Psychological Theories and Models

Announcements

  • Next week's lecture will feature a speaker from Careers and Employment/Employability.
  • The session aims to assist students in subject selection, degree choices, and future career planning.
  • Pre-Session Activities:
    • Complete two activities on the Moodle site before the session next week, found in week 2 and week 5 sections.
    • Week 2 activity: Focuses on identifying your skill set.
    • Week 5 activity: Part of the Career Smart suite of activities.
    • Completing these activities will enhance engagement with the material presented by Jen Porter from Careers and Employability.
  • The session will be interactive, so preparation is encouraged for maximum benefit.

Theory in Psychology

  • The lecture will discuss various terms like causes, hypotheses, and laws, and sequence them to understand their meanings and implications for psychology.
  • Theory acts as the conceptual link between past observations of a phenomenon and future predictions.

Theories and Hypotheses

  • Theory Definition: A proposed explanation for a phenomenon or related phenomena.
    • Theories in this context are more formal than everyday "folk psychology" theories.
  • Hypothetical Mechanism:
    • A theory involves a statement or set of statements describing a hypothetical mechanism to explain observations.
    • Concepts within the theory must be formalized, detailed, and well-specified, including the relationships between them.
  • Assumptions:
    • Theories rely on a set of base-level assumptions.
    • If these assumptions are untrue, the theories built upon them may fail.
    • A basic assumption in psychology and many sciences is the existence of a real world that we can directly interact with and understand to some extent.
    • This contrasts with scenarios like the Matrix or computer simulations.

Hypotheses

  • Definition: A conjectural statement logically derived from a theory.
    • Hypotheses are predictions of specific instances of a theory under certain conditions or states of affairs.
    • This is a deductive process.
  • Deductive Reasoning:
    • If a phenomenon arises due to a hypothetical mechanism described by a theory, then under specific conditions outlined in the theory, particular behavior is expected to occur.
  • Example: Swearing and Pain Tolerance Article:
    • The article tested the script theory of swearing.
    • The hypothesis suggested that swearing's effect on pain tolerance might be due to a script present for Caucasian individuals but not for Japanese individuals.

Theory's Role

  • Theories explain and predict behavior, acting as a conceptual bridge between past observations and future expectations.
    • Theories have both explanatory and predictive components.
  • Hypothesis Generation:
    • A hypothesis is a prediction about what should happen in a new, untested situation.
  • Empirical Results vs. Theoretical Explanations:
    • Sometimes, hypotheses are based on previous empirical results rather than theoretical explanations.
    • Example: A generic hypothesis about Japanese participants showing lower pain tolerance than Caucasian participants was based on previous research indicating that Asian populations may be more sensitive to pain.
  • Extending Knowledge:
    • Theories allow us to expand our understanding by testing predictions and exploring the boundaries of our knowledge.
    • We can use theories to "leapfrog" into the unknown and explore unobserved circumstances.

Eysenck's Personality Theory

  • Eysenck's personality theory involves concepts like extroversion, introversion, neuroticism, and psychoticism.
    • The theory specifies how these traits relate to each other; they are independent.
  • Biological Basis:
    • Eysenck's theory is biologically based, attributing personality trait variations to biological mechanisms.
    • Personalities are composed of various combinations of these traits.
  • Extroversion-Introversion Continuum:
    • Eysenck suggests a balance between excitation and inhibition in the autonomic nervous system.
    • Extroverts: Slightly under-aroused, seeking external stimulation to increase arousal, leading to approach-oriented behavior.
    • Introverts: Internally more aroused, preferring quieter environments to reduce arousal.
  • Theory Application:
    • The theory explains differences in behavior and predicts individual behavior, generally aligning with observed behaviors of extroverts and introverts.

Developing Theories

  • Starts with observations that lead to the discovery of regularity.
  • Independent observations, possibly from experimental studies, coalesce around a phenomenon.
  • Observed regularity in outcomes leads to the formulation of a law.
  • Law Definition: Summarizes regularity in observations.
Example 1: Law of Distributed Practice
  • Intensive learning is less effective for memory and recall than distributing learning in smaller sessions across other activities.
  • This pattern can be observed in education, sports, and other environments.
Example 2: Forgetting
  • Learning similar material sequentially can lead to interference, where information from one source blocks memory of another.
  • Interference is a principle of forgetting.
  • Similarity between successive learning episodes induces interference, making recall difficult.

Theory of Memory

  • Laws: We can cluster events and summarize them into laws describing observed patterns across multiple observations.
    • Theories propose mechanisms that explain these regularized principles.
    • A theory of memory would explain the law of distributed practice and interference as a principle of forgetting.
  • Summarizing Past Observations:
    • Theories explain past observations and offer explanations for them.
    • They provoke new knowledge through prediction, allowing us to anticipate what will happen in novel situations.
  • Hypotheses are tested via research, leading to results that either confirm or disconfirm the theory.
  • Confirmed Prediction:
    • Strengthens belief in the theory, adding a new observation that the theory can explain, enhancing its explanatory power (the extent to which it can explain related phenomena).
  • Unconfirmed Prediction:
    • Reduces confidence in the theory.
    • Researchers may question the sample's representativeness, methodology, or presence of uncontrolled variables.
    • Replication attempts may occur.
  • Theory Modification or Rejection:
    • Theories are not discarded based on a single negative finding but may be modified to explain new outcomes or dropped if a preponderance of evidence suggests it cannot explain new circumstances.

Paradigm Shift

  • In extreme cases, when a theory has a high-level influence, a paradigm shift may occur.
    • This involves abandoning an established way of thinking about psychological phenomena and adopting a new approach that better describes the range of observations.

Early Stages in Science

  • Before theory development, the focus is on discovering regularity and identifying patterns.
  • Example: Classification of animals and plants in biological sciences through observation of attributes and features.
  • Key Questions:
    • What is related?
    • How can relationships between various plants and animals be explained?
    • Psychology Example: Anxiety:
      • Anxiety manifests differently under different settings and affects individuals differently.
      • Some activities trigger anxiety, while others do not.
      • Questions arise about whether there are different types of anxiety and if they are driven by a broad mechanism or specific mechanisms.
    • These observations and organization efforts set the basis for theory-based work.

Mendeleev's Periodic Table

  • Mendeleev's periodic table demonstrates the benefits of observation, organization, and identifying regularities.
  • Dashes in the chart represented predictions of unknown elements based on the organization of known elements and their relationships.
  • Later discoveries of elements validated Mendeleev's predictions, fitting into the order he had suggested.

Discovering Laws

  • Laws are discovered by observing particular events that are consistently associated with each other.
Example: Law of Distributed Practice
  • As previously discussed, distributing learning over time is more effective than intensive learning.
Example: Yerkes-Dodson Law
  • Relates to the level of arousal for optimum performance.
  • Peak performance requires some level of arousal, with an optimum level in between under-arousal (too relaxed) and over-arousal.
  • Too little or too much arousal is not conducive to optimal performance.
  • People regulate themselves to find this optimum, using caffeine to increase arousal or seeking calming activities to decrease arousal.

Connection Between Law and Cause

  • The search for cause attempts to explain a law.
  • Laws describe regularity in observations, but they do not explain why the observations occur.
  • Causes are used to flesh out the law and convert our understanding of it into a theory.
  • The Greek philosophers were interested in identifying the nature of cause and its role in how we think about things.
  • Most research is about causation, seeking to understand why things happen, not just that they happen.

Aristotle's Four Causes

  • Aristotle proposed four ways of thinking about causation, which also serve as explanation:
    • Material Cause: The physical explanation for why something occurs.
      • Example: Boiling water involves heat transfer, the excitation of molecules, and the conversion of liquid into vapor.
    • Formal Cause: The defining qualities that make a phenomenon unique or a class of its own.
    • Final Cause: The functional explanation or the end purpose of a phenomenon, asking why it arises and what its purpose or value is in the broader scheme of things.
    • Efficient Cause: The necessary and sufficient conditions or activating events that allow something to arise, asking what must be present for the phenomenon to occur.
  • In experiments:
    • If we have a hypothetical mechanism (HM), then a phenomenon (P) will occur under particular conditions (A, B, C, etc.).

Example: Learning

  • Learning is a fundamental property of human behavior that allows individuals to acquire knowledge and use their experience.
  • Learning enables us to build a knowledge base sufficient to understand concepts and make informed choices.
    • We are all the product of our learning.
    • Material Cause: Neuroscience perspectives that identify changes in neural structures and neurons as a function of learning.
    • Formal Cause: Defines learning by its creation of new knowledge that ultimately changes behavior, leading to more options in thinking and problem-solving.
    • Final Cause: Evolutionary psychologists would argue that learning occurs because it has survival value, helping us to survive in the future, ensuring our genes survive and we can procreate.
    • Efficient Cause: The conditions of learning, related to psychology and education, include necessary factors like attention, accessibility of learning material, and the language used.

Models

  • Models are used in psychological literature instead of theory, particularly in areas like cognition and perception.
  • They are often narrower but more precise, explaining fewer phenomena but in more detail.
  • The detail can include mathematical computational descriptions that model behavior.
  • The relationships between factors important to a phenomenon are tested to replicate human data, suggesting human systems may have those properties and relationships.
  • Models can test whether human data can be replicated.
  • Successful models can predict what will happen in the future.
    • Because of greater specificity, models may be able to predict the level of performance, not just whether or not a difference or phenomenon will occur.

Distributed Practice (Again)

  • If we have a lot of information that hasn't been associated, it just sits in memory with no real connection between ideas.
  • When you're learning: recalling existing information and bringing them into consciousness at the same time drives the association with new information.
  • The act of bringing information into consciousness together is what's going to drive association.
  • When they leave consciousness, the strength of their association doesn't return to the original level (lower).
  • This creates association strength, which is important for learning.
Potential Mechanism for Distributed Practice
  • Comparing one 10-minute continuous study session versus five 2-minute sessions: In the continuous session, items are brought into consciousness for 10 minutes and then have associations only slightly above what it was beforehand.
  • The dispersed sessions that are broken into 2 minutes will bring them into consciousness multiple times for strengthening of association with new level of activation each time.
    • Theoretical thinking suggests this could explain why distributed learning works better than mass practice.
Is It A Possible Mechanism For Distributed Practice?
  • Is it an explanation for the reasons for having distributed practice across different events and activities?

Personality Theory

  • Big Five: Built upon the early work of Eysenck.
  • Drops Phsychoticism, and ends up with 5 higher order traits.
  • The five traits are: openness, conscientiousness, extroversion, agreeableness, and neuroticism, right, so if we looked at this particular um breakdown, this is a model,
  • Of, um, extroversion, where the higher order trait sits at the top, and then you see successively lower levels, so then you've got the traits that are consistent with that higher-order trait, and they're the things that we were talking about earlier on, right?
  • Extroverts tend to be more active, and go seeking sensation, and they're more sociable, and they want to be engaging in the world and people, um, more so than introverts, right? And underneath that, you've got the habitual responses that, um, Might sort of fall under each of those categories, so there might be particular ways in which an individual will be sociable, for example, and then um, You've got the specific responses that people will make in certain circumstances, right? So this is a model that explains how, for example, a high order, um, trait like extroversion might actually play out in real life in more specific instances, that there are various hierarchical levels, um, and through those hierarchical levels you come down to, uh, specific behaviors.

Cognitive Models

  • DRC Model is another model that is the dual root cascaded model of reading.
  • It has been converted to a computational model.
  • Impairment in reading, as with Dyslexia, shows different cognitive subsists that we think are associated with reading, and once you have a computational model, what you can do is you can do really interesting things like you can impair one of those subsystems to see whether the output then replicates what you see with people who have impairments, like, like those people with dyslexia and the like, and that helps develop our knowledge further about what might be happening for those people.
How Cognitive Models Generally Work

  • There are two ways in which you can take written print and convert it into spoken speech, right? So you're reading a word and then speaking out that word afterwards.

  • If you are a skilled reader and are aware of string and the letters that you've been asked to read, then it's likely that, identifying the group of letters together, um, as a lexical entry, um, and you would read the word as a word, right? And that means that you'd become aware of the patterns of the letters, identify that as a word, that matters.

  • The second means is used if you are unfamiliar, and if you come across an odd word, or perhaps even a non-word that you've never met before, and you can't recognize it as a word, then you're going to use this second pathway, which is sort of reading by sounding it out, essentially.

  • Either a letter or a cluster of letters might, um, indicate a particular speech sound that you have to produce.

  • The fast mapping, as with horse, is when you know it is a horse without sounding individual letters.

  • If you don't know "cow", you are forced to read by sounding out.