Practical Research 2 - Lesson 1 PDF

PRACTICAL RESEARCH 2 outcome is not conclusive nor generalizable LESSON 1 What is research? TYPES OF DATA ANALYSIS non-...

PRACTICAL RESEARCH 2 outcome is not conclusive nor generalizable LESSON 1 What is research? TYPES OF DATA ANALYSIS non-statistical contextual RESEARCH thematic a systematic investigation to establish facts and reach new 2. QUANTITATIVE conclusions studies about the statistics of a - has a step-by-step procedure population a careful consideration of study data are numerical regarding a particular concern or a make non-numerical data into problem using scientific methods quantitative a systematic inquiry to describe, trying to relate two variables explain, predict and control the determining significance between observed phenomenon two variables - (Earl Robert Babbie) outcomes are: the processes are sequentially - broad-based insights arranged - population-based careful consideration of a particular understanding concern of a problem (we can only talk about one problem) SIMILARITIES creation of new knowledge systematic (advance new conclusion) advancing thoughts to solve a trying to compare different specific problem conclusions requires data analysis synthesis and analysis of previous research to the extent that it leads to new and creative outcomes RESEARCH SAMPLING METHODS - identify what is common in Qualitative different studies - purposive sampling used to make informed decisions Quantitative - random sampling QUALITATIVE VS QUANTITATIVE FUNDAMENTAL CONCEPTS OF 1. QUALITATIVE QUANTITATIVE RESEARCH an in-depth analysis or involves “figures” in the conduct of understanding of a specific concept inquiry - has a meaningful objective the result of a thinking process that data are more expressed in primarily involves “quantitative words/too narrative questioning techniques” studies variables  - ex. age, gender, educational INQUIRY-BASED LEARNING status in the form of authentic (real-life) standardized instruments guide data problems within the context of a collection, ensuring the accuracy, curriculum and/or community reliability and validity of data capitalizes on two “statistically figures, tables or graphs showcase related” variables summarized data collected in order quantitative data and information are to show trends, relationships or actively used, interpreted, refined, differences among variables digested, and discussed - allows you to see the evidence collected a large population yields more QUANTITATIVE RESEARCH reliable data, but principles of a type of educational research in random sampling must be strictly which the researcher decides what followed to prevent researcher’s bias to study; asks specific, narrow methods can be repeated to verify questions and collects quantifiable findings in another setting, thus data from participants reinforcing validity of findings analyzes these numbers using puts emphasis on proof, rather than statistical tools; and conducts the discovery inquiry in an unbiased, objective manner STRENGTHS OF QUANTITATIVE RESEARCH most reliable and valid way of NATURE OF QUANTITATIVE RESEARCH concluding results, giving way to a use numbers in stating new hypothesis or disproving it generalizations about a given results and generalizations are more problem or inquiry reliable and valid because of bigger these numbers are the results of number of population sample objective scales of measurements of filter out external factors, if properly the units of analysis called variables designed, so results can be seen as research findings are subjected to real and unbiased statistical treatment to determine significant relationships or WEAKNESSES OF QUANTITATIVE differences between variables, the RESEARCH results of which are the bases for can be costly, time consuming, and generalization about the phenomena difficult because most researchers are non-mathematicians require extensive statistical CHARACTERISTICS OF QUANTITATIVE treatment with stringent standards, RESEARCH more so with confirmation of results methods or procedures include tend to turn out only proved or items that call for measurable unproven results characteristics of the population RESEARCH DESIGN 3. Pre-experimental: one shot overall strategy that integrates case study and one group different components of the study in pretest/posttest design a coherent and logical way, ensuring you will effectively address the NON-EXPERIMENTAL research problem observes the phenomena as they constitutes the blueprint for the occur naturally and no external selection, measurement and variables are introduced analysis of data variables are not deliberately research problem determines the manipulated nor is the setting research design you will use controlled quantitative methods emphasize researchers collect data without objective measurements and the making changes or introducing statistical, mathematical, or treatments numerical analysis of data collected there are no treatments that are being utilized we are not able to define the CLASSIFICATIONS OF QUANTITATIVE variables well RESEARCH DESIGNS 1. Descriptive-statistical a. survey EXPERIMENTAL b. correlational allows the researcher to control the c. ex-post facto studies situation d. comparative “what causes something to occur?” e. evaluative allows to identify cause and effect f. methodological relationships with variables distinguishes placebo effects from PRE-EXPERIMENTAL treatment effects apply to experimental designs with supports the ability to limit the least internal validity alternative explanations used if you would like to compare infer direct causal relationships in behavior the study statistical question: significant provides the highest level of difference evidence for single studies measures the group twice (before and after the intervention) TYPES OF QUASI-EXPERIMENTAL 1. True experimental: pre-test DESIGN design, post-test design and 1. NON-EQUIVALENT CONTROL post-test only/control group GROUP DESIGN design chance failure random assignment 2. Quasi-experimental: to equalize the conditions by non-equivalent control group converting a true experiment into design and time series this kind of design, for purposes of design analysis  randomly choosing respondents to 3. Ex-post facto research design avoid bias investigates causal relationship examine wether one or more 2. INTERRUPTED TIME SERIES pre-existing conditions could DESIGN possibly have caused subsequent employs multiple measures before differences in group of subjects and after the experimental discover whether differences intervention between groups have results in an users assume that the time threats observed difference in the such as history or maturation appear independent variables as regular changes in the measures a. dependent prior to the intervention - predictor before and after experimental b. independent several pre-tests and post-tests - the one being predicted TYPES OF DESCRIPTIVE RESEARCH 4. Comparative design DESIGNS comparing and contrasting two or observe, describe, and document more sample of study on one or aspects of a situation as it naturally more variables, often at a single occurs and sometimes to serve as a point in time starting point for hypothesis compare two distinct groups on the generation or theory development basis of select attributes compare among indicators of 1. Survey respondents establish what’s common 5. Evaluative research numeric description of trends assess in some way providing 2. Correlational information about something other a. Bivariate than might be gleaned in more two variables for each observation or investigation of subject relationships understand if there is seeks to find information about relationship something b. Prediction studies what can be measured obviously show how one make deeper comparisons variable (predictor) 6. Methodological predicts another (the implementation of a variety of criterion variable) methodologies forms a critical part of if it causes another achieving the goal of developing a variable to exist scale-matched approach, where c. Multiple regression prediction data from disciplines can be studies integrated two or more predictor implements multiple methodologies variables to predict what the number said is different another variable than the actual observed  used to validate among the fundamental concepts of research, alongside with measurement, validity, reliability, LESSON 2: cause, effect, and theory something that can take several Importance of quantitative research values across fields - values can be words or numbers - (Bernard, 1994) to find solutions, even tentative any entity that can take on different ones to problems in order to improve values or enhance ways of doing things anything that can vary can be disprove/provide a new hypothesis considered as variable find answers to problems in daily life - attribute, on the other hand, establish knowledge as basis for is a specific value on a policy formation or the enactment of variable relevant laws - ex. sex (variable); male/female (attribute) Why conduct a quantitative units of analysis research? characteristics or attributes of an In the natural, social, and military science: individual or an organization that can to come up with systematic and be measured or observed empirical investigation of - (Creswell, 2002) observable phenomena most common variables are age, process of measurement is central sex/gender, education, income, to this because it provides the marital status, occupation, fundamental connection between leadership style, managerial trait etc empirical observation and mathematical expression of PURPOSE OF VARIABLE quantitative relationships research is based on defining you observe what is experienced vs variables operationally, looking for what is measured associations among them, and trying In health sciences: to understand whether one variable to present breakthroughs causes another LESSON 3: NATURE OF VARIABLES AND DATA quantitative researchers try to count Kinds of variables and their uses human behaviors attempt to count multiple variables at the same time VARIABLE 1. NOMINAL VARIABLES “vary” - ability to change/transform from one to another  represent categories that cannot be the independent variable on the ordered in any particular way dependent can be determined because of its qualitative nature 5. CONFOUNDING VARIABLES ex. males vs females not actually measured or observed can be quantified as to frequency in a study 2. ORDINAL VARIABLES they exist but their influence cannot represent categories that can be be directly detected in a study ordered from greatest to smallest for purposes of further studies 3. INTERVAL VARIABLES have values that lie along an evenly dispersed range of numbers LESSON 4: 4. RATIO VARIABLES have values that lie along an evenly Formulating Research Topics & dispersed range of numbers when Questions there is an absolute zero no negative values “If I had an hour to solve a problem and my life depended on it, I would KINDS OF VARIABLES 1. INDEPENDENT VARIABLES use the first 55 minutes determining cause, influence, or affect outcomes the proper questions to ask.” invariably called treatment, - Albert Einstein manipulated, antecedent, or predictor variables 2. DEPENDENT VARIABLES RESEARCH TOPIC rely on the independent variables broadly defines the area of research the outcomes or the results of the influence of the independent the initial process variables followed by the formulation of the 3. INTERVENING OR MEDIATING research problem and specific VARIABLES “stand between” the independent questions and dependent variables show the effects of the independent 5 EASY STEPS IN CONCEPTUALIZING A variable on the dependent variable RESEARCH TOPIC 4. CONTROL VARIABLES According to Moyer, (2011) special types of independent 1. FINDING YOUR FOCUS variables that are measured in a Which aspects of your discipline study because they potentially interest you most? influence the dependent variable What have you observed that you may be demographic or personal have questions about? variables that need to be What articles have you read that “controlled” so the true influence of have raised questions in your mind?  2. WHAT ARE THE GAPS IN THE LITERATURE? By topic, what is not being looked at? Methods, what is not being done? Populations, who is not being studied? Comparisons, who is not being compared? 3. WHERE TO START? read detailed literature searches attend seminars, conferences & presentations discuss subject area with peers listen and ask questions 4. REFINING RESEARCH TOPIC discuss with fellow researchers discuss with stakeholders assess what is most critical to learn assess research sources available 5. QUESTIONS TO ASK YOURSELF discuss with fellow researchers discuss with stakeholders assess what is most critical to learn assess research sources available 3 EASIER STEPS By Online Writing Research Center 1. REVIEW YOUR CRITERIA 2. DO A TIMING REALITY CHECK 3. TEST-OUT PRELIMINARY TOPIC END OF REVIEWER By: Sharlene H. Esternon Good luck sa exam! Kayang kaya mo ina. :)