IP214 Topic 1_ENG_13022024_student

Page 1: Introduction to Industrial Psychology

• Department of Industrial Psychology

• Faculty of Economic and Management Sciences

• Course: Industrial Psychology 214 Psychometrics

• Topic 1: Research in Industrial Psychology

Page 2: Units of Study

• Philosophical basis for Psychology research

• Industrial Psychology's commitment to the scientific research process

• Types of research in Industrial Psychology

• Theorising in research

• Basic statistical concepts

• Using data for hypothesis testing (explanatory research process)

Page 3: Philosophical Basis

• Definition: Industrial Psychology is defined as the scientific study of the behavior of individuals in the workplace.

• Fundamental questions:

  • Why study anything?

  • Can we explain what we observe around us?

Page 4: Beginning Considerations

• Humans do not exist in isolation; they interact symbiotically with nature.

• The definition and understanding of nature are pivotal for research.

Page 5: Understanding Nature

• Nature: Encompasses physical phenomena and life in general.

• Varied interpretations include:

  • Mother Nature

  • Creation

  • Cosmos

  • Material World

• Three major philosophical views of nature:

  • Pantheism

  • Theism/Deism

  • Naturalism

Page 6: Reasons to Study

• Survival Necessity: Understanding nature is essential for survival.

Page 7: Correlation Analysis

• Variables Analyzed:

  • LIFEEX

  • EDINDEX

  • GDP

• Statistical Summary:

  • LIFEEX: 35 samples, Mean: 0.6760, Std Dev: 0.1764

  • EDINDEX: Mean: 0.7534

  • GDP: Mean: 0.5963

• Pearson Correlation Coefficients:

  • LIFEEX and EDINDEX: r = 0.85913 (significant)

  • LIFEEX and GDP: r = 0.78720

  • EDINDEX and GDP: r = 0.65498

Page 8: Moral Obligations

• Moral Obligation: A responsibility to study and understand nature for greater societal benefit.

Page 9: Curiosity

• Curiosity and Personal Interest: The innate desire to learn about our surroundings motivates research.

Page 10: Explainability of the Universe

• Order and Complexity: The universe demonstrates complex order, essential for understanding life.

Page 11: Mechanisms of Regularities

• Recognize patterns in nature as mechanisms to aid knowledge production, including the human mind's functionality.

Page 12: Unique Role of Humans

• Emphasis on the individual’s role and responsibility in understanding existence through various virtues and qualities.

Page 13: Research Approaches

• Informal vs Formalized Study: The importance of structured investigation methods in research.

Page 14: Focus of Industrial Psychology

• Industrial Psychology examines the working man through scientific inquiry to construct psychological explanations.

Page 15: Importance of the Working Man

• Organizations as constructs delivering services and products, reliant on the performance of their human components.

• Considerations for success: Technology's impact, AI, and human redundancy.

Page 16: Assumption of Roles

• Hypothetical Scenario: An applicant reflecting on their potential contributions as an HR manager at Apple.

Page 17: Value Addition through IP

• The link between employee performance and organizational success, influenced by understanding human behavior.

• HR actions' effectiveness judged by performance improvement against investment costs.

Page 18: Types of HRM Interventions

• Three Types: Diagnoses, advice, interventions for employee management.

• Broad Categories:

  • Flow of employees

  • Quality of employees

• Specific Interventions: Selection, development, culture change, morale, leadership development.

Page 19: Impact of HRM

• Dual impact observed on organizational finances and individual lives.

Page 20: Evaluation Criteria

• Milkovich and Boudreau’s Criteria: Needs assessment via efficiency and equity.

• Stakeholders: Management, organized labor, the state.

Page 21: Understanding Human Behavior

• Key Assumption: Human behavior is explainable and can be studied like any other natural phenomenon.

Page 22: Regularities in Behavior

• Identifying patterns aligns with determinism and free will perspectives, significant to the role of IP.

Page 23: The Mind Debate

• Exploring the existence of the mind within the context of free will and determinism.

Page 24: Views on Mind & Free Will

• Materialism vs Dualism: Philosophical conflicts regarding human thought, behavior, and identity.

• Implications of neuro-research raising questions on free will.

Page 25: Free Will in Psychology

• Needs for reevaluation of research practices in light of free will vs determinism.

Page 26: Complexity of Human Behavior

• The intricate nature of human behavior influenced by numerous variables and situational constructs.

Page 27: Dynamic Structures

• Antony Gormley's Chord Concept: A holistic approach, indicating interaction within systems.

Page 28: Psychological Mechanisms

• Representing key psychological constructs visually.

Page 29: Model Limitations

• Models are approximations of reality and cannot perfectly explain all individual behaviors; aim for plausible constructs.

Page 30: Structural Model for Intention to Quit

• Framework illustrating various factors influencing intention to quit, such as talent management and job satisfaction.

Page 31: Learning Potential Model

• Structural model outlining factors influencing learning performance and outcomes.

Page 32: Competency Model Overview

• Highlights competencies essential for effective performance in organizational roles.

Page 33: Comprehensive Appraisal Model

• Structuring various motivational and engagement concepts within organizations.

Page 34: Example of Structural Model

• An illustrative structural model focusing on key variables within organizational behavior.

Page 35: Safety Behavior Model

• Relationships evident between attitudes, safety culture, and actual safety behaviors.

Page 36: Research Model Development

• Development process involving observation, hypothesis creation, and validity questioning.

Page 37: Commitment to Scientific Method

• Trust in scientific methodologies to achieve knowledge reliability.

Page 38: Principles of the Scientific Method

• Essential components: Objectivity, control, rationality, transparency, and acknowledging limitations.

Page 39: Research Process Steps

1. Identifying problems

2. Formulating questions

3. Reviewing existing theories

4. Hypothesis formulation

5. Observation and data collection

6. Analysis and conclusions

Page 40: Research Types Overview

• Explanatory, Descriptive, and Evaluation research types defined.

Page 41: Importance of Scientific Commitment

• Justifies the rigorous commitment to scientific method in studying human behavior for applicable insights.

Page 42: Stakeholder Insistence

• Necessity for validating HRM actions to demonstrate efficacy and fairness.

Page 43: Structuring Evidence-based Actions

• Importance of validation and informed action through rigorous investigation methods in HRM.

Page 44: Evaluation Frameworks

• Criteria-centric evaluations: Efficiency, effectiveness, and fairness of actions are critical for stakeholder trust.

Page 45: Structural Model Elements

• Breakdown of key symbols and their meanings within structural models regarding human behavior.

Page 46: Research Design Overview

• Steps in structuring research questions, hypotheses, sampling, and design for operational research.

Page 47: Experimental and Correlational Design Comparison

• Clarification of how different designs yield insights into relationships between independent and dependent variables.

Page 48: Experimental Research Design

• Overview of experimental approaches in testing hypotheses pertaining to independent and dependent variables.

Page 49: Correlational Design Insights

• Strategies for analyzing the co-variation of variables across individuals using correlational design.

Page 50: Correlational Design Utility

• Advantages such as ease of data collection versus limitations regarding causality claims.

Page 51: Research Example

• Practical application of experimental and correlational definitions to elucidate their procedures and outcomes.

Page 52: Statistical Hypotheses Definition

• Understanding the null and alternative hypotheses in the context of population parameters.

Page 53: Statistical Parameters Defined

• Explaining correlations and the statistical interpretation of data distribution within hypothesis testing.

Page 54: Statistical Analysis: Correlations

• Visualizing correlation strengths between variables, including positive, negative, weak, and non-correlations.

Page 55: Statistical Analysis: Mean Differences

• Impact of treatments on dependent variables and visual representations of their distributions.

Page 56: Correlational vs. Experimental Outcomes

• Comparative results between participant group performances across various experimental conditions.

Page 57: Significance Determination of Statistical Findings

• Discusses factors influencing findings, emphasizing proper sampling and statistical credibility methods.

Page 58: p-Value Comparisons

• Establishing thresholds for accepting or rejecting null hypotheses based on statistical evidence.

Page 59: Correlational Testing Logic

• Steps to determine the statistical significance of correlation results in hypothesis testing.

Page 60: Statistical Significance Table

• Reference table for assessing statistical correlations with respective sample sizes and significance levels.

Page 61: Significance Testing Explained

• Detailed steps for hypothesis testing in correlational research including decision-making processes.

Page 62: Summary of Hypothesis Testing

• Condensed steps for testing hypotheses, particularly within correlational research contexts.

Page 63: Application Questions

• Practical scenarios relating to statistical significance testing based on sample data.