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Showing 1 to 15 of 19 results Save | Export
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Smith-Millman, Marissa K.; Flaspohler, Paul D.; Maras, Melissa A.; Splett, Joni Williams; Warmbold, Kristy; Dinnen, Hannah; Luebbe, Aaron – Advances in School Mental Health Promotion, 2017
Some universal behavioural screening processes require classroom teachers to complete a risk assessment measure on each student in their class, leading to a possible, but unexplored, problem: risk assessment scores may be influenced by the teacher completing the measure. The current study investigated whether teacher-reported risk assessment…
Descriptors: Risk Assessment, Differences, Scores, Elementary School Teachers
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Chen, Chen-Tung; Chang, Kai-Yi – EURASIA Journal of Mathematics, Science & Technology Education, 2017
The phenomenon of low fertility has been negatively impacted on the social structure of the educational environment in Taiwan. To increase the learning effectiveness of students became the most important issue for the Universities in Taiwan. Due to the subjective judgment of evaluators and the attributes of influenced factors are always fuzzy, it…
Descriptors: Data Collection, Data Analysis, Foreign Countries, Higher Education
Ye, Cheng; Segedy, James R.; Kinnebrew, John S.; Biswas, Gautam – International Educational Data Mining Society, 2015
This paper discusses Multi-Feature Hierarchical Sequential Pattern Mining, MFH-SPAM, a novel algorithm that efficiently extracts patterns from students' learning activity sequences. This algorithm extends an existing sequential pattern mining algorithm by dynamically selecting the level of specificity for hierarchically-defined features…
Descriptors: Learning Activities, Learning Processes, Data Collection, Student Behavior
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Jasper, Andrea D.; Taber Doughty, Teresa – Focus on Autism and Other Developmental Disabilities, 2015
This study examined the effects of delayed recording on the accuracy of data recorded by special educators serving students with high- or low-incidence disabilities. A multi-element design was used to compare the accuracy of data recorded across three conditions: (a) immediately after a student's target behavior occurred, (b) immediately after the…
Descriptors: Special Education Teachers, Special Education, Disabilities, Comparative Analysis
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Cross, Donna; Epstein, Melanie; Hearn, Lydia; Slee, Phillip; Shaw, Therese; Monks, Helen – International Journal of Behavioral Development, 2011
In 2003 Australia was one of the first countries to develop an integrated national policy, called the National Safe Schools Framework (NSSF), for the prevention and management of violence, bullying, and other aggressive behaviors. The effectiveness of this framework has not yet been formally evaluated. Cross-sectional data collected in 2007 from…
Descriptors: Bullying, Foreign Countries, Barriers, School Safety
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Christ, Theodore J.; Riley-Tillman, T. Chris; Chafouleas, Sandra; Jaffery, Rosemary – School Psychology Review, 2011
The method of Direct Behavior Rating (DBR) incorporates aspects of both systematic direct observation and behavior rating scales to provide an efficient means to collect time series data. This study extended the development and evaluation of DBR Single-Item Scales (DBR-SIS) as a behavior assessment tool. Eighty-eight undergraduate students used…
Descriptors: Video Technology, Behavior Problems, Student Behavior, Observation
Jernigan, John Orr – ProQuest LLC, 2010
The purpose of this study was to examine the behavioral and demographic characteristics of deaf males enrolled at state school for the Deaf. An analysis of student, family, and educational variables was conducted in order to provide a composite description of both the type and frequency of the offenses and of the offender. Participants were 90…
Descriptors: At Risk Students, Student Behavior, Males, Information Systems
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Chafouleas, Sandra M.; Riley-Tillman, T. Chris; Sassu, Kari A.; LaFrance, Mary J.; Patwa, Shamim S. – Journal of Positive Behavior Interventions, 2007
In this study, the consistency of on-task data collected across raters using either a Daily Behavior Report Card (DBRC) or systematic direct observation was examined to begin to understand the decision reliability of using DBRCs to monitor student behavior. Results suggested very similar conclusions might be drawn when visually examining data…
Descriptors: Special Education, Student Behavior, Observation, Effect Size
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Barth, Richard P.; Lloyd, E. Christopher; Green, Rebecca L.; James, Sigrid; Leslie, Laurel K.; Landsverk, John – Journal of Emotional and Behavioral Disorders, 2007
Children identified as having emotional and behavioral disorders (EBD) may have different out-of-home care placements than their peers without EBD. This study compared the factors influencing placement movements for 362 children with EBD and 363 children without EBD, using clinical "Child Behavior Checklist" (CBCL) scores at baseline…
Descriptors: Child Behavior, Check Lists, Siblings, Depression (Psychology)
Gardner, C. H.; And Others – 1982
The classroom behaviors recorded during three second grade reading lessons provide suitable evidence for comparing the relative merits of using narrative observations versus videotapes as data collection techniques. The comparative analysis illustrates the detail and precision of videotape. Primarily, videotape gives a true picture of linear time,…
Descriptors: Classroom Observation Techniques, Classroom Research, Comparative Analysis, Data Collection
Kissel, Mary Ann; Yeager, John L. – 1971
Several sampling procedures for collecting observational data on student activities were studied in an effort to determine their relative efficiency. The setting was a fifth grade Individually Prescribed Instruction (IPI) mathematics class of thirty-three pupils. A criterion measure was obtained by cumulating the measurements obtained on the…
Descriptors: Class Activities, Classroom Observation Techniques, Comparative Analysis, Data Collection
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Zang, Wei; Lin, Fuzong – International Journal of Distance Education Technologies, 2006
Student behavior analysis is an active research topic in distance education in recent years. In this article, we propose a new method called Boosting to investigate students' behaviors. The Boosting Algorithm can be treated as a data mining method, trying to infer from a large amount of training data the essential factors and their relations that…
Descriptors: Student Behavior, Distance Education, Data Collection, Data Analysis
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Morphew, Christopher C.; Williams, Andrew N. – Journal of Computing in Higher Education, 1998
A study conducted at one large research university compared electronic mail and telephones as methods for gathering survey data from undergraduate students. Problems associated with electronic-mail use include higher rate of socially undesirable activity among respondents and difficulty in identifying the target population. Implications for campus…
Descriptors: Behavior Patterns, Bias, College Students, Comparative Analysis
Fadale, LaVerna M.; Martinez, Ernest A. – 1993
A study was conducted to generate a profile of the movement of State University of New York (SUNY) two-year college students to four-year institutions. In addition, out-of-state and in-state independent institutions, identified as frequent recipients of transfers from SUNY two-year colleges, were surveyed to determine the types of transferee data…
Descriptors: Associate Degrees, College Graduates, College Transfer Students, Community Colleges
Lehman, Penny W.; And Others – 1992
The Community College Student Experiences Questionnaire (CCSEQ) is an instrument designed to determine how community college students spend their time and what quality of effort they put into learning. Specifically, the content of the questionnaire focuses on four elements: who students are and why they are at the college; how extensively and…
Descriptors: College Environment, Community Colleges, Comparative Analysis, Data Collection
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