Practical Learning
Practical Learning - Related Videos
01:26
Good Manufacturing Practices
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2026
Good Manufacturing Practices (GMP) constitute a foundational set of guidelines that ensure the production of safe, consistent, and high-quality products, particularly in industries such as pharmaceuticals, biotechnology, and food processing. These protocols encompass all aspects of production, from the sourcing of raw materials to the final distribution of the finished product.A core pillar of GMP is stringent hygiene and sanitation across all production environments. This includes routine...
10:07
Using Learning Outcome Measures to assess Doctoral Nursing Education
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Cited by 2 •
2010
The structure and process for measuring student learning outcomes through customizable assessment rubrics is discussed and applied to a doctoral nursing education program.
07:59
Using Practice Testing, Public Speaking, and Source Monitoring to Examine the Influences of Learning Strategies and Stress on Episodic Memory
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2019
The present experiment combined three experimental procedures — a retrieval-practice learning manipulation, a list-discrimination task, and a stress-induction technique — to examine the influences of different learning strategies and acute stress on multiple measures of episodic memory.
12:00
A Practical Guide to Phylogenetics for Nonexperts
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Cited by 11 •
2014
Here we describe a step-by-step pipeline for generating reliable phylogenies from nucleotide or amino acid sequence datasets. This guide aims to serve researchers or students new to phylogenetic...
10:06
An Introduction to Learning and Memory
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2023
Learning is the process of acquiring new information and memory is the retention or storage of that information. Different types of learning, such as non-associative and associative learning, and different types of memory, such as long-term and short-term memory, have been associated with human behaviors. Studying these components in detail helps behavioral scientists understand the neural mechanisms behind these two complex phenomena. JoVE's overview on learning and memory introduces common...
FAQs
Practical learning strengthens physics reasoning by linking a prediction to evidence. A learner applies a concept, observes measurable behavior, and compares the result with a mathematical model. Agreement can support the prediction, while disagreement encourages closer examination of the reasoning or observations. This cycle makes forces, energy, and motion easier to analyze as behaviors in real systems.
Measurements connect physical concepts with evidence, while uncertainty shows that observations must be interpreted carefully. Recording results allows learners to compare actual behavior with mathematical expectations rather than relying only on abstract reasoning. Considering uncertainty also helps refine conclusions and develops the quantitative judgment needed when investigating forces, energy, motion, and other physical systems.
Studying explanations and equations can introduce physical principles, but practical learning adds direct contact with measurable behavior. Learners test predictions, collect observations, and examine how well mathematical models describe real systems. This comparison can reveal the effects of factors such as force, energy, motion, and uncertainty, strengthening understanding beyond symbolic manipulation alone.
A typical activity begins with applying a physics concept to make a prediction. Learners then conduct an experiment, collect measurements, and compare the observations with a mathematical model. The evidence is used to assess the prediction and refine reasoning. This sequence connects conceptual expectations with the behavior of a real system and supports evidence-based conclusions.
Practical learning can develop laboratory technique, data analysis, problem-solving, and experimental design. These skills work together: learners handle direct investigations, interpret measurements, address problems that arise during analysis, and plan ways to test ideas. Building this combination helps students move from understanding individual concepts toward carrying out quantitative investigations with greater independence.
It is especially useful when learners need to connect abstract principles with measurable behavior or prepare for settings requiring quantitative investigation. Physics activities can show how force, energy, motion, and uncertainty shape real systems. The resulting experience supports further work in research, engineering, and other contexts where observations must be related to mathematical models.