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Çevik, Mustafa; Tabaru-Örnek, Gizem – International Online Journal of Education and Teaching, 2020
In this study, it was aimed to compare the predictions of the academic achievement of the artificial neural networks (ANN) run in MATLAB and SPSS software and to determine the factors related to their academic achievement. Sample consisted of 465 students who were studying at Grade 4 in primary schools in the Central Anatolian Region of Turkey in…
Descriptors: Comparative Analysis, Academic Achievement, Computer Software, Prediction
Mirmoghtadaie, Zohresadat; Keshavarz, Mohsen; Mohammadimehr, Mojgan; Rasouli, Davood – International Review of Research in Open and Distributed Learning, 2023
In peer observation of teaching, an experienced colleague in the educational environment of a faculty member observes the educational performance of that faculty member and provides appropriate feedback. The use of peer review as an alternative source of evidence of teaching effectiveness is increasing. However, no research has been done in the…
Descriptors: Learning Management Systems, Academic Achievement, Peer Evaluation, Teacher Evaluation
Bayard, Sybille; Imlig, Flavian; Schmid, Simona – Education Sciences, 2022
The Canton of Zurich is characterized by strong socio-spatial polarization typical for large and dynamic metropolitan areas. A helpful way to depict spatial dimensions is spatial typologies. Existing spatial categorizations of the Canton of Zurich are limited for education because they focus primarily on economic factors, which are not the only…
Descriptors: Municipalities, Socioeconomic Status, Neighborhoods, Extracurricular Activities
Papageorgiou, Elmarie; Callaghan, Chris William – Accounting Education, 2020
This paper uses data from 4745 first-year accountancy students of a large South African university, for a 7-year period (2011-2017), to understand how certain skills endowments and individual attributes have changed in their contributions to student's performance over time. To do so, the variance associated with an external shock to the learning…
Descriptors: Accounting, Professional Education, Academic Achievement, Factor Analysis
Yoo, Hanwook; Wolf, Mikyung Kim; Ballard, Laura D. – Practical Assessment, Research & Evaluation, 2023
As the theme of the 2022 annual meeting of the American Education Research Association, cultivating equitable education systems has gained renewed attention amid an increasingly diverse society. However, systemic inequalities persist for traditionally underserved student populations. As a way to better address diverse students' needs, it is of…
Descriptors: Comparative Analysis, Native Language, English Language Learners, Multilingualism
Lin, Wei-Sheng; Hsu, Yuling; Liang, Chaoyun – International Journal of Technology and Design Education, 2014
Three studies were combined to examine the effects of creativity and imagination on the academic performance of design students. Study 1 conducted an exploratory factor analysis to determine the most appropriate structure of the Creativity Capability Scale (CCS) in a sample of 313 college students. The scale was a new self-report measure, and it…
Descriptors: Imagination, Academic Achievement, Creativity, Factor Analysis
Walker, Allan David; Lee, Moosung; Bryant, Darren A. – School Effectiveness and School Improvement, 2014
This article aims to explain the role principals play in the variation in academic achievement between secondary schools in Hong Kong. The article draws on survey data from 179 key staff and 2,037 students from 42 schools. The study uses 2 analytical approaches. First, it employs classification and regression tree analysis (CART). This was used to…
Descriptors: Foreign Countries, Accountability, Principals, Administrator Role
Kilgus, Stephen P.; Sims, Wesley A.; von der Embse, Nathaniel P.; Riley-Tillman, T. Chris – School Psychology Quarterly, 2015
The purpose of this investigation was to evaluate the models for interpretation and use that serve as the foundation of an interpretation/use argument for the Social and Academic Behavior Risk Screener (SABRS). The SABRS was completed by 34 teachers with regard to 488 students in a Midwestern high school during the winter portion of the academic…
Descriptors: Screening Tests, Factor Analysis, Models, High School Students
Blazar, David; Litke, Erica; Barmore, Johanna – American Educational Research Journal, 2016
Education agencies are evaluating teachers using student achievement data. However, very little is known about the comparability of test-based or "value-added" metrics across districts and the extent to which they capture variability in classroom practices. Drawing on data from four urban districts, we found that teachers were…
Descriptors: Educational Quality, Teacher Evaluation, Academic Achievement, School Districts
Salta, Katerina; Tzougraki, Chryssa – Research in Science Education, 2011
The students' performance in various types of problems dealing with the conservation of matter during chemical reactions has been investigated at different levels of schooling. The participants were 499 ninth grade (ages 14, 15 years) and 624 eleventh grade (ages 16, 17 years) Greek students. Data was collected using a written questionnaire…
Descriptors: Low Achievement, Chemistry, Problem Solving, Correlation
Gaotlhobogwe, Michael; Laugharne, Janet; Durance, Isabelle – Educational Research, 2011
Background: Understanding student attitudes to curriculum subjects is central to providing evidence-based options to policy makers in education. Purpose: We illustrate how quantitative approaches used in the social sciences and based on multivariate analysis (categorical Principal Components Analysis, Clustering Analysis and General Linear…
Descriptors: Student Attitudes, Social Sciences, Factor Analysis, Foreign Countries

Khan, S. B.; Roberts, Dennis M. – Educational and Psychological Measurement, 1975
The survey was administered to high school seniors. Analysis supported 3 of the 4 hypothesized factors: Delay Avoidance (DA), Work Methods (WM), and Teacher Approval (TA). The Educational Acceptance (EA) factor was not supported. Implications for counseling are discussed. (Author/BJG)
Descriptors: Academic Achievement, Attitude Measures, Classification, Factor Analysis
Springer, Matthew G.; Lewis, Jessica L.; Podgursky, Michael J.; Ehlert, Mark W.; Taylor, Lori L.; Lopez, Omar S.; Peng, Art – National Center on Performance Incentives, 2009
This report presents findings from the second-year evaluation of the Governor's Educator Excellence Grant (GEEG) program. The GEEG program was federally- and state-funded and provided three-year grants to schools to design and implement performance pay plans from the 2005-06 to 2007-08 school years. GEEG was implemented in 99 high poverty, high…
Descriptors: Teacher Persistence, Achievement Gains, Academic Achievement, Factor Analysis
Texas Educator Excellence Grant (TEEG) Program: Year Two Evaluation Report. Policy Evaluation Report
Springer, Matthew G.; Podgursky, Michael J.; Lewis, Jessica L.; Ehlert, Mark W.; Gronberg, Timothy J.; Hamilton, Laura S.; Jansen, Dennis W.; Lopez, Omar S.; Peng, Art; Stecher, Brian M.; Taylor, Lori L. – National Center on Performance Incentives, 2008
This report presents findings from the second year of a multi-year evaluation of the Texas Educator Excellence Grant (TEEG) program and background information about the design and implementation of the District Awards for Teacher Excellence (DATE) program. The TEEG and DATE programs operating in Texas make up the largest state-funded performance…
Descriptors: Teacher Persistence, Achievement Gains, Academic Achievement, Program Effectiveness
Stamper, John, Ed.; Pardos, Zachary, Ed.; Mavrikis, Manolis, Ed.; McLaren, Bruce M., Ed. – International Educational Data Mining Society, 2014
The 7th International Conference on Education Data Mining held on July 4th-7th, 2014, at the Institute of Education, London, UK is the leading international forum for high-quality research that mines large data sets in order to answer educational research questions that shed light on the learning process. These data sets may come from the traces…
Descriptors: Information Retrieval, Data Processing, Data Analysis, Data Collection