Research Report Writing PDF

REPORTING AND SHARING THE FINDINGS  Blank Spot: with MINIMAL or NO LITERATURE to Address a specific problem or inquiry  A research report must be written in an  Blind...

REPORTING AND SHARING THE FINDINGS  Blank Spot: with MINIMAL or NO LITERATURE to Address a specific problem or inquiry  A research report must be written in an  Blind Spot: with AVAILABLE LITERATURE BUT WITH ACADEMICALLY ACCEPTED MANNER. It is NOT A CONTRADICTING RESULTS or CONCLUSIONS MERE NARRATIVE OF IDEAS and data that have Objectives been discovered and unearthed, it conforms with standards and prescribed format. – What do the researchers intend to do to address  When we write in accordance with the formalities of the concerns? research reporting, this ASSURES RELEVANT – It must be SMART INFORMATION AND INTELLECTUAL HONESTY. Contributions Making the study genuine and scientifically sound. – What BENEFIT will the study OFFER to the current STRUCTURE OF RESEARCH REPORT theories, practices, and future researches? Manuscript Content: A. Preliminaries  Title Page  Endorsement  Certificate of Originality  Table of Contents  List of Tables  List of Figures B. Abstract  The SUMMARY of the whole content of the research paper.  It should be CLEAR and THE STATEMENTS 2.0 BACKGROUND must be CONCISE and written in COMPLETE This portion provides the FOUNDATION OF THE SENTENCES and PARAGRAPH instead of an outline or note form. STUDY. Through the LITERATURE REVIEW, the reader would know HOW OR WHY the researchers produce the topic  It must be FULLY SELF-CONTAINED and objectives. MAKE SENSE BY ITSELF, without further reference to outside sources or to the actual Parts to Be Discussed: paper.  Theoretical Framework C. Body  Variable Discussion 1.0 INTRODUCTION TIP: Do not underestimate the power of literature reviews. Properly literature-  Leads the reader from a general subject area to a reviewed research papers could answer the trickiest questions of critics. particular field of research.  It ESTABLISHES THE CONTEXT AND SIGNIFICANCE of the THEORETICAL FRAMEWORK RESEARCH being conducted by SUMMARIZING current understanding and background information – Discusses the THEORIES that HELPED THE RESEARCHERS about the topic and STATING THE PURPOSE OF THE in CONTEXTUALIZING the topic. This provides a strong WORK. SCIENTIFIC FOUNDATION that serves as a guide in making SCIENTIFICALLY SOUND RESEARCH. Introduction – Theoretical frameworks are best discussed following the S-E-C format. The introduction is best written using the T-I-O-C format STATE TRENDS – State the theory that was UTILIZED by the researchers. – What are the latest trends about the topic? EXPLAIN ISSUES – Using PROPER CITATIONS, discuss the theory AS – What are the issues that transcended within the EXPLAINED by LITERATURE SOURCES topic? CONTEXTUALIZE RESEARCH INSTRUMENTS – APPLY the theory to the set-up of the study. – Equipment and materials available off the shelf should be described exactly and the sources of VARIABLE DISCUSSION materials or specimens should be given. The VARIABLES PRESENTED IN THE STUDY are the – Researchers will explain what instrument will they items reviewed using various kinds of literature. The use and if there is validation and reliability testing proper citation must always be observed and must that happened. always be written in paragraph form. – The researcher can start with: Discussion of such can best be written in S-E-A format. “This study will use 18 researcher-made interview questions..........” Sypnosis DATA ANALYSIS – State what PARTICULAR TOPIC is all about. – Qualitative data analysis is a process of gathering, Evidence structuring, and interpreting qualitative data to – Provide pieces of evidence about the topic understand what it represents. – This part explains what type of technique was used in Argument the study. – State the PROBLEMS THAT EMERGED from the TECHNIQUES: GATHERED EVIDENCES. THEMATIC ANALYSIS Example: – Thematic analysis is used to DEDUCE the meaning In a study entitled “Eliciting Challenges on Social behind the words people use. This is Connectedness among Filipino Nurse Returnees: A cross- accomplished by discovering REPEATING THEMES Sectional Mixed- Method Research” variables below in text. were discussed: GROUNDED THEORY 1. Migration 2. Return Migration – Useful approach when LITTLE is KNOWN ABOUT A 3. Social Connectedness SUBJECT. This starts by FORMULATING A THEORY 4. Returnee Experiences around a single data case. This means that the theory is “grounded”. It’s based on actual data, 3.0 RESEARCH METHODOLOGY and not entirely speculative.  The main purpose of the materials and methods DISCOURSE ANALYSIS section is to PROVIDE ENOUGH DETAIL for a competent reader to REPLICATE THE STUDY AND – Used to get a THOROUGH UNDERSTANDING of the REPRODUCE the RESULTS. political, cultural, and POWER DYNAMICS that exist  This ENSURES that the study has UNDERGONE in SPECIFIC SITUATIONS. SCIENTIFIC PROCESS and that the tools utilized in the – Discourse analysis is commonly used by brand study are VALID AND RELIABLE. strategists who hope to understand why a group of people feel the way they do about a brand or RESEARCH DESIGN product. This part discusses the APPROACH (Quantitative or CONTENT ANALYSIS Qualitative) and the DESIGN (Phenomenology, Ethnography, Case-study, etc.) that the researcher used – Other analysis techniques may fit within the broad for the study scope of content analysis. Thematic analysis is a part of content analysis. Content analysis is used STUDY PARTICIPANTS AND LOCALE to identify the patterns that emerge from text, by GROUPING CONTENTS INTO WORDS, concepts,  Describe the DEMOGRAPHIC CHARACTERISTICS of the and themes. Content analysis is useful to RESPONDENTS/PARTICIPANTS. Describe the SAMPLING QUANTIFY the RELATIONSHIP between all of the TECHNIQUE used. Enumerate the INCLUSION and grouped content. EXCLUSION criteria in the selection of the participants.  Describe also characteristics of the place of the NARRATIVE ANALYSIS study. – Narrative analysis FOCUSES ON THE STORIES PEOPLE TELL and the language they use to make sense of them. It is particularly useful for getting a  deep understanding of customers’ perspectives GUIDELINES IN WRITING CONCLUSIONS on a specific issue. A narrative analysis might enable us to summarize the outcomes of a A conclusion that is well-written gives the FOCUSED CASE STUDY. researcher the opportunity to demonstrate to the reader an understanding of the research problem. These RESEARCH ETHICS include: Enumerated the ETHICAL PRINCIPLES maintained 1. Highlight key points and put emphasis on the last throughout the study, this includes the consent form, the sentence to make a lasting impression. ETHICAL ETHICS REVIEW, and permission to conduct 2. Summarize your reflections and thoughts and human and/or animal study. communicate what is the relevance of your study. 3. Identify how gaps in previous literature have been 4.0 RESULTS addressed. Presents the DATA, PROCESSES AND CONDENSED, 4. Demonstrate the relevance of your thoughts. with important trends EXTRACTED and DESCRIBED. It is 5. Introduce new strategies for formulating a potential important that the findings be CLEARLY AND SIMPLY research problem. STATED. The results should be BRIEF AND DIRECT. 5.0 DISCUSSION The result should be communicated. What generalizations can be drawn? How do the findings compare to the finding of others or to expectations based on previous work? Are there any theoretical/practical implications of the results? CONCLUSION and RECOMMENDATION are the most important. REFERENCES – The reference section should be given on a new page with the title bold and left intended. o The references should STRICTLY FOLLOW THE AMERICAN PSYCHOLOGICAL ASSOCIATION (APA) 6th edition. – All reference type is integrated and ARRANGED ALPHABETICALLY REFERENCE CITATION FORMAT Journal Citation: 1. Author(s) 2. Date Of Publication 3. Article Title 4. Journal Name (Italic) 5. Volume (Issue) (Italic) 6. Page Numbers 7. DOI Number Website & Report Citation: 1. Author(s) 2. Date Of Publication 3. Page & Report Title (Italic in Report) 4. Link Of Page Book Citation: 1. Author(s) 2. Date Of Publication 3. Book Title (Italic) 4. City, State/Country: Publisher  1 CAUSE-AND-EFFECT RELATIONSHIPS CAUSATION & THE DIRECTIONALITY PROBLEM Experimental Research Strategy Although a research study may establish a relationship between two variables, the existence of a Establishes the existence of a cause-and-effect relationship does not always explain the direction of the relationship between two variables. To accomplish this relationship. goal, an experiment manipulates one variable while a second variable is measured and other variables are CONTROLLING NATURE controlled. To establish a cause-and-effect relationship, an Experiment or a True Experiment experiment must control nature, essentially creating an unnatural situation wherein the two variables being Attempts to show that changes in one variable examined are isolated from the influence of other are directly responsible for changes in a second variable. variables and wherein the exact character of a relationship can be seen clearly. Four Basic Elements: 1. Manipulation DISTINGUISHING ELEMENTS OF AN EXPERIMENT  The researcher manipulates one variable by Manipulation changing its value to create a set of two or more treatment conditions. Consists of identifying the specific values of the 2. Measurement independent variable to be examined and then creating  A second variable is measured for a group of a set of treatment conditions corresponding to the set of participants to obtain a set of scores in each identified values. treatment condition. 3. Comparison  Manipulation and the Directionality Problem  The scores in one treatment condition are  Simply observing that a relationship exists does not compared with the scores in another treatment explain the relationship and certainly does not condition. identify the direction of the relationship. 4. Control  Manipulation and the Third-Variable Problem  All other variables are controlled to be sure that  Manipulation is to help researchers control the they do not influence the two variables being influence of outside variables. However, the examined. existence of a relationship does not necessarily mean that there is a direct connection between TERMINOLOGIES the two variables.  Independent variable is the variable manipulated by Control the researcher.  Treatment condition is a situation or environment  Control and the Third-Variable Problem characterized by one specific value of the  The particular concern is to identify and control manipulated variable. any third variable that changes systematically  Levels are the different values of the independent along with the independent variable and has the variable selected to create and define the treatment potential to influence the dependent variable. conditions.  Extraneous Variables and Confounding Variables  Dependent variable is the variable that is observed  With thousands of potentially confounding for changes to assess the effects of manipulating the variables, however, the problem of controlling (or independent variable. even monitoring) every extraneous variable  Extraneous variables are all variables in the study appears insurmountable. other than the independent and dependent variables. CONTROLLING EXTRANEOUS VARIABLES CAUSATION & THE THIRD-VARIABLE PROBLEM John Henry Effect  One problem for experimental research is that  Refers to the tendency of individuals in the control variables rarely exist in isolation. group to perceive themselves as being at a  Although, a study may establish that two variables disadvantage compared to the experimental group. are related, it does not necessarily mean that there is  This perception leads them to work harder or change their a direct (causal) relationship between the two behavior in an attempt to overcome the perceived disadvantage. variables. This effect can significantly skew the results of an experiment. When the control group is aware of the comparison, they may exert extra effort or change their behavior, which can make it difficult to determine the true effect of the treatment being tested  2 Control by Holding, Constant or Matching  Placebo Control Conditions A. Placebo  Holding a Variable Constant  An inert or innocuous medication, a fake  By standardizing the environment and medical treatment that, by itself, has procedures, most environmental variables can be absolutely no medicinal effect, but produces held constant. Holding a variable constant a positive or helpful effect simply because an eliminates its potential to become a confounding individual expects or believes it will happen. variable. B. Placebo effect  Matching Values across Treatment Conditions  Refers to a positive response by a participant  Control over an extraneous variable can also be to an inert medication that has no real effect exercised by matching the levels of the variable on the body. The placebo effect occurs across treatment conditions. simply because the individual thinks the medication is effective. Control by Randomization C. Placebo control condition  A condition in which participants receive a  Randomization placebo instead of the actual treatment.  The use of a random process to help avoid a systematic relationship between two variables. Manipulation Checks The goal of randomization is to disrupt any systematic relation between extraneous variables and the independent variable, thereby preventing the Manipulation check is an additional measure to extraneous variables from becoming confounding variables. assess how the participants perceived and interpreted the manipulation and/or to assess the direct effect of the  Random assignment manipulation.  The use of a random process to assign participants to treatment conditions. It is particularly important in four situations: Specifically, the use of random assignment should ensure that the participant variables do not change systematically from one treatment to another and, 1. Participant Manipulations therefore, cannot be confounding variables 2. Subtle Manipulations 3. Placebo Controls Comparing Methods of Control 4. Simulations The goal of an experiment is to show that the scores obtained in one treatment condition are INCREASING EXTERNAL VALIDITY: SIMULATION AND consistently different from the scores in another treatment FIELD STUDIES and that the differences are caused by the treatments. Simulation In the terminology of the experimental design, the goal is to show that differences in the dependent variable are caused by the independent variable. In this The creation of conditions within an experiment context, the purpose of control is to ensure that no variable, other than the independent variable, could be responsible for causing the scores to differ. that simulate or closely duplicate the natural environment in which the behaviors being examined Advantages & Disadvantages of Control Methods would normally occur. The two active methods of control (holding Field Studies constant and matching) require some extra effort or extra measurement and, therefore, are typically used Research conducted in a place that the with only one or two specific variables identified as real participant or subject perceives as a natural threats for confounding. environment. CONTROL CONDITIONS & MANIPULATION CHECKS Advantages and Disadvantages of Simulation and Field Studies Control Conditions  Advantage  Experimental condition  They allow researchers to investigate behavior in  The condition in which the treatment is more lifelike situations and, therefore, should administered increase the chances that the experimental  Control condition results accurately reflect natural events.  The condition in which the treatment is not × Disadvantage administered.  Allowing nature to intrude on an experiment  No-Treatment Control Conditions means that the researcher often loses some  A condition in which the participants do not control over the situation and risks compromising receive the treatment being evaluated. the internal validity of the experiment.  FINDING ANSWERS THROUGH QUALITATIVE DATA COLLECTION AND DATA ANALYSIS 1 QUALITATIVE RESEARCH possibility of manipulating the results because of subjectivity.  Qualitative researchers generally begin with a  Qualitative observations can be done using less focused research question, collect large various methods, including direct observation, amounts of relatively “unfiltered” data from a interviews, focus groups, or case studies. relatively small number of individuals, and  They can provide rich and detailed information describe their data using nonstatistical about the behavior, attitudes, perceptions, and techniques. experiences of individuals or groups.  They are usually less concerned with drawing  Rather, the observation is based on the general conclusions about human behavior than observer’s subjective interpretation of what with understanding in detail the experience of they see, hear, smell, taste, or feel. their research participants. According to Meng (2012), because of the PURPOSE OF QUALITATIVE RESEARCH element of subjectivity, this makes observation  Qualitative research can help researchers to inferior among the other techniques. generate new and interesting research questions and hypotheses. TYPES OF OBSERVATION  Qualitative research can also provide rich and There are several types of qualitative detailed descriptions of human behavior in the observation. Here are some of the most common real-world contexts in which it occurs. types to help you choose the best one for your  Qualitative research can convey a sense of work. what it is actually like to be a member of a particular group or in a particular situation— 1. Naturalistic Observation what qualitative researchers often refer to as the 2. Participant Observation “lived experience” of the research 3. Covert Observation participants. 4. Case Study DATA COLLECTION IN QUALITATIVE RESEARCH The curiosity of the researcher is the main motivator in searching for answers to his inquiries with the following data collections methods: observation, interview and survey questionnaire. This unit will focus on Observation and Interview as the method of data-collection in qualitative research. Data Gathering OBSERVATION  Is a type of data gathering technique wherein the researcher, communicates, interacts and watch the subjects of the study.  This enables the researcher to record activities of a person in his day to day life, whereby the data are all gathered in a naturalistic manner.  In qualitative research, observational data is collected with minimum structure (Polit and Beck, 2012), thus the researcher must be skillful, as the data to obtain is dependent on the researcher. The trustworthiness and integrity must also be innate upon the researcher due to the  FINDING ANSWERS THROUGH QUALITATIVE DATA COLLECTION AND DATA ANALYSIS 2 ADVANTAGES OF QUALITATIVE OBSERVATIONS Interviews involve two or more people, one of whom is the interviewer asking the questions. 1. Qualitative observations allow you to  They allow you to gather rich information and generate rich and nuanced qualitative draw more detailed conclusions than other data—aiding you in understanding a research methods, taking into consideration phenomenon or object and providing insights nonverbal cues, off-the-cuff reactions, and into the more complex and subjective aspects emotional responses. of human experience.  Asking set questions in a set order can help 2. Qualitative observation is a flexible research you see patterns among responses, and it method that can be adjusted based on allows you to easily compare responses research goals and timeline. It also has the between participants while keeping other potential to be quite non-intrusive, allowing factors constant. However, they can also be observation of participants in their natural time-consuming and deceptively challenging to settings without disrupting or influencing their conduct properly. Smaller sample sizes can behavior. cause their validity and reliability to suffer, and 3. Qualitative observation is often used in there is an inherent risk of interviewer effect combination with other research methods, arising from accidentally leading questions. such as interviews or surveys, to provide a TYPES OF INTERVIEW more complete picture of the phenomenon being studied. This triangulation can help There are several types of interviews, often improve the reliability and validity of the differentiated by their level of structure. research findings. 1. Structured interviews have predetermined DISADVANTAGES OF QUALITATIVE questions asked in a predetermined order. OBSERVATIONS 1. Semi-structured interviews fall in between. 2. Unstructured interviews are more free flowing. 1. Like many observational studies, qualitative observations are at high risk for many Structured Interviews research biases, particularly on the side of  Have predetermined questions in a set order. the researcher in the case of observer bias. They are often closed-ended, featuring These biases can also bleed over to the dichotomous (yes/no) or multiplechoice participant size, in the case of the Hawthorne questions. effect or social desirability bias.  Asking set questions in a set order can help you 2. Qualitative observations are typically based see patterns among responses, and it allows you on a small sample size, which makes them to easily compare responses between very unlikely to be representative of the participants while keeping other factors larger population. This greatly limits the constant. generalizability of the findings if used as a Semi-structured Interviews standalone method, and the data collection process can be long and onerous.  Interviews have a general plan for what they 3. Like other human subject research, qualitative want to ask, the questions do not have to follow observation has its share of ethical a particular phrasing or order. considerations to keep in mind and protect,  Semi-structured interviews are often open- ended, allowing for flexibility, but follow a particularly informed consent, privacy, and predetermined thematic framework, giving a confidentiality. sense of order. For this reason, they are often INTERVIEW considered “the best of both worlds.”  Is a qualitative research method that relies on Unstructured Interview asking questions in order to collect data.  the most flexible type of interview. The questions and the order in which they are  FINDING ANSWERS THROUGH QUALITATIVE DATA COLLECTION AND DATA ANALYSIS 3 asked are not set. Instead, the interview can QUESTIONNAIRE proceed more spontaneously, based on the participant’s previous answers.  A questionnaire is a tool that contains a list of  You must be very careful not to ask leading predetermined questions. This is prepared to questions, as biased responses can lead to elicit data from the participants about the lower reliability or even invalidate your researcher's inquiry. research.  One of purpose of the questionnaire is to provide several options from which the respondents will APPROACHES IN INTERVIEW choose.  It is very much important for a questionnaire to 1. Individual Interviews are usually conducted be valid and reliable since this will be the face to face. This offers the researcher the source of data for the study. opportunity to interpret non-verbal cues through observation of body language, facial expression SUBJECT MATTER EXPERT and eye contact and thus may be seen to enhance the interviewers under- standing of  A subject-matter expert has specialist skills, what is being said. knowledge, and experience in a particular field. 2. Dyadic interviews bring together two  This skill/ knowledge/experience is acquired participants who will interact and respond to over many years, and must be open-ended questions. These two participants demonstrable and documented. have a chance to co-construct their version of  The SME must be qualified in the competencies the answer on a research topic. they practice. The SME will be continuously 3. A Focus Group brings together a group of learning, and have their expertise recognized by participants to answer questions on a topic of their industry and peers, which gives further interest in a moderated setting. Focus groups are support to their credibility. qualitative in nature and often study the group’s dynamic and body language in addition to their DATA ANALYSIS IN QUALITATIVE RESEARCH answers. Types of Qualitative Data Analysis 4. Mediated Interviews or online interview that uses a computer as their medium in data Content Analysis gathering via certain virtual platform.  A research method that examines and INTERVIEW GUIDE quantifies the presence of certain words, subjects, and concepts in text, image, video,  You need to prepare such a guide before you or audio messages. start interviewing. The interview guide serves  The method transforms qualitative input into many purposes. quantitative data to help you make reliable  Most important, it is a memory aid to ensure conclusions about what customers think of your that the interviewer covers every topic and brand, and how you can improve their obtains the necessary detail about the topic. experience and opinion. For this reason, the interview guide should contain all the interview items in the order that Narrative Analysis you have decided. A method used to interpret research  The exact wording of the items should be given, participants’ stories—things like testimonials, case although the interviewer may sometimes depart studies, interviews, and other text or visual data. from this wording. Interviews often contain some Some formats of narrative analysis don’t work for are questions that are sensitive or potentially heavily-structured interviews and written surveys, offensive. For such questions, it is vital to work out which don’t give participants as much the best wording of the question ahead of time opportunity to tell their stories in their own and to have it available in the interview. words.  FINDING ANSWERS THROUGH QUALITATIVE DATA COLLECTION AND DATA ANALYSIS 4 Discourse Analysis conversations, open-ended survey The act of researching the underlying responses, and social media posts. meaning of qualitative data. It involves the DIFFERENT APPROACHES TO THEMATIC ANALYSIS observation of texts, audio, and videos to study the relationships between the information and its Inductive approach context. In contrast to content analysis, the method Deductive Approach focuses on the contextual meaning of language: INDUCTIVE APPROACH discourse analysis sheds light on what audiences think of a topic, and why they feel the way they  Involves allowing the data to determine your do about it. themes.  The inductive approach involves deriving Grounded Theory meaning and creating themes from data without This method of analysis starts by formulating a any preconceptions. In other words, you’d dive theory around a single data case. Therefore, the into your analysis without any idea of what codes theory is “grounded’ in actual data. Grounded and themes will emerge, and thus allow these to theory analysis is a method of conducting emerge from the data. qualitative research to develop theories by For example, if you’re investigating typical lunchtime examining real-world data. conversational topics in a university faculty, you’d enter the research without any preconceived codes, themes, or expected outcomes. Of course, you may have thoughts about THEMATIC ANALYSIS what might be discussed (e.g., academic matters because it’s an academic setting), but the objective is to not let these  Good approach to research where you’re trying preconceptions inform your analysis. to find out something about people’s views, opinions, knowledge, experiences or values Best suited to research aims and questions that are from a set of qualitative. exploratory in nature and cases where there is  A qualitative data analysis method that little existing research on the topic of interest. involves reading through a data set DEDUCTIVE APPROACH e.g such as transcripts from in-depth interviews or focus groups  Involves coming to the data with some  Identifying patterns in meaning across the data preconceived themes you expect to find to derive themes. reflected there, based on theory or existing  Involves an active process of reflexivity, where a knowledge. researcher’s subjective experience plays a  Jumping into your analysis with a pre- central role in meaningmaking from data. determined set of codes. Usually, this approach is informed by prior knowledge SO WHY USE THEMATIC ANALYSIS? and/or existing theory or empirical research There are many potential qualitative analysis (which you’d cover in your literature review). methods that you can use to analyze a dataset. For example, a researcher examining the impact of a specific psychological intervention on mental health outcomes may Content Analysis, draw on an existing theoretical framework that includes Discourse Analysis, concepts such as coping strategies, social support, and self- Narrative Analysis efficacy, using these as a basis for a set of pre-determined  Thematic analysis is highly beneficial when codes. working with large bodies of data, as it allows Best suited to research aims and questions that are you to divide and categorize large amounts of confirmatory in nature and cases where there is a data in a way that makes it easier to digest. lot of existing research on the topic of interest.  Thematic analysis is particularly useful when looking for subjective information, such as a participant’s experiences, views, and opinions.  For this reason, thematic analysis is often conducted on data derived from interviews,  FINDING ANSWERS THROUGH QUALITATIVE DATA COLLECTION AND DATA ANALYSIS 5 CODING 5. Producing the report: “The final analysis; selection of vivid, compelling extract examples,  Is the process of labeling and organizing your the final analysis of selected extracts, relating to qualitative data to identify different themes and the analysis to their search question and the relationships between them. literature, producing a scholarly report of the  Coding is a qualitative data analysis strategy in analysis” (Braun & Clarke, 2006, p. 87). which some aspect of the data is assigned a o Several vital statements/features representing descriptive label that allows the researcher the data were extracted to showcase the to identify related content across the data. resulting outcomes both as statements in How you decide to code – or whether to code- the form of ideas and feelings, and visual your data should be driven by your representations drawn using methodology. interconnections between codes. PHASES OF THEMATIC ANALYSIS REFLEXIVITY as described by Braun and Clarke (2006)  There are several different goals held by 1. Data familiarization: this step involves transcribing researchers when they engage in reflexivity, the data, reading and re-reading the data, including neutralizing the influence of their and noting down the initial ideas. subjectivity, acknowledging it, explaining it, or o Major ideas were highlighted and written capitalizing on it (Gentles et al.). down for each transcript.  These purposes point to different ways 2. Generating initial code: “Coding interesting researchers might think about the relationships features of the data in a systematic fashion between their identity, context, nand research. across the entire data set, collecting data  The primary role of reflexivity has also been relevant to each code” (Braun & Clarke, 2006, p. seen as acknowledging subjectivity. 87). o While translating and transcribing, features Furthermore, reflections upon the relationship were coded as a small phrase or between ‘us’ as researchers and ‘them’ as keyword representing a specific idea. participants has drawn some attention to power Memos were written down to keep track of in research relations (Hayfield and Huxley, 25). the condensed information. Reflexivity is, however, not a natural skill but 3. Searching for themes across the data: “Collating one which can be improved by education and codes into potential themes, gathering all data training (Mortari, 25). relevant to each potential theme” (Braun & Clarke, 2006, p. 87). Pillow (2010) strongly suggests that researchers, in o The data were read and re-read, and the particular novice researchers, consistently keep cycle was repeated several times to narrow researcher logs, field notes and journals. down the number of codes and categorized them into identifiable themes. HOW DO I WRITE MY REFLEXIVE JOURNAL? o The codes were then analyzed and Rather than reporting reflexivity via a discreet grouped into four central themes as paragraph or as an apology for the researcher’s stated in the next section. influence on the data, we suggest that effective 4. Reviewing themes: “Checking if the themes work reporting should embrace researcher subjectivity in relation to the coded extracts at the first level and address the nuances of decisions throughout and then the entire data set at the second level, the research process. generating a thematic map of the analysis” (Braun & Clarke, 2006, p. 87). So instead, we recommend focusing on decisions o The complete interview data were re- and dynamics that were most impactful in the research process, highlighting personal, read to validate the codes. interpersonal, methodological, and contextual dimensions.  RESEARCH STRATEGIES NOTE: o The purpose of the experimental research strategy is to A general approach to research determined by explain the relationship by determining the underlying the kind of question that the research study hopes to cause. answer. o An experimental study is conducted with rigorous control to help ensure an unambiguous demonstration of a cause- The Descriptive Research Strategy: and-effect relationship. EXAMINING INDIVIDUAL VARIABLES THE QUASI-EXPERIMENTAL RESEARCH STRATEGY  The only strategy that focuses on individual variables. Although this strategy usually attempts to answer  This strategy intends to answer questions about the cause-and-effect questions about the relationship current state of individual variables for a specific between two variables, it can never produce an group of individuals. unambiguous explanation. However, unlike a true  The goal is to obtain a description of specific experiment, a quasi-experiment does not rely on random characteristics of a specific group of individuals. assignment. Instead, subjects are assigned to groups based on non-random criteria. NOTE: NOTE: The descriptive research strategy is not concerned with relationships between variables but rather with the description The quasi-experimental research strategy uses some of of individual variables. The goal of the descriptive strategy is to the rigor and control that exist in experiments; however, quasi- obtain a snapshot (a description) of specific characteristics of a experimental studies always contain a flaw that prevents the specific group of individuals research from obtaining an absolute cause-and- effect answer. For this example, the researcher used preexisting groups and did not control the assignment of individuals to groups. Therefore, there is no STRATEGIES THAT EXAMINE RELATIONSHIPS BETWEEN way to know whether the people in the treatment program are similar to VARIABLE those in the no- treatment program. The two groups could be very different in terms of age, income, motivation, or a variety of other variables. THE NONEXPERIMENTAL RESEARCH STRATEGY The nonexperimental research strategy is intended to demonstrate a relationship between variables, but it does not attempt to explain the relationship. In particular, this strategy does not try to produce cause-and-effect explanations. NOTE: Nonexperimental studies do not use the rigor and control that exist in experiments and in quasi-experimental studies and do not produce cause-and-effect explanations. The Correlational Research Strategy: For example, a study may demonstrate that girls have higher verbal MEASURING TWO VARIABLES FOR EACH INDIVIDUAL skills than boys, but it does not explain why the girls’ scores are higher. One technique for examining the relationship FIVE RESEARCH STRATEGIES ORGANIZED BY THE DATA between variables is to observe the two variables as they STRUCTURES THEY USE exist naturally for a set of individuals. That is, simply CATEGORY 1: Strategies that examine individual measure the two variables for each individual. variables. NOTE: DESCRIPTIVE Correlational strategy only attempts to describe the Purpose: Produce a description of individual variables relationship (if one exists); it is not trying to explain the as they exist within a specific group. relationship. For example, although there may be a relationship between Facebook Data: A list of scores obtained by measuring each time and GPA, this does not mean that limiting students’ time on individual in the group being studied. Facebook would cause them to get better grades CATEGORY 2: Strategies that examine relationships Comparing Two or More Sets of Scores: between variables by measuring two (or more) variables THE EXPERIMENTAL, QUASI-EXPERIMENTAL, AND for each participant. NONEXPERIMENTAL CORRELATIONAL THE EXPERIMENTAL RESEARCH STRATEGY Purpose: Produce a description of the relationship between two variables but do not attempt to explain  The experimental research strategy is intended to the relationship. answer cause-and-effect questions about the relationship between two variables. Data: Measure two variables (two scores) for each  To answer this question, a researcher could individual in the group being studied. create two treatment conditions by changing the amount of manipulation. CATEGORY 3: Strategies that examine relationships DATA STRUCTURES AND STATISTICAL ANALYSIS between variables by comparing two (or more) groups of scores. A. Experimental, quasi- experimental, & non- experimental studies EXPERIMENTAL All involve comparing groups of scores. The Purpose: Produce a cause-and-effect explanation for comparison involves looking for mean differences or the relationship between two variables. differences in proportions. Data: Create two treatment conditions by changing B. Correlational studies the level of one variable. Then measure a second variable for the participants in each condition Do not involve comparing different groups of scores. It measures two different variables (two different QUASI-EXPERIMENTAL scores) for each individual in a single group and then Purpose: Attempt to produce a cause-and-effect looks for patterns within the set of scores. explanation but fall short. C. Descriptive studies Data: Measure before/after scores for one group that Are intended to summarize single variables for a receives treatment and for a different group that specific group of individuals. does not receive the treatment NONEXPERIMENTAL PARAMETRIC TESTS Purpose: Produce a description of the relationship Parametric tests assume that the data follows a between two variables but do not attempt to explain specific distribution, typically a normal distribution. They the relationship. are used when certain parameters (like mean and variance) of the population are known or can be Data: Measure scores for two different groups of estimated. participants or for one group at two different times  Assumptions: RESEARCH STRATEGIES, RESEARCH DESIGNS, AND Requires assumptions about the population RESEARCH PROCEDURES distribution (e.g., normality) and homogeneity of variance. RESEARCH STRATEGY  Central Tendency:  The general approach and goals of a research study. Measures central tendency using the mean  Usually determined by the kind of question you plan to address and the kind of answer you hope  Data Type: to obtain. Suitable for continuous data and interval scales. RESEARCH DESIGNS  Sensitivity to Outliers:  It specifies whether the study will involve groups or More sensitive to outliers, which can significantly individual participants, will make comparisons affect results. within a group or between groups, and how many variables will be included in the study. NON-PARAMETRIC TESTS Determining a research design requires decisions about Non-parametric tests do not assume a specific three basic aspects of the research study: distribution for the data. They are often referred to as 1. Group versus individual. "distribution-free" tests and are useful when the  Will the study examine a group of individuals, assumptions of parametric tests cannot be met. producing an overall description for the entire  Assumptions: group, or should the study focus on a single individual? Make no assumptions about population 2. Same individuals versus different individuals. distributions; suitable for ordinal or nominal data.  Some research examines changes within the  Central Tendency: same group of individuals. Other research uses a different group of individuals for each. Measures central tendency using the median 3. The number of variables to be included.  The simplest study involves examining the  Data Type: relationship between two variables. Can handle various data types, including ordinal RESEARCH PROCEDURES and nominal scales. An exact, step-by-step description of a specific  Robustness to Outliers: research study, including a precise determination of: Generally more robust against outliers compared  Exactly how the variables will be manipulated, to parametric tests. regulated, and measured.  Exactly how many individuals will be involved.  Exactly how the individual participants or subjects will proceed through the course of the study.  Threats to Internal Validity Environmental Variables: General Threats to Internal Validity for All Studies Participant Variables: Threats to Internal Validity for Studies Comparing Different Groups  Participant variable: Personal characteristics that can differ from one individual to another.  Individual differences: The differences from one participant to another. The individuals in a research study differ on a variety of participant variables such as age, height, weight, IQ, and personality. Choosing Between Tests Time-Related Variables: Threats to Internal Validity for THE CHOICE BETWEEN PARAMETRIC AND NON- Studies Comparing One Group over Time PARAMETRIC TESTS DEPENDS ON SEVERAL FACTORS An alternative to having a different group in each Data Distribution: If data is normally distributed and meets other assumptions, parametric tests are preferred due to their higher statistical power. Sample Size: Parametric tests require larger sample sizes for reliable results. Non-parametric tests can be more appropriate for smaller samples or when data is skewed. Type of Data: treatment condition is to have the same group of For ordinal or nominal data, non-parametric tests individuals participate in all of the different treatments are more suitable as they do not rely on strict conditions. The basic problem with this type of research is distributional assumptions. that it not only compares scores obtained in different treatments but often compares scores obtained at EXTERNAL & INTERNAL VALIDITY different times. External Validity THREATS TO EXTERNAL VALIDITY The extent to which we can generalize the results Category 1: Generalizing across Participants or of a research study to people, settings, times, measures, Subjects and characteristics other than those used in that study. 1. Selection bias: The sampling procedure favors the Threats to external validity: selection of some individuals over others. 1. Generalization from a sample to the general 2. College students: Evidence is accumulating to population. suggest that many of the characteristics of college students limit the ability to generalize the results to Most research questions concern a large group of other adults. individuals known as a population. 3. Volunteer bias: Volunteers are not perfectly representative of the general population. 2. Generalization from one research study to another. 4. Participant characteristics: When a study uses As we noted earlier, each research study is a participants who share similar characteristics. unique event, conducted at a specific time and place Demographic characteristics such as gender, age, using specific procedures with a specific group of race, ethnic identity, and socioeconomic status can individuals. limit the ability to generalize the results. 5. Cross-species generalizations: External validity is also 3. Generalization from a research study to a real-world in question when research is conducted with situation. nonhumans and presumed to be readily applicable to humans. Most research is conducted under relatively controlled conditions with individuals who know that they Category 2: Generalizing across Features of a Study are participating in a research study. 1. Novelty effect: Participating in a research study is a Internal Validity novel, often exciting or anxiety-provoking experience for most individuals. In this novel situation, individuals  A research study has internal validity if it produces a may perceive and respond differently than they single, unambiguous explanation for the relationship would in the normal, real world. between two variables. 2. Multiple treatment interference: When individuals are  A threat to internal validity is any factor that allows tested in a series of treatment conditions, for an alternative explanation. participation in one condition may have an effect on the participants that carries over into the next  treatment and influences their performance or behavior. (ex. fatigue and practice) 3. Experimenter characteristics: The results of a study are demonstrated with a specific experimenter conducting the study. Category 3: Generalizing across Features of the Measures 1. Sensitization: The process of measurement, often called the assessment procedure, can alter participants so that they react differently to treatment. 2. Generality across response measures: The results of the study may be limited to that specific measurement that the researcher selects and may not generalize to other definitions or other measures. 3. Time of measurement: In a research study, the scores for individuals are measured at a specific time after (or during) the treatment. The actual effect of the treatment may decrease or increase with time. THREATS TO INTERNAL VALIDITY Extraneous Variables Any variable in a research study other than the specific variables being studied. Confounding Variables An extraneous variable (usually unmonitored) that changes systematically along with the two variables being studied. It provides an alternative explanation for the observed relationship between the two variables and, therefore, is a threat to internal validity. o EXTRANEOUS VARIABLES can introduce variability into research findings, o CONFOUNDING VARIABLES can obscure true causal relationships, complicating the interpretation of results in psychological studies. Extraneous Variable Example: In a study investigating the effects of a new educational program on student performance in psychological statistics, researchers measure test scores after the program is implemented. However, some students have access to additional tutoring outside of the program, while others do not. The availability of tutoring is an extraneous variable because it can influence students' test scores but is not part of the educational program being studied. If not controlled, this variable could lead to variability in test scores unrelated to the effectiveness of the program. Confounding Variable Example: In a research study examining the relationship between physical activity and weight loss, researchers find that individuals who exercise more tend to lose more weight. However, they fail to account for dietary habits. If individuals who exercise also tend to eat healthier diets, then diet becomes a confounding variable. It influences both the independent variable (amount of physical activity) and the dependent variable (weight loss), making it difficult to determine whether weight loss is due to increased physical activity, dietary changes, or a combination of both.