Related Experiment Video
Updated: Apr 5, 2026

Interactive and Visualized Online Experimentation System for Engineering Education and Research
Published on: November 24, 2021
From novice to expert: Student conceptual growth in understanding experimental error using a hands-on laboratory
Charlotte Disney1, Dana-Marie Dennis1, Tamra Legron-Rodriguez1
1University of Central Florida, Department of Chemistry, 4111 Libra Dr., Orlando, FL 32816.
Abstract:
This study investigates how a targeted, sustainable laboratory activity can be used to develop students' understanding of measurement errors and experimental uncertainty. The activity prompted students to critically consider sources of error in an experimental context and the need for calibration of measuring devices, thereby reinforcing principles of Good Laboratory Practices and Quality Assurance. Unlike complex procedures that often involve multiple variables and chemicals, this activity was intentionally designed to isolate and highlight the issues related to measurements using simple, sustainable materials: an analytical balance, a weighing container, an adjustable volume micropipette, and water. The primary aim of this study is to investigate students' conceptual development regarding error, uncertainty, and calibrations. To accomplish this, a pre-test/post-test (prelab/postlab) design was used to compare student understanding before and after the laboratory activity. Students were given a prelab and postlab assessment that included a scenario: A student pipettes 1.00 mL of water into a weighing container and determines the mass using an analytical balance. The assessment included two open-ended questions (OEQs): 1) What are the sources of error associated with the process? and 2) What are some ways to minimize the errors associated with the process? Student responses from the two questions before (prelab) and after (postlab) the experiment were collected. Using qualitative analysis, responses were thematically analyzed, and codes were grouped according to the level of conceptual sophistication (e.g., novice ideas and expert ideas). Analysis of student responses over two semesters showed a shift in student understanding. Before the activity, the most common errors identified by students (OEQ1) were novice ideas (86% novice, 32% expert). After the experiment, a greater number of expert responses were encountered (33% novice, 67% expert). Before the experiment, the most common solutions identified by students (OEQ2) were novice ideas (60% novice, 40% expert). After the experiment, a greater number of expert responses were encountered (37% novice, 63% expert). These findings highlight the pedological value of incorporating targeted, conceptually focused, sustainable laboratory activities to support student learning in measurement, uncertainty, and calibrations. Supplementary materials, including the qualitative analysis codebooks and experimental protocol are provided to support adoption of the activity and further research.
More Related Videos
10:17Improving Student Outcomes with an Adaptable Molecular Cloning Course-Based Undergraduate Research Experience
Published on: November 15, 2024
06:54A Virtual Simulation Experiment of Mechanics: Material Deformation and Failure Based on Scanning Electron Microscopy
Published on: January 20, 2023
Related Concept Videos
Random and Systematic Errors
Random and Systematic Errors
Systematic Error: Methodological and Sampling Errors
Sampling errors originate from improper sampling methods or the wrong sample population. These errors can be minimized by refining the sampling strategy. Defective instruments or faulty calibrations are the sources of instrumental...
Types of Errors: Detection and Minimization
Absolute error in a measurement is the numerical difference from the true or central value. Relative error is the ratio between absolute error and the true or central value, expressed as a percentage.
Errors can be classified by source, magnitude, and sign. There are three types of errors: systematic, random, and gross.
Systematic or...
Uncertainty in Measurement: Accuracy and Precision
Propagation of Uncertainty from Random Error