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Rollinson, Joseph; Brunskill, Emma – International Educational Data Mining Society, 2015
At their core, Intelligent Tutoring Systems consist of a student model and a policy. The student model captures the state of the student and the policy uses the student model to individualize instruction. Policies require different properties from the student model. For example, a mastery threshold policy requires the student model to have a way…
Descriptors: Prediction, Models, Educational Policy, Intelligent Tutoring Systems
Snow, Erica L. – International Educational Data Mining Society, 2015
Intelligent tutoring systems are adaptive learning environments designed to support individualized instruction. The adaptation embedded within these systems is often guided by user models that represent one or more aspects of students' domain knowledge, actions, or performance. The proposed project focuses on the development and testing of user…
Descriptors: Intelligent Tutoring Systems, Models, Individualized Instruction, Needs Assessment
Mellody, Maureen – National Academies Press, 2014
As the availability of high-throughput data-collection technologies, such as information-sensing mobile devices, remote sensing, internet log records, and wireless sensor networks has grown, science, engineering, and business have rapidly transitioned from striving to develop information from scant data to a situation in which the challenge is now…
Descriptors: Workshops, Training, Competence, Data Collection
Reporting Data with "Over-the-Counter" Data Analysis Supports Increases Educators' Analysis Accuracy
Rankin, Jenny Grant – Online Submission, 2013
There is extensive research on the benefits of making data-informed decisions to improve learning, but these benefits rely on the data being effectively interpreted. Despite educators' above-average intellect and education levels, there is evidence many educators routinely misinterpret student data. Data analysis problems persist even at districts…
Descriptors: Statistical Data, Data Interpretation, Data Analysis, Error of Measurement
Pattison, Sandra; Hargreaves, Jo – National Centre for Vocational Education Research (NCVER), 2009
The National Centre for Vocational Education Research (NCVER) was asked by Technical and Further Education (TAFE) Directors Australia to consider, in a discussion paper for their conference held on the Gold Coast in September 2009, how a "tertiary education" sector impacts on the way people think about research and statistics. While a…
Descriptors: Higher Education, Foreign Countries, Databases, Statistics
Davis, Benjamin G.; Irwin, Paul M. – 1974
This paper documents a successful methodology for the validation of data in general and for evaluating educational finance data in particular. The report addresses the errors found as a result of the independent completion of Part B-1 of the Elementary-Secondary General Information System (ELSEGIS)--the Local Education Agency Fiscal Report. This…
Descriptors: Data, Data Analysis, Data Collection, Educational Finance
Babcock, Judith A. – 1983
Indexing is a tool that can be used with longitudinal, quantitative data for analysis of relative changes and for comparisons of changes among items. For greater accuracy, raw financial data should be deflated into constant dollars prior to indexing. This paper demonstrates the procedures for indexing, statistical deflation, and the use of…
Descriptors: Cost Indexes, Data Analysis, Decision Making, Economics
Horst, Leslie; Donahue, Maryellen – 1989
Based on an assessment of the research of others and personal research experience, suggestions are provided on the analysis and reporting of data on high school dropouts. Most of the experience upon which these insights are based is associated with schools in Boston, Massachusetts. Topics covered include types of statistics to be reported,…
Descriptors: Data Analysis, Data Collection, Dropout Characteristics, Dropout Rate
Burstein, Leigh – 1975
Since problems associated with the statistical methodology of educational research are becoming increasingly important, this paper examines a subset of problems associated with the analysis and interpretation of aggregated data. Two major questions arise: (1) if a researcher knows the level (e.g., individual, teacher/classroom, school, school…
Descriptors: Data Analysis, Data Collection, Data Processing, Educational Research
Mu, Xiangming; Marchionini, Gary – Proceedings of the ASIST Annual Meeting, 2001
Describes a novel design of a Table Browser for casual users of statistical data. Focuses on the overall system architecture and the user interface. Describes the prototype interface and presents results of experiments testing the efficacy of the multi-threaded data flow. (AEF)
Descriptors: Computer Interfaces, Computer System Design, Data Analysis, Information Systems
Hoffman, Lee McGraw – 1990
Some issues in defining dropouts and reporting information about them are explored, with reference to the Common Core of Data (CCD) survey of the National Center for Education Statistics. There has not been any uniform national count of how many students leave school, and no commonly accepted definition has been developed that allows a number to…
Descriptors: Data Analysis, Data Collection, Definitions, Dropout Research
Sanford, Timothy R. – 1982
The most advantageous relationship between computer technology and institutional research is considered. Three potential problem areas are discussed: those associated with a central data processing center, those germane to minicomputers or terminals within the institutional research office, and those nondiscriminating types which cover both…
Descriptors: Computer Oriented Programs, Computers, Data Analysis, Data Collection
Burstein, Leigh – 1977
The author contends that the secondary analyst may have a different perspective and theoretical persuasion than the original investigator, may have the advantage of more current theory and practices than those originally available, may move beyond the substantive and methodological limitations of the original investigation, and may not be faced by…
Descriptors: Confidentiality, Data Analysis, Data Collection, Educational Research
Shim, Wonsik; Kantor, Paul B. – Proceedings of the ASIS Annual Meeting, 1998
Describes a new analytical tool, data envelope analysis (DEA) model, which can provide better understanding of the efficiency of academic research libraries. Reports the results of a study using 1994-1995 Association of Research Libraries statistics together with expert judgments, in terms of constraints, to make the model more applicable to the…
Descriptors: Academic Libraries, Cost Effectiveness, Data Analysis, Evaluation Criteria
Phelps, Thomas C. – 1975
The data gathering forms and activities developed during the planning and implementation of an adult independent study and guidance program at the Salt Lake City Public Library are described. The need for a utilization of this data is outlined, and the study's goals and objectives are stated. Appendixes contain flow charts of the Salt Lake City…
Descriptors: Adult Education, Data Analysis, Data Collection, Independent Study
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