Artículos de revistas sobre el tema "Student Outcome Prediction"
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Mohd Talib, Nur Izzati, Nazatul Aini Abd Majid y Shahnorbanun Sahran. "Identification of Student Behavioral Patterns in Higher Education Using K-Means Clustering and Support Vector Machine". Applied Sciences 13, n.º 5 (3 de marzo de 2023): 3267. http://dx.doi.org/10.3390/app13053267.
Texto completoIssaro, Sasitorn y Panita Wannapiroon. "Intelligent Student Relationship Management Platform with Machine Learning for Student Empowerment". International Journal of Emerging Technologies in Learning (iJET) 18, n.º 04 (23 de febrero de 2023): 66–87. http://dx.doi.org/10.3991/ijet.v18i04.32583.
Texto completoRoberts, Scott L. "Keep’em Guessing: Using Student Predictions to Inform Historical Understanding and Empathy". Social Studies Research and Practice 11, n.º 3 (1 de noviembre de 2016): 45–50. http://dx.doi.org/10.1108/ssrp-03-2016-b0004.
Texto completoHarwati, Defi Sri y Heri Yanto. "Vocational High School (SMK) Students Accounting Competence Prediction Model by Using Astin I-E-O Model". Dinamika Pendidikan 12, n.º 2 (1 de marzo de 2018): 98–113. http://dx.doi.org/10.15294/dp.v12i2.10826.
Texto completoP S, Ambili y Biku Abraham. "A Predictive Model for Student Employability Using Deep Learning Techniques". ECS Transactions 107, n.º 1 (24 de abril de 2022): 10149–58. http://dx.doi.org/10.1149/10701.10149ecst.
Texto completoKhan, Ijaz Muhammad, Abdul Rahim Ahmad, Nafaa Jabeur y Mohammed Najah Mahdi. "A Conceptual Framework to Aid Attribute Selection in Machine Learning Student Performance Prediction Models". International Journal of Interactive Mobile Technologies (iJIM) 15, n.º 15 (11 de agosto de 2021): 4. http://dx.doi.org/10.3991/ijim.v15i15.20019.
Texto completoGhodke, Keerti. "Stream Processing for Association Rule to Generate Student Dataset using Apriori Algorithm". International Journal for Research in Applied Science and Engineering Technology 10, n.º 7 (31 de julio de 2022): 3721–27. http://dx.doi.org/10.22214/ijraset.2022.45884.
Texto completoBehr, Andreas, Marco Giese, Herve D. Teguim K y Katja Theune. "Early Prediction of University Dropouts – A Random Forest Approach". Jahrbücher für Nationalökonomie und Statistik 240, n.º 6 (11 de febrero de 2020): 743–89. http://dx.doi.org/10.1515/jbnst-2019-0006.
Texto completoPan, Feng, Bingyao Huang, Chunhong Zhang, Xinning Zhu, Zhenyu Wu, Moyu Zhang, Yang Ji, Zhanfei Ma y Zhengchen Li. "A survival analysis based volatility and sparsity modeling network for student dropout prediction". PLOS ONE 17, n.º 5 (5 de mayo de 2022): e0267138. http://dx.doi.org/10.1371/journal.pone.0267138.
Texto completoNyompa, Sukri, Suprapta Suprapta, Sri Wahyuni y Muhamad Ihsan Azhim. "The Effect of Student Perception of Teacher Professional Competency On The Result of Geography Learning Class XI Social Science Student’s SMA 12 Sinjai". UNM Geographic Journal 1, n.º 2 (1 de febrero de 2018): 131. http://dx.doi.org/10.26858/ugj.v1i2.6597.
Texto completoZhang, Qizhen, Audrey Durand y Joelle Pineau. "Literature Mining for Incorporating Inductive Bias in Biomedical Prediction Tasks (Student Abstract)". Proceedings of the AAAI Conference on Artificial Intelligence 34, n.º 10 (3 de abril de 2020): 13983–84. http://dx.doi.org/10.1609/aaai.v34i10.7264.
Texto completoSullivan, Arthur P., Robert Guglielmo y Prudence Opperman. "Measuring and Interpreting School-Based Prevention Outcomes: The New York City Model". Journal of Drug Education 16, n.º 2 (junio de 1986): 181–90. http://dx.doi.org/10.2190/4mfb-2u39-3u50-ncpv.
Texto completoSon, Nguyen Thi Kim, Nguyen Van Bien, Nguyen Huu Quynh y Chu Cam Tho. "Machine Learning Based Admission Data Processing for Early Forecasting Students' Learning Outcomes". International Journal of Data Warehousing and Mining 18, n.º 1 (1 de enero de 2022): 1–15. http://dx.doi.org/10.4018/ijdwm.313585.
Texto completoAlhothali, Areej, Maram Albsisi, Hussein Assalahi y Tahani Aldosemani. "Predicting Student Outcomes in Online Courses Using Machine Learning Techniques: A Review". Sustainability 14, n.º 10 (19 de mayo de 2022): 6199. http://dx.doi.org/10.3390/su14106199.
Texto completoIsmail Yusuf Panessai, Muhammad Modi Lakulu, Mohd Hishamuddin Abdul Rahman, Noor Anida Zaria Mohd Noor, Nor Syazwani Mat Salleh y Aldrin Aran Bilong. "PSAP: Improving Accuracy of Students' Final Grade Prediction using ID3 and C4.5". International Journal of Artificial Intelligence 6, n.º 2 (3 de diciembre de 2019): 125–33. http://dx.doi.org/10.36079/lamintang.ijai-0602.42.
Texto completoSiregar, Nurhasana, Rodiah Ulfah Lubis y Puspa Riani Nasution. "Student Practicum Competencies through Lesson Study with the application of Argument Driven Inquiry". Jurnal Pembelajaran Fisika 9, n.º 2 (30 de junio de 2019): 243–51. http://dx.doi.org/10.23960/jpf.v9.n2.202111.
Texto completoCronin, Christopher. "Reasons for Drinking Versus Outcome Expectancies in the Prediction of College Student Drinking". Substance Use & Misuse 32, n.º 10 (enero de 1997): 1287–311. http://dx.doi.org/10.3109/10826089709039379.
Texto completoOwusu-Boadu, Bridgitte, Isaac Kofi Nti, Owusu Nyarko-Boateng, Justice Aning y Victoria Boafo. "Academic Performance Modelling with Machine Learning Based on Cognitive and Non-Cognitive Features". Applied Computer Systems 26, n.º 2 (1 de diciembre de 2021): 122–31. http://dx.doi.org/10.2478/acss-2021-0015.
Texto completoModell, H. I., J. A. Michael, T. Adamson, J. Goldberg, B. A. Horwitz, D. S. Bruce, M. L. Hudson, S. A. Whitescarver y S. Williams. "Helping undergraduates repair faulty mental models in the student laboratory." Advances in Physiology Education 23, n.º 1 (junio de 2000): S82–90. http://dx.doi.org/10.1152/advances.2000.23.1.s82.
Texto completoSubhash, Ambika Rani. "Student Campus Placement Prediction Analysis using ChiSquared Test on Machine Learning Algorithms". International Journal for Research in Applied Science and Engineering Technology 9, n.º VIII (15 de agosto de 2021): 427–34. http://dx.doi.org/10.22214/ijraset.2021.37368.
Texto completoJawthari, Moohanad y Veronika Stoffa. "Predicting At-Risk Students Using Weekly Activities and Assessments". International Journal of Emerging Technologies in Learning (iJET) 17, n.º 19 (14 de octubre de 2022): 59–73. http://dx.doi.org/10.3991/ijet.v17i19.31349.
Texto completoNadaf, Ali, Sebas Eliëns y Xin Miao. "Interpretable-Machine-Learning Evidence for Importance and Optimum of Learning Time". International Journal of Information and Education Technology 11, n.º 10 (2021): 444–49. http://dx.doi.org/10.18178/ijiet.2021.11.10.1548.
Texto completoJoksimović, Srećko, Oleksandra Poquet, Vitomir Kovanović, Nia Dowell, Caitlin Mills, Dragan Gašević, Shane Dawson, Arthur C. Graesser y Christopher Brooks. "How Do We Model Learning at Scale? A Systematic Review of Research on MOOCs". Review of Educational Research 88, n.º 1 (14 de noviembre de 2017): 43–86. http://dx.doi.org/10.3102/0034654317740335.
Texto completoPaliwal, Nikhil, Prakhar Jaiswal, Vincent M. Tutino, Hussain Shallwani, Jason M. Davies, Adnan H. Siddiqui, Rahul Rai y Hui Meng. "Outcome prediction of intracranial aneurysm treatment by flow diverters using machine learning". Neurosurgical Focus 45, n.º 5 (noviembre de 2018): E7. http://dx.doi.org/10.3171/2018.8.focus18332.
Texto completoEhimwenma, Kennedy Efosa, Safiya Al Sharji y Maruf Raheem. "Difference of Probability and Information Entropy for Skills Classification and Prediction in Student Learning". International Journal of Artificial Intelligence & Applications 13, n.º 5 (30 de septiembre de 2022): 1–19. http://dx.doi.org/10.5121/ijaia.2022.13501.
Texto completoBalaji, Prasanalakshmi, Salem Alelyani, Ayman Qahmash y Mohamed Mohana. "Contributions of Machine Learning Models towards Student Academic Performance Prediction: A Systematic Review". Applied Sciences 11, n.º 21 (26 de octubre de 2021): 10007. http://dx.doi.org/10.3390/app112110007.
Texto completoKamagi, David Hartanto y Seng Hansun. "Implementasi Data Mining dengan Algoritma C4.5 untuk Memprediksi Tingkat Kelulusan Mahasiswa". Jurnal ULTIMATICS 6, n.º 1 (1 de junio de 2014): 15–20. http://dx.doi.org/10.31937/ti.v6i1.327.
Texto completoKarlos, Stamatis, Georgios Kostopoulos y Sotiris Kotsiantis. "Predicting and Interpreting Students’ Grades in Distance Higher Education through a Semi-Regression Method". Applied Sciences 10, n.º 23 (26 de noviembre de 2020): 8413. http://dx.doi.org/10.3390/app10238413.
Texto completoMansouri, Taha, Ahad ZareRavasan y Amir Ashrafi. "A Learning Fuzzy Cognitive Map (LFCM) Approach to Predict Student Performance". Journal of Information Technology Education: Research 20 (2021): 221–43. http://dx.doi.org/10.28945/4760.
Texto completoAxelsen, Megan, Petrea Redmond, Eva Heinrich y Michael Henderson. "The evolving field of learning analytics research in higher education". Australasian Journal of Educational Technology 36, n.º 2 (15 de mayo de 2020): 1–7. http://dx.doi.org/10.14742/ajet.6266.
Texto completoKhan, Ijaz Muhammad, Abdul Rahim Ahmad, Nafaa Jabeur y Mohammed Najah Mahdi. "Machine Learning Prediction and Recommendation Framework to Support Introductory Programming Course". International Journal of Emerging Technologies in Learning (iJET) 16, n.º 17 (6 de septiembre de 2021): 42. http://dx.doi.org/10.3991/ijet.v16i17.18995.
Texto completoSharma, Sneha y Raman Tandon. "Predicting Burn Mortality Using a Simple Novel Prediction Model". Indian Journal of Plastic Surgery 54, n.º 01 (enero de 2021): 046–52. http://dx.doi.org/10.1055/s-0040-1721867.
Texto completoGraefe, Andreas y Christof Weinhardt. "LONG-TERM FORECASTING WITH PREDICTION MARKETS – A FIELD EXPERIMENT ON APPLICABILITY AND EXPERT CONFIDENCE". Journal of Prediction Markets 2, n.º 2 (14 de diciembre de 2012): 71–91. http://dx.doi.org/10.5750/jpm.v2i2.442.
Texto completoXie, Shu-tong, Qiong Chen, Kun-hong Liu, Qing-zhao Kong y Xiu-juan Cao. "Learning Behavior Analysis Using Clustering and Evolutionary Error Correcting Output Code Algorithms in Small Private Online Courses". Scientific Programming 2021 (14 de junio de 2021): 1–11. http://dx.doi.org/10.1155/2021/9977977.
Texto completoLee, Kibeom, Michael C. Ashton, Jocelyn Wiltshire, Joshua S. Bourdage, Beth A. Visser y Alissa Gallucci. "Sex, Power, and Money: Prediction from the Dark Triad and Honesty–Humility". European Journal of Personality 27, n.º 2 (marzo de 2013): 169–84. http://dx.doi.org/10.1002/per.1860.
Texto completoBruce, Scott L., Elizabeth Crawford, Gary B. Wilkerson, David Rausch, R. Barry Dale y Martina Harris. "Prediction Modeling for Academic Success in Professional Master's Athletic Training Programs". Athletic Training Education Journal 11, n.º 4 (1 de octubre de 2016): 194–207. http://dx.doi.org/10.4085/1104194.
Texto completoMbise, E. R. y R. S. J. Tuninga. "Measuring business schools’ service quality in an emerging market using an extended SERVQUAL instrument". South African Journal of Business Management 47, n.º 1 (31 de marzo de 2016): 61–74. http://dx.doi.org/10.4102/sajbm.v47i1.53.
Texto completoKhechine, Hager y Sawsen Lakhal. "Technology as a Double-Edged Sword: From Behavior Prediction with UTAUT to Students’ Outcomes Considering Personal Characteristics". Journal of Information Technology Education: Research 17 (2018): 063–102. http://dx.doi.org/10.28945/4022.
Texto completoGrebener, Binia-Laureen, Janina Barth, Sven Anders, Tim Beißbarth y Tobias Raupach. "A prediction-based method to estimate student learning outcome: Impact of response rate and gender differences on evaluation results". Medical Teacher 43, n.º 5 (27 de enero de 2021): 524–30. http://dx.doi.org/10.1080/0142159x.2020.1867714.
Texto completoSoni, Tanu y Priyadarshini Tiwari. "Predictors of maternal outcome in women on mechanical ventilation in an obstetric intensive care unit: an observational study". International Journal of Reproduction, Contraception, Obstetrics and Gynecology 8, n.º 2 (25 de enero de 2019): 721. http://dx.doi.org/10.18203/2320-1770.ijrcog20190312.
Texto completoEllington, Roni, James Wachira y Asamoah Nkwanta. "RNA Secondary Structure Prediction by Using Discrete Mathematics: An Interdisciplinary Research Experience for Undergraduate Students". CBE—Life Sciences Education 9, n.º 3 (septiembre de 2010): 348–56. http://dx.doi.org/10.1187/cbe.10-03-0036.
Texto completoWan, Qing y Yoonsuck Choe. "Action Recognition and State Change Prediction in a Recipe Understanding Task Using a Lightweight Neural Network Model (Student Abstract)". Proceedings of the AAAI Conference on Artificial Intelligence 34, n.º 10 (3 de abril de 2020): 13945–46. http://dx.doi.org/10.1609/aaai.v34i10.7245.
Texto completoNarayanasamy, Senthil Kumar y Atilla Elçi. "An Effective Prediction Model for Online Course Dropout Rate". International Journal of Distance Education Technologies 18, n.º 4 (octubre de 2020): 94–110. http://dx.doi.org/10.4018/ijdet.2020100106.
Texto completoK., Ravi, Vinay K. y Akhila Rao K. "Study of spectrum of sepsis and prediction of its outcome in patients admitted to ICU using different scoring systems". International Journal of Advances in Medicine 6, n.º 1 (23 de enero de 2019): 155. http://dx.doi.org/10.18203/2349-3933.ijam20190123.
Texto completoVerma, Sneh Lata, Rigzing Lepcha, Rohit Khanna, Tripti Tikku, Rana Pratap Maurya y Kamna Srivastava. "Comparision of predicted and actual treatment outcome based on steiner cephalometric analysis using nemotech software". IP Indian Journal of Orthodontics and Dentofacial Research 8, n.º 3 (15 de octubre de 2022): 151–55. http://dx.doi.org/10.18231/j.ijodr.2022.026.
Texto completoYusoff, Marina, Muhammad Najib Bin Fathi y . "Evaluation of Clustering Methods for Student Learning Style Based Neuro Linguistic Programming". International Journal of Engineering & Technology 7, n.º 3.15 (13 de agosto de 2018): 63. http://dx.doi.org/10.14419/ijet.v7i3.15.17408.
Texto completoBowman, Thomas G., Jay Hertel y Heather D. Wathington. "Programmatic Factors Associated with Undergraduate Athletic Training Student Retention and Attrition Decisions". Athletic Training Education Journal 10, n.º 1 (1 de enero de 2015): 5–17. http://dx.doi.org/10.4085/10015.
Texto completode Paor, Muireann, Fiona Boland, Xinyan Cai, Susan Smith, Mark H. Ebell, Eoin Mac Donncha y Tom Fahey. "Derivation and validation of clinical prediction rules for diagnosis of infectious mononucleosis: a prospective cohort study". BMJ Open 13, n.º 2 (febrero de 2023): e068877. http://dx.doi.org/10.1136/bmjopen-2022-068877.
Texto completoRamaswami, Gomathy, Teo Susnjak, Anuradha Mathrani, James Lim y Pablo Garcia. "Using educational data mining techniques to increase the prediction accuracy of student academic performance". Information and Learning Sciences 120, n.º 7/8 (8 de julio de 2019): 451–67. http://dx.doi.org/10.1108/ils-03-2019-0017.
Texto completoDeRuisseau, Lara R. "The flipped classroom allows for more class time devoted to critical thinking". Advances in Physiology Education 40, n.º 4 (1 de diciembre de 2016): 522–28. http://dx.doi.org/10.1152/advan.00033.2016.
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