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Melissa Bond; Hassan Khosravi; Maarten De Laat; Nina Bergdahl; Violeta Negrea; Emily Oxley; Phuong Pham; Sin Wang Chong; George Siemens – International Journal of Educational Technology in Higher Education, 2024
Although the field of Artificial Intelligence in Education (AIEd) has a substantial history as a research domain, never before has the rapid evolution of AI applications in education sparked such prominent public discourse. Given the already rapidly growing AIEd literature base in higher education, now is the time to ensure that the field has a…
Descriptors: Meta Analysis, Artificial Intelligence, Databases, Higher Education
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Fedushko, Solomiia; Ustyianovych, Taras; Syerov, Yuriy – Journal of Intelligence, 2022
In this article, we provide an approach to solve the problem of academic specialty selection in higher educational institutions with Ukrainian entrants as our target audience. This concern affects operations at universities or other academic institutions, the labor market, and the availability of in-demand professionals. We propose a…
Descriptors: Higher Education, College Admission, Foreign Countries, Majors (Students)
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Xu, Jia; Wei, Tingting; Lv, Pin – International Educational Data Mining Society, 2022
In an Intelligent Tutoring System (ITS), problem (or question) difficulty is one of the most critical parameters, directly impacting problem design, test paper organization, result analysis, and even the fairness guarantee. However, it is very difficult to evaluate the problem difficulty by organized pre-tests or by expertise, because these…
Descriptors: Prediction, Programming, Natural Language Processing, Databases
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Langan, A. M.; Harris, W. E.; Barrett, N.; Hamshire, C.; Wibberley, C. – Studies in Higher Education, 2018
There is an increasing requirement in higher education (HE) worldwide to deliver excellence. Benchmarking is widely used for this purpose, but methodological approaches to the creation of benchmark metrics vary greatly. Approaches require selection of factors for inclusion and subsequent calculation of benchmarks for comparison. We describe an…
Descriptors: Benchmarking, Nursing Education, Prediction, Graduation Rate
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Holmes, Lauren; Schumacker, Randall – Measurement: Interdisciplinary Research and Perspectives, 2020
Latent classes of effective and non-effective Algebra I teachers were established using measurements of teacher promoted engagement, teacher promoted understanding, and classroom management from the Measures of Effective Teaching Project (MET Project) database. Historically, robust measures of effective teaching exist in the literature; however,…
Descriptors: Algebra, Mathematics Teachers, Teacher Effectiveness, Databases
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Yitao, Wang; Hua, Wang – Chinese Education & Society, 2019
Research on the group characteristics and channels for selection of party secretaries at private institutions of higher education has important significance in strengthening leadership by party organizations and perfecting internal governance structures at private institutions of higher education. A survey of 293 private institutions of higher…
Descriptors: Educational Policy, Private Colleges, Public Officials, Governance
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Pittayachawan, Siddhi; Macauley, Peter; Evans, Terry – Journal of Higher Education Policy and Management, 2016
This article reports how statistical analyses of PhD thesis records can reveal future research capacities for disciplines beyond their primary fields. The previous research showed that most theses contributed to and/or used methodologies from more than one discipline. In Australia, there was a concern for declining mathematical teaching and…
Descriptors: Databases, Doctoral Dissertations, Foreign Countries, Statistical Analysis
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Treacy, Páraic; Faulkner, Fiona – International Journal of Mathematical Education in Science and Technology, 2015
Deficiencies in beginning undergraduate students' basic mathematical skills has been an issue of concern in higher education, particularly in the past 15 years. This issue has been tracked and analysed in a number of universities in Ireland and internationally through student scores recorded in mathematics diagnostic tests. Students beginning…
Descriptors: Mathematics Instruction, College Mathematics, Undergraduate Students, Mathematics Skills
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Lee, Young-Jin – Educational Technology & Society, 2015
This study investigates whether information saved in the log files of a computer-based tutor can be used to predict the problem solving performance of students. The log files of a computer-based physics tutoring environment called Andes Physics Tutor was analyzed to build a logistic regression model that predicted success and failure of students'…
Descriptors: Physics, Science Instruction, Computer Software, Accuracy
Kroll, Judith A.; Bakerman, Philip – Council for Advancement and Support of Education, 2015
The Council for Advancement and Support of Education (CASE) launched the volunteer-led Asia-Pacific Alumni Relations Survey in 2014 to provide a resource for alumni relations professionals to benchmark performance internally and against fellow institutions of higher education. That was the first survey CASE has done on alumni relations programmes…
Descriptors: Foreign Countries, Alumni, Higher Education, Benchmarking
Nemoto, Tomoko – ProQuest LLC, 2013
Program evaluation in the fields of second language acquisition (SLA) and teaching English to speakers of other languages (TESOL) has a history dating from the 1960's. The focus of previous program evaluations has been on language achievement at the end of the program of study (Lynch, 1996). However, to improve or maintain program quality, teacher…
Descriptors: Graduate Study, Applied Linguistics, Program Evaluation, Foreign Countries
Smith, Vernon C.; Lange, Adam; Huston, Daniel R. – Journal of Asynchronous Learning Networks, 2012
Community colleges continue to experience growth in online courses. This growth reflects the need to increase the numbers of students who complete certificates or degrees. Retaining online students, not to mention assuring their success, is a challenge that must be addressed through practical institutional responses. By leveraging existing student…
Descriptors: Academic Achievement, At Risk Students, Prediction, Community Colleges
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Pomykalski, James J.; Dion, Paul; Brock, James L. – Journal of Education for Business, 2008
In this study, the authors developed a structural equation model that accounted for 79% of the variability of a student's final grade point average by using a sample size of 147 students. The model is based on student grades in 4 foundational business courses: introduction to business, macroeconomics, statistics, and using databases. Educators and…
Descriptors: Grade Point Average, Structural Equation Models, Macroeconomics, Business Administration Education
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Vandamme, J. -P.; Meskens, N.; Superby, J. -F. – Education Economics, 2007
Academic failure among first-year university students has long fuelled a large number of debates. Many educational psychologists have tried to understand and then explain it. Many statisticians have tried to foresee it. Our research aims to classify, as early in the academic year as possible, students into three groups: the "low-risk"…
Descriptors: College Freshmen, Educational Psychology, Questionnaires, Databases
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Bailey, Brenda L. – New Directions for Institutional Research, 2006
Data mining of IPEDS data is used to develop models that calculate predicted graduation rates for two- and four-year institutions. (Contains 7 tables and 5 figures.)
Descriptors: Graduation Rate, Models, Data, Prediction
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