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Sensory Science: Measuring the Senses

Offered By: University of California, Davis via Coursera

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Sensory Science Courses

Course Description

Overview

The brain is the most sophisticated sensory interpreter that we know of. Our brain is like a very powerful computer, but no engineered computer exists that can mimic our human sensory capabilities. This course will explore sensory science by examining how the senses are connected to the brain and how the brain makes meaning of the signals it receives. Various types of testing, scales, and measurements are described that allow scientists to quantify senses and the brain’s experience of senses. Through this course, you will learn to employ scientific approaches such as discrimination testing and Thurstonian Modeling to measure the senses.

Syllabus

  • The Senses and the Brain
    • In this module, we will dive into the senses and the brain and discuss tricks the senses may play. We will then discuss the mind and how information is processed. We’ll finish up this module with the Theory of Sensory Measurement and Psychophysics. There is also an optional podcast conversation with Dr. Martin Kern. Let’s get started.
  • Scaling
    • What is happening cognitively when we do scaling? In this module, we will review what scaling is, the purpose, and methods of scaling. We’ll wrap up this module with a discussion on the different types of scales, including ordinal scales, quantitative scales, interval scales, and analysis. Let’s begin.
  • Measurements
    • In this module, we will continue our discussion on scales and measurements. We will also discuss methods of scaling and ranking and review other types of scales, such as Hedonic scales, Label Affective Magnitude, Just-About-Right, and other scales of interest. Let's begin.
  • Discrimination Theory and Testing Methods
    • Why do some people perform better on tests than others? In this final module, we will end our discussion with an overview of discrimination testing methods. We'll also take a closer look at discrimination tests and response bias - and how to avoid it. We'll move on to Thurstonian Modeling and finish up with an optional podcast conversation with Lori Rothman. Let's begin.

Taught by

Rebecca Bleibaum

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