Lecture Notes on Inquiries, Investigations, and Immersion PDF

Instructor: Ms. Honey T. Borleo Chapter One: The Problem and Its Background Inquiries, Investigations, and Immersion 1 Inquiries, Investigations, and Immersion Chapter I: Introduction Background of the Study Theoretical Framework Conceptual Framework Statement of the Problem Hypothesis of the Study...

Instructor: Ms. Honey T. Borleo Chapter One: The Problem and Its Background Inquiries, Investigations, and Immersion 1 Inquiries, Investigations, and Immersion Chapter I: Introduction Background of the Study Theoretical Framework Conceptual Framework Statement of the Problem Hypothesis of the Study Scope and Delimitation of the Study Significance of the Study Definition of Terms Inquiries, Investigations, and Immersion Conceptual Framework IPO IV-DV IV-Mod-DV Concept Maps Inquiries, Investigations, and Immersion Variables Characteristic of an individual or organization that can be observed or measured, and it can vary among people or organization being studied Inquiries, Investigations, and Immersion Nature of Variables 1. NOMINAL VARIABLES represent categories that cannot be ordered in any particular way. 2. ORDINAL VARIABLES represent categories that can be ordered from greatest to smallest. 3. INTERVAL VARIABLES have values that lie along an evenly dispersed range of numbers. 4. RATIO VARIABLES have values that lie along an evenly dispersed range of numbers WHEN there is an absolute zero. Usually uses colon/s) Inquiries, Investigations, and Immersion Kinds of Variables INDEPENDENT: those that cause, influence, or affect outcomes. Variably called treatment, manipulated, antecedent, or predictor variables. 2. DEPENDENT: those that show the effects, results, or the outcomes of the influence of the independent variables. 3. INTERVENING: In-between the independent and dependent variables. Inquiries, Investigations, and Immersion Kinds of Variables 4. CONTROL : measured in the study because they potentially influence variables like analysis of covariance to control these variables. 5. CONFOUNDING: these are not actually measured but exists. It’s the researchers comment on the influence of variables. Instructor: Ms. Honey T. Borleo Chapter Two: Review of Related Literature and Studies Inquiries, Investigations, and Immersion 8 Inquiries, Investigations, and Immersion Chapter II: Local Literature Foreign Literature Local Studies Foreign Studies Relevance of Literature and Studies Synthesis Instructor: Ms. Honey T. Borleo Chapter Three: Methodology Inquiries, Investigations, and Immersion 10 Inquiries, Investigations, and Immersion Chapter III: Research Design Population and Sampling Respondents of the Study Research Instruments Data Gathering Procedures Statistical Treatment of Data Inquiries, Investigations, and Immersion Research Design Qualitative Research Quantitative Research Inquiries, Investigations, and Immersion Experimental Research Design 1. True Experimental: highest internal validity lifetime research absence of random assignment of subjects to different conditions 2. Quasi- Experimental: Collects more data by scheduling observations Quasi: almost; as if (Latin) Inquiries, Investigations, and Immersion Experimental Research Design Pre- Experimental: Least internal validity Variables are not deliberately manipulated Collects data without making changes or introducing treatments Inquiries, Investigations, and Immersion Descriptive Research Design Observe, describe, and document aspects of situation Serve as starting point for hypothesis generation or theory development Inquiries, Investigations, and Immersion Surveys quantitative or numeric description of trends, attitudes, opinions of a population by studying a sample of the population Inquiries, Investigations, and Immersion Correlational Studies Design BIVARIATE CORRELATIONAL STUDIES: two variables for each subject PREDICTION STUDIES: correlation coefficient MULTIPLE REGRESSION PREDICTION STUDIES: variables can contribute to overall prediction in an equation that adds together the predictive power Inquiries, Investigations, and Immersion Ex- Post Facto Design investigates causal relationships examines pre-existing conditions attempts to discover differences Inquiries, Investigations, and Immersion Comparative Design Comparing and contrasting two or more samples of study subjects on one or more variables, at a single point of time Inquiries, Investigations, and Immersion Evaluative Design To assess or judge by proving information about something in observation or investigation of relationships Formative and/ or summative Inquiries, Investigations, and Immersion Methodological Design Implementation of variety of methodologies Part of achieving the goal of developing a scale- matched approach Data from different disciplines can be integrated Inquiries, Investigations, and Immersion Population and Sampling Identification Generalizability Contextual Understanding Resource Feasibility Accuracy and Precision Statistical Analysis Inquiries, Investigations, and Immersion Sampling Techniques: Simple Random Sampling Purpose: To ensure that every individual has an equal chance of being selected, minimizing bias. Usability: Useful when you have a homogeneous population and want generalizable results. Formula: Sample size can be calculated using: Where 𝑛 = sample size, 𝑁 = population size, and 𝑒= margin of error. Inquiries, Investigations, and Immersion 2. Stratified Sampling Purpose: To ensure representation of specific subgroups (strata) within the population. Usability: Effective when the population is heterogeneous and you want to compare specific groups. Formula for sample size in each stratum:𝑛ℎ=𝑁ℎ𝑁×𝑛 Where 𝑛ℎ = sample size for stratum ℎ, 𝑁ℎ​ = size of stratum ℎ, 𝑁 = total population size, and 𝑛 = total sample size. Inquiries, Investigations, and Immersion 3. Cluster Sampling Purpose: To simplify the sampling process by selecting whole groups or clusters rather than individuals. Usability: Useful in large populations where creating a complete list is impractical; often used in geographic studies. Formula: No specific formula; the number of clusters can be calculated based on desired sample size. Inquiries, Investigations, and Immersion 4. Systematic Sampling Purpose: To select participants at regular intervals, providing a structured sampling method. Usability: Useful when a complete list of the population is available; can be easier and faster than simple random sampling. Formula: Where 𝑘 = sampling interval, 𝑁N= total population size, and 𝑛 = desired sample size. Inquiries, Investigations, and Immersion 5. Convenience Sampling Purpose: To quickly and easily gather data from readily available participants. Usability: Common in preliminary research or when time and resources are limited; however, it may introduce bias. Formula: No specific formula; based on availability. Inquiries, Investigations, and Immersion 6. Snowball Sampling Purpose: To reach hidden or hard-to-reach populations through referrals from existing participants. Usability: Useful in qualitative research or studies involving specialized populations (e.g., drug users, marginalized groups). Formula: No specific formula; relies on participant referrals. Inquiries, Investigations, and Immersion 7. Purposive Sampling (Judgmental Sampling) Purpose: To select participants based on specific characteristics or criteria relevant to the research. Usability: Useful in qualitative studies where particular insights are needed; may introduce bias due to researcher judgment. Formula: No specific formula; selection is based on researcher criteria. Inquiries, Investigations, and Immersion Research Instruments Surveys and Questionnaires Description: Structured sets of questions designed to gather information from respondents. Purpose: To collect quantitative or qualitative data on opinions, behaviors, or demographics. Inquiries, Investigations, and Immersion 2. Interviews Description: A method involving direct, face-to-face or virtual interaction with participants to gather detailed information. Purpose: To explore in-depth perspectives, experiences, or insights. Inquiries, Investigations, and Immersion 3. Focus Groups Description: Guided discussions with a small group of participants to gather collective insights on a topic. Purpose: To explore attitudes and perceptions in a social context. Inquiries, Investigations, and Immersion 4. Observation Checklists Description: Tools used to systematically record behaviors, events, or phenomena during observations. Purpose: To gather data on specific behaviors or settings without direct interaction. Inquiries, Investigations, and Immersion 5. Tests and Assessments Description: Standardized measures (e.g., academic tests, psychological assessments) to evaluate knowledge, skills, or attributes. Purpose: To quantify performance or abilities in a specific area. Inquiries, Investigations, and Immersion 6. Scales and Rating Instruments Description: Tools (like Likert scales) that measure attitudes or perceptions along a continuum. Purpose: To quantify subjective measures for statistical analysis. Inquiries, Investigations, and Immersion 7. Diaries and Journals Description: Personal records maintained by participants to track behaviors, thoughts, or feelings over time. Purpose: To gather qualitative data on ongoing experiences or processes. Inquiries, Investigations, and Immersion 8. Content Analysis Tools Description: Instruments for analyzing text, images, or media to identify patterns or themes. Purpose: To evaluate qualitative data systematically. Inquiries, Investigations, and Immersion 9. Case Studies Description: In-depth examinations of a single case or a small number of cases, using multiple sources of data. Purpose: To gain detailed insights into complex issues or phenomena. Inquiries, Investigations, and Immersion Data Gathering Procedure Research Objectives Research Design Sampling Strategy Data Collection Instruments 5. Data Collection Plan Inquiries, Investigations, and Immersion Data Gathering Procedure 6. Pilot Testing 7. Ethical Considerations 8. Data Gathering Process 9. Monitoring and Supervision 10. Data Management Inquiries, Investigations, and Immersion Statistical Treatment of Data 1. Descriptive Statistics Purpose: To summarize and describe the main features of a dataset. Inquiries, Investigations, and Immersion Common Measures: Mean: The average of the data. Median: The middle value when data is ordered. Mode: The most frequently occurring value. Standard Deviation: Measures the dispersion of data points from the mean. Range: Difference between the highest and lowest values. Inquiries, Investigations, and Immersion 2. Inferential Statistics Purpose: To make inferences or generalizations about a population based on a sample. Common Techniques: Hypothesis Testing: Assessing the validity of a hypothesis using tests like t-tests, chi-square tests, or ANOVA. Confidence Intervals: Estimating the range within which a population parameter lies with a specified level of confidence. Inquiries, Investigations, and Immersion Types of T- Test Independent Samples t-test: Compares the means of two independent groups Paired Samples t-test: Compares means from the same group at different times One-sample t-test: Compares the mean of a single group to a known value Inquiries, Investigations, and Immersion Inquiries, Investigations, and Immersion T- Test 1. Set Up Your Hypothesis: Null Hypothesis (H0): There is no difference between the groups. Alternative Hypothesis (H1): There is a difference. 2. Calculate the Average (Mean):Add up the scores for each group and divide by the number of scores to find the average. Inquiries, Investigations, and Immersion Chi- Square When to Use It: When you have two categorical variables (like yes/no answers, or different groups like male/female). For example, checking if there's a relationship between sex and preference for a certain type of music. Inquiries, Investigations, and Immersion Types of Chi- Square Chi-Square Test of Independence: Tests if two variables are related (e.g., does gender affect music preference?). Chi-Square Goodness of Fit: Tests if a sample matches a population (e.g., do the survey results match expected proportions?). Inquiries, Investigations, and Immersion Chi- Square 1. Set Up a Hypothesis: Null Hypothesis (H0): Assumes no association between the variables (they are independent). Alternative Hypothesis (H1): Assumes there is an association. 2. Create a Contingency Table: Organize your data into a table that shows the counts for each combination of the variables. Inquiries, Investigations, and Immersion Inquiries, Investigations, and Immersion ANOVA (Analysis of Variance) used to compare the means of three or more groups to see if at least one group is different from the others. determine if differences in group averages are significant or if they could have happened by chance. Inquiries, Investigations, and Immersion Types of ANOVA One-Way ANOVA: Compares one independent variable across multiple groups. (test scores from students taught by three different teachers) Two-Way ANOVA: Compares two independent variables. (examining the effect of teaching method and gender on test scores) Inquiries, Investigations, and Immersion Set Up Hypotheses: Null Hypothesis (H0): All group means are equal (no difference). Alternative Hypothesis (H1): At least one group mean is different. 2. Calculate Group Means: Find the average for each group. 3. Calculate the Overall Mean: Find the average of all groups combined. Inquiries, Investigations, and Immersion 4. Calculate Variability: Between-group variability: How much the group means differ from the overall mean. Within-group variability: How much the individual scores in each group differ from their respective group mean. Inquiries, Investigations, and Immersion Inquiries, Investigations, and Immersion 3. Correlation Analysis Purpose: To examine the relationship between two or more variables. Common Measures: Pearson Correlation Coefficient: Measures the strength and direction of a linear relationship between two continuous variables. Spearman's Rank Correlation: A non-parametric measure of correlation based on rank. Inquiries, Investigations, and Immersion Pearson Correlation Coefficient It tells you how closely two variables are related and whether they move together (positively or negatively). Use It when you have two continuous variables (like height and weight) and want to see if they are related. Inquiries, Investigations, and Immersion Pearson Correlation Coefficient Range: It ranges from -1 to 1.𝑟=1r=1: Perfect positive correlation (both variables increase together).𝑟=−1 r=−1: Perfect negative correlation (one variable increases while the other decreases). 𝑟=0 r=0: No correlation (no linear relationship) Inquiries, Investigations, and Immersion Inquiries, Investigations, and Immersion Spearman’s Rank Correlation It evaluates how well the relationship between two variables can be described using a monotonic function, meaning as one variable increases, the other either consistently increases or decreases. Use it when you have ordinal data (ranked data) or when the assumptions of Pearson correlation (normal distribution) are not met. Inquiries, Investigations, and Immersion Spearman’s Rank Correlation Key Concepts: Ranges from -1 to 1, similar to Pearson: 1: Perfect positive correlation (ranks move together). -1: Perfect negative correlation (one rank increases while the other decreases). 0: No correlation. Inquiries, Investigations, and Immersion Spearman’s Rank Correlation 1. Rank the Data: Assign ranks to each value in both datasets. If there are ties, assign the average rank for the tied values. 3. Calculate the Difference: For each pair of ranks, calculate the difference (𝑑) between the ranks. Inquiries, Investigations, and Immersion Inquiries, Investigations, and Immersion 4. Regression Analysis Purpose: To model the relationship between a dependent variable and one or more independent variables. To predict the value of the dependent variable based on the values of the independent variables. Common Types: Linear Regression: Models the relationship using a straight line. Multiple Regression: Extends linear regression to include multiple independent variables. Inquiries, Investigations, and Immersion Types of Regression Inquiries, Investigations, and Immersion Inquiries, Investigations, and Immersion Types of Regression Inquiries, Investigations, and Immersion 5. Analysis of Variance (ANOVA) Purpose: To compare the means of three or more groups to see if at least one is significantly different. Types: One-Way ANOVA: Tests differences between groups based on one independent variable. Two-Way ANOVA: Tests differences based on two independent variables and their interaction. Inquiries, Investigations, and Immersion 6. Non-parametric Tests Purpose: To analyze data that do not meet the assumptions required for parametric tests (e.g., normality). Common Tests: Mann-Whitney U Test: Compares differences between two independent groups. Kruskal-Wallis Test: An alternative to one-way ANOVA for non-parametric data. Inquiries, Investigations, and Immersion Mann-Whitney U Test It assesses whether the ranks of values from two groups differ significantly, making it useful for ordinal data or when the data doesn’t meet normality assumptions. Use It when you have two independent groups and want to compare their distributions (e.g., test scores from two different classes). The test ranks all the data from both groups together. It then compares the sum of the ranks for each group. Inquiries, Investigations, and Immersion Inquiries, Investigations, and Immersion Kruskal-Wallis Test Assesses whether there are statistically significant differences between the medians of multiple groups, making it suitable for ordinal data or when assumptions of normality are not met. Use it when you have three or more independent groups and want to compare their distributions (e.g., test scores across three different teaching methods). Test ranks all the data from all groups together and compares the average ranks for each group. Inquiries, Investigations, and Immersion Inquiries, Investigations, and Immersion Inquiries, Investigations, and Immersion 7. Data Visualization Purpose: To represent data graphically to facilitate understanding and interpretation. Common Tools: Bar Charts: For categorical data. Histograms: For distribution of continuous data. Scatter Plots: To visualize relationships between two continuous variables.