Related Experiment Video

Updated: Nov 5, 2025

Mixed Reality for Education MRE Implementation and Results in Online Classes for Engineering
04:12

Mixed Reality for Education MRE Implementation and Results in Online Classes for Engineering

Published on: June 23, 2023

861

Validation Evidence from using Generalizability Theory in a Basic-Science Course: Reliability of Course-Grades from

Michael J Peeters1, M Kenneth Cor2, Sai Hs Boddu1,3

  • 1University of Toledo College of Pharmacy & Pharmaceutical Sciences, Toledo, OH.

Innovations in Pharmacy
|May 19, 2021
PubMed
Summary

Combining multiple exams using Generalizability Theory (G-Theory) significantly enhances the reliability of course grades for high-stakes decisions. More exams mean fewer items are needed overall for acceptable reliability.

Keywords:
coursegeneralizability theoryoccasionreliabilityvalidation

More Related Videos

Improving Student Outcomes with an Adaptable Molecular Cloning Course-Based Undergraduate Research Experience10:17

Improving Student Outcomes with an Adaptable Molecular Cloning Course-Based Undergraduate Research Experience

Published on: November 15, 2024

1.3K
Use of Galvanic Skin Responses, Salivary Biomarkers, and Self-reports to Assess Undergraduate Student Performance During a Laboratory Exam Activity07:32

Use of Galvanic Skin Responses, Salivary Biomarkers, and Self-reports to Assess Undergraduate Student Performance During a Laboratory Exam Activity

Published on: February 10, 2016

9.6K

Related Concept Videos

Reliability and Validity01:29

Reliability and Validity

Reliability and validity are two important considerations that must be made with any type of data collection. Reliability refers to the ability to consistently produce a given result. In the context of psychological research, this would mean that any instruments or tools used to collect data do so in consistent, reproducible ways.
13.3K
Comparing Experimental Results: Student's t-Test01:09

Comparing Experimental Results: Student's t-Test

The t-test is a statistical method used to compare the sample mean with a population mean or compare two means from two data sets. The test statistic is calculated from the standard deviation, mean, and number of measurements in the data set at a selected confidence interval and then compared to a table of critical values at this confidence level. If the test statistic is smaller than the critical value, the null hypothesis is accepted. In this case, we state that the difference between the...
3.7K
Random and Systematic Errors01:20

Random and Systematic Errors

Scientists always try their best to record measurements with the utmost accuracy and precision. However, sometimes errors do occur. These errors can be random or systematic. Random errors are observed due to the inconsistency or fluctuation in the measurement process, or variations in the quantity itself that is being measured. Such errors fluctuate from being greater than or less than the true value in repeated measurements. Consider a scientist measuring the length of an earthworm using a...
13.9K
Data Validation01:15

Data Validation

Method validation is a crucial process in analytical chemistry designed to confirm that a given method consistently produces reliable and high-quality results. This process is essential when a method is applied to different sample matrices or when procedural modifications are made, ensuring that the results meet acceptable standards across various applications.
Key parameters for method validation include:
361
Data Validation01:03

Data Validation

Data validation is an essential part of a comprehensive assessment. Validation is confirming or verifying and opening the door to gathering more assessment data as it clarifies vague or unclear data. The process of checking and verifying the collected information is called data validation. The primary purpose of data validation is to ensure data is as free from error, bias, and misinterpretation as possible.
Nursing assessment guides are generally based on holistic models rather than medical...
6.0K
One-Way ANOVA: Equal Sample Sizes01:15

One-Way ANOVA: Equal Sample Sizes

One-Way ANOVA can be performed on three or more samples with equal or unequal sample sizes. When one-way ANOVA is performed on two datasets with samples of equal sizes, it can be easily observed that the computed F statistic is highly sensitive to the sample mean.
Different sample means can result in different values for the variance estimate: variance between samples. This is because the variance between samples is calculated as the product of the sample size and the variance between the...
3.6K