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Simsek, Ahmet Salih – International Journal of Assessment Tools in Education, 2023
Likert-type item is the most popular response format for collecting data in social, educational, and psychological studies through scales or questionnaires. However, there is no consensus on whether parametric or non-parametric tests should be preferred when analyzing Likert-type data. This study examined the statistical power of parametric and…
Descriptors: Error of Measurement, Likert Scales, Nonparametric Statistics, Statistical Analysis
Calver, Michael; Fletcher, Douglas – American Biology Teacher, 2020
Data collected in many biology laboratory classes are on ratio or interval scales where the size interval between adjacent units on the scale is constant, which is a critical requirement for analysis with parametric statistics such as t-tests or analysis of variance. In other cases, such as ratings of disease or behavior, data are collected on…
Descriptors: Statistical Analysis, Data Collection, Biology, Science Laboratories
Van Norman, Ethan R.; Ysseldyke, James E. – School Psychology Review, 2020
Within multitiered systems of support, assessment practices that limit the amount of time students miss instruction should be prioritized. At the same time, decisions about student response to intervention need to be based upon technically adequate data. We evaluated the impact of data collection frequency and trend estimation method on the…
Descriptors: Data Collection, Adaptive Testing, Computer Assisted Testing, Computation
Park, Jungkyu; Yu, Hsiu-Ting – Educational and Psychological Measurement, 2016
The multilevel latent class model (MLCM) is a multilevel extension of a latent class model (LCM) that is used to analyze nested structure data structure. The nonparametric version of an MLCM assumes a discrete latent variable at a higher-level nesting structure to account for the dependency among observations nested within a higher-level unit. In…
Descriptors: Hierarchical Linear Modeling, Nonparametric Statistics, Data Analysis, Simulation
Marshall, Margaret J.; Duffy, Ashlee Mills; Powell, Stephen; Bartlett, Lesley Erin – International Journal of ePortfolio, 2017
An ePortfolio Assessment Institute (AI) structured as a faculty development opportunity was undertaken to increase faculty confidence in teaching and assessing ePortfolios and to collect reliable data about student performance on four learning outcomes associated with an institutionwide ePortfolio initiative. Faculty raters participated in the…
Descriptors: Electronic Publishing, Portfolio Assessment, Faculty Development, Data Collection
Ju, Boryung; Jin, Tao – Information Research: An International Electronic Journal, 2013
Introduction: The Delphi technique is widely used in library and information science research. However, many researchers in the field fail to employ standard statistical tests when using this technique. This makes the technique vulnerable to criticisms of its reliability and validity. The general goal of this article is to explore how…
Descriptors: Nonparametric Statistics, Delphi Technique, Library Science, Information Science
Kalaian, Sema A.; Kasim, Rafa M. – Practical Assessment, Research & Evaluation, 2012
The Delphi survey technique is an iterative mail or electronic (e-mail or web-based) survey method used to obtain agreement or consensus among a group of experts in a specific field on a particular issue through a well-designed and systematic multiple sequential rounds of survey administrations. Each of the multiple rounds of the Delphi survey…
Descriptors: Delphi Technique, Mail Surveys, Online Surveys, Data Collection
Rosmaniar, Widhyanti; Marzuki, Shahril Charil bin Hj. – Higher Education Studies, 2016
The purpose of this study is to look closely at how aspects of instructional leadership, and organizational learning affect the quality of madrasah in improving the quality of graduate the state madrasah aliyah. The experiment was conducted using a quantitative approach with descriptive and inferential methods, in inferential methods used…
Descriptors: Principals, Instructional Leadership, Workplace Learning, Organizational Development