RES104B.pdf

RES104B Lesson 1: Nature and Inquiry of Research Research Approach - plan and the procedure for research that span the steps from broad assumptions to detailed methods of data collection, analysis, and interpretation - The following are to be considered in choosing what research ap...

RES104B Lesson 1: Nature and Inquiry of Research Research Approach - plan and the procedure for research that span the steps from broad assumptions to detailed methods of data collection, analysis, and interpretation - The following are to be considered in choosing what research approach will be utilized: - Philosophical assumptions the researcher brings to the study - Procedures of inquiry - Specific research methods Quantitative vs Qualitative Research - Quanti is for testing objective theories by examining the relationship among variables - Quali is for exploring and understanding the meaning of individuals or groups ascribe to a social or human problem Characteristics of Research Approaches 1. Researcher’s involvement with subject of study - Quali: Subjective - Quanti: Objective 2. Expression of Data - Quali: Verbal Language - Quanti: Numbers, Statistics 3. Research Plan - Quali: takes place during research - Quanti: plans before collecting data 4. Behavior towards research - Quali: preserves the natural setting of research - Quanti: control or manipulation of research 5. Researcher’s involvement with subject of study - Quali: Multiple Methods - Quanti: Scientific Method 6. Purpose - Quali: makes social interactions understandable - Quanti: evaluates objectives and studies cause and effect relationships 7. Data Analysis Techniques’ - Quali: Thematic codal ways, competence-based - Quanti: Mathematically based methods 8. Style of Expression - Quali: Personal, lacks formality - Quanti: Impersonal, scientific or systematic 9. Sampling Technique - Quali: Purposive sampling or based from criteria - Quanti: Random sampling 10. Mental survey of reality - Quali: Results from social interactions - Quanti: Exists in physical world 11. Researcher’s involvement with subject of study - Quali: people’s objective desires - Quanti: automatic descriptions of circumstances or conditions Strengths and Weaknesses of Qualitative Approach Strengths: 1. Adopts a naturalistic approach 2. Promotes full understanding of human behavior or personality traits in their natural setting 3. Instrumental for positive societal changes. 4. Engenders respect for people’s individuality. 5. A way of understanding and interpreting social interactions Weaknesses: 1. It involves a lot of researcher’s subjectivity in data analysis. 2. It is hard to know the validity or reliability of the data. 3. Its open-ended questions yield data overload that requires long-time analysis. 4. It is time-consuming. 5. It involves several processes which results greatly depend on the researcher’s views or interpretations Strengths and Weaknesses of Quantitative Approach Strengths: 1. It can be replicated or repeated in other contexts. 2. It provides findings that are generalizable to a large population. 3. It can establish causality more conclusively. 4. It can make predictions based on numerical, quantifiable data. 5. Its validity and reliability can be measured. Weaknesses: 1. It cannot adequately provide in-depth information necessary for describing and explaining complex phenomena. 2. Numerical data may be insufficient in analyzing intangible factors, such as gender roles, socio-economic status, and social norms of a given population.  3. It has less flexibility in terms of study design. 4. Responses of participants are strictly limited to what has been asked Importance of Research Approach in Fields of Studies 1. Humanities and Social Inquiry - Quali: helps us understand the behavior and experience of other people. In turn, their actions can help one become an effective and functional member of the community. - Quanti: helps us better understand the behavior and social interactions among individuals through defined factors that are found by means of testing a certain population. 2. Culture and the Arts - Quali: helps us understand other people’s culture. It allows us, on the other hand, to discern the individuality of a person or culture through art. - Quanti: helps us know one’s thought process through investigation of their lifestyle. It leads us to numerical conclusions that give us understanding about how they pursue creativity. 3. Sports - Quali: can explore on the issues and concerns athletes experience that may lead to realizations of better policy making and implementations - Quanti: can explore athletes' experiences and relate them to numerical variables that they can base on in improving their performances. 4. Agriculture and Fisheries - Quali: can be utilized to learn farmers’ beliefs, practices, and challenges. - Quanti: can be utilized to look for trends that may affect other countries’ economic standing. 5. Science and Technology - Quali: can help in discovering how innovations in the said field affects the lives of people in different sectors. - Quanti: helps in determining effectiveness levels of new technologies in addressing health problems. 6. Business - Quali: can be utilized in exploring attitudes of employees, customers, and entrepreneurs towards selling and buying goods and services. - Quanti: can help businessmen know their strengths and weaknesses in running their companies through the lenses of different business frameworks. 7. Information and Communications Technology - Quali: can be utilized to explore how one’s exposure to ICT could lead to betterment of their life. It could also help in learning that ICT leads to new patterns of behavior - Quanti: used to learn new trends that may uplift people’s lifestyles. In this field, people may innovate new software that may cater to people’s needs Nature of Variables Variable - factor or property that a researcher measures, controls, and/or manipulates - changing quantity or measure of any factor, trait, or condition that can exist in differing amounts or types. Classifications 1. Categorical - values that describe a quality or characteristic of a data unit like “what type” or “which category” - Types: a) Nominal – variables that cannot be organized in a logical sequence (e.g. name, eye color, language) b) Ordinal – can be arranged in a rank or order (e.g. first, second, third) c) Dichotomous – shows two categories only (e.g. yes and no) d) Polychotomous – shows many categories (e.g. educational attainment, religion, political affiliation) 2. Numeric - values that describe a measurable numerical quantity and answer the questions “how many” or “how much”. - Types: a) Continuous - Can assume any value between a certain set of real numbers (e.g. weight, height, age) b) Discrete - Can only assume any whole value within the limits of the given variables (e.g. population, number of students in a class)  3. Experimental - define the samples in an experiment. - Types: a) Independent – the variables that are manipulated in an experiment. b) Dependent - usually affected by the manipulation of the independent variables. c) Extraneous - also called as mediating or intervening variables, these variables are already existing during the conduct of an experiment and could influence the result of the study. 4. Non-Experimental - not seen in an experiment. Usually, they are used to show relationships of two factors - Types: a) Predictor - These variables change the other variable/s in a non-experimental study. b) Criterion - These variables are usually influenced by the predictor variables. Lesson 2: Learning from Others and Reviewing the Literature Reviewing the Literature - a survey of scholarly sources on a specific topic. (McCombes, 2023) - By doing literature reviews, researchers can have the confidence that he could address questions related to the gap and variables. Purposes of Literature Review 1. Familiarization with the current state of knowledge on your topic 2. Ensuring that a researcher will avoid repetition on the study of others  3. Identification of gaps in knowledge and unresolved problems that one’s research can address 4. Development of theoretical or conceptual framework and methodology 5. Provision of an overview of the key findings and debates on the topic Conceptual vs Theoretical Framework - Theoretical: foundation of the study where the researcher discusses relevant theories that shapes the context of the paper - Conceptual: When a researcher would combine two or more theories or if there is no theory at all, he could formulate a Conceptual framework Paradigm of the Study - Serves as the visual representation of the study as it becomes the pattern of the study\ 1. Input-Process-Model (IPO Model) 2. IV-DV Model 3. Predictor-Criterion Model 4. -P Model (Proposed Program or Intervention) 5. POM Model Hypothesis of the Study - tentative prediction about the relationship between two or more variables in a population under study. Hypotheses are formulated to anticipate results in a certain study. Simple Hypothesis - formulated when predicting a relationship between an independent and dependent variable - Examples: a) The nature of teachers is related to the nature of the students. b) There is a relationship between the level of exercise and weight retention among elementary school children. Complex Hypothesis - formulated when predicting the relationship of two or more variables to two or more dependent variables - Examples: a) There is no significant relationship between the profile, classroom leadership, and management skills and the school’s performance of Sunday school teachers. b) The intrapersonal and interpersonal competencies of principals do not relate significantly to the performance of secondary schools Directional Hypothesis - specifies not only the existence but also the expected direction of the relationship between the independent and dependent variables - Examples: a) Lower levels of exercise are associated with greater weight retention than higher levels of exercise. b) The types of promotional campaigns positively affect the level of patronage of customers. Non-directional - does not stipulate the direction of the relationship between the independent and dependent variables - Examples: a) Women with different levels of postpartum depression differ with regard to weight retention b) The sources of stress are related to the different coping mechanisms among teachers Null Hypothesis - formulated for the purpose of statistical analysis. This kind is always expressed as a negative statement. It is subjected to testing in which the decision is either to accept or reject it - Examples: a) There is no significant relationship between the reasons for using alternative medicine and the level of comfort of the patients. Research Hypothesis - states the actual expected relationships between variables. It is always expressed affirmatively and is called substantive or scientific hypotheses Lesson 3: Understanding Data and Ways to Systematically Collect Data Research Methodology - Provides readers information as to how would the researcher address the question raised in the first chapter Elements of Methodology 1. Research Design 2. Instrument of the Study 3. Statistical Treatment 4. Respondents of the Study 5. Establishing and Validating Reliability Research Design - important aspect of the research methodology which describes the researcher mode. This element shows what the researcher chose as the approach and what design under the specific approach was chosen. Respondents of the Study - It describes the target population and the sample frame Instrument of the Study - describes the specific type of research instrument that will be used such as questionnaires, checklist, questionnaire-checklist, interview schedule, teacher-made test, and the like. Establishing and Validating Reliability - The instrument must pass the validity and reliability tests before it is utilized Statistical Treatment - One of the many ways of establishing the objectivity of research findings is by subjecting the data to different but appropriate statistical formulas and processes. Types of Research Designs 1. True Experiment Design - In this design, the researcher establishes the cause-and-effect relationships of subjects chosen randomly. There are control and treatment groups in this design and the treatment is designed by the researcher. 2. Quasi-Experimental Design - establishes cause-and-effect relationships but unlike true experiments, it does not rely on random assignments. 3. Pre-Experimental - Usually done before true experiments, pre-experiment design is done to conduct experiments to a smaller group but researchers utilizing this design has little to no control over the study. 4. Action Research - focused on solving a problem or informing individual and community-based knowledge in a way that impacts teaching, learning, and other related processes. 5. Descriptive Research - focuses on accurately portraying or giving picture of what is common to a population. This is usually employed as a starting point of developing theories or interventions. 6. Comparative Research - focuses on the similarities and difference of representative samples from two or more groups in relation to certain designated variables that occur in normal conditions. 7. Correlational Research - Used to investigate the relationships among variables in a population 8. Survey Research - Provides a quantitative, or numeric description of trends, attitudes, or opinions of a population by studying its sample  9. Narrative Research - the researcher studies the lives of individuals. The stories of the subject is retold into narrative chronology. On the other hand, the narrative of the subject and the researcher is combined which is called collaborative narrative 10. Phenomenological Research - discusses the lived experiences of individuals about a phenomenon as described by them. This design yields to deep emotions and essence of the phenomenon. 11. Ethnography - Investigates the shared pattern of behaviors, language, and actions of an intact cultural group in a natural setting over a period of time 12. Grounded Theory - revolves around the idea of creating a general, abstract theory of a process, action, or interaction grounded in the views of the participants. 13. Case Study - comprehensive, in-depth examination of a specific, individual, group of people, or institution. It may be used to gain insights into an obscure or specific problem; provide background data for broader studies; or explain socio-psychological and socio-cultural processes Population and Sampling - Population: composed of the people or objects that possess some common characteristics that are of interest to the researcher - Sample: subset of the Population Factors in Determining Sample Size 1. Homogeneity of the Population 2. Degree of Precision desired by the researcher 3. Types of Sampling Procedures 4. The use of formulas 5. Other considerations Probability Sampling - Sampling method that allows the researcher to give equal opportunities to members of the population Non-Probability Sampling - Selected based on non-random criteria not everyone can be selected Types of Probability Sampling 1. Random Sampling - Everyone has equal chance of being selected 2. Systematic Sampling - Same as random sampling but selects based on interval 3. Stratified Random Sampling - When population is usually mixed, they get classified and then researcher will pick from each classification 4. Cluster Sampling - used to study large population by means of setting non-overlapping subgroups called clusters. This is to keep the heterogeneity of the population. Types of Non-Probability Sampling 1. Convenience Sampling - Individuals who are easily accessible by the researcher are picked  2. Purposive Sampling - Sample selected is based on the expertise of the researcher 3. Snowball Sampling - When sample is hard to get, the participants are used to get more of them 4. Quota Sampling - relies on the non-random selection of a predetermined number or proportion of units. This is called a quota Instrument of the Study - Encompasses the different procedures and questions that a researcher will utilize to collect the data needed to conduct the study. Characteristics of a Good Data Collection Instrument 1. It must be concise yet able to elicit the needed data. According to Shelly (1984), the questionnaire should be two-four pages long and can be answered within ten minutes. A question, on the other hand, should be less than 20 words. 2. It seeks information which cannot be obtained from other sources like documents that are available at hand. 3. Questions must be arranged in sequence, from the simplest to the complex. 4. It must also be arranged according to the questions posed in the statement of the problem. 5. It should pass validity and reliability. 6. It must be easily tabulated and interpreted Types of Data Collection Techniques 1. Document Analysis 2. interview 3. Observation 4. Physiological Measures 5. Psychological Tests 6. Questionnaires a. Yes or No Questions b. Recognition Type Questions – Multiple Choice c. Completion Type Questions – Fill in the Blanks d. Coding Type Question – rate ur shit 1-10 e. Subjective Type Question f. Combination Type Question – has recog, completion, mixed g. Likert Scale – Strongly Agree to Strongly Disagree h. Semantic Differential Scale – like coding but with words