NotesFAQContact Us
Collection
Advanced
Search Tips
Audience
Laws, Policies, & Programs
What Works Clearinghouse Rating
Showing 1 to 15 of 21 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Yang, Tzu-Chi; Liu, Yih-Lan; Wang, Li-Chun – Educational Technology & Society, 2021
The recently increased importance of practicing precision education has attracted much attention. To better understand students' learning and the relationship between their individual differences and learning outcomes, the bird-eye view possible for educational policymakers and stakeholders from educational data mining and institutional research…
Descriptors: Institutional Research, Prediction, Learning Analytics, Undergraduate Students
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Chenglong Wang – Turkish Online Journal of Educational Technology - TOJET, 2024
The rapid development of education informatization has accumulated a large amount of data for learning analytics, and adopting educational data mining to find new patterns of data, develop new algorithms and models, and apply known predictive models to the teaching system to improve learning is the challenge and vision of the education field in…
Descriptors: Decision Making, Prediction, Models, Intervention
Peer reviewed Peer reviewed
Direct linkDirect link
Krefeld-Schwalb, Antonia; Donkin, Chris; Newell, Ben R.; Scheibehenne, Benjamin – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2019
Past research indicates that individuals respond adaptively to contextual factors in multiattribute choice tasks. Yet it remains unclear how this adaptation is cognitively governed. In this article, empirically testable implementations of two prominent competing theoretical frameworks are developed and compared across two multiattribute choice…
Descriptors: Models, Cues, Probability, Experiments
Peer reviewed Peer reviewed
Direct linkDirect link
Nahar, Khaledun; Shova, Boishakhe Islam; Ria, Tahmina; Rashid, Humayara Binte; Islam, A. H. M. Saiful – Education and Information Technologies, 2021
Information is everywhere in a hidden and scattered way. It becomes useful when we apply Data mining to extracts the hidden, meaningful, and potentially useful patterns from these vast data resources. Educational data mining ensures a quality education by analyzing educational data based on various aspects. In this paper, we have analyzed the…
Descriptors: Learning Analytics, College Students, Engineering Education, Data Collection
Peer reviewed Peer reviewed
Direct linkDirect link
Bezerra, Luis Naito Mendes; Silva, Márcia Terra – International Journal of Distance Education Technologies, 2020
In the current context of distance learning, learning management systems (LMSs) make it possible to store large volumes of data on web browsing and completed assignments. To understand student behavior patterns in this type of environment, educators and managers must rethink conventional approaches to the analysis of these data and use appropriate…
Descriptors: Learning Analytics, Data Collection, Class Size, Online Courses
Peer reviewed Peer reviewed
Direct linkDirect link
Berger, Cynthia; Crossley, Scott; Skalicky, Stephen – Studies in Second Language Acquisition, 2019
A large dataset of word recognition behavior from nonnative speakers (NNS) of English was collected using an online crowdsourced lexical decision task. Lexical features were used to predict NNS lexical decision latencies and accuracies. Predictors of NNS latencies and accuracy included contextual diversity, age of acquisition, and contextual…
Descriptors: Word Recognition, Decision Making, Second Language Learning, English (Second Language)
Peer reviewed Peer reviewed
Direct linkDirect link
Mimis, Mohamed; El Hajji, Mohamed; Es-saady, Youssef; Oueld Guejdi, Abdellah; Douzi, Hassan; Mammass, Driss – Education and Information Technologies, 2019
The educational recommendation system to provide support for academic guidance and adaptive learning has always been an important issue of research for smart education. A bad guidance can give rise to difficulties in further studies and can be extended to school dropout. This paper explores the potential of Educational Data Mining for academic…
Descriptors: Educational Counseling, Guidance, Educational Research, Data Collection
Peer reviewed Peer reviewed
Direct linkDirect link
Attaran, Mohsen; Stark, John; Stotler, Derek – Industry and Higher Education, 2018
Business leaders around the world are using emerging technologies to capitalize on data, to create business value and to compete effectively in a digitally driven world. They rely on data analytics to accelerate time to insight and to gain a better understanding of their customers' needs and wants. However, big data and data analytics solutions in…
Descriptors: Models, Higher Education, Data Collection, Program Implementation
Pouliakas, Konstantinos, Ed. – Cedefop - European Centre for the Development of Vocational Training, 2021
The world of work is being impacted by a fourth industrial revolution, transformed by artificial intelligence and other emerging technologies. With forecasts suggesting large shares of workers, displaced by automation, in need of upskilling/reskilling, the design of active skills policies is necessary. Conventional methods used to anticipate…
Descriptors: Job Skills, Information Technology, Artificial Intelligence, Employment Qualifications
Peer reviewed Peer reviewed
Direct linkDirect link
Baker, Ryan S. – International Journal of Artificial Intelligence in Education, 2016
The initial vision for intelligent tutoring systems involved powerful, multi-faceted systems that would leverage rich models of students and pedagogies to create complex learning interactions. But the intelligent tutoring systems used at scale today are much simpler. In this article, I present hypotheses on the factors underlying this development,…
Descriptors: Artificial Intelligence, Intelligent Tutoring Systems, Hypothesis Testing, Data Collection
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
Peer reviewed Peer reviewed
Direct linkDirect link
White, Katherine M.; O'Connor, Erin L.; Hamilton, Kyra – British Journal of Educational Psychology, 2011
Background: Although class attendance is linked to academic performance, questions remain about what determines students' decisions to attend or miss class. Aims: In addition to the constructs of a common decision-making model, the theory of planned behaviour, the present study examined the influence of student role identity and university student…
Descriptors: Student Attitudes, Maintenance, Correlation, Academic Achievement
Pascopella, Angela – District Administration, 2012
Predicting the future is now in the hands of K12 administrators. While for years districts have collected thousands of pieces of student data, educators have been using them only for data-driven decision-making or formative assessments, which give a "rear-view" perspective only. Now, using predictive analysis--the pulling together of data over…
Descriptors: Expertise, Prediction, Decision Making, Data
Kennedy, William R. – 1980
As more emphasis is placed upon institutional research that provides information relating to long-term strategic planning, as well as to short-term operational considerations, program evaluation techniques that merely analyze past or current budget and enrollment statistics will become increasingly inadequate. Such techniques are based on data…
Descriptors: Accountability, Community Colleges, Data Collection, Decision Making
WATSON, CICELY, ED. – 1967
THIS BOOK COMPRISES THE MAJOR PAPERS DELIVERED AT A CONFERENCE ON MARCH 20-22, 1967, SPONSORED BY THE POLICY AND DEVELOPMENT COUNCIL, AN ADVISORY UNIT OF THE DEPARTMENT OF EDUCATION IN ONTARIO. THE CONFERENCE WAS ATTENDED BY REPRESENTATIVE PERSONS FROM DEPARTMENTS OF GOVERNMENT, UNIVERSITIES, AND MAJOR SCHOOL SYSTEMS ACROSS CANADA. THE CONFERENCE…
Descriptors: Data Collection, Decision Making, Economic Development, Economic Factors
Previous Page | Next Page »
Pages: 1  |  2