PR2-Reviewer-Q1.pdf

12-NEWTON Practical Research 2 - Q1 Lesson 1: Characteristics of Quantitative Research Quantitative research involves gathering numerical data to test hypotheses and theories using statistical methods. It aims to explore causal relationships, make predictions...

12-NEWTON Practical Research 2 - Q1 Lesson 1: Characteristics of Quantitative Research Quantitative research involves gathering numerical data to test hypotheses and theories using statistical methods. It aims to explore causal relationships, make predictions, and generalize findings across populations. Typically involving larger samples and probability sampling, quantitative research is considered more objective and generalizable than qualitative research, as it seeks to represent not just the sample but the broader population. Understanding the characteristics of quantitative research, as noted by Barrot (2017), helps researchers maintain standards when collecting and analyzing numerical data for unbiased results that represent larger populations. This method is popular in industries, allowing companies to assess market demand and customer preferences before investing. According to Vanderstoep and Johnston (2009), quantitative research produces numerical answers displayed through graphs, tables, and percentages, utilizing mathematical models for analysis. Its outcomes are statistically analyzed to yield generalizable results from large sample sizes. Key characteristics of quantitative research (Babbie, 2010) include: 1.) Large Sample Size - Conducted on a large audience to ensure reliability and represent the target population, making it preferred by organizations over qualitative research. 2.) Structured Methods - Uses structured tools like survey questionnaires for easy data collection, allowing respondents to quickly provide information. 3.) Reliable Outcomes - The use of close-ended questions minimizes unclear or incorrect responses, yielding trustworthy results. 4.) Close-ended Questions - These provide specific, reliable answers compared to open-ended questions, making analysis straightforward. 5.) Numerical Outcome - Results are expressed in numerical formats (e.g., percentages), facilitating easy comprehension and conclusions. 6.) Generalization - Findings can be generalized to the broader population due to the large sample size. 7.) Clearly Defined Questions - Focuses on objective answers to accept or reject specific hypotheses. Lesson 2: Strengths and Weaknesses of Quantitative Research According to Palmer (2019), the following are the strengths and weaknesses of employing quantitative research. 12-NEWTON STRENGTHS A. It is GENERALIZABLE. This can approximately represent a wider population because of its greater number of respondents. B. It is OBJECTIVE. Divis The use of systematic and mathematical procedures in summarizing and analyzing the data is scientifically accurate and rational. C. It can be REPLICATED. Repetition of this study in other locations and different sets of respondents is allowed and it can be compared with its related studies since it has a well- structured standard. D. It can PROCESS FASTER DATA ANALYSIS. The use of statistical software can summarize information and can compare across categories and over time in a short period of time. E. It can TEST HYPOTHESES. The statistical analysis is capable of testing significant relationships, differences and effects. of F. It is UNBIASED. Gathering of data preferred the respondents. random sampling which keeps distances from the respondents WEAKNESSES A. It may miss some circumstantial or contextual facts (SUPERFICIAL). In the process of data collection, the researcher cannot explain the meaning of the questions for the respondents and there are no opportunities for respondents to explain their answers. It may gather a much narrower and shallow dataset. B. A fixed structure may lead to its inflexibility process of discovery. 12-NEWTON The study is designed first before it is conducted which makes its fixed that leads to limited information. C. It can lead to structural bias and false representation. The researcher may define more personalized and standard questions instead of the respondents' reflection. D. It is COSTLY Due to the very large sample, the expenses will be greater in reaching out to these people and in reproducing the questionnaires. Lesson 3: Kinds of Quantitative Research There are several approaches used in conducting quantitative research n conductin studies. These approaches may fall into two (2) categories classified as non- experimental and experimental research designs. The diagram below shows the framework of the classification of the common quantitative research designs. 1.) Non-experimental Research Designs - involve techniques for conducting quantitative research without manipulating variables. Variables are measured as they occur naturally, either due to prior natural manipulation or because manipulation is not feasible (Mertler, 2014). Common types include: 12-NEWTON A. Descriptive -> Aims to describe and interpret the current status of individuals or events without manipulation. For example, "What is the level of COVID-19 knowledge among Senior High School students?" B. Comparative -> Compares two or more groups based on specific attributes, such as knowledge or attitudes. An example question is, "Is there a significant difference in COVID-19 awareness between grades 11 and 12?" C. Correlational -> Seeks to identify relationships between variables, noting that correlation does not imply causation. For instance, "Is there a significant relationship between hours of study and academic performance?" 2.) Experimental Research Designs -involves manipulating conditions to study their effects on participants, making it the most conclusive research design. Key types include: A. True Experimental - Involves random assignment of participants to treatment conditions, effectively controlling extraneous variables (Gay et al., 2009). For example, a study may randomly select two sections of students to assess the effectiveness of a Strategic Intervention Material (SIM-Module) on performance. Fig. 1. True Experimental B. Quasi-experimental - resembles true experiments but lacks random assignment of participants to groups, limiting control over extraneous influences. For example, a study examining the effectiveness of a Strategic Intervention Material (SIM-Module) on student performance may randomly select two sections (B and D) from five. However, if 12-NEWTON the researcher does not randomly assign the module to section D, this design remains quasi-experimental. Fig. 2. Quasi-Experimental Lesson 4: Importance of Quantitative Research Across Fields Presented in the table below is the purpose of quantitative research in each discipline and sample research study: 12-NEWTON Lesson 5: Kinds of Variables and their Uses A variable is anything that changes (Shukla, 2018), defined as a characteristic that varies between individuals, texts, or objects. For instance, height varies as people grow, and temperature differs based on location. Variables can be independent or dependent (Wright, 2013). Identifying a variable's type should align with relevant literature, though practical experience can also guide understanding. Independent Variables - refers to the one that may cause the results. The variable that the researcher analyzes is likely the change agent for one or more other variables. There are two classifications of Independent Variable: 1.) Active Independent Variable - It is an independent variable that the researcher manipulates the condition or value of the independent variable. It is the one that is designed, imposed, controlled by the investigators.. Example: In studying the effect of Vitamin C on illness prevention, Vitamin C is actively manipulated in the experimental group. Example: In investigating how technology integration affects student performance, the teaching style is the active independent variable. 12-NEWTON 2.) Assigned Independent Variable - It is an independent variable where the researcher has no control over how the variable appears for each subject. Example: A study on COVID-19 awareness among Grades 11 and 12 students uses grade level as an assigned independent variable since it’s intrinsic to the participants. Example: In comparing male and female students' knowledge of COVID-19, gender is the assigned independent variable. Dependent Variables - refers to those variables that change as an effect of the changes brought by the other variable. This is the variable that is affected by the independent variable. Example 1: In studying the relationship between hours of studying and academic performance among Grade 12 students, academic performance is the dependent variable. Example 2: In investigating COVID-19 awareness in Grades 11 and 12, COVID-19 awareness is the dependent variable. Lesson 6: Nature of Variables General Classification of the Nature of Variables Continuous quantitative variables can take any value within a range, including decimals. For instance, a scale measuring up to 100 kilos can show a person's weight as 45.5, 60.8, or 70 kilos. 12-NEWTON In contrast, discrete quantitative variables are whole numbers and cannot have intermediate values. For example, you can state there are 10 females and 10 males in a class, but not 10.5 females or 9.5 males, as fractions do not apply to countable entities. Here's a summary chart of variable types, their descriptions, and examples: 12-NEWTON Lesson 7: Design a Research Useful in Daily Life Planning is the first crucial step in research. A researcher should start by selecting a topic based on their interests, as this can lead to practical and relevant research. Without a sound conceptual framework, research can become disorganized (McKenna & McKenna, 2000). Key considerations for designing research: 1.) Area of Interest - Identify topics that intrigue you. Consider your talents, skills, or subjects you enjoy, as well as current events that catch your attention. 2.) Timeliness and Relevance - Ensure your research addresses contemporary societal issues. 3.) Clear and Specific Goals - Focus your research topic and define specific objectives. For instance, if studying environmental problems, specify the exact issue you intend to explore. 4.) Contribution - Reflect on how your research can benefit society. Aim for topics that have practical applications in daily life (Csikszentmihalyi, 2011). 5.) Availability of Information - Gather sufficient evidence from diverse sources such as books, journals, and newspapers. Check your library for relevant materials on your chosen topic. Lesson 8: Research Title The title is the gateway to a research paper, and it should clearly convey the main elements of the study. A good title typically includes three or more of the following components: WHAT (variables) WHERE (location) WHO (population) WHEN (time frame) HOW (research design) Standards for Writing a Research Title: - Include key variables (independent and dependent). - Identify respondents and their location. - Define the research design (if applicable). - Be concise and avoid repetition. - Use scientific language. Types of Titles: 1.) Declarative -> States the results of the study. 12-NEWTON Example: "A Three-Month Weight Loss Program Increases Self-Esteem in Adolescent Girls." 2.) Descriptive -> Focuses on methods rather than findings. Example: "The Effects of Family Support on Patients with Dementia." 3.) Interrogative -> Poses a question without study details. Example: "Does cognitive training improve performance on pattern recognition tasks?" Attributes of a Good Title: 1.) Accurately informs the reader about the 2.) Is simple, clear, brief, and informative. paper's content. 3.) Avoids abbreviations and jargon. 4.) Excludes numerical values. Strategies for Title Development: 1.) Single Title -> A straightforward statement. Example: "The Satisfaction Level of SHS Students on School Programs." 2.) Double Title -> Two statements combined. Example: "The Satisfaction Level of SHS Students on School Programs: Comparing Grade 11 and 12." Lesson 9: Research Background The research background is the introductory section of your study, providing essential context for your topic. It may include descriptions of the subjects and relevant history, helping readers understand the chosen issue (Barrot, 2017). For example, if researching the impact of COVID-19 in your area, the background should outline aspects such as local, national, and global case numbers, and the pandemic's effects on social behavior, the environment, and the economy. Identifying the research gap—issues not fully addressed in previous studies—is crucial as it situates your work within the academic field. Key Components of a Good Research Background: 12-NEWTON 1.) Provide the General Information of the topic -> Offer an overview of the current situation related to your topic. 2.) Determine the Research Gaps or missing links that need to be addressed -> Clearly identify what has not been studied, addressing the missing links in existing research. 3.) Highlight the Significance of addressing those gaps: Highlight why addressing these gaps is important, explaining the relevance of your study. 12-NEWTON Lesson 10: Statement of the Problem A statement of the problem outlines an existing issue that needs addressing, forming the basis for a research study and generating necessary questions. A clear problem statement lays the groundwork for the research, minimizing potential challenges in the conceptual and theoretical frameworks and methodology (Bwisa, 2008). 12-NEWTON 12-NEWTON 12-NEWTON Lesson 11: Stating Research Questions Research questions (RQs) are derived from the study's purpose and guide the introductory section of a proposal, quickly directing attention to the research issues. They should be specific; if the purpose is complex, multiple RQs can be formulated (Pardede, 2018). The answers to these questions aim to resolve the research problem (Faltado et al., 2016). Guidelines for Formulating Quantitative Research Questions: 1.) Ensure the question is within your subject of interest and researchable. 2.) Review existing literature on the topic. 3.) Construct a problem that can be addressed through your research. 12-NEWTON 4.) Define the variables and their relationships. 5.) Evaluate the effectiveness of your question; refine if necessary. 6.) State the question in an interrogative form. 7.) Make your questions SMARTER: Specific - Clear and focused on a particular issue. Measurable - Analyzable through appropriate tools. Achievable - Feasible for the researcher. Realistic - Relevant to the research context. Time-constrained - Can be completed within a set timeframe. Ethical - Avoids deceptive practices and minimizes harm. Relevant - Responds to current situations or literature. Stating Research Questions: Consider the research objectives and design types, such as descriptive (analyzing population characteristics), comparative (examining differences between groups), and correlational (exploring relationships among variables). Research questions can be framed in both general and specific forms, following the appropriate steps for each design type. 12-NEWTON 12-NEWTON 12-NEWTON 12-NEWTON Lesson 12: Scope and Delimitation of A Research Study Scope of a Study The scope defines the extent of the research area. It includes relevant facts and theories, but it's impractical to cover every aspect. For example, if studying the impact of digital technology on high school students' academic performance, the scope may be limited to a specific group, such as 30 students in grades 7 to 9 at one school over five months. Delimitation of a Study Delimitation sets the boundaries of the study by defining parameters like sample size, time, and geographic area. Researchers choose research tools and methodologies and may face limitations such as time and budget constraints. It's essential for researchers to justify their choices and exclusions, explaining how these may influence the research outcomes. For instance, the researcher might clarify why they selected a group of 30 students instead of including younger grades. Lesson 13: Conceptual Framework A conceptual framework visually illustrates the connections between phenomena under study, showing how key concepts or variables relate logically and sequentially (Akintoye, 2015). These connections, represented by arrows, should be based on theories, as the goal of quantitative research is to test these theories. While the study's purpose may be presented as questions, it does not require a conceptual illustration if it focuses solely on gathering descriptive data. In a comparative study (testing differences), researchers identify independent and dependent variables, with the independent variable being manipulated and the dependent variable measured for changes (Amorado et al., 2017). In correlation studies (testing relationships), neither variable 12-NEWTON is manipulated; instead, the statistical relationship is examined in terms of direction (positive or negative) and degree of correlation (strong, moderate, or weak) (Wilkinson, 2016). 12-NEWTON 12-NEWTON Lesson 14: Research Hypothesis A hypothesis lacks a single definition, but authors like Ellison (2010) describe it as an educated guess about why things are, while Kumar (2011) cites Black & Champion (1976) as defining it as a "tentative statement" of unknown validity. Generally, a hypothesis is a tentative proposition that specifies relationships between variables, whether causal or not, and can indicate 12-NEWTON differences between groups or effects of interventions. Thus, it can be defined as a testable and tentative educated guess. 12-NEWTON 12-NEWTON 😔 Summary: …Kapoy na bro