The Psychophysics of Learning

Implications for Learning Systems Design and Configuration

John N. Moye Ph.D., John N. Moye

• Publisher: Emerald Publishing Limited
• Year: 2021
• Print ISBN:
  9781801171144
• eBook ISBN:
  9781801171151
• Topic: Éducation
• Subtopic: Théorie et pratique de l'éducation

The Psychophysics of Learning presents a learning system design approach that is formulated by the strategies and techniques the brain uses to process external information and make sense of that information to the learning ecology of all learners. The psychophysics of sensation, perception, and cognition provide the research information, which is used to formulate the learning system framework. These processes are inherent to all individuals and result in a model that promotes access, learning, and academic success for all learners.

This information is applied to the design of the learning engagement, learning experience, and learning environment dimensions of a learning system. The psychophysics of sensation are applied to the design of the learning engagement strategies to ensure that all learners can intellectually access and comprehend the information presented as inputs to the learning system. The psychophysics of cognition are applied to the development of learning environments that integrate and internalize the external learning into the unique cognition of each learner. The resulting system creates a learning system design that is aligned with the natural learning processes of the brain.

Chapter 1

Purpose and Intent

John N. Moye

Abstract

Chapter 1 introduces the science of psychophysics to establish the initial condition and expectations for the work. The chapter begins with an overview of psychophysics, its limitations, and its measurement approaches, which are equivalent to the sensation processes. The science of psychophysics is delineated and differentiated from similar fields of study to discriminate it as a science, which is equivalent to the processes of perception. Finally, this information is compiled into a table, which integrates the information into a cognitive model of the nested systems to be discussed (cognition).

In a psychophysical learning system, this chapter establishes the definition of psychophysics, removes irrelevant information from the conceptual framework, and relates the information to future discussions (immediacy), which creates a flow within the learning process.

Educators regularly design and implement learning systems. A learning system involves the input of information, the processes that transform information into useful knowledge, and the procedures the brain uses to internalize knowledge into the individual's learning ecology. Regardless of the medium used to deliver and process information for learning, the actual learning takes place inside each learner's brain. Designing effective learning for other humans requires the designer to know and understand the neurological processes and procedures all humans employ to learn (Collins, 2019).

These neurological processes are the systematic study of sensation, perception, and cognition, which are the electrical processes the brain uses to receive, transform, and make sense of external information. The sciences of sensation, perception, and cognition provide conceptual frameworks that learning designers can use to configure learning objects, processes, and environments for all learners. The transduction of external information into internal learning is the science of psychophysics.

The purpose of this work is to synthesize the extensive findings of psychophysical research identifying the factors to which the perceptual system attends to make sense of external stimuli (Ashby, 1992; Townsend et al., 1992; Tsushima & Watanabe, 2009) into models and frameworks that can design effective and efficient learning systems. This work assumes that the psychophysics of sensation, perception, and sensory cognition mirror the psychophysics of active learning (Connolly, 2019; Jensen, 2008). Therefore, the psychophysics of sensation, perception, and cognition provide practical and useful frameworks to design an effective learning system, which engineers learning. In the psychophysical approach, a learning system contains the dimensions of learning engagement, learning experience, and learning environment, which directly correlate to the sensation, perception, and cognition processes of the neurological system. In a learning system, the transduction of information from a physical stimulus into neurological data is the psychophysics of learning.

Limitations

This work conducts a high-level review of the psychophysics of the perception of hearing, vision, taste, smell, and touch to determine those factors to which the brain attends to learn. Therefore, this work is not an in-depth exploration of the neurosciences, anatomy and physiology, or other sciences that measure and assess the electrical processes of the brain. It is limited to synthesizing the conclusions of those sciences into cogent learning system design frameworks to achieve the goal of creating “ideal” learning systems (Diamond, 1998) for all learners.

The field of psychophysics is an extensive and comprehensive collection of primary research, which systematically examines the sensory processes of sensation, perception, and cognition. These neurological processes equate to the processes the brain uses to learn, which this work describes as the psychophysics of learning. The most applicable (and accessible) references are reported for each concept extracted from the psychophysical research and emulated in learning to process information into deep learning. However, these works are often highly technical and provide a level of detail that is unnecessary and distracting for the current purpose.

Need

The Reference List in this work demonstrates the prior and current interest of the learning professions in the order a psychophysical perspective brings to the processes of learning system design (Hamilton, 2013). Many references provide direct evidence of the professional education community's interest in the neurological processes of learning to reveal strategies to improve curriculum, instruction, and learning.

Neuroscientists have warned educators about the use of neuroscientific research to “defend” their educational decisions (Bowers, 2016; Bruer, 1997; Hook & Farah, 2013; Jaeggi & Shah, 2018; Mayer, 2017; Weisberg et al., 2007). Their concern is that the lack of neuroscientific expertise could lead to misinterpretation or misapplication of primary neurological research. This concern is valid and justified for any research used by other disciplines.

Additionally, several authors have indicated the need for works that apply psychophysics' findings to practical situations (Al Dahhan et al., 2016; Glick, 2011; Kingdom & Prins, 2016; Ljunggren & Dornic, 1989; Lu & Dosher, 2014; Rhodes et al., 2014; Treisman, 1991). Psychophysical approaches increasingly appear in published educational research (Collins, 2019; Esteban-Guitart & Gee, 2020; Howard-Jones et al., 2016; Kricos et al., 1996; Lubashevsky, 2019; Osgood-Campbell, 2015; Tsushima & Watanabe, 2009; Zirk-Sadowski, 2014). The findings of psychophysical research provide plausible strategies and tactics, which can be adapted, applied, and assessed to determine their effectiveness in learning (Kim & Cameron, 2016; Moye, 2019a).

Psychophysics reflects the conclusions of neuroscientific research and neuroscientists as defined and communicated by neuroscientists. These conclusions are applied, tested, and confirmed at the boundary between the neurological processes and the physical result. In this work, neuroscience is mentioned only when necessary to support or explain the psychophysics of a process and only when it is necessary to understand the influence of that conclusion on learning systems design.

Measurement

A well-discussed main limitation to the field of psychophysics occurs in the measurement strategies used to study perceptual and cognitive phenomena (Carterette, 1974; Colonius & Dzhafarov, 2006; Holman & Marley, 1974). Most texts on the subject of psychophysics include lengthy explanations of the measurement and assessment strategies used to find meaning in the research data and the limitations of those strategies.

Psychophysics is an applied science, as is learning. The field of psychophysics provides a collection of research and statistical models for practical research models and assessments, such as institutional research and phenomenological assessment (Berglund, 2012; Gyr & Pribram, 1994; Holman & Marley, 1974; Indow, 1974; Jones, 1974; Lawless, 2013). The value and contribution of this discipline to the field of higher education are profound, and the lack of certainty surrounding its findings does not preclude its use to develop plausible models, which can be applied to real-world situations and measured in that environment. Learning science is based on observation. The psychophysics of sensation, perception, and cognition provides plausible evidence for the configuration of curriculum and assessments (Moye, 2019a, b; Reynolds, 2005).

One of the most critical conclusions from the field of psychophysics is that learning is multilinear and phenomenological (Ashby, 1992; Gescheider et al., 2009; Tsushima & Watanabe, 2009). As such, linear strategies cannot achieve or measure it. At the very least, it is multidimensional and dynamic (interactive), which requires the use of multidimensional scaling strategies (Carroll & Wish, 1974), and many laboratory researchers are not comfortable with these strategies (Lawless, 2013). The discomfort with the measurement strategies has led many researchers to dismiss the research findings and conclusions of the field as non-scientific (Savage, 2021). Therefore, in this work, the word “systematic” will describe the research designs that provide the data and information upon which the conclusions in this work are based (Carterette, 1974; Carterette & Friedman, 1978; Colonius & Dzhafarov, 2006).

The brain of either human or animal subjects cannot be dissected and observed responding to sensory stimuli in real-time. Even with neuroimaging methods, it is necessary to use indirect measures to understand the brain's behavior and attention (Phélip et al., 2016; Richardson et al., 1992).

In psychophysics, the data collection takes place at the sensory level, where it cannot be directly measured and is encoded and reported in models to the perceptual level. There appears to be no data transformation at the sensory level, just the reporting of the architecture (content and structure) of the characteristics of the stimulus. Sensory information is detected in the sensation process and communicated to the perceptual system, where the brain responds to those characteristics to discriminate the meaning of the external stimulus. Cognition filters the perception through prior learning and behaviors of the individual who has experienced, discriminated, and internalized them as learning within the brain. This process follows a basic systems model in which data are input, transformed, and output as internalized cognition.

As a result of these constraints, psychophysics contains very sophisticated measurement and assessment techniques to collect research data, which also provide excellent models to consider in the study of many educational phenomena (Berglund, 2012; Carroll & Wish, 1974; Gyr & Pribram, 1994).

Related Disciplines

This effort analyzes and categorizes the brain's factors to make sense of (learn) from the external environment. While each sensory system responds to different types of physical energy, there are commonalities (invariances) across the five senses in the neurological processes used to sense (detect), perceive (discriminate), and make sense of events, artifacts, and interactions with these stimuli. These commonalities delineate a model for the configuration of instructional systems, which emulates the psychophysics of perception and cognition to build a learning system. It attempts to allow the brain to identify the characteristics of experience to which it attends, to input a stimulus accurately, process that perception signal to make sense of it, and use that information to generate cognition, in other words, to learn from a physical stimulus.

The field of research is different from several closely related disciplines, often conflated with psychophysics. This work differentiates these fields as follows.

Neuroscience studies the response of cells within the brain to an external physical stimulus (Vaughan-Graham et al., 2019; Xiaolong et al., 2015). Neuroscience focuses on the electrical activity within the brain and at the cellular level. While its findings are often related to higher-level functions in human experience, neuroscience itself is limited in its ability to related directly to human experience without factoring in the higher level sensemaking, which takes place beyond the neuronal level (Haller, 2014; Müller et al., 2011).

Neurophysiology studies the structure and components of the nervous systems and how they transmit the information received from the external environment to the cerebral cortex of the brain (Carpenter & Reddi, 2012). It examines the brain's physical response patterns to a stimulus (Perruchoud et al., 2018) to develop or repair physical ailments and diseases (Schalow & e-Libro Corporation, 2013).

Neuropsychology, according to Westwood & Goodale (2011), is a subdivision of the field of psychology, which is equivalent to psychophysics.

Signal detection is the systematic study of sensory systems' response to a physical stimulus and how those systems encode the information into neurological (electrical) representations (Soto et al., 2018; Walsh, 2017). In the sensory systems, the information is compiled into the neurological models, which summarize and categorize the physical information (Mariani et al., 2019).

Information processing is a multilinear process the sensory conducts with the encoded information to summarize and compile that information into groups (channels) and patterns (clusters) of response (Gescheider et al., 2009; Yard et al., 2005). The characteristics (alignment, c...

Table of contents

• Cover
• Title
• Copyright
• Contents
• List of Figures and Tables
• Abstract
• Chapter 1 Purpose and Intent
• Chapter 2 Overview of the Relevance of Psychophysics to Learning
• Chapter 3 The Psychophysics of Sensation
• Chapter 4 The Psychophysics of Perception
• Chapter 5 The Psychophysics of Cognition
• Chapter 6 Learning Engagement
• Chapter 7 Learning Experience
• Chapter 8 Learning Environment
• Chapter 9 A Psychophysical Learning System
• References
• Index