scholarly journals Mining of Completion Rate of Higher Education Based on Fuzzy Feature Selection Model and Machine Learning Techniques

2019 ◽  
Vol 8 (2S10) ◽  
pp. 393-400
Keyword(s):  
Higher Education ◽  
Fuzzy Logic ◽  
Feature Selection ◽  
The United States ◽  
Ratio Method ◽  
Support Vector ◽  
Completion Rates ◽  
Academic Degree ◽  
Attribute Evaluation ◽  
Fuzzy Logic Technique

In the context of the great change in the labor market and the higher education sector, great attention is given to individuals with an academic degree or the so-called graduates class. However, each educational institution has a different approach towards students who wish to complete their university degree. This study aims at (1) identifying the most important factors that directly affect the completion, and (2) predicting the completion rates of students for university degrees according to the system of higher education in the United States. Unlike previous studies, this project contributes to the use of the fuzzy logic technique on three methods for feature selection, namely the Correlation Attribute Evaluation, Relief Attribute Evaluation, and Gain Ratio Method. Since these three methods give different weight to the same attribute, the fuzzy logic technique has been used to get one weight for the attribute. A great challenge faced throughout this study is the curse of dimensionality, because the college scorecard dataset launched by the US Department of Education contains approximately (8000) educational institutions and (1825) features. Applying the method used in this study to identify important features lead to their reduction to only (79). Accordingly, two models have been used to predict the completion rates of students for their university studies which are the Random Forest and the Support Vector Regression with a Mean Absolute Error (MAE) value of (0.068) and (0.097) respectively.

scholarly journals Mining of Completion Rate of Higher Education Based on Fuzzy Feature Selection Model and Machine Learning Techniques

2019 ◽  
Author(s):  
Tahseen A. Wotaifi
Keyword(s):  
Higher Education ◽  
Fuzzy Logic ◽  
Feature Selection ◽  
The United States ◽  
Ratio Method ◽  
Support Vector ◽  
Completion Rates ◽  
Academic Degree ◽  
Attribute Evaluation ◽  
Fuzzy Logic Technique

In the context of the great change in the labor market and the higher education sector, great attention is given to individuals with an academic degree or the so-called graduates class. However, each educational institution has a different approach towards students who wish to complete their university degree. This study aims at (1) identifying the most important factors that directly affect the completion, and (2) predicting the completion rates of students for university degrees according to the system of higher education in the United States. Unlike previous studies, this project contributes to the use of the fuzzy logic technique on three methods for feature selection, namely the Correlation Attribute Evaluation, Relief Attribute Evaluation, and Gain Ratio Method. Since these three methods give different weight to the same attribute, the fuzzy logic technique has been used to get one weight for the attribute. A great challenge faced throughout this study is the curse of dimensionality, because the college scorecard dataset launched by the US Department of Education contains approximately (8000) educational institutions and (1825) features. Applying the method used in this study to identify important features lead to their reduction to only (79). Accordingly, two models have been used to predict the completion rates of students for their university studies which are the Random Forest and the Support Vector Regression with a Mean Absolute Error (MAE) value of (0.068) and (0.097) respectively.

scholarly journals FUZZY UNORDERED RULE USING GREEDY HILL CLIMBING FEATURE SELECTION METHOD: AN APPLICATION TO DIABETES CLASSIFICATION

2021 ◽  
Vol 20 (Number 3) ◽  
pp. 391-422
Author(s):  
Hayder Naser Khraibet Al-Behadili ◽  
Ku Ruhana Ku-Mahamud
Keyword(s):  
Fuzzy Logic ◽  
Feature Selection ◽  
Feature Selection Method ◽  
Classification Problem ◽  
Classification Criteria ◽  
Hill Climbing ◽  
Classification Model ◽  
Support Vector ◽  
Input Variables ◽  
Fuzzy Logic Technique

Diabetes classification is one of the most crucial applications of healthcare diagnosis. Even though various studies have been conducted in this application, the classification problem remains challenging. Fuzzy logic techniques have recently obtained impressive achievements in different application domains especially medical diagnosis. Fuzzy logic technique is not able to deal with data of a large number of input variables in constructing a classification model. In this research, a fuzzy logic technique using greedy hill climbing feature selection methods was proposed for the classification of diabetes. A dataset of 520 patients from the Hospital of Sylhet in Bangladesh was used to train and evaluate the proposed classifier. Six classification criteria were considered to authenticate the results of the proposed classifier. Comparative analysis proved the effectiveness of the proposed classifier against Naive Bayes, support vector machine, K-nearest neighbour, decision tree, and multilayer perceptron neural network classifiers. Results of the proposed classifier demonstrated the potential of fuzzy logic in analyzing diabetes patterns in all classification criteria.

Promoting divergent leadership philosophies to improve student success outcomes for black and brown students in higher education

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Nicholas Petty ◽  
Dakota King-White ◽  
Tachelle Banks
Keyword(s):  
Higher Education ◽  
United States ◽  
Student Success ◽  
Baccalaureate Degree ◽  
The United States ◽  
Retention Rates ◽  
Completion Rates ◽  
Marginalized Groups ◽  
Support Students

Abstract Throughout the United States there are millions of Black and Brown students starting the process of attending college. However, research indicates that students from traditionally marginalized groups are less likely than their counterparts to complete the process and graduate college (Shapiro et al., 2017). While retention rates for students from traditionally marginalized backgrounds continue to decline, universities are beginning to pay attention to the needs of this population in search of ways of better supporting them. The examination of these factors may also inform programmatic adjustments, leadership philosophies, and future practices to help retain students and lead to eventual completion of a baccalaureate degree. In this article, the authors review the literature to explore factors that can affect Black and Brown students’ completion rates in higher education. By reviewing the literature and the factors impacting Black and Brown students, the authors share with readers initiatives at one university that are being used to support students from a strengths-based approach.

scholarly journals The use of gamification in xMOOCs about energy: Effects and predictive models for participants’ learning

2019 ◽  
pp. 43-59 ◽  
Author(s):  
Elvira G Rincon Flores ◽  
Juanjo Mena ◽  
María Soledad Ramírez Montoya ◽  
Raul Ramirez Velarde
Keyword(s):  
Predictive Models ◽  
Online Courses ◽  
National Laboratory ◽  
Analytical Data ◽  
The United States ◽  
Massive Open Online Courses ◽  
Completion Rates ◽  
Academic Degree ◽  
Added Benefit ◽  
The Relationship

Open access education has significantly grown in strength as a new way of fostering innovation in schools. Such is the case of massive open online courses (MOOCs), which have the added benefit of encouraging the democratisation of learning. In this sense, the Bi-National Laboratory on Smart Sustainable Energy Management and Technology Training between Mexico and the United States of America was launched with the purpose of trying MOOC technology and measuring its impact on the academic, business, and social sectors. Under this scenario, this study aimed to show the relationship between using gamification and level of performance in a MOOC on energy topics. The methodology was quantitative, using the course analytical data for socio-demographic information and predictive models. A total of 6246 participants enrolled in the MOOC and 1060 finished it. The results showed that participants aged between 20 and 50 had the highest completion rates in the gamified challenge; the higher academic degree, the more inclined participants were to solve the gamified challenge; and no such distinction exists by gender.

scholarly journals Hybrid Fault Diagnosis of Bearings: Adaptive Fuzzy Orthonormal-ARX Robust Feedback Observer

2020 ◽  
Vol 10 (10) ◽  
pp. 3587 ◽  
Author(s):  
Farzin Piltan ◽  
Jong-Myon Kim
Keyword(s):  
Fuzzy Logic ◽  
Fault Diagnosis ◽  
Single Type ◽  
Support Vector ◽  
Signal Estimation ◽  
Adaptive Fuzzy ◽  
Reliability And Robustness ◽  
Non Stationary Signal ◽  
Fuzzy Logic Technique ◽  
Logic Structure

Rolling-element bearings (REBs) make up a class of non-linear rotating machines that can be applied in several activities. Conceding a bearing has complicated and uncertain behavior that exhibits substantial challenges to fault diagnosis. Thus, the offered anomaly-diagnosis algorithm, based on a fuzzy orthonormal-ARX adaptive fuzzy logic-structure feedback observer, is developed. A fuzzy orthonormal-ARX algorithm is presented for non-stationary signal modeling. Next, a robust, stable, reliable, and accurate observer is developed for signal estimation. Therefore, firstly, a classical feedback observer is implemented. To address the robustness drawback found in feedback observers, a multi-structure technique is developed. Furthermore, to generate signal estimation performance and reliability, the fuzzy logic technique is applied to the structure feedback observer. Also, to improve the stability, reliability, and robustness of the fuzzy orthonormal-ARX fuzzy logic-structure feedback observer, an adaptive algorithm is developed. After generating the residual signals, a support vector machine (SVM) is developed for the detection and classification of the bearing fault conditions. The effectiveness of the proposed procedure is validated using two different datasets for single-type fault diagnosis based on the Case Western Reverse University (CWRU) vibration dataset and multi-type fault diagnosis of bearing using the Smart Health Safety Environment (SHSE) Lab acoustic emission dataset. The proposed algorithm increases the classification accuracy from 86% in the SVM-based fuzzy orthonormal-ARX feedback observer to 97.5% in single-type fault and from 80% to 98.3% in the multi-type faults.

Higher Education for Whom? Higher Education for What?

2017 ◽  
pp. 104-134
Author(s):  
Brooke Midkiff
Keyword(s):  
Higher Education ◽  
Educational Experiences ◽  
The United States ◽  
College Completion ◽  
Access To Higher Education ◽  
Completion Rates ◽  
Post Secondary ◽  
College Completion Rates ◽  
Quantitative Examination ◽  
First Offers

This chapter provides a critical quantitative examination of issues related to increasing access to higher education in the United States. The chapter first offers insights into the utility of using empirical evidence within a critical, theoretical framework to unpack underlying issues of expanding accessibility. Specifically, critical theory is used to excavate the limits of liberal approaches to expanding higher education through increasing access, coupled with empirical analysis of disparities in college completion rates. That is, while increasing access is important, access is hardly enough to decrease social and economic gaps. Issues of hegemony within higher education are examined through an examination of which students, despite increased access to higher education broadly, have access to specific types of post-secondary educational experiences.

scholarly journals Doctoral Education as an Institutional Resource for Training Research and Higher Education Personnel (Article 1)

2019 ◽  
Vol 28 (8-9) ◽  
pp. 44-54 ◽  
Author(s):  
B. I. Bednyi ◽  
A. A. Mironos ◽  
N. V. Rybakov
Keyword(s):  
Higher Education ◽  
Doctoral Students ◽  
Empirical Data ◽  
Doctoral Education ◽  
Doctoral Programs ◽  
Doctoral Program ◽  
The United States ◽  
Information Support ◽  
Teaching Staff ◽  
Academic Degree

The diversification of professional trajectories of academic degree holders is now becoming a global trend, and it prompts us to take a fresh look at the problem of evaluating the effectiveness of existing institutions for the training of academic and research personnel – the systems of doctoral education in Russia and abroad – in terms of the training of academic researchers and higher education teaching staff. Our two articles which share the scope of problems and have a single general concept, consecutively address the following issues: the collection and analysis of empirical data on training in doctoral programs; the dynamics of dissertation defense by graduates after the completion of doctoral programs; the actual timeframe of doctoral students’ advancement to their degree; the proportion of graduates who continue their scientific career after graduating from the doctoral program. The first article analyzes the organizational and methodological aspects of information and analytical support of institutions responsible for doctoral education in the countries of the European Union, the United States and Russia. It provides information about the organization of the systems for monitoring doctoral education and doctoral program graduates’ professional careers in foreign countries. The authors note the insufficient information support for the programs aiming to develop doctoral education in Russia, as well as the lack of empirical data necessary to assess the effectiveness of Russian doctoral education in the reproduction of human resources for the research and education sector. The results of the authors’ scientometric research concerning doctoral program graduates’ retention in the field of research and higher education are announced. The second article will present the details of the method and the results of these studies.

scholarly journals The policy filtering process: Understanding distinctive state responses to the National College Completion Agenda in the United States

2018 ◽  
Vol 26 ◽  
pp. 60 ◽  
Author(s):  
Paul G. Rubin ◽  
James C. Hearn
Keyword(s):  
Higher Education ◽  
United States ◽  
South Carolina ◽  
Postsecondary Education ◽  
State Level ◽  
The United States ◽  
College Completion ◽  
Completion Rates ◽  
Completion Agenda ◽  
State Responses

The United States has faced stagnant postsecondary education degree completion rates for over a decade. When coupled with improved educational outcomes in other nations, the one-time world leader in higher education attainment has precipitously declined in standing internationally. Coupling this reality with the need for a more educated workforce domestically led President Barack Obama to proclaim improving higher education completion rates a national imperative in 2009. Despite input from the federal government, due to the decentralized nature of American postsecondary education, individual states maintain primary responsibility for governance and policy decisions. Consequently, there has been a range of state responses to improving college completion. Through a comparative case analysis, this study considers a putatively homogenous region to investigate state-level factors that “filtered” the national college completion agenda to distinct responses in Georgia, South Carolina, and Texas.

The Early Years of the Jewish Presence at the University of Illinois

1992 ◽  
Vol 2 (2) ◽  
pp. 215-245
Author(s):  
Winton U. Solberg
Keyword(s):  
Higher Education ◽  
The United States ◽  
Early Years ◽  
Late Nineteenth Century ◽  
Characteristic Form ◽  
University Of Illinois ◽  
American Higher Education ◽  
Jewish Students ◽  
The University ◽  
The Church

For over two centuries, the College was the characteristic form of higher education in the United States, and the College was closely allied to the church in a predominantly Protestant land. The university became the characteristic form of American higher education starting in the late nineteenth Century, and universities long continued to reflect the nation's Protestant culture. By about 1900, however, Catholics and Jews began to enter universities in increasing numbers. What was the experience of Jewish students in these institutions, and how did authorities respond to their appearance? These questions will be addressed in this article by focusing on the Jewish presence at the University of Illinois in the early twentieth Century. Religion, like a red thread, is interwoven throughout the entire fabric of this story.

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