Research Lesson 3 PDF

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This document is a research lesson covering research titles, variables, conceptual frameworks, and theoretical frameworks. Topics include independent variables, dependent variables, and different types of variables. It introduces several theories relevant to leadership and job satisfaction.

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Capitol University RESEARCH 1 Lesson 3 Casirayan/Valdez/Congreso Overview Research Title Variables Conceptual Framework Theoretical Framework...

Capitol University RESEARCH 1 Lesson 3 Casirayan/Valdez/Congreso Overview Research Title Variables Conceptual Framework Theoretical Framework Definition of Temrs DEFINITION A clear and concise title gives the reader a Strengths quick understanding of the study's focus. It should summarize the main topic, variables, of a Good and context of the research. Research Title Example: “The Impact of Transformational Leadership on Employee Job Satisfaction in Healthcare Settings.” Specificity A strong title is specific and provides enough Strengths detail to indicate the scope and direction of the research. It avoids ambiguity and gives readers a of a Good clear idea of the study's content. Research Title Example: “Assessing the Effect of Online Learning on High School Students’ Academic Performance in Urban Public Schools.” Engagement A well-crafted title grabs the reader's attention Strengths and piques their interest in the research topic. It is engaging and suggests relevance to current of a Good issues or problems. Research Title Example: “Unveiling the Digital Divide: How Socioeconomic Status Impacts Access to Online Education.” Balanced Length An effective title is concise but informative, Strengths typically between 10 to 15 words. It conveys the essence of the research without being overly of a Good wordy. Research Title Example: “The Influence of Corporate Social Responsibility on Consumer Buying Behavior.” Keywords A good research title includes relevant keywords Strengths that make it easier to find the study in databases. Keywords should reflect the core concepts of the of a Good research. Research Title Example: “The Role of Artificial Intelligence in Enhancing Cybersecurity in Financial Institutions.” Here, "Artificial Intelligence" and "Cybersecurity" are keywords that enhance discoverability. Vagueness : A vague or ambiguous title fails to Weakness communicate the focus of the research clearly. It leaves the reader uncertain about the scope and of a Good subject matter of the study. Research Title Example: “Technology and Education.” Overly Long and Complex An excessively long title can be confusing and Weakness hard to read. It may dilute the focus and make it of a Good difficult for readers to grasp the main idea. Example: “An Exploratory Study of the Impact Research Title of Leadership Styles on Employee Motivation, Satisfaction, and Performance in Various Types of Organizations across Different Sectors and Regions.” Too Narrow or Limited A title that is too narrow or specific might limit Weakness the potential impact of the research. It may fail of a Good to capture the broader relevance of the study. Example: “A Study of the Effect of Eating Research Title Breakfast on John Doe’s Productivity on September 15th, 2022.” Lack of Keywords Titles that do not include important keywords Weakness make the research difficult to find in academic of a Good databases, reducing its visibility and reach. Example: “A Study on Learning.” Research Title Too Technical or Jargon-heavy Titles filled with jargon or overly technical Weakness language can alienate readers who are not of a Good familiar with the terminology, limiting the audience. Research Title Example: “The Effects of HLA-DQ Alpha 1 Gene Polymorphisms on Insulin-Dependent Diabetogenesis.” Components or characteristics that researchers measure, manipulate, and control in a study to understand relationships and effects. Research Variables Variables can be classified into several types based on their roles and nature in research. Independent Variable (IV) It is the factor that researcher manipulates or Research changes to observe its effect on other variables. Variables Example: In a study examining the effect of different teaching methods on student performance, the teaching method (traditional vs. online) is the independent variable. Dependent Variable (DV) It is the outcome of effect that the Research researcher measures.. Variables Example: In the same study about teaching methods, the dependent variable would be student performance (e.g., test scores). Control Variable Factors that are kept constant or Research regulated to prevent them from influencing results. Variables Example: In a study on exercise and weight loss, factors like diet, age, and baseline fitness level may be controlled to ensure they don't skew the results. Extraneous Variable Any variables other than the IV that Research could affect the outcome of the experiment if not controlled. Variables Example: In a study on how sleep affects memory, an extraneous variable could be stress levels, which might also influence memory retention. Confounding Variable It is a type of extraneous variable that is related to Research both IV an DV variables, potentially distorting the Variables true relationship between them. Example: In a study examining the relationship between exercise and heart health, diet could be a confounding variable if it is not controlled, as it affects heart health independently of exercise. Moderating Variable Affects the strength or direction of the Research relationship between the IV and DV Variables Example: In a study on job satisfaction and employee performance, age could be a moderating variable if the relationship between satisfaction and performance differs across age groups. Mediating Variable Explains the process through which the Research independent variable influences the dependent variable. Variables In a study on the effect of education level (IV) on job performance (DV), job knowledge might be a mediating variable that explains how education improves performance. Intervening Variable Similar to a mediating variable, an intervening Research variable explains the mechanism through which an independent variable produces an effect on a Variables dependent variable. Example: In a study where income level (IV) affects health outcomes (DV), access to healthcare services could be an intervening variable. Categorial Variable Represent data that can be grouped into distinct Research categories or classifications. Variables Example: Gender (male, female), ethnicity (Caucasian, Asian, African American), and education level (high school, college, graduate) are examples of categorical variables. Continuous Variable Represent data that can take any value within a Research range. These variables are usually numerical and can be measured on a scale. Variables Example: Height, weight, age, temperature, and income are examples of continuous variables that can take an infinite number of values within a range. DEFINITION The researcher’s understanding of how the variables in the study CONCEPTUAL connect. FRAMEWORK Define the conceptual framework as the researcher’s understanding of how the variables in the study connect. PURPOSE Helps organize ideas and clarify relationships between variables. CONCEPTUAL Provides a visual model to help FRAMEWORK readers understand the flow of the study. Guides the research design and methodology. DEFINITION Use of a theory (or theories) to explain THEORETICAL the relationships between variables in FRAMEWORK the research. Explains the why behind the relationships studied. Purpose Provides a foundation for understanding the problem being THEORETICAL studied. Helps establish the boundaries of the FRAMEWORK research and guides the data collection process. Links existing theory to the research problem. Theoretical Framework Herzberg's two-factor theory of Frederick Herzberg The self-care deficit theory developed by Dorothea Orem Example This study examines the relationship between transformational and transactional leadership styles and job satisfaction among personnel at Camp Evangelista Station Hospital (CESH). To understand this relationship, the study integrates Dorothea Orem's Self-Care Deficit Nursing Theory and Herzberg's Two-Factor Theory as the foundational theoretical frameworks. Dorothea Orem’s Self-Care Deficit Nursing Theory (1971) emphasizes the importance of self-care in maintaining health and well-being. According to Orem, individuals engage in self-care behaviors to maintain their personal health, and when they are unable to meet their self-care needs, nurses or leaders intervene to assist. In the context of this study, Orem’s theory is extended to leadership, where leaders (like nurses) play a critical role in enhancing the well-being and job satisfaction of employees. Transformational leadership can be seen as fostering an environment that encourages self-care behaviors among employees, providing support, motivation, and individualized consideration, much like the support nurses offer to individuals with self-care deficits. Leaders empower employees to take charge of their professional and personal growth, thus promoting job satisfaction and reducing job-related stress. Example Herzberg's Two-Factor Theory (1959) distinguishes between hygiene factors (extrinsic factors such as salary, company policies, and working conditions) and motivators (intrinsic factors like recognition, achievement, and personal growth). According to Herzberg, hygiene factors can prevent job dissatisfaction, but only motivators can truly enhance job satisfaction. In this study, transactional leadership is linked to Herzberg’s hygiene factors, as it focuses on rewards and punishments based on performance and goal achievement, which help maintain a minimum level of job satisfaction but do not necessarily enhance it. On the other hand, transformational leadership is aligned with Herzberg’s motivators. By fostering personal development, intrinsic motivation, and a sense of purpose, transformational leaders elevate job satisfaction beyond the baseline level established by hygiene factors. Example In this study, Orem’s theory emphasizes the leadership role in supporting employees' professional well- being through self-care mechanisms, while Herzberg’s theory provides a framework for understanding how different leadership styles (transformational and transactional) impact job satisfaction. Transformational leaders, by inspiring and encouraging self-care behaviors and intrinsic motivation (linked to Herzberg’s motivators), are likely to have a stronger positive influence on job satisfaction than transactional leaders, who focus on external rewards (linked to Herzberg’s hygiene factors). This theoretical framework suggests that leaders who combine elements of both transformational and transactional leadership can optimize job satisfaction by addressing both intrinsic and extrinsic needs of employees. This framework ties Orem’s nursing perspective on support and empowerment with Herzberg’s differentiation between intrinsic and extrinsic factors of job satisfaction, thus providing a comprehensive understanding of how leadership styles influence job satisfaction among hospital personnel. Importance Clarifies key concepts and variables used in the research. DEFINITION OF Ensures readers understand exactly how terms are being used in the TERMS context of the study. Minimizes misunderstandings and provides clear direction. Example Definition of Terms Transformational Leadership: A leadership style where leaders inspire, motivate, and encourage employees to innovate and create change that will help grow and shape the future success of the organization. This style of leadership is characterized by the leader’s ability to create a vision, communicate effectively, demonstrate empathy, and act as a role model, fostering an environment where employees feel valued and empowered. Operational Definition Transformational Leadership: In this study, transformational leadership is measured by the Multifactor Leadership Questionnaire (MLQ), which evaluates leadership behaviors such as idealized influence, inspirational motivation, intellectual stimulation, and individualized consideration. Respondents will rate their agreement with statements related to these behaviors on a Likert scale from 1 (strongly disagree) to 5 (strongly agree). The overall score will be used to quantify the level of transformational leadership exhibited by supervisors in the organization. Definition a statement that can be tested and is used to predict the relationship HYPOTHESIS between two or more variables. It provides direction for the research and is subject to verification or rejection. Types Null Hypothesis (H0): States there is no relationship between the HYPOTHESIS variables. Alternative Hypothesis (H1): Suggests there is a relationship between the variables. Types Null Hypothesis (H0):There is no significant relationship between HYPOTHESIS leadership style and job satisfaction. Alternative Hypothesis (H1): There is a significant relationship between leadership style and job satisfaction Formulation of Hypothesis Identify variables, determine relationships, make predictions. HYPOTHESIS There is a significant relationship between transformational leadership style and job satisfaction. Formulation of Hypothesis Identify variables, determine relationships, make predictions. HYPOTHESIS Transformational leadership will have a greater positive impact on job satisfaction than transactional leadership among hospital staff. A Testable Hypothesis should be: Clear and Specific Measurable HYPOTHESIS Based on Existing Knowledge Falsifiable Ethically Stable Logical A Testable Hypothesis should be: Clear and Specific Measurable HYPOTHESIS Based on Existing Knowledge Falsifiable Ethically Stable Logical Example of Testable Hypothesis Example of a Testable Hypothesis Testable Hypothesis: "There is a positive correlation between transformational leadership and job satisfaction among nurses working in military hospitals." Specific: The variables are transformational leadership and job satisfaction among a specific group (nurses in military hospitals). Measurable: Both transformational leadership and job satisfaction can be measured using appropriate scales or questionnaires. Falsifiable: The hypothesis can be disproven if data shows no correlation or a negative correlation between the variables. By ensuring a hypothesis meets these criteria, you can confidently determine whether it is testable. “Therefore do not worry about tomorrow, for tomorrow will worry about itself. Each day has enough trouble of its own.”- Matthew 6:34

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