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Usage of machine learning for strategic decision making at higher educational institutions

Yuri Nieto, Vicente Gacia-Diaz, Carlos Montenegro, Claudio Camilo Gonzalez, Ruben Gonzalez Crespo
2019 IEEE Access  
INDEX TERMS Decision trees, random forest, logistic regressions, machine learning, strategic decisions, Higher Educational Institutions.  ...  Decisions made at the strategic level of Higher Educational Institutions (HEIs) affect policies, strategies, and actions that the institutions make as a whole.  ...  Afterward, we provide an overview of selected works that uses Machine Learning at Higher Educational Institutions for solving academic problems. We set their stakeholder, goals, and algorithms used.  ... 
doi:10.1109/access.2019.2919343 fatcat:tm75uivny5cnnhf3taaf46dtgu

Student Performance Prediction Model using Machine Learning Approach: The Case of Wolkite University

Ermiyas Birihanu Belachew, Feidu Akmel Gobena
2017 International Journal of Advanced Research in Computer Science and Software Engineering  
Machine learning is used to attain this objective. Machine learning techniques are used to discover models or patterns of data, and it is helpful in the decision-making.  ...  In order to analysis this complex data base we can able to use machine learning techniques.  ...  ACKNOWLEDGMENTS We would like to thanks Wolkite University collage of computing and Informatics Dean, Ato fedu Akmal and Wolkite University Registrar office dean, Ato Fekadu Mamo for their support giving  ... 
doi:10.23956/ijarcsse/v7i2/01219 fatcat:6agw2uz5qrgy5f7yuisrqbtdje


Sandhya Maitra
2018 International Journal of Advanced Research in Computer Science  
The applicability of the algorithms in quality management of teaching learning in Higher Education Institutions is yet to be explored.  ...  Subsequently the model shall support effective quality management of teaching learning process in higher educational institutions of the country. © 2015-19, IJARCS All Rights Reserved  ... 
doi:10.26483/ijarcs.v9i1.5268 fatcat:xjywhpnjt5hlvp5fq6zwjxnpe4

Machine Learning for Strategic Decision Making during COVID-19 at Higher Education Institutes

Amjed Sid Ahmed Mohamed Sid Ahmed, Mazhar Hussain Malik
2020 2020 International Conference on Decision Aid Sciences and Application (DASA)  
Machine learning is becoming driving force for strategic decision making in higher educational institutions and it calls for cooperation between stakeholders and the use of efficient computation methods  ...  This paper analyses the output generated using machine learning algorithms that help in prediction of no detriment policy applicability rate in the case of e-learning during COVID-19.  ...  MACHINE LEARNING ALGORITHMS FOR DECISION MAKING IN HIGHER EDUCATION A. Support Vector Machine Support Vector Machine (SVM) is machine learning algorithm which is used in supervised learning.  ... 
doi:10.1109/dasa51403.2020.9317042 fatcat:qbqqbrlnn5hp5bq4cjqynb47v4


Afolashade Kuyoro, Prof. Nicolae Goga, Dr. Oludele Awodele, Dr. Samuel Okolie
Recently, this paradigm is been employed to enhance and evaluate higher education tasks.  ...  Waikato Environment for Knowledge Analysis (WEKA) was used to generate 10 classification models( five decision tree algorithms -Random forest, Random tree, J48, Decision stump and REPTree and five rule  ...  Kalles and Pierrakeas 2004 discussed different machine learning techniques (decision trees, neural networks, Naive Bayes, instance-based learning, logistic regression and support vector machines) and compared  ... 
doi:10.24297/ijct.v4i1b.3061 fatcat:q5wda6sj5jcyha4c5hcha6uqve

Guaranteeing Correctness of Machine Learning based Decision Making at Higher Educational Institutions

Muhammad Nauman, Nadeem Akhtar, Adi Alhudhaif, Abdulrahman Alothaim
2021 IEEE Access  
ACKNOWLEDGMENT This publication was supported by the Deanship of Scientific Research at Prince Sattam bin Abdulaziz University, Alkharj, Saudi Arabia.  ...  The authors would also like to thank Directorate of Information Technology, The Islamia University Bahawalpur for providing admission data for academic research purposes.  ...  CONCLUSION Supervised Machine Learning, specifically decision trees, to analyse educational data can support higher educational institutes' better decision-making.  ... 
doi:10.1109/access.2021.3088901 fatcat:rpviiipfuja2vdzcpyepqerw4y

Review on Predictive Modelling Techniques for Identifying Students at Risk in University Environment

Mat Yaacob Nik Nurul Hafzan, Deris Safaai, Mat Asiah, Mohamad Mohd Saberi, Safaai Siti Syuhaida, Lim Meng Hee
2019 MATEC Web of Conferences  
Many different machine learning techniques have been implemented for predictive modelling in the past including decision tree, k-nearest neighbour, random forest, neural network, support vector machine  ...  However, in higher education institution, there are significant numbers of students that stop their studies before graduation, especially for undergraduate students.  ...  Academic analytics is a process for providing higher education institutions with the data necessary to support operational and financial decision making [5] , [10] , while learning analytics is the measurement  ... 
doi:10.1051/matecconf/201925503002 fatcat:z3cy2tkro5dutcktvhnzt73zji

Student Intervention System using Machine Learning Techniques

2019 International Journal of Engineering and Advanced Technology  
Using support vector machines (SVM), Decision Tree and Naïve Bayes (NB) classification algorithms F1 score is calculated for each algorithm.  ...  For which the huge information available with educational institutes can be used to predict student's future in academics.  ...  LITERAYURE SURVEY Many researchers have used statistics and machine learning algorithms for predicting the student's performances in educational institutes.  ... 
doi:10.35940/ijeat.f1392.0986s319 fatcat:7qnq5hs2svbbxd3vx7bdc7fahe

The Role of Machine Learning and Data Mining Techniques in Predicting Students' Academic Performance

Dr. Aliyu Y. Rufai, Dr.Hassan U. Suru, James Afrifa
2021 International Journal of Computer Applications Technology and Research  
Educational Data Mining (EDM) uses different methods and techniques from machine learning, statistics, data mining and data analysis, to analyze data collected during teaching and learning.  ...  This paper gave an overview of several applications using these disciplines in education, with focus on student's academic performance prediction.  ...  These factors could be useful in decision making concerning student's academic performance.  ... 
doi:10.7753/ijcatr1008.1001 fatcat:gubuyxevezc3zf3hixy6572jqm

Study Of Students' Performance Prediction Models Using Machine Learning

Mr. S. Viswanathan, Et. al.
2021 Turkish Journal of Computer and Mathematics Education  
Prediction attempts to shape trends that will allow it to predict results or learning outcomes based on available data. Predicting student success has become an appealing challenge for researchers.  ...  The numerous research models used to solve the problem of student success prediction using educational data mining are discussed in this paper.  ...  Many models are used in machine learning to solve a binary classification problem, such as the regression algorithm, decision tree algorithm, kernel-based algorithm, Bayesian process algorithm, clustering  ... 
doi:10.17762/turcomat.v12i2.2351 fatcat:rbxca3wxgzhz3hoxx7tatskyku

A Review of Educational Data Mining in Higher Education System

Thangamuthu Thilagaraj, Nallasamy Sengottaiyan
2017 Proceedings of the Second International Conference on Research in Intelligent and Computing in Engineering  
Classification is used to classify the records based on the preparation set and also it uses the pattern to categorize the new records.This paper aims to show the various techniques of Educational data  ...  The discovery of hidden patterns in educational data is a promising research in Educational Data Mining.The students achievement rate were reduced continuously is the major problem in higher education.  ...  to discover the patterns for improving the decision making to identify the students at risk.  ... 
doi:10.15439/2017r87 dblp:conf/rice/ThilagarajS17 fatcat:3phnxkyorredvmsjxkcuxps6bq

Student's Placement Prediction Using Support Vector Machine

Yashodeep Ingale, Tanuja Bedse, Shivani Khairnar, Dhyaneshawari Ghute
2020 International Journal of Scientific Research in Computer Science Engineering and Information Technology  
There are lots of machine learning algorithms and statistical base technique which may be taken as good assets for classify the student data set in the education field.  ...  In this paper, various machine learning algorithms like Naïve Baiyes, SVM, KNN, decision tree algorithm has been applied to predict student performance which will help to identify performance of the students  ...  Support Vector Machine (SVM) : Support Vector Machine (SVM) is a supervised machine learning algorithm which can be used for both classification or regression challenges.  ... 
doi:10.32628/cseit206511 fatcat:g5rg2hwvrbfabkhcbwztpnzpbe

Significance of Non-Academic Parameters for Predicting Student Performance Using Ensemble Learning Techniques

Deepti Aggarwal, Sonu Mittal, Vikram Bali
2021 International Journal of System Dynamics Applications  
The academic institutions are focusing more on improving the performance of students using various data mining techniques.  ...  The models are built using eight classification algorithms that are then compared to find the parameters that help to give the most appropriate model to classify a student based on his performance.  ...  , Jaipur, India to provide complete support in carrying out the research work and writing this research paper.  ... 
doi:10.4018/ijsda.2021070103 dblp:journals/ijsda/AggarwalMB21 fatcat:uaus7wfdangrhbqnqcpjcl5v54

A Decision Support System for Effective Academic Analysis by Using the Concept of Data Mining

2020 International Journal of Emerging Trends in Engineering Research  
In India, higher education institutions experience the need for effective analysis and decision support tools to assist in all academic processes.  ...  Some of the higher learning institutions only manage financial, administrative and academic data used for common analysis works.  ...  CONCLUSION The DM-HEDSS is useful for educational decision making for academic administrators.  ... 
doi:10.30534/ijeter/2020/263892020 fatcat:5h2auumhufbepl2j7piwkxt5la

Visualizing the Educational Data Mining Literature

I. Papadogiannis, N. Platis, V. Poulopoulos, C. Vassilakis, G. Lepouras, M. Wallace, G. Karountzou
2020 European Journal of Engineering Research and Science  
Various aspects of the literature are examined, such as the algorithms adopted, the type of results drawn, the educational setting of the application and the actual exploitation of the outcomes.  ...  This article provides a visualization of a literature review in students' performance prediction using educational data mining (EDM) techniques for the period 2015-2019.  ...  Evidence-Based decision making enables strong decision support at local, regional, national and even supranational level.  ... 
doi:10.24018/ejers.2020.0.cie.2306 fatcat:imjmyou7dvev5bxpkhxq7dkhey
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