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Proceedings of the International Conference on Educational Data Mining (EDM) (11th, Raleigh, North Carolina, July 16-20, 2018)
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Boyer, Kristy Elizabeth, Ed.; Yudelson, Michael, Ed. – International Educational Data Mining Society, 2018
The 11th International Conference on Educational Data Mining (EDM 2018) is held under the auspices of the International Educational Data Mining Society at the Templeton Landing in Buffalo, New York. This year's EDM conference was highly competitive, with 145 long and short paper submissions. Of these, 23 were accepted as full papers and 37…
Descriptors: Data Collection, Data Analysis, Computer Science Education, Program Proposals
Utilizing Throw-Away Data: Invalid and Missing Data Can Have Meaning! AIR 1992 Annual Forum Paper.
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Smith, Constance K.; Waggener, Anna T. – 1992
Two studies were conducted at the Southeastern Louisiana University (SLU) to determine possible uses of errors and omissions on surveys of incoming and freshmen college students. The subjects of the first study were 1,927 individuals who had applied for admission to SLU and attended freshman orientation in the summer of 1989. Blanks and incorrect…
Descriptors: Academic Achievement, Academic Persistence, College Applicants, College Freshmen
Teaching Common Errors in Applying a Procedure.
Marcone, Stephen; Reigeluth, Charles M. – Educational Communication and Technology Journal, 1988
Discusses study that investigated whether or not the teaching of matched examples and nonexamples in the form of common errors could improve student performance in undergraduate music theory courses. Highlights include hypotheses tested, pretests and posttests, and suggestions for further research with different age groups. (19 references)…
Descriptors: Academic Achievement, Analysis of Covariance, Error Patterns, Higher Education
The Effects of Texture and Number of Parts on the Ability of Music Majors to Detect Performance Errors.
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Byo, James L. – Journal of Research in Music Education, 1997
Examines graduate and undergraduate music majors' ability to detect pitch and rhythm errors in various settings of textually contrasting musical excerpts. Students listened to intentionally marred excerpts and attempted to identify the errors. Analysis of variance revealed that the predictor variables did not function independently of each other.…
Descriptors: Auditory Discrimination, Auditory Perception, Auditory Stimuli, Auditory Tests
Development of the 1984-85 Validation Selection Criteria: The Eclectic Error Prone Model.
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Advanced Technology, Inc., Reston, VA. – 1984
The development of the error prone model (EPM) for the 1984-1985 student financial aid validation criteria for Pell Grant recipient selection is discussed, based on a comparison of the 1983-1984 EPM criteria and a newly estimated EPM. Procedures/assumptions on which the new EPM was based include: a sample of 1982-1983 Pell Grant recipients…
Descriptors: Comparative Analysis, Dependents, Error Patterns, Evaluation Criteria
Development and Use of Error-Prone Models to Supplement Pre-Established Criteria (PEC) in Selecting Pell Grant Recipients for Validation.
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Advanced Technology, Inc., Reston, VA. – 1982
The development of a number of error-prone models to select Pell Grant recipients for validation is discussed. The 1983-1984 Pell Grant validation strategy consists of a two-stage approach: selection using Pre-Established Criteria (PEC) followed by selection using Error Prone Modeling (EPM). The database used for model development consists of a…
Descriptors: Comparative Analysis, Cost Effectiveness, Dependents, Error Patterns