}, number={1}, journal={Revista Electrónica Educare}, year={2019}, month={01}, pages={1-25} } # New (incluir en cadena de busqueda y formulario de extraccion) # ============================================================== @article{Kemper2020, title = {Predicting student dropout: {A} machine learning approach}, volume = {10}, issn = {2156-8235, 2156-8243}, shorttitle = {Predicting student dropout}, url = {https://www.tandfonline.com/doi/full/10.1080/21568235.2020.1718520}, doi = {10.1080/21568235.2020.1718520}, language = {en}, number = {1}, urldate = {2023-04-18}, journal = {European Journal of Higher Education}, author = {Kemper, Lorenz and Vorhoff, Gerrit and Wigger, Berthold U.}, month = jan, year = {2020}, pages = {28--47} } # CONCEPTOS @book{russell_artificial_2010, address = {Upper Saddle River}, edition = {3rd ed}, series = {Prentice {Hall} series in artificial intelligence}, title = {Artificial intelligence: a modern approach}, isbn = {978-0-13-604259-4}, shorttitle = {Artificial intelligence}, publisher = {Prentice Hall}, author = {Russell, Stuart J. and Norvig, Peter and Davis, Ernest}, year = {2010}, keywords = {Artificial intelligence}, } @book{mohri_foundations_2012, address = {Cambridge, MA}, series = {Adaptive computation and machine learning series}, title = {Foundations of machine learning}, isbn = {978-0-262-01825-8}, publisher = {MIT Press}, author = {Mohri, Mehryar and Rostamizadeh, Afshin and Talwalkar, Ameet}, year = {2012}, keywords = {Computer algorithms, Machine learning}, } @book{mitchell_machine_1997, address = {New York}, series = {{McGraw}-{Hill} series in computer science}, title = {Machine {Learning}}, isbn = {978-0-07-042807-2}, publisher = {McGraw-Hill}, author = {Mitchell, Tom M.}, year = {1997}, keywords = {Computer algorithms, Machine learning}, } @book{bishop_pattern_2006, address = {New York}, series = {Information science and statistics}, title = {Pattern recognition and machine learning}, isbn = {978-0-387-31073-2}, publisher = {Springer}, author = {Bishop, Christopher M.}, year = {2006}, keywords = {Machine learning, Pattern perception}, } # Review (E.g., systematic reviews, not exactly university dropout analysis) # =================================================================== # Agrusti2019 # Agrusti, F., Bonavolontà, G., & Mezzini, M. (2019). University Dropout Prediction through Educational Data Mining Techniques: A Systematic Review. Journal of E-Learning and Knowledge Society, 15(3), 161-182. https://doi.org/10.20368/1971-8829/1135017 @article{Agrusti2019, author = {Agrusti, F and Bonavolontà, G and Mezzini, M}, title = {University Dropout Prediction through Educational Data Mining Techniques: A Systematic Review}, journal = {Journal of E-Learning and Knowledge Society}, doi = {10.20368/1971-8829/1135017}, url = {https://doi.org/10.20368/1971-8829/1135017}, year = {2019}, volume = {15}, number = {3}, pages = {161-182} } # Yang2020 # Y. Yang, P. Fu, X. Yang, H. Hong and D. Zhou, "Mooc learner’s final grade prediction based on an improved random forests method," Computers, Materials & Continua, vol. 65, no.3, pp. 2413–2423, 2020. @Article{Yang2020, AUTHOR = {Yang, Yuqing and Fu, Peng and Yang, Xiaojiang and Hong, Hong and Zhou, Dequn}, TITLE = {MOOC Learner’s Final Grade Prediction Based on an Improved Random Forests Method}, JOURNAL = {Computers, Materials \& Continua}, VOLUME = {65}, YEAR = {2020}, NUMBER = {3}, PAGES = {2413--2423}, URL = {http://www.techscience.com/cmc/v65n3/40178}, ISSN = {1546-2226}, DOI = {10.32604/cmc.2020.011881} } # Extra # ===== @Inbook{Fellbaum2010, author="Fellbaum, Christiane", editor="Poli, Roberto and Healy, Michael and Kameas, Achilles", title="WordNet", bookTitle="Theory and Applications of Ontology: Computer Applications", year="2010", publisher="Springer Netherlands", address="Dordrecht", pages="231--243", isbn="978-90-481-8847-5", doi="10.1007/978-90-481-8847-5_10", url="https://doi.org/10.1007/978-90-481-8847-5_10" } @misc{wordnet, author = {Fellbaum, Christiane}, title = {WordNet and wordnets}, howpublished = "\url{https://wordnet.princeton.edu/}", year = {2005}, note = "[Online; recuperado el 20-09-2022]" } # Unsorted # ======== @article{Spady1970, author = {Spady, William G.}, title = {Dropouts from higher education: An interdisciplinary review and synthesis}, journal = {Interchange}, volume = {1}, number = {1}, pages = {64-85}, year = {1970}, publisher = {}, doi = {10.1007/BF02214313}, URL = {https://doi.org/10.1007/BF02214313} } @inproceedings{Delbonifro2020, title={Student dropout prediction}, author={Del Bonifro, Francesca and Gabbrielli, Maurizio and Lisanti, Giuseppe and Zingaro, Stefano Pio}, booktitle={International Conference on Artificial Intelligence in Education}, pages={129--140}, year={2020}, organization={Springer} } @book{hastie2009elements, title={The elements of statistical learning: data mining, inference, and prediction}, author={Hastie, Trevor and Tibshirani, Robert and Friedman, Jerome H and Friedman, Jerome H}, volume={2}, year={2009}, publisher={Springer} } @book{mitchell1997machine, title={Machine learning}, author={Mitchell, Tom M and Mitchell, Tom M}, volume={1}, number={9}, year={1997}, publisher={McGraw-hill New York} } @inproceedings{de_o_santos_supervised_2019, address = {Maceió, Brazil}, title = {Supervised {Learning} in the {Context} of {Educational} {Data} {Mining} to {Avoid} {University} {Students} {Dropout}}, isbn = {978-1-72813-485-7}, url = {https://ieeexplore.ieee.org/document/8820813/}, doi = {10.1109/ICALT.2019.00068}, urldate = {2023-04-16}, booktitle = {2019 {IEEE} 19th {International} {Conference} on {Advanced} {Learning} {Technologies} ({ICALT})}, publisher = {IEEE}, author = {de O. Santos, Kelly J. and Menezes, Angelo G. and de Carvalho, Andre B. and Montesco, Carlos A. E.}, month = jul, year = {2019}, pages = {207--208}, file = {de O. Santos et al. - 2019 - Supervised Learning in the Context of Educational .pdf:/home/mitsuo/.local/share/Zotero/storage/26P8CNIE/de O. Santos et al. - 2019 - Supervised Learning in the Context of Educational .pdf:application/pdf}, } @inproceedings{perez_applying_2018, address = {Medellin}, title = {Applying {Data} {Mining} {Techniques} to {Predict} {Student} {Dropout}: {A} {Case} {Study}}, isbn = {978-1-5386-6740-8}, shorttitle = {Applying {Data} {Mining} {Techniques} to {Predict} {Student} {Dropout}}, url = {https://ieeexplore.ieee.org/document/8484847/}, doi = {10.1109/ColCACI.2018.8484847}, urldate = {2023-04-16}, booktitle = {2018 {IEEE} 1st {Colombian} {Conference} on {Applications} in {Computational} {Intelligence} ({ColCACI})}, publisher = {IEEE}, author = {Perez, Boris and Castellanos, Camilo and Correal, Dario}, month = may, year = {2018}, pages = {1--6}, file = {Perez et al. - 2018 - Applying Data Mining Techniques to Predict Student.pdf:/home/mitsuo/.local/share/Zotero/storage/HSD4DDIX/Perez et al. - 2018 - Applying Data Mining Techniques to Predict Student.pdf:application/pdf}, } @inproceedings{chitti_need_2020, address = {Liverpool, United Kingdom}, title = {Need for {Interpretable} {Student} {Performance} {Prediction}}, isbn = {978-1-66542-238-3}, url = {https://ieeexplore.ieee.org/document/9450735/}, doi = {10.1109/DeSE51703.2020.9450735}, urldate = {2023-04-16}, booktitle = {2020 13th {International} {Conference} on {Developments} in {eSystems} {Engineering} ({DeSE})}, publisher = {IEEE}, author = {Chitti, Manjari and Chitti, Padmini and Jayabalan, Manoj}, month = dec, year = {2020}, pages = {269--272}, file = {Chitti et al. - 2020 - Need for Interpretable Student Performance Predict.pdf:/home/mitsuo/.local/share/Zotero/storage/JJGSFRMJ/Chitti et al. - 2020 - Need for Interpretable Student Performance Predict.pdf:application/pdf}, } # 10-generalidades # Metodos, Procedimientos, Herramientas @online{github, author = {{GitHub}}, title = {{GitHub's Frequently Asked Questions}}, url = {https://resources.github.com/faq/}, urldate = {2023-06-07}, } @online{bases-de-datos-bibliograficas, title = {SCOPUS}, url = {https://www.elsevier.com/es-es/solutions/scopus}, urldate = {2023-06-05} } @online{python, title = {Python}, url = {https://www.python.org}, urldate = {2023-06-05} } @online{matplotlib, title = {Matplotlib}, url = {https://matplotlib.org}, urldate = {2023-06-05} } @online{pandas, title = {Pandas}, url = {https://pandas.pydata.org}, urldate = {2023-06-05} } @online{poetry-python, title = {Poetry-python}, url = {https://python-poetry.org}, urldate = {2023-06-05} } @online{scikit-learn, title = {Scikit-learn}, url = {https://scikit-learn.org}, urldate = {2023-06-05} } @online{jupyter-notebooks, title = {Jupyter Notebooks}, url = {https://jupyter.org}, urldate = {2023-06-05} } @online{google-sheets, title = {Google Sheets}, url = {https://www.google.com/sheets/about/}, urldate = {2023-06-05} } @online{draw-io, title = {Draw.io}, url = {https://www.draw.io}, urldate = {2023-06-05} } @online{figma, title = {Figma}, url = {https://www.figma.com}, urldate = {2023-06-05} } @online{git, title = {Git}, url = {https://git-scm.com}, urldate = {2023-06-05} } @online{github, title = {GitHub}, url = {https://github.com}, urldate = {2023-06-05} } @online{aws, title = {AWS}, url = {https://aws.amazon.com}, urldate = {2023-06-05} } @online{visual-studio-code, title = {Visual Studio Code}, url = {https://code.visualstudio.com}, urldate = {2023-06-05} } @online{postgresql, title = {PostgreSQL}, url = {https://www.postgresql.org}, urldate = {2023-06-05} } @online{nginx, title = {Nginx}, url = {https://nginx.org}, urldate = {2023-06-05} } @online{markdown, title = {Markdown}, url = {https://daringfireball.net/projects/markdown/}, urldate = {2023-06-05} } @online{mermaid-diagrams, title = {Mermaid diagrams}, url = {https://mermaid.js.org/}, urldate = {2023-06-05} }