NotesFAQContact Us
Collection
Advanced
Search Tips
Laws, Policies, & Programs
What Works Clearinghouse Rating
Showing all 15 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
CannistrĂ , Marta; Masci, Chiara; Ieva, Francesca; Agasisti, Tommaso; Paganoni, Anna Maria – Studies in Higher Education, 2022
This paper combines a theoretical-based model with a data-driven approach to develop an Early Warning System that detects students who are more likely to dropout. The model uses innovative multilevel statistical and machine learning methods. The paper demonstrates the validity of the approach by applying it to administrative data from a leading…
Descriptors: Dropouts, Potential Dropouts, Dropout Prevention, Dropout Characteristics
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Gomes, Cristiano Mauro Assis; Almeida, Leandro S. – Practical Assessment, Research & Evaluation, 2017
Predictive studies have been widely undertaken in the field of education to provide strategic information about the extensive set of processes related to teaching and learning, as well as about what variables predict certain educational outcomes, such as academic achievement or dropout. As in any other area, there is a set of standard techniques…
Descriptors: Predictive Measurement, Statistical Analysis, Decision Making, Foreign Countries
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Hao, Jinmei; Li, Suke – Journal of Education and Practice, 2017
With the adjustment of industrial structure of China in recent years, the market urgently needs different levels of professionals. Specialty education is an important part of higher education in China, has its unique advantages. Through the analysis of the history data of specialty education in our country, the result shows that the specialty…
Descriptors: Foreign Countries, Specialization, Specialists, Enrollment Trends
Peer reviewed Peer reviewed
Direct linkDirect link
Williamson, Ben – Journal of Education Policy, 2016
Educational institutions and governing practices are increasingly augmented with digital database technologies that function as new kinds of policy instruments. This article surveys and maps the landscape of digital policy instrumentation in education and provides two detailed case studies of new digital data systems. The Learning Curve is a…
Descriptors: Visualization, Synchronous Communication, Governance, Data Collection
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Livieris, Ioannis E.; Mikropoulos, Tassos A.; Pintelas, Panagiotis – Themes in Science and Technology Education, 2016
Educational data mining is an emerging research field concerned with developing methods for exploring the unique types of data that come from educational context. These data allow the educational stakeholders to discover new, interesting and valuable knowledge about students. In this paper, we present a new user-friendly decision support tool for…
Descriptors: Predictive Measurement, Decision Support Systems, Academic Achievement, Exit Examinations
Peer reviewed Peer reviewed
Direct linkDirect link
Conijn, Rianne; Snijders, Chris; Kleingeld, Ad; Matzat, Uwe – IEEE Transactions on Learning Technologies, 2017
With the adoption of Learning Management Systems (LMSs) in educational institutions, a lot of data has become available describing students' online behavior. Many researchers have used these data to predict student performance. This has led to a rather diverse set of findings, possibly related to the diversity in courses and predictor variables…
Descriptors: Blended Learning, Predictor Variables, Predictive Validity, Predictive Measurement
Peer reviewed Peer reviewed
Direct linkDirect link
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
National Centre for Vocational Education Research (NCVER), 2016
This work asks one simple question: "how reliable is the method used by the National Centre for Vocational Education Research (NCVER) to estimate projected rates of VET program completion?" In other words, how well do early projections align with actual completion rates some years later? Completion rates are simple to calculate with a…
Descriptors: Vocational Education, Graduation Rate, Predictive Measurement, Predictive Validity
Peer reviewed Peer reviewed
Direct linkDirect link
Tsai, Chih-Fong; Tsai, Ching-Tzu; Hung, Chia-Sheng; Hwang, Po-Sen – Australasian Journal of Educational Technology, 2011
Enabling undergraduate students to develop basic computing skills is an important issue in higher education. As a result, some universities have developed computer proficiency tests, which aim to assess students' computer literacy. Generally, students are required to pass such tests in order to prove that they have a certain level of computer…
Descriptors: Foreign Countries, Undergraduate Students, At Risk Students, Graduation Requirements
Peer reviewed Peer reviewed
Direct linkDirect link
Teo, Timothy – Interactive Learning Environments, 2012
This study examined pre-service teachers' self-reported intention to use technology. One hundred fifty-seven participants completed a survey questionnaire measuring their responses to six constructs from a research model that integrated the Technology Acceptance Model (TAM) and Theory of Planned Behavior (TPB). Structural equation modeling was…
Descriptors: Foreign Countries, Educational Technology, Structural Equation Models, Computer Uses in Education
Peer reviewed Peer reviewed
Direct linkDirect link
Fusilier, Marcelline; Durlabhji, Subhash; Cucchi, Alain – Journal of Educational Computing Research, 2008
National background of users may influence the process of technology acceptance. The present study explored this issue with the new, integrated technology use model proposed by Sun and Zhang (2006). Data were collected from samples of college students in India, Mauritius, Reunion Island, and United States. Questionnaire methodology and…
Descriptors: Foreign Countries, Data Analysis, Internet, Technology Integration
Peer reviewed Peer reviewed
Francisca, M.; And Others – Physics Education, 1986
Analyzes data presented in a recent article (EJ 328 649) examining the relationship between A-level physics and mathematics and degree performance in engineering or physics. A grade of A in A-level physics predicted first class degree performance. (JM)
Descriptors: College Science, Data Analysis, Engineering, Foreign Countries
Stanley, Julian C; And Others – College Board Review, 1986
The initial effort in applying the SAT-M to young Chinese students revealed that many of them reason extraordinarily well mathematically before age 13 and before having covered the bulk of the high-school mathematics curriculum. The conclusion seems to be that they must have keen analytical ability. (MLW)
Descriptors: Ability Identification, Aptitude Tests, College Entrance Examinations, Comparative Analysis
Lieshoff, Sylvia – 1993
This paper examines the use of environmental scanning for institutions of higher education to achieve the following objectives: (1) provide early warning of changes that will have an impact on education; (2) define potential threats and opportunities to the institution or department; (3) promote a future orientation in faculty; and (4) alert…
Descriptors: College Planning, Data Analysis, Data Collection, Environmental Scanning
Saunders, S. – 2001
Training indicators are functional suites of quantitative and qualitative indicators of current or future vocational education and training (VET) supply and demand. The training indicators approach to educational planning considers indicators of present and likely future conditions for skilled labor and forms judgments about the most appropriate…
Descriptors: Academic Standards, Benchmarking, Comparative Analysis, Data Analysis