Higher Education Engagement and Economic Participation: Divide and Conquer

2016 ◽  
pp. 49-57
Author(s):  
Kassie Freeman
Keyword(s):  
Higher Education ◽  
Divide And Conquer ◽  
Economic Participation

scholarly journals Comparative Analysis for Boosting Classifiers in the Context of Higher Education

2020 ◽  
Vol 15 (10) ◽  
pp. 16
Author(s):  
Eslam Abou Gamie ◽  
Samir Abou El-Seoud ◽  
Mostafa A. Salama
Keyword(s):  
Higher Education ◽  
At Risk ◽  
Prediction Accuracy ◽  
Learning Systems ◽  
Divide And Conquer ◽  
Machine Learning Techniques ◽  
Students At Risk ◽  
Data Set ◽  
Electronic Learning ◽  
Divide And Conquer Algorithm

Machine learning techniques are applied on higher education data for analyzing the interac-tion between the students and electronic learning systems. This type of analysis serves in predicting students’ scores, in alerting students-at-risk, and in managing the degree of stu-dent engagement to educational system. The approaches in this work implements the divide and conquer algorithm on feature set of an educational data set to enhance the analysis and prediction accuracy. It divides the feature set into a number of logical subgroups based on the problem domain. Each subgroup is analyzed separately and the final result is the combi-nation of the results of the analysis of these subgroups. The classifier that shows the best prediction accuracy is dependent on the logical non-statistical nature of the features in each group. Both traditional and boosting classifiers are utilized on each dataset, from which a comparison is conducted to show the best classifiers along with the best dataset. This ap-proach provides the possibility to apply a brute force algorithm in the selection of the best feature subgroups with a low computational complexity. The experimental work shows a high prediction accuracy of the students-at-risk relative to the current research, and provides a list of new important features in the field of electronic learning systems.

Cluttering in the Communicative Disorders Curriculum

2009 ◽  
Vol 19 (2) ◽  
pp. 52-57
Author(s):  
John A. Tetnowski
Keyword(s):  
Higher Education ◽  
Doctoral Students ◽  
Communication Disorders ◽  
Educational Opportunities ◽  
Opportunities For Learning ◽  
Communicative Disorders ◽  
Theoretical Issues

Abstract Cluttering is discussed openly in the fluency literature, but few educational opportunities for learning more about cluttering exist in higher education. The purpose of this manuscript is to explain how a seminar in cluttering was developed for a group of communication disorders doctoral students. The major theoretical issues, educational questions, and conclusions are discussed.

Systems of Oppression in Geriatric Clinical Service Delivery

2021 ◽  
pp. 1-3
Author(s):  
Diane L. Kendall
Keyword(s):  
Higher Education ◽  
Service Delivery ◽  
Clinical Setting ◽  
Service Providers ◽  
Hard Work ◽  
Clinical Service ◽  
Meaningful Change ◽  
Important Work ◽  
Speech Language Pathologists ◽  
Medical Institutions

Purpose The purpose of this article was to extend the concepts of systems of oppression in higher education to the clinical setting where communication and swallowing services are delivered to geriatric persons, and to begin a conversation as to how clinicians can disrupt oppression in their workplace. Conclusions As clinical service providers to geriatric persons, it is imperative to understand systems of oppression to affect meaningful change. As trained speech-language pathologists and audiologists, we hold power and privilege in the medical institutions in which we work and are therefore obligated to do the hard work. Suggestions offered in this article are only the start of this important work.

Outcomes Measurement in Higher Education: Graduate Program Admission Issues

1998 ◽  
Vol 2 (1) ◽  
pp. 9-10
Author(s):  
Linda Cleeland ◽  
Ellen Meyer Gregg
Keyword(s):  
Higher Education ◽  
Graduate Program ◽  
Outcomes Measurement
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