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Mengjiao Yin; Hengshan Cao; Zuhong Yu; Xianyu Pan – International Journal of Web-Based Learning and Teaching Technologies, 2024
This study presents the Academic Investment Model (AIM) as a novel approach to predicting student academic performance by incorporating learning styles as a predictive feature. Utilizing data from 138 Marketing students across China, the research employs a combination of machine learning clustering methods and manual feature engineering through a…
Descriptors: Predictor Variables, Artificial Intelligence, Performance, Cluster Grouping
Ashley Haigler – ProQuest LLC, 2021
The results of an industry research survey showed, understanding Dissertation Research categories has not been the focused on many researchers and institutions. This research expands on machine learning methodologies using two similar datasets to answer these three questions: 1. Is there a way to track the trends of Pace University's Doctor of…
Descriptors: Artificial Intelligence, Content Analysis, Cluster Grouping, Classification
Theobald, Elli – CBE - Life Sciences Education, 2018
Discipline-based education researchers have a natural laboratory--classrooms, programs, colleges, and universities. Studies that administer treatments to multiple sections, in multiple years, or at multiple institutions are particularly compelling for two reasons: first, the sample sizes increase, and second, the implementation of the treatments…
Descriptors: Educational Research, Hierarchical Linear Modeling, Program Implementation, Predictor Variables
Hall, Jessica; McGregor, Karla K.; Oleson, Jacob – Journal of Speech, Language, and Hearing Research, 2017
Purpose: The purpose of this study is to determine whether deficits in executive function and lexical-semantic memory compromise the linguistic performance of young adults with specific learning disabilities (LD) enrolled in postsecondary studies. Method: One hundred eighty-five students with LD (n = 53) or normal language development (ND, n =…
Descriptors: Executive Function, Semantics, Memory, Young Adults
Rentroia-Bonito, Maria Alexandra; Gonçalves, Daniel; Jorge, Joaquim A. – International Journal of Mobile and Blended Learning, 2015
Technological advances during the last decade have provided huge possibilities to support e-learning. However, there are still concerns regarding Return-on-Investment (ROI) of e-learning, its sustainability within organizational boundaries and effectiveness across potential learner groups. Much previous research has concentrated on learners'…
Descriptors: Blended Learning, Learning Motivation, Cluster Grouping, Courseware
Riofrio-Luzcando, Diego; Ramirez, Jaime; Berrocal-Lobo, Marta – IEEE Transactions on Learning Technologies, 2017
Data mining is known to have a potential for predicting user performance. However, there are few studies that explore its potential for predicting student behavior in a procedural training environment. This paper presents a collective student model, which is built from past student logs. These logs are first grouped into clusters. Then, an…
Descriptors: Student Behavior, Predictive Validity, Predictor Variables, Predictive Measurement
Jabnoun, Naceur – Quality Assurance in Education: An International Perspective, 2015
Purpose: This paper aims to explore the influence of wealth, transparency and democracy on the number of universities per million people ranked among the top 300 and 500. The highly ranked universities in the world tend to be concentrated in a few countries. Design/Methodology/Approach: ANOVA was used to test the differences between the two groups…
Descriptors: Universities, Classification, Influences, Fiscal Capacity
Soh, Kay Cheng – Higher Education Review, 2012
Three university ranking systems in vogue have been shown in the previous issue of "Higher Education Review" to be capable of modifications to make them more parsimonious by using only about half of the number of predictors currently in use. This makes some of the predictors "redundant" as they contributed little to the overall ranking. It is…
Descriptors: Higher Education, Predictor Variables, Profiles, Test Items
Gielen, Sarah; Dochy, Filip; Onghena, Patrick – Assessment & Evaluation in Higher Education, 2011
Since Topping published his literature review on peer assessment in 1998, the number of studies on this subject has doubled, if not tripled. However, along with this expansion, the diversity of peer assessment applications increased equally fast. Based on recent literature, this contribution focuses specifically on the diversity that has come to…
Descriptors: Peer Evaluation, Evaluation Methods, Educational Practices, Predictor Variables
Hendrix, Dean – College & Research Libraries, 2010
This study analyzed 2005-2006 Web of Science bibliometric data from institutions belonging to the Association of Research Libraries (ARL) and corresponding ARL statistics to find any associations between indicators from the two data sets. Principal components analysis on 36 variables from 103 universities revealed obvious associations between…
Descriptors: Bibliometrics, Correlation, Research Libraries, Library Associations
Shaw, Emily J.; Kobrin, Jennifer L.; Packman, Sheryl F.; Schmidt, Amy Elizabeth – Journal of Advanced Academics, 2009
The media communicates the existence of two distinct types of college applicants: the frenzied, overachieving, anxious student who applies to many institutions, and the underprepared, less advantaged student whose parents are not at all familiar with the application process. The purpose of this study is to more realistically describe distinct…
Descriptors: College Preparation, College Choice, College Applicants, Enrollment Management
Gibson, Allen – American Journal of Business Education, 2009
This paper demonstrates a new application of cluster analysis to segment business school students according to their degree of satisfaction with various aspects of the academic program. The resulting clusters provide additional insight into drivers of student satisfaction that are not evident from analysis of the responses of the student body as a…
Descriptors: Multivariate Analysis, Student Surveys, Participant Satisfaction, College Programs
de Guzman, Allan B.; Uy, Millard M.; Siy, Elmore Y.; Torres, Ramon Kristoffer C.; Tancioco, Joseph Bryan F.; Hernandez, Jomar R. – Asia Pacific Education Review, 2008
Caring, as a universal human phenomenon, should permeate elementary, secondary and tertiary level instruction. The practice of teaching, especially at the tertiary level, is not only substantial and procedural but relational as well. To teach with a heart is the essence that makes teaching a form of caring. When teaching is viewed as a form of…
Descriptors: College Students, Student Attitudes, Teacher Role, Caring
Ayoubi, Rami M.; Massoud, Hiba K. – International Journal of Educational Management, 2007
Purpose: The purpose of this research is to examine the extent to which UK universities' achal international achievements match their strategic intent on internationalization. Design/methodology/approach: Both factor analysis and cluster analysis were applied on data collected from HESA (2001), and on the data collected from the mission statements…
Descriptors: Higher Education, Factor Analysis, Content Analysis, Global Approach
Turk-Bicakci, Lori; Brint, Steven – Higher Education: The International Journal of Higher Education and Educational Planning, 2005
Following landmark legislation passed more than 20 years ago, university-industry relationships have now become central to understanding the changing role of research universities in American Society. The paper analyzes the development of university-industry partnerships during the 1990s. Past studies have used a broad array of measures of ties…
Descriptors: School Business Relationship, Research Universities, Research Methodology, Cooperation
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