Practical Research 2 Planning Data Collection Procedure PDF

**Practical Research 2** **LAS 2 : Planning Data Collection Procedure** **Lesson 1 Understanding Data and Ways Systematically Collect Data** ***[Importance of Data Collection ]*** There are underlying reasons why a researcher collects data. The following are some of the importance of data collec...

**Practical Research 2** **LAS 2 : Planning Data Collection Procedure** **Lesson 1 Understanding Data and Ways Systematically Collect Data** ***[Importance of Data Collection ]*** There are underlying reasons why a researcher collects data. The following are some of the importance of data collection: **1. Integrity of the Research** A researcher must provide accurate and honest procedure in conducting research. **2. Reduce Errors** The use of proper tools will produce an accurate and desired result must be considered in conducting a research. **3. Decision Making** Accurate data must be collected so that the researcher will arrive with a correct interpretation of the research. **4. Save Cost and Time** Make sure to familiarize or knowledgeable to the topic selected in conducting research and the procedures undertaken. This will result to the smooth flow of your research thus saving much time and effort as well as the financial resources in reproducing the research instrument and the like. **5. To support a need for a new idea, change and/or innovation** It is important to gather data as evidence to support the assumptions to show the need for a shift in the standard or the implementation of new knowledge that will be generally accepted. **[Sources of Data Collection ]** Data in research can be collected from primary sources and secondary sources. - **Primary sources** provide raw information and first-hand evidence. Examples include interview transcripts, statistical data, and works of art. A primary source gives you direct access to the subject of your research. - **Secondary sources** provide second-hand information and commentary from other researchers. Examples include journal articles, reviews, and academic books. A secondary source describes, interprets, or synthesizes primary sources. **[Data Collection Methods ]** Data collection tools refer to the devices/instruments used to collect data depending on the research design and methodologies employed in your research study. The goal behind data collection is to collect quality evidence that enables research to lead to convincing and credible answers to the questions asked. It is important to decide the tools for data collection because research is carried out in different ways and for different purposes. The following are the techniques in gathering data for quantitative research: **1. Interview** A face-to-face conversation between two individuals with the sole purpose of collecting relevant information to satisfy a research purpose. It can be a **Structured** which asks standard sets of questions and followed in the same order or straight forward questions. **Semi-Structured** which asks open- ended questions allowing for a discussion and **Unstructured** wherein no specific set of predetermined questions and flow like an everyday conversation and tend to be more informal and open-ended. **Pros:** In-depth information, freedom of flexibility, accurate data. **Cons:** Time-consuming, expensive to collect. **2. Questionnaire** This is the method of gathering information through a tool that consists of a set of questions and prompts to receive an answer from people to whom it is administered. It is meant to collect a group\'s data. A questionnaire is not a survey, but rather a part of it. A survey is a data collection procedure involving several methods of data collection, including a questionnaire. Questionnaires often make use of checklist and rating scales. Checklist is a list of behaviors, characteristics or other entities that the researcher is looking for while rating scale is more useful when behavior needs to be evaluated. Rating scales state the criteria and provide three or more responses to describe the quality of frequency of behavior, skills, strategies, or variables of the study. **Pros:** Administered in large numbers and is cost-effective Used to compare and contrast previous research to measure change Easy to visualize and analyze Questionnaires offer actionable data **Cons:** Answers may be dishonest or the participants lose interest halfway through Questionnaires can\'t produce qualitative data Questions might be left unanswered Respondents may have a hidden agenda Not all questions can be analyzed easily **3. Observation** This is a data collection method by which information on a phenomenon is gathered through observation. The nature of the observation could be accomplished either as a complete observer, an observer as a participant, a participant as an observer or as a complete participant. This method is a key base of formulating a hypothesis. It can be collected through recording sheets and checklists. Observation guides list the interactions, processes, and behaviors to be observed while field notes do not include preset questions or responses. **Pros**: Easy to administer There subsists a greater accuracy with results It is a universally accepted practice It diffuses the situation of an unwillingness of respondents to administer a report It is appropriate for certain situations **Cons**: Some phenomena aren't open to observation It cannot be relied upon; Bias may arise It is expensive to administer Its validity cannot be predicted accurately **4. Reporting** The process of collecting and sending data to be further analyzed is data reporting. Reporting accurate data is the main component of data reporting since incorrect data reporting contributes to uninformed decision- making. Examples are NGO reports, newspapers, website articles and hospital care records. **Pros**: Informed decision making Easily accessible **Cons**: Self-reported answers may be exaggerated The results may be affected by bias Respondents may be too shy to give out all the details Inaccurate reports will lead to uninformed decisions **5. Tests** Tests provide a way to assess subjects knowledge and capacity to apply this knowledge into new situations. It can provide information that is measured against a variety of standards. - **Norm-reference tests** provide information on how the target performs against a reference group. Examples of norm-referenced tests include the SAT, IQ tests, and tests that are graded on a curve. Anytime a test offers a percentile rank, it is a norm-referenced test. If you score at the 80th percentile, that means that you scored better than 80% of people in your group. - A **criterion- referenced test** are constructed to determine whether the respondents have attained the mastery of a skill or knowledge. Examples are NAT, SHS Exit Assessment, quarterly or periodical exams. **Pros:** Determine the effectiveness of an intervention; It has high validity and reliability or results; **Cons**: Evaluates students' performance without considering external factors; It is limited with the cognitive domain of the students **Lesson 2 Data Analysis Using Statistics and Hypothesis Testing** **Quantitative Analysis** Quantitative data analysis is a systematic approach where data are collected and transforms the collected data or observed into numerical data. It often describes a situation or event, answering the research questions or objectives of the study. It is often concerned with finding evidence to either support or contradict an idea or hypothesis you might have. ***[Methods Used in Quantitative Analysis]*** **[A. Descriptive Statistics ]** To explain the information collected, descriptive statistics are used, such as the range of values, their average, and the most common category. It is also used to present quantitative descriptions in a manageable form. In a research study we may have lots of measures. As such, it helps us to simplify large amounts of data in a sensible way. Each descriptive statistic reduces lots of data into a simpler summary. **Types of Descriptive Statistics :**There are four major types of descriptive statistics: **1. Measures of Frequency:** - Count, Percent, Frequency Shows how often something occurs Use this when you want to show how often a response is given **2. Measures of Central Tendency** - Mean, Median, and Mode **3. Measures of Dispersion or Variation** - Range, Variance, Standard Deviation Identifies the spread of scores by stating intervals Range = High/Low points Variance or Standard Deviation = difference between observed score and mean Use this when you want to show how \"spread out\" the data are. It is helpful to know when your data are so spread out that it affects the mean **4. Measures of Position** - Percentile Ranks, Quartile Ranks Describes how scores fall in relation to one another. Relies on standardized scores Use this when you need to compare scores to a normalized score (e.g., a national norm) **[B. Inferential Statistics ]** Inferential statistics are used from the research data to make comparisons and draw conclusions. Information obtained from inferential statistics enables researchers to draw inferences and generalize to other classes outside their study sample. With inferential statistics, you are trying to reach conclusions that extend beyond the immediate data alone. **[Types of Inferential Statistics]** In this area, there are several tests, some of the most significant of which are listed below. **1. Linear Regression Analysis** In this test, a linear algorithm is used to understand the relationship between two variables from the data set. One of those variables is the dependent variable, while there can be one or more independent variables used. **2. Analysis of Variance** This is another statistical method which is extremely popular in data science. It is used to test and analyze the differences between two or more means from the data set. The significant differences between the means are obtained, using this test. **3. Analysis of Co-variance** A co-variate is an independent variable which is continuous and are used as regression variables. This method is used extensively in statistical modelling, to study the differences, present between the average values of dependent variables. **4. Statistical Significance (t-test)** A relatively simple test in inferential statistics, this is used to compare the means of two groups and understand if they are different from each other. The order of difference, or how significant the differences are can be obtained from this. **5. Correlation Analysis** Another extremely useful test, this is used to understand the extent to which two variables are dependent on each other. The correlation can also be negative or positive, depending upon the variables. A negative correlation means that the value of one variable decrease while the value of the other increases and positive correlation means that the value both variables decrease or increase simultaneously. **Tools for Data Analysis** The table below shows a sample statistical tool to be used in data analysis on the specific focus of the research. +-----------------------------------+-----------------------------------+ | **Focus of the Research** | **Tools for Data Analysis** | +-----------------------------------+-----------------------------------+ | Profile of the Respondents | Frequency counts, Percentages, | | | Ranking, summation | +-----------------------------------+-----------------------------------+ | Correlational Part of the | Chi-Square Test, Pearson- Product | | Research | of | | | | | | Moment Correlation, Spearman Rank | | | Order of Correlation, Regression | | | Analysis | +-----------------------------------+-----------------------------------+ | Significant Difference | t-test, One Way/Two Way Analysis | | (Comparison Data) | of Variance (ANOVA), | +-----------------------------------+-----------------------------------+ | Experimental Research | Dependent sample t -test | | | | | | Paired sample t-test | +-----------------------------------+-----------------------------------+ An understanding of the scoring system and the descriptive interpretation that comes with it will also help the researcher in the statistical treatment. Examples are seen below. The format of a typical five-level Likert Item could be: ----------- ------------- ----------------------------- **Scale** **Range** **Qualitative Description** 5 4.21- 5:00 Strongly Agree 4 3.41- 4.20 Moderately Agree 3 2.61- 3.40 Neither Agree nor Disagree 2 1.81- 2.60 Moderately Disagree 1 1.00 - 1.80 Strongly Disagree ----------- ------------- ----------------------------- The format of a typical four-level Likert Item could be: ----------- ----------- ----------------------------- **Scale** **Range** **Qualitative Description** 4 3.25-4.00 Always 3 2.50-3.24 Sometimes 2 1.75-2.49 Often 1 1.00-1.74 Never ----------- ----------- ----------------------------- **[Hypothesis Testing ]** A hypothesis is an educated guess about something in the world around you. It should be testable, either by experiment or observation. - The **null hypothesis** is a general statement that states that there is no relationship between two phenomena under consideration or that there is no association between two groups. The symbol for the null hypothesis is **H0,** and it is read as **H-null, H-zero, or H-naught.** The null hypothesis is usually associated with just **'equals to'** sign as a null hypothesis can either be accepted or rejected. - An **alternative hypothesis** is a statement that describes that there is a relationship between two selected variables in a study. The symbol of the alternative hypothesis is **either H1 or Ha** while using less than, greater than or not equal signs. Examples: +-----------------------+-----------------------+-----------------------+ | **Research | **Null Hypothesis | **Alternative (H1)** | | Questions** | (H0)** | | +-----------------------+-----------------------+-----------------------+ | Is there significant | There is no | There is a | | | significant | significant | | difference between | | | | the | difference between | difference between | | | the | the | | posttest performance | | | | of | posttest performance | posttest performance | | | of | of | | the control and | | | | | the control and | the control and | | experimental group | | | | after exposing to the | experimental group | experimental group | | | after exposing to the | after exposing to the | | intervention. | | | | | intervention | intervention | +-----------------------+-----------------------+-----------------------+ | **Research Titles** | **Null Hypothesis | **Alternative (H1)** | | | (H0)** | | +-----------------------+-----------------------+-----------------------+ | Impact of the | There is no impact of | There is an impact of | | | the implementation of | the implementation of | | Implementation of | COVID -- 19 Health | | | COVID -- 19 Health | Protocols in | COVID-- 19 Health | | Protocols in | Supermarkets on | | | Supermarkets on | | Protocols in | | | Consumer Behaviors | | | Consumer Behaviors | | Supermarkets on | | | | Consumer Behaviors | +-----------------------+-----------------------+-----------------------+ ***Lesson 3 Writing Research Methodology*** **What is a Research Methodology?** A research methodology is a part of research paper that contains the description of ways and means to conduct the research. The basic aim of a research methodology is to explain what techniques are being used or will be used in order to obtain the data or information that is expected to be gained at the end of the research. **Components of a Research Methodology** The research methodology of your research is under Chapter II. Before stating the different components, make sure to write a brief statement or introduction regarding the contents that are covered in this chapter. *(e.g. This chapter presents the research design, sources of data, instrumentation and data collection and tools for data analysis.)* A. **A. Research Design** ***Sample Research Design*** *The research design used in this study is the quasi-experimental design or the one -shot pretest-posttest research design. A pretest-posttest design is an experiment where measurements are taken both before and after a treatment (Lane, 2012). This design is fitting for this study since the main purpose of the study is to determine the difference in the performance of the respondents before and after exposing the respondents with the strategy used in the study.* *The approach is quantitative. According to Wyse (2011), quantitative research is used to quantify the problem by way of generating numerical or data be transformed into usable statistics. It is used in this study because it will describe the performance of the learners after exposing to a researcher- initiated intervention strategy in teaching General Physics 1.* A. **A. Locale and Population of the Study/Sources of Data** In this area, you must describe the place where the study will be conducted and the reason of your choice. Make sure to describe the respondents of your study as well as the sampling design used. Because if incorrect sample calculation, it will have a questionable validity of your research. Generally, you can use the Slovin's Formula to solve or determine the sample size of the population. ***Sample Locale and Population*** *The respondents of the study were the Science, Technology, Engineering, and Mathematics (STEM) of Don Eufemio F. Eriguel Memorial National High School for the school year 2018-2019 (First Semester). The respondents passed the qualification criterion for the STEM strand. There are 30 respondents and total enumeration was used. All of the respondents were considered based on the low pretest scores of the respondents with below 74 percent transmuted grade of the respondents.* A. **B. Instrumentation and Data Collection** In this area, you have to describe the sources of data, the instruments to be used, what each will measure, how to interpret, to whom they will be administered and how they will be administered. Don't forget to present the validity and reliability of the tools used in the study. ***Sample Instrumentation and Data Collection*** *A researcher-made test was prepared and organized based on the inputs and suggestions of the validators. It is a multiple- choice type of test with four choices crafted from the selected competencies in General Physics I. The 60-item test instrument was subjected to reliability and validity with Table of Specifications presented to the validators. Exhibit walk activities were also prepared and served as the summative test of the respondents given at the end of the quarter. The different activities were validated by the same validators of the test instrument. The activities were patterned from the selected learning competencies found in the curriculum guide in General Physics I. The activities were placed strategically in the different corners of the classroom. The respondents were group and given two to three minutes to answer the problem, questions or illustration presented. After two to three minutes (2-3), the respondents will proceed to the next exhibit or activities until the respondents answered all the activities. The respondents were given five (5) minutes to consolidate and finalize their answers. Group reporting was done and group critiquing was also implemented for further evaluation of their output and to manifest cooperative learning.* *The test instrument and activities were validated by the head teacher of science department and master teachers in the Junior High School. Kuder Richardson Formula 20 was used to determine the reliability of the test instrument and computed for its index of difficulty to indicate the level of appropriateness of the test questions.* **C. Data Analysis** In this area, you must discuss what appropriate statistical tools to be used in your study. Always account for the research problem you have enumerated in your study. ***Sample Data Analysis*** *The data gathered were processed and analyzed for a systematic presentation using dummy tables, mean, frequency counts, and percentages.* *Moreover, t -- test was used to determine the significant difference between the performance of the respondents along pretest and posttest using Microsoft Excel and SPSS at 0.05 level of significance.* *The index of difficulty using the Kuder Richardson Formula 20 indicates the appropriateness of the level of difficulty of the test item for the group (Keshava, 2016)* *where: Di = difficulty index* *Nr = number of students who got the item correctly* *Nt = number of students who took the test* *The index of difficulty of each item was based on the computed values which describes as follows:* *Computed Di Descriptive Equivalent* *0 -- 39 Very difficult items, delete or revise* *40 -- 70 Moderate, include* *71 -- 100 Very easy, delete or modify* *After the administration of the exhibit walk activities or questions, a posttest was given with the same content as the pretest. The scores in the pretest and posttest were computed using the formula.* *Score= Raw Score/Number of Items X 50 + 50* *This formula has the lowest possible score of 50 points and the highest possible score of 100. The scores in the pre-test and posttest of the learners were treated using frequency and percentage. Their scores along the different summative tests were graded using prepared rubrics and their scores in the pre -- test -- posttest, and summative tests were interpreted using the DepEd proficiency descriptive rating: (DepEd Order 8, s.2015, DepEd Order 36, s. 2016)* *Score Range Descriptive Rating* *90-100 Outstanding* *85 -- 89 Very Satisfactory* *80 -- 84 Satisfactory* *75 -- 79 Fairly Satisfactory* *below 75 Did Not Meet Expectations*