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Kemper, Lorenz; Vorhoff, Gerrit; Wigger, Berthold U. – European Journal of Higher Education, 2020
We perform two approaches of machine learning, logistic regressions and decision trees, to predict student dropout at the Karlsruhe Institute of Technology (KIT). The models are computed on the basis of examination data, i.e. data available at all universities without the need of specific collection. Therefore, we propose a methodical approach…
Descriptors: Foreign Countries, Predictor Variables, Potential Dropouts, School Holding Power
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Xin, Yan Ping; Zhang, Dake – Journal of Educational Research, 2011
This article presents the authors' response to Asha K. Jitendra's Response to Xin and Zhang ("The Journal of Educational Research," 2009, Vol. 102, No. 6). The claim of "factual errors, including inappropriate quotes, misrepresentation of information, and inadequate scholarship in Xin and Zhang's text" are not justified. In this rejoinder, the…
Descriptors: Educational Research, Word Problems (Mathematics), Evaluation Methods, Teaching Methods
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Paterson, Judy; Thomas, Mike; Taylor, Steve – International Journal of Mathematical Education in Science and Technology, 2011
A group of mathematicians and mathematics educators are collaborating in the fine-grained examination of selected "slices" of video recordings of lectures, drawing on Schoenfeld's Resources, Orientations and Goals framework of teaching-in-context. In the larger project, we are exploring ways in which this model can be extended to examine…
Descriptors: Video Technology, Mathematics Education, Lecture Method, Mathematics
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Spengler, Paul M.; White, Michael J.; Aegisdottir, Stefania; Maugherman, Alan S. – Counseling Psychologist, 2009
The reactions by Ridley and Shaw-Ridley (EJ832451) and Lichtenberg (EJ832452) to the authors' meta-analysis on the effects of experience on judgment accuracy add positively to what is hoped will become an ever more focused discourse on this most basic question: How can mental health clinical decision making be improved? In this rejoinder, the…
Descriptors: Feedback (Response), Psychological Evaluation, Construct Validity, Counseling Psychology
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Teasley, C.E. Wynn; Hornyak, Martin – American Journal of Business Education, 2010
The 2009 college football season is here, but there has been a continuing controversy swirling over how the Football Bowl Subdivision (FBS) selects its national champion. College football uses a multi-criterion decision matrix (MCDM) evaluation technique to determine which two teams will play for the national championship. We analyzed the BCS…
Descriptors: Business Administration, Business Administration Education, Team Sports, College Athletics
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Burt, Gordon – Open Learning, 1996
Analyzes student progress within the framework of models of choice based on experiences at the Open University (United Kingdom). Investigates why students choose to continue studying in light of their success or failure in previous study and suggests that mathematical models need to be further developed to assist in this field. (Author/LRW)
Descriptors: Academic Achievement, Decision Making, Educational Experience, Higher Education
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Naylor, Maiken; Walsh, Kathleen – Library & Information Science Research, 1994
Discussion of methods for gathering journal use information in academic libraries (for retention decisions) highlights an 8.4-year time-series of weekly library journal pickup data. Use of the autocorrelation function, spectral analysis, and intervention analysis is described.(LRW)
Descriptors: Academic Libraries, Decision Making, Higher Education, Library Collection Development
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Troutt, Marvin D.; And Others – Journal for Higher Education Management, 1995
Discussion of guaranteed college tuition programs first explores their origins and reasons for continuing high inflation rates for tuition. The relationship between tuition increase and enrollment is examined, and many current guaranteed tuition plans are reviewed. Basic considerations in developing a model for a multiyear plan are outlined and a…
Descriptors: College Administration, Decision Making, Enrollment Management, Enrollment Rate
Dempsey, William M. – Trusteeship, 1997
A Rochester Institute of Technology (New York) program costing model designed to reflect costs more accurately allocates indirect costs according to salaries and wages, modified total direct costs, square footage of space used, credit hours, and student and faculty full-time equivalents. It allows administrators to make relative value judgments…
Descriptors: Budgeting, College Administration, College Planning, Cost Effectiveness
Montgomery, James R.; And Others – 1981
A computerized faculty allocation and reallocation model is presented to aid the decision maker in evaluating the outcomes of various strategies. A unique goal can be computed for each department based on the average index of the institution, the average of the college, the preceding average of the department, and a goal established by management…
Descriptors: College Faculty, College Planning, Computer Oriented Programs, Decision Making
Hotchkiss, Lawrence – 1979
This document was prepared in connection with a three-year longitudinal study of career expectations of high school students conducted to explain scientifically the process by which youth form career expectations, e.g., educational, occupational, and income expectations. Divided into six chapters, this document contains a theoretical rationale for…
Descriptors: Career Development, Concept Formation, Decision Making, Educational Research
Duckwall, Julia M.; Johnson, F. Craig – 1982
The communication of research findings among collegiate institutional researchers is considered in relation to the contribution of qualitative language in general, and catastrophe theory in particular. The qualitative language of catastrophe theory may help reduce the arbitrariness of description, through identification of qualitative features…
Descriptors: College Planning, Comparative Analysis, Decision Making, Educational Finance
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Elliott, William F. – New Directions for Institutional Research, 1980
As tuition charges increase and more students are eligible for financial aid, colleges must develop a concrete strategy to manage financial aid resources. Mechanisms to help financial aid officers effectively utilize aid resources in enrolling students are discussed. Mathematical formulas and calculations are included. (Author/JMD)
Descriptors: Decision Making, Educational Finance, Enrollment Influences, Higher Education