different research design ppt

Research Design PPT: Concept, Elements, Types, Need

Research design is the blueprint for a study, outlining how to collect, measure, and analyze data. It starts with defining the research question and selecting a suitable methodology, whether qualitative, quantitative, or mixed methods. A well-thought-out research design includes identifying the population, sampling methods, and data collection techniques like surveys, interviews, or experiments.

Also See: Steps In Research Process PPT Free Download

It also considers variables and how to control for them to ensure valid and reliable results. A good design minimizes biases, ensures accuracy, and helps in drawing meaningful conclusions. Essentially, it’s the plan that guides the entire research process, ensuring systematic and effective investigation.

Also See: Research Report PPT

Table of Content for Research Design PPT

• Introduction
• Characterstics of Research Design
• Main Elements of a Research Design?
• Need for Research Design
• Concepts of Research Design
• Different Types of Research Design

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Home » Research Design – Types, Methods and Examples

Research Design – Types, Methods and Examples

Table of Contents

Research Design

Definition:

Research design refers to the overall strategy or plan for conducting a research study. It outlines the methods and procedures that will be used to collect and analyze data, as well as the goals and objectives of the study. Research design is important because it guides the entire research process and ensures that the study is conducted in a systematic and rigorous manner.

Types of Research Design

Types of Research Design are as follows:

Descriptive Research Design

This type of research design is used to describe a phenomenon or situation. It involves collecting data through surveys, questionnaires, interviews, and observations. The aim of descriptive research is to provide an accurate and detailed portrayal of a particular group, event, or situation. It can be useful in identifying patterns, trends, and relationships in the data.

Correlational Research Design

Correlational research design is used to determine if there is a relationship between two or more variables. This type of research design involves collecting data from participants and analyzing the relationship between the variables using statistical methods. The aim of correlational research is to identify the strength and direction of the relationship between the variables.

Experimental Research Design

Experimental research design is used to investigate cause-and-effect relationships between variables. This type of research design involves manipulating one variable and measuring the effect on another variable. It usually involves randomly assigning participants to groups and manipulating an independent variable to determine its effect on a dependent variable. The aim of experimental research is to establish causality.

Quasi-experimental Research Design

Quasi-experimental research design is similar to experimental research design, but it lacks one or more of the features of a true experiment. For example, there may not be random assignment to groups or a control group. This type of research design is used when it is not feasible or ethical to conduct a true experiment.

Case Study Research Design

Case study research design is used to investigate a single case or a small number of cases in depth. It involves collecting data through various methods, such as interviews, observations, and document analysis. The aim of case study research is to provide an in-depth understanding of a particular case or situation.

Longitudinal Research Design

Longitudinal research design is used to study changes in a particular phenomenon over time. It involves collecting data at multiple time points and analyzing the changes that occur. The aim of longitudinal research is to provide insights into the development, growth, or decline of a particular phenomenon over time.

Structure of Research Design

The format of a research design typically includes the following sections:

• Introduction : This section provides an overview of the research problem, the research questions, and the importance of the study. It also includes a brief literature review that summarizes previous research on the topic and identifies gaps in the existing knowledge.
• Research Questions or Hypotheses: This section identifies the specific research questions or hypotheses that the study will address. These questions should be clear, specific, and testable.
• Research Methods : This section describes the methods that will be used to collect and analyze data. It includes details about the study design, the sampling strategy, the data collection instruments, and the data analysis techniques.
• Data Collection: This section describes how the data will be collected, including the sample size, data collection procedures, and any ethical considerations.
• Data Analysis: This section describes how the data will be analyzed, including the statistical techniques that will be used to test the research questions or hypotheses.
• Results : This section presents the findings of the study, including descriptive statistics and statistical tests.
• Discussion and Conclusion : This section summarizes the key findings of the study, interprets the results, and discusses the implications of the findings. It also includes recommendations for future research.
• References : This section lists the sources cited in the research design.

Example of Research Design

An Example of Research Design could be:

Research question: Does the use of social media affect the academic performance of high school students?

Research design:

• Research approach : The research approach will be quantitative as it involves collecting numerical data to test the hypothesis.
• Research design : The research design will be a quasi-experimental design, with a pretest-posttest control group design.
• Sample : The sample will be 200 high school students from two schools, with 100 students in the experimental group and 100 students in the control group.
• Data collection : The data will be collected through surveys administered to the students at the beginning and end of the academic year. The surveys will include questions about their social media usage and academic performance.
• Data analysis : The data collected will be analyzed using statistical software. The mean scores of the experimental and control groups will be compared to determine whether there is a significant difference in academic performance between the two groups.
• Limitations : The limitations of the study will be acknowledged, including the fact that social media usage can vary greatly among individuals, and the study only focuses on two schools, which may not be representative of the entire population.
• Ethical considerations: Ethical considerations will be taken into account, such as obtaining informed consent from the participants and ensuring their anonymity and confidentiality.

How to Write Research Design

Writing a research design involves planning and outlining the methodology and approach that will be used to answer a research question or hypothesis. Here are some steps to help you write a research design:

• Define the research question or hypothesis : Before beginning your research design, you should clearly define your research question or hypothesis. This will guide your research design and help you select appropriate methods.
• Select a research design: There are many different research designs to choose from, including experimental, survey, case study, and qualitative designs. Choose a design that best fits your research question and objectives.
• Develop a sampling plan : If your research involves collecting data from a sample, you will need to develop a sampling plan. This should outline how you will select participants and how many participants you will include.
• Define variables: Clearly define the variables you will be measuring or manipulating in your study. This will help ensure that your results are meaningful and relevant to your research question.
• Choose data collection methods : Decide on the data collection methods you will use to gather information. This may include surveys, interviews, observations, experiments, or secondary data sources.
• Create a data analysis plan: Develop a plan for analyzing your data, including the statistical or qualitative techniques you will use.
• Consider ethical concerns : Finally, be sure to consider any ethical concerns related to your research, such as participant confidentiality or potential harm.

When to Write Research Design

Research design should be written before conducting any research study. It is an important planning phase that outlines the research methodology, data collection methods, and data analysis techniques that will be used to investigate a research question or problem. The research design helps to ensure that the research is conducted in a systematic and logical manner, and that the data collected is relevant and reliable.

Ideally, the research design should be developed as early as possible in the research process, before any data is collected. This allows the researcher to carefully consider the research question, identify the most appropriate research methodology, and plan the data collection and analysis procedures in advance. By doing so, the research can be conducted in a more efficient and effective manner, and the results are more likely to be valid and reliable.

Purpose of Research Design

The purpose of research design is to plan and structure a research study in a way that enables the researcher to achieve the desired research goals with accuracy, validity, and reliability. Research design is the blueprint or the framework for conducting a study that outlines the methods, procedures, techniques, and tools for data collection and analysis.

Some of the key purposes of research design include:

• Providing a clear and concise plan of action for the research study.
• Ensuring that the research is conducted ethically and with rigor.
• Maximizing the accuracy and reliability of the research findings.
• Minimizing the possibility of errors, biases, or confounding variables.
• Ensuring that the research is feasible, practical, and cost-effective.
• Determining the appropriate research methodology to answer the research question(s).
• Identifying the sample size, sampling method, and data collection techniques.
• Determining the data analysis method and statistical tests to be used.
• Facilitating the replication of the study by other researchers.
• Enhancing the validity and generalizability of the research findings.

Applications of Research Design

There are numerous applications of research design in various fields, some of which are:

• Social sciences: In fields such as psychology, sociology, and anthropology, research design is used to investigate human behavior and social phenomena. Researchers use various research designs, such as experimental, quasi-experimental, and correlational designs, to study different aspects of social behavior.
• Education : Research design is essential in the field of education to investigate the effectiveness of different teaching methods and learning strategies. Researchers use various designs such as experimental, quasi-experimental, and case study designs to understand how students learn and how to improve teaching practices.
• Health sciences : In the health sciences, research design is used to investigate the causes, prevention, and treatment of diseases. Researchers use various designs, such as randomized controlled trials, cohort studies, and case-control studies, to study different aspects of health and healthcare.
• Business : Research design is used in the field of business to investigate consumer behavior, marketing strategies, and the impact of different business practices. Researchers use various designs, such as survey research, experimental research, and case studies, to study different aspects of the business world.
• Engineering : In the field of engineering, research design is used to investigate the development and implementation of new technologies. Researchers use various designs, such as experimental research and case studies, to study the effectiveness of new technologies and to identify areas for improvement.

Advantages of Research Design

Here are some advantages of research design:

• Systematic and organized approach : A well-designed research plan ensures that the research is conducted in a systematic and organized manner, which makes it easier to manage and analyze the data.
• Clear objectives: The research design helps to clarify the objectives of the study, which makes it easier to identify the variables that need to be measured, and the methods that need to be used to collect and analyze data.
• Minimizes bias: A well-designed research plan minimizes the chances of bias, by ensuring that the data is collected and analyzed objectively, and that the results are not influenced by the researcher’s personal biases or preferences.
• Efficient use of resources: A well-designed research plan helps to ensure that the resources (time, money, and personnel) are used efficiently and effectively, by focusing on the most important variables and methods.
• Replicability: A well-designed research plan makes it easier for other researchers to replicate the study, which enhances the credibility and reliability of the findings.
• Validity: A well-designed research plan helps to ensure that the findings are valid, by ensuring that the methods used to collect and analyze data are appropriate for the research question.
• Generalizability : A well-designed research plan helps to ensure that the findings can be generalized to other populations, settings, or situations, which increases the external validity of the study.

Research Design Vs Research Methodology

About the author.

Muhammad Hassan

Researcher, Academic Writer, Web developer

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Guide to Research Methods

About the guide

This guide will

• Introduce you to a range of research methods
• Help you think about the value and limitations of different research methods
• Identify when to use alternative research methods

You should use the guide

• After or while you establish your research questions (See the Guide to Research Questions )
• When you are completing your Research Design Framework
• When you are thinking about who you want to talk to and why (See the Guide to Sampling )

You should print or read this guide

These slides are set up so that they can be printed back to back (two/four sided) to give:

• A short hand overview about when to use each method
• A summary of the method, what it’s good for and limitations (linking to other slides in this pack)

Choosing research methods

When you need to think about which method is best in theory and in practice

Choosing Research Methods

Providing a rationale for the methods you choose to use and how you employ them.

• What are your research goals? If you are looking to influence experts or policy makers, quantitative approaches will add weight to your findings. If you are looking to understand problems, inform innovation or develop a prototype, look at qualitative methods or user research
• What are your research questions? If they begin with ‘explore’ or ‘what’ look at qualitative methods (talking). If they begin with ‘identify’ or ‘why’ look at quantitative (see guide to research questions )
• What research traditions exist? You may choose to follow or challenge them. Think about whether you want your research to be noted for its quality and robustness or creative approach and unique insights
• What are your/your teams skills? You may not be an expert in the most appropriate method so consider asking for other team members or commissioning out research
• Who are you research participants? Think about your relationship to participants (especially if you are doing qualitative research) and how they will respond to you and the method. Consider if they are often consulted or surveyed and whether if could be helpful or unhelpful to stick with their comfort zone or not.

Using online tools

When you need to decide which tools to use for research

What to think about when choosing a tool to conduct research

• What’s the cost to the research quality ? Most tools are ‘freemium’, use a basic version for free. BUT these are designed to annoy you to pay to do good research. Consider privacy settings, data access, storage and value for money. Survey tools will have no option to filter participants (if yes/no answer this q), a 10Q limit, no branding. Mapping/visualisations are published online and open source tools aren’t always user friendly
• Start with user needs, understand the context and think about everyone. Consider what technology they have, how they will access the tool and what they need to do this. Do they have internet, data, time?
• Be creative: Online tools may not be designed for research, but Google Forms, Trello, Workflowy and Slack are all valuable collaboration tools. Twitter and Facebook polls may increase participation in research. However, think about what they are missing, what they can’t do and pilot your analysis approach first
• See what’s out there: This online sheet of Applied Social Research Guides and Resources includes a list of online tools for research and evaluation to test. Those widely used for your research method or sector are likely to be the best starting point. Some tools allow you to do research (see Tags for Twitter data capture), analyse it or present it in new ways (see Raw Graph s for data visualisation)

Contents: Methods summary

• Structured Interviews : When you want to gain a broad range of perspectives about specific questions
• Semi-Structured Interviews : When you want to gain in-depth insights about broad questions
• Unstructured Interviews : When you want to gain in-depth insights about a complex research topics
• Telephone Interviews : A tool for when you want to interview people quickly and easily
• Guerilla Interviews : When you want to carry out user research or explore general perspectives quickly
• Contextual Interviews : When you want to understand actions and particular experiences indepth and in context
• Focus Groups : When you want to understand shared experiences and different perspectives
• Participant Observation : When you want to ‘learn by doing’ or observe social interactions and behaviour
• Ethnography : When you want to experience social practices, interactions and behaviour with minimal influence
• Surveys: When you want to generate numerical data about the scale of people’s opinions and feelings
• Mixed Methods: When one method cannot fully answer your main research question
• User Research : When you want to learn about the behaviours and motivations of your target audience
• Service Design Research : When you want to design a service to meet people’s needs.
• Content Analysis : When you want to understand public discourse through secondary or online data
• Workshops : When you want to engage stakeholders in research, generate ideas or codesign solutions
• Usability tests : When you want to test prototypes or learn about problems with an existing service

Find out more

How to do good…

• Applied social research: A curated online sheet of Applied Social Research Guides and Resources
• Surveys : Guide to creating questions here and here , build on existing data/questions , analysis guide
• Interviews : A nice overview here which includes how to structure an interview
• User research : The GDS for intro guides and DisAmbiguity blog
• Service design: This is Service Design Doing has great tools and formats for workshops

Inspiration for emerging research methods and creative formats for research

• Ethnography and mixed methods presented well: Ikea At Home Report
• User mapping techniques as a social research method NPC Report
• User Research to understand domestic abuse experiences and the potential for technology Tech Vs Abuse
• Using Twitter data for social research Demos
• Data visualisation as a tool for research communication - Nesta data visualisation and Women’s Aid Map
• Data journalism and data storytelling - Guardian reading the riots
• An online games to shift perspective on a social problem - Financial Times Uber Story
• Content analysis to map trends - Nesta analysed creative skills in job adverts
• Issue mapping online - networks of websites and people on Twitter - Warwick University Issue Mapping

Structured Interviews

When you want to gain a broad range of perspectives about specific questions

Also consider

Semi-structured interviews

A conversation with a set structure (a script of fixed questions) and specific purpose. Can be a method to undertake a survey or called a ‘directed’ interview.

• Asking standardised questions across many participants makes data easier to analyse and compare
• Giving participants a clear guide about what you want to learn from them
• Topics that would be too complex to capture in a questionnaire tick box/short response
• Respondents with limited time, who want to consider responses in advance or do not want to write
• The quality of the interview is less dependent on the interviewer and their rapport with the interviewee

Limitations (and how to avoid or what to consider instead)

• The structure prevents participants from bringing in other ideas (consider semi-structured interviews )
• Whilst quicker to conduct and analyse than semi-structured interviews, they are still resource intensive and only possible to do with limited numbers of people (consider questionnaires online - see surveys )

Semi-Structured Interviews

When you want to gain in-depth insights about broad questions

Participant Observation

User research

Focus groups

Semi-Structured interviews

Conversation with a structure (set of open questions) and clear purpose. Also called directed interviews.

• Exploring a range of perspectives on research questions, engaging experts and getting buy-in to research
• Gaining in-depth insights about how people feel or interpret complex issues
• Topics which are sensitive, difficult to express in writing or to articulate views about in a survey
• Allowing participants to respond in their words, framing what they see as important

Limitations

• Quality can depend on interviewer skills and put people on the spot (consider setting topics in advance)
• The set-up affects the quality of engagement and discussion (consider location, relationship with the interviewee and whether you should do a face to face or Telephone/Online interview )
• Time consuming to do, analyse and compare (consider Structured Interviews or Focus groups )
• Can lack validity as evidence (consider Surveys )
• Explore what people say, think and remember, not what they actually do (consider Participant Observation contextual interviews or User Research ) or shared perspectives (consider Focus groups )
• Easy to provide too much structure and prevent open exploration of a topic (see unstructured interviews )

Unstructured Interviews

When you want to gain in-depth insights about a complex research topics

Contextual interviews

Unstructured interviews

A loosely structured open conversation guided by research topics (also called non-directed interviews)

• Very exploratory research and broad research questions
• Letting the participant guide the interview according to their priorities and views
• In-depth and broad discussion about a person's expertise, experiences and opinions
• Participant can feel like the they are not saying the ‘right’ thing (explain technique and rationale well)
• Whilst useful for expert interviews, an unstructured approach can give the impression that the interviewer is unprepared, lacks knowledge or the research purpose is unclear (consider semi-structured interviews )
• Interviews are longer, resource intensive and only smaller numbers are possible (consider focus groups )
• Generates in-depth insights that are difficult to analyse and compare
• A lack of structure can encourage participants to focus in-depth on one thing they are positive about or know very well in-depth (consider using desk research to inform the interview topics)

Guerilla Interviews

When you want to carry out user research or explore general perspectives quickly and easily

An ‘impromptu’ approach to interviewing, often talking to real people on the street or at a key site

• Gaining immediate responses to a tool or design and insights into a problem
• Informal method means participants can be more relaxed and open
• Speaking to a lot of people, simply, quickly and cheaply about one key question
• User research and user experience of interacting with digital products
• Speaking to people for convenience (users are available in a single place and time) introduces sample bias (but you can add more targeting and profiling of participants, see the Guide to Sampling )
• The lack of formal structure can mean that you miss important questions or insights
• Findings are often unreliable and not generalisable because they rely on a single type of user
• Difficult to understand complexity or gain contextual insights

Telephone / online interviews

A tool for when you want to interview people quickly and easily

Telephone or Online interviews

A tool to conduct an interview (it is not a method in itself) which is not in person/ face to face

• Conducting interviews without the costs of travel and meeting time (often shorter)
• Expert and stakeholder interviews, when you already know the participant well or they are short of time
• Taking notes and looking up information whilst interviewing is less disruptive than in person, easy to record
• Sending informed consent information and interview questions in advance
• Can be difficult to undertake an engaging interview (hard to build rapport on the phone)
• Often need to be shorter and put alongside other meetings

What method are you using?

• Structured interviews : When you want to gain a broad range of perspectives about specific questions
• Semi-structured interviews : When you want to gain in-depth insights about broad questions
• Unstructured interviews : When you want to gain in-depth insights about a complex research topics

Further guides to Interviews : A nice overview here , including how to structure an interview

Contextual Interview

When you want to understand actions and particular experiences in-depth and in context

Ethnography

Interviews conducted with people in a situational context relevant to the research question; also known as contextual inquiry.

• Understanding what happens, experiences and emotions whilst interacting with a tool, service or event.
• Easier for research participants to show rather than explain, participants are active and engaged
• Uncover what happens, what people do, how they behave in the moment, rather than how they remember this and give meaning to these responses later.
• Open and flexible method giving depth of insights about a tool or specific interaction
• Time and resource intensive for the researcher
• Each context is unique - making it difficult to generalise from or to answer broader research questions about experiences (consider semi-structured interviews )
• The researcher influences the interactions and events (consider ethnography or participant observation )

When you want to understand shared experiences and different perspectives

Focus Groups

An organised discussion with a group of participants, led by a facilitator around a few key topics

• Gaining several perspectives about the same topic quickly
• Research contexts and topics where familiarity between participants can generate discussion about similar experiences (or different ones) which may not arise in a one to one interview
• When attitudes, feelings and beliefs are more likely to be revealed in social gathering and interactions
• Including tasks and creative methods to elicit views (e.g. shared ranking of importance of statements)
• Difficult to identify the individual view from the group view (consider semi-structured interviews )
• Group dynamics will affect the conversation focus and participation levels of different members
• The role of the moderator is very significant. Good levels of group leadership and interpersonal skill are required to moderate a group successfully.
• The group set-up is an ‘artificial’ social setting and discussion (consider Participant Observation )

Participant observation

When you want to ‘learn by doing’ and observe social interactions and behaviour

Participant observation/ shadowing

The researcher immerses themselves in lives of participants as an ‘observer’ of their behaviours, practices and interactions. A type of ethnography. The people being observed know about the research.

• Understanding everyday behaviours, interactions and practice in the context that they occur
• Gaining an intuitive understanding of what happens in practice and what this means for those involved
• Allowing research participants to show you what they do, when they can’t describe and remember this well
• Establishing topics for further investigation through more structured or focused research methods
• If explicit (shadowing for example) the research situation is still ‘artificial’
• Your audience may not respect it and can be difficult to generalise from (consider mixed methods)
• The quality of the data is dependent on the researchers’ skills and relationships with participants

When you want to experience social practices, interactions and behaviour with minimal influence on what happens

The systematic study of a group of people or cultures to understand behaviours and interactions. The researcher becomes an ‘insider’. It is a way of presenting research findings, as well as a method, which can include participant observation, document analysis and visual methods.

• When you need to be an ‘insider’ to fully access the research context (such as organisational cultures)
• Presenting how everyday behaviours, interactions and practice occur in context
• Gaining an in-depth knowledge of your research context, participants and social relationships
• When little is known about a research context or topic
• If covert (at a conference or workplace for example) it has implications for informed consent
• If explicit (shadowing for example) the researcher’s presence can affect the interactions and findings

Example use case : Ikea At Home research study to understand how people feel about their home

When you want to generate numerical data about the scale of people’s opinions and feelings

Mixed Methods

A process of systematically collecting information from a large number of different people. Responses are summarised as statistics (online surveys automate this analysis for you).

• Targeting specific types of research participant and providing data about their views
• If designed well, they can be quick, simple and non intrusive for research participants
• Findings can have more credibility than other methods because of their breadth
• Describing, measuring and understanding (a basic questionnaire)
• Statistical analysis, modelling cause and effect (large scale survey designed to represent the population)
• Can raise more questions about what happens and why, lack depth of insight (consider mixed methods )
• Hard to design well and require a lot of time upfront and data skills to analyse the results
• Low completion rates and people feel ‘over surveyed’ (consider incentives )
• Assumes people will be honest and sufficiently aware of the research context to provide credible answers.

Further information: A great guide to creating questions here and here , build on existing data/questions here

When one research method cannot fully answer your main research question

Mixed methods

Combining different methods to answer your research questions, can be a mix of quantitative or qualitative methods or both. It may mean working with different types of data, research designs or being part of a research team (covering different research disciplines)

• Overcoming the limitation of relying on a single research method or approach
• Triangulating findings (i.e. using an additional method) can give them more validity
• Accessing different types of research participants
• A more holistic understanding about how, why and the extent to which something happens
• Answering different types of research questions about frequency and perceptions
• Giving findings more validity and influence because of the range of data and insights
• Requires a broader range of skills and more time to deliver, analyse and report on
• Research design must have strong sequencing (when each method is used and analysed , why) to make the most of a mixed methods approach - not always possible in a tight timescale or short research project

User Research

When you want to learn about people’s needs, behaviours and motivations for using a service

Service Design

S emi-Structured Interviews

Usability testing

A research approach employed to understand users and their needs, motivations and behaviours, primarily to inform service design.

• User-centered design processes which look to ensure services meet the needs of their audience
• Gaining specific insights into how a person interacts with a digital tool or service
• Exploring general needs, behaviours and motivations for a specific target group using a range of services
• Focus on a tool or service can prevent wider analysis, relevance and applicability
• Research can lack credibility due to small numbers, set up, documentation (often highly specific focus)
• Can overlook those who do not use a service for a whole range of reasons

What method?

• User research involves any method which looks at who users are, the problems they face, what they are trying to do and how they use existing services. This can create user personas, user journeys and user experience maps. It largely includes qualitative research methods.

When you want to design a service to meet people’s needs, including planning, organising, infrastructure, communication and components)

A research approach employed in the activity of planning and organising of people, infrastructure, communication and material components of a service, in order to improve quality and interaction.

• Gaining a holistic picture of all components (infrastructure, people, organisations, culture) affecting how a person interacts with a service
• Service design often begins with user research but participants in research include all those involved in delivering (not just using) a service, such as employees and stakeholders in an organisation as well as looking at the context and system which affect how a service works and its effectiveness

Content analysis

When you want to understand public discourse through secondary or online data

A systematic process of classifying and interpreting documents, text or images to analyse key discourses (their meaning) or to quantify patterns (such as word frequencies). This can be done manually or it can be automated.

• Exploring the focus of messages, text or imagery and change over time
• Secondary data sources, such as archives, online social media data (such as Tweets) and news articles
• Gaining a qualitative or quantitative insights about key messages
• Focuses on public and documented interpretations of events and experiences
• Documents are not exhaustive and not all are accessible (or available online/freely)
• Qualitative coding is time intensive to manually classify, reliant on researcher interpretation
• Automated coding for key words can miss nuances and difficult to produce meaningful findings

When you want to engage stakeholders in research, generate ideas or codesign solutions

Also consider:

A tool to undertake research. It is an interactive session, often taking a full day, in which research participants sor stakeholders work intensively on an issue or question. The process can combine elements of qualitative research, brainstorming or problem solving.

• Engaging stakeholders - building empathy with and understanding of research findings
• Understanding problems or prototyping solutions, linked to user research and service design approaches
• Participatory research, allowing participants to shape agendas and outcomes
• Creative, collaborative and engaging activities to build rapport and understanding with participants
• Participatory design, enabling participants to co-design solutions which work for them
• Highly dependent on the right people attending and the facilitation skills
• Can be a lot of time and effort to coordinate a workshop effectively and analyse findings
• The immersive and collaborative environment makes it difficult to document effectively
• Collaborative solutions may duplicate existing problems or solutions

When you want to test prototypes or learn about problems with an existing service

A user research method where you watch participants try to complete specific tasks using your service. Moderated testing involve interaction with the research participant, asking them to explain what they are doing, thinking and feeling. Unmoderated testing is completed alone by the participant.

• Identify any usability issues with a digital service - for example, problems with the language or layout
• Seeing if users understand what they need to do in order to complete designated tasks
• Generating ideas to improve a prototype of existing digital service
• Assessing user experience
• Focus is not on ‘natural’ use (consider contextual interviews , participant observation , ethnography )
• Data is about a specific design and interaction with a tool at that moment
• Findings cannot be generalised or applicable more broadly to understand users and behaviours

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RESEARCH DESIGN.

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The Research Process step 6: Elements of Research Design

Apr 08, 2012

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The Research Process step 6: Elements of Research Design. CHAPTER 6. Chapter Objectives. Understand the different aspects relevant to designing a research study. Identify the scope of any given study and the end use of the results.

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• causal study question
• normal course
• case study analysis
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The Research Processstep 6: Elements of Research Design CHAPTER 6

Chapter Objectives • Understand the different aspects relevant to designing a research study. • Identify the scope of any given study and the end use of the results. • Describe the type of investigation needed, the study setting, the extent of researcher interference, the unit of analysis, and the time horizon of the study. • Identify which of the two, a causal or a correlational study, would be more appropriate in a given situation.

The Research Design • In this step we need to design the research in a way that the requisite data can be gathered and analyzed to arrive at a solution. • The research design was originally presented in a simple manner in box 6 of Figure 6.1.

Figure 6.2: The Various Issues Involved in the Research Design

Purpose of The Study The Nature of Studies: • Exploratory Study • Descriptive Study • Hypothesis Testing (Analytical and Predictive) • Case Study Analysis

Exploratory Study • Exploratory Study is undertaken when not much is known about the situation at hand, or no information is available on how similar problems or research issues have been solved in the past.

Example 6.1 • The manager of a multinational corporation is curious to know if the work ethic values of employees working in Prince Hassan Industrial City would be different from those of Americans. That city is a small city, and no information about the ethic values of its workers. Also, the work ethic values mean be different to people in different cultures.

Example 6.1 (Cont.) • The best way to study the above situation is by conducting an exploratory study, by interviewing the employees in organizations in Irbid area.

Descriptive Study • Is undertaken in order to ascertain and be able to describe the characteristics of the variables of interest in a situation. • For instance, a study of a the Research Methods 200 class in terms of the percentage of members who are in their senior ( will be in the graduation stage), sex composition, age groupings, number of semesters left until graduation, can be considered as descriptive in nature.

Descriptive Study • In addition, descriptive studies are undertaken in organizations to learn about and describe the characteristics of a group of employees, as for example, the age, education level, job status, and length of service.

Example 6.2 • A bank manager wants to have a profile of the individuals who have loan payments outstanding for 6 months and more. This profile would include details of their average age, earnings, nature of occupation, full-time/ part-time employment status, and the like. The above information might help the manager to decide right away on the types of individuals who should be made ineligible for loans in the future.

Example 6.4 • A marketing manager might want to develop a pricing, sales, distribution, and advertising strategy for his product. The manager might ask for information regarding the competitors, with respect to the following: 1. the percentage of companies who have prices higher and lower than the industry norm. 2. the percentage of competitors hiring in-house staff to handle sales and those who use independent agents.

Example 6.4 (Cont.) 3. percentage of sales groups organized by product line, by accounts, and by region. 4. the types of distribution channels used and the percentage of customers using each. 5. percentage of competitors spending more dollars on advertising/promotion than the firm and those spending less. 6. Percentage of those using the web to sell the product.

Hypotheses Testing • Studies that engage in hypotheses testing usually explain the nature of certain relationships, or establish the differences among groups or the independence of two or more factors in a situation. • Hypotheses testing is undertaken to explain the variance in the dependent variable or to predict organizational outcomes.

Example 6.5 • A marketing manager wants to know if the sales of the company will increase if he doubles the advertising dollars. • Here, the manager would like to know the nature of the relationship between advertising and sales by testing the hypothesis: If advertising is increased, then sales will also go up.

Case Study Analysis • Case studies involve in-depth, contextual analyses of matters relating to similar situations in other organizations. • Case studies, as a problem solving technique, are not frequently resorted to in organizations because findings the same type of problem in another comparable setting is difficult due to the reluctance of the companies to reveal their problems.

Case Study Analysis • Case studies that are qualitative in nature are, however, useful in applying solutions to current problems based on past problem-solving experiences. • Also, case studies are useful in understanding certain phenomena, and generating further theories for empirical testing.

Type of Investigation: Causal versus Correlational • A causal study: Is an inquiry to know the cause of one or more problems. • A correlational study: Is an inquiry to know the important variables associated with the problem.

Example 6.9 • A causal study question: Does smoking cause cancer? • A correlational study question: Are smoking and cancer related? Or Are smoking, drinking, and chewing tobacco associated with cancer? If so, which of these contributes most to the variance in the dependent variable?

Example 6.10 • Fears of an earthquake predicted recently in an area were a causal of a number of crashes of some houses in the area in order to be eligible of insurance policy.

Example 6.11 • Increases in interest rates and property taxes, the recession, and the predicted earthquake considerably slowed down the business of real state agents in the country.

Extent of Researcher InterferenceWith the Study • The extent of interference by the researcher with the normal flow of work at the workplace has a direct bearing on whether the study undertaken is causal or correlational.

Extent of Researcher InterferenceWith the Study • A correlational study is conducted in the natural environment of the organization with minimum interference by the researcher with the normal flow of work.

Extent of Researcher InterferenceWith the Study • In studies conducted to establish cause-and-effect relationships, the researcher tries to manipulate certain variables so as to study the effects of such manipulation on the dependent variable of interest. • In other words, the researcher deliberately changes certain variables in the setting and interferes with the events as they normally occur in the organization.

Minimal Interference Example 6.12 • A hospital administrator wants to examine the relationship between the perceived emotional support in the system and the stress experienced by the nursing staff. In other words, she wants to do a correlational study.

Example 6.12 (Cont.) • The researcher will collect data from the nurses ( through a questionnaire) to indicate how much emotional support they get in the hospital and to what extent they experience stress. By correlating the two variables, the answer is found. • In this case, beyond administering a questionnaire to the nurses, the researcher has not interfered with the normal activities in the hospital.

Moderate Interference • If the researcher wants to establish a causal connection between the emotional support in the hospital and stress, or, wants to demonstrate that if the nurses had emotional support, this indeed would cause them to experience less stress.

Moderate Interference • To test the cause-and-effect relationship, the researcher will measure the stress currently experienced by the nurses in three wards in the hospital, and then deliberately manipulate the extent of emotional support given to the three groups of nurses in the three wards for perhaps a week, and measure the amount of stress at the end of that period.

Moderate Interference • For one group, the researcher will ensure that a number of lab technicians and doctors help and comfort the nurses when they face stressful events. • For a second group of nurses in another ward, the researcher might arrange for them only a moderate amount of emotional support and employing only the lab technicians and excluding doctors.

Moderate Interference • The third ward might operate without any emotional support. • If the experimenter’s theory is correct, then the reduction in the stress levels before and after the 1-week period should be greater for the nurses in the first ward, moderate for those in the second ward, and nil for the nurses in the third ward.

Moderate Interference • We find that not only does the researcher collect data from nurses on their experienced stress at two different points in time, but also manipulated the normal course of events by deliberately changing the amount of emotional support received by the nurses in two wards, while leaving things in the third ward unchanged. • Here, the researcher has interfered more than minimally.

Excessive Interference Example 6.14 • IF the researcher feels, after conducting the previous experiments, that the results may not be valid since other external factors might have influenced the stress levels experience by the nurses. • For example, during that particular experimental week, the nurses in one or more wards may not have experienced high levels of stress because there were no serious illnesses or deaths in the ward. Hence the emotional support received might not be related to the level of stresses experienced.

Excessive Interference • The researcher want to make sure that such external factors that might affect the cause-and-effect relationship are controlled.

Controlling the External factors • The researcher might take three groups of medical students, put them in different rooms, and confront all of them with the same stressful task. • For example, he might ask them to describe in detail, the surgical procedures in performing surgery on a patient who has not responded to chemotherapy and keep asking them with more and more questions.

Controlling the External factors • Although all are exposed to the same intensive questioning, one groupmight get help from a doctor who voluntarily offers clarifications and help when students stumble. • In the second group, a doctor might be nearby, but might offer clarifications and help only if the group seeks it. • In the third group, there is no doctor present and no help is available.

Controlling the External factors • In the above example, not only is the support manipulated, but even the setting in which this experiment is conducted is artificial inasmuch as the researcher has taken the subject away from their normal environment and put them in a totally different setting. • The researcher has intervened maximally with the normal setting, the participants, and their duties.

Excessive Interference • The extent of researcher interference would depend on whether the study is correlational or causaland also the importance of establishing causal relationship beyond any doubt. • Most organizational problems seldom call for a causal study, except in some market research areas.

Study Setting: Contrived and Noncontrived • Correlational studies are conducted in noncontrived settings (normal settings), whereas most causal studies are done in contrived settings. • Correlational studies done in organizations are called field studies.

Study Setting: Contrived and Noncontrived • Studies conducted to establish cause-and-effect relationship using the same natural environment in which employees normally function are called field experiments. • Experiments done to establish cause-and- effect relationship in a contrived environment and strictly controlled are called lab experiments.

Example 6.15 Field Study • A bank manager wants to analyze the relationship between interest rates and bank deposit patterns of clients. The researcher tries to correlate the two by looking at deposits into different kinds of accounts (such as savings, certificates of deposit, and interest-bearing checking accounts) as interest rates changed.

Example 6.15 Field Study • This is a field study where the bank manager has taken the balances in various types of accounts and correlated them to the changes in interest rates. • Research here is done in a noncontrived setting with no interference with the normal work routine.

Example 6.16 Field Experiment • The bank manager now wants to determine the cause-and-effect relationship between interest rate and the inducements it offers to clients to save and deposit money in the bank. The researcher selects four branches within 60/km radius for the experiment.

Example 6.16 Field Experiment • For 1 week only, he advertises the annual rate for new certificates of deposit received during that week. The interest rate would be 9% in one branch, 8% in another, and 10% in the third. In the fourth branch, the interest rate remains unchanged at 5%. Within the week, the researcher would be able to determine the effects, if any, of interest rates on deposit mobilization.

Example 6.16 Field Experiment • This example would be a field experiment since nothing but the interest rate is manipulated, with all activities occurring in the normal and natural work environment. • Hopefully, all four branches chosen would be compatible in size, number of depositors, deposit patterns, and the like, so that the interest-savings relationships are influenced by some third factor.

Example 6.17 Lab Experiment • To be sure about the true relationship between the interest rate and deposits, the researcher could create an artificial environment by choosing, for instance, 40 students who are all business majors in their final year of study and in the same age. The researcher splits the students into four groups and give each one of them $1000, which they are told they might buy their needs or save for the future, or both.

Example 6.17 Lab Experiment The researcher offers them interest on what they save as followings: • 6% on savings for group 1. • 8% for group 2. • 9% for group 3. • 1% for group 4 ( the old rate of interest). Here, the researcher has created an artificial laboratory environment and has manipulatedthe interest rates for savings. He also chosen subjects with similar backgrounds.

Unit of Analysis • The unit of analysis refers to the level of aggregation of the data collected during the subsequent data analysis. • Individual • Dyads • Groups • Organizations • Cultures

Unit of Analysis: Individual • If the researcher focuses on how to raise the motivational levels of employees, then we are interested in individual employees in the organization. Here the unit of analysis is the individual (the data will be gathered from each individual).

Unit of Analysis: Dyads • If the researcher is interested in studying two-person interaction, then several two-person groups also known as dyads, will become the unit of analysis ( analysis of husband-wife, and supervisor-subordinate relationships at the work place.

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Types of research design

Types of research design experiments chapter 8 in babbie & mouton (2001) introduction to all research designs all research designs have specific objectives they ... – powerpoint ppt presentation.

• Chapter 8 in Babbie Mouton (2001)
• Introduction to all research designs
• All research designs have specific objectives they strive for
• Have different strengths and limitations
• Have validity considerations
• When we say that a knowledge claim (or proposition) is valid, we make a JUDGEMENT about the extent to which relevant evidence supports that claim to be true
• Is the interpretation of the evidence given the only possible one, or are there other plausible ones?
• "Plausible rival hypotheses" potential alternative explanations/claims
• e.g. New York City's "zero tolerance" crime fighting strategy in the 1980s and 1990s - the reverse of the "broken windows" effect
• Explanatory rather than descriptive
• Different from correlational research - one variable is manipulated (IV) and the effect of that manipulation observed on a second variable (DV)
• "Animals respond aggressively to crowding" (causal)
• "People with premarital sexual experience have more stable marriages" (noncausal)
• Independent and dependent variables
• Pre-testing and post-testing
• Experimental and control groups
• Dependent (DV)
• Independent (IV)
• To off-set the effects of the experiment itself to detect effects of the experiment itself
• The IV is an active variable it is manipulated
• The participants who receive one level of the IV are equivalent in all ways to those who receive other levels of the IV
• 1. Selecting subjects to participate in the research
• Careful sampling to ensure that results can be generalized from sample to population
• The relationship found might only exist in the sample need to ensure that it exists in the population
• Probability sampling techniques
• 2. How the sample is divided into two or more groups is important
• to make the groups similar when they start off
• randomization - equal chance
• matching - similar to quota sampling procedures
• match the groups in terms of the most relevant variables e.g. age, sex, and race
• One-shot case study
• No real comparison
• Milgram's study on obedience
• Obedience to authority
• The willingness of subjects to follow E's orders to give painful electrical shocks to another subject
• A real, important issue here how could "ordinary" citizens, like many Germans during the Nazi period, do these incredibly cruel and brutal things?
• If a person is under allegiance to a legitimate authority, under what conditions will the person defy the authority if s/he is asked to carry out actions clearly incompatible with basic moral standards?
• We want to find out whether a family literacy programme enhances the cognitive development of preschool-age children.
• Find 20 families with a 4-year old child, enrol the family in a high-quality family literacy programme
• Administer a pretest to the 20 children - they score a mean of say 50 on the cognitive test
• The family participates in the programme for twelve months
• Administer a post-test to the 20 children now they score 75 on the test - a gain of 25
• 1 The children gained 25 points on average in terms of their cognitive performance
• 2 the family literacy programme caused the gain in scores
• VALIDITY - rival explanations
• We know the structure of research
• We understand designs
• We know the requirements of "good" research
• Then we can evaluate a study
• Is it good? Can we believe its conclusions?
• Back to plausible rival hypotheses
• If the design is not valid, then the conclusions drawn are not supported it is like not doing research at all
• Validity of designs come in two parts
• Internal validity
• can the design sustain the conclusions?
• External validity
• can the conclusions be generalized to the population?
• Each design is only capable of supporting certain types of conclusions
• e.g. only experiments can support conclusions about causality
• Says nothing about if the results can be applied to the real world (generalization)
• Generally, the more controlled the situation, the higher the internal validity
• The conclusions drawn from experimental results may not accurately reflect hat has gone on in the experiment itself
• These sources often discussed as part of experiments, but can be applied to all designs (e.g. see reactivity)
• Historical events may occur that will be confounded with the IV
• Especially in field research (compare the control in a laboratory, e.g. nonsense syllables in memory studies
• Changes over time can be caused by a natural learning process
• People naturally grow older, tired, bored, over time
• People realize they are being studied, and respond the way they think is appropriate
• The very act of studying something may change it
• In qualitative research, the "on stage" effects
• Improved performance because of the researcher's presence - people became aware that they were in an experiment, or that they were given special treatment
• Especially for people who lack social contacts, e.g. residents of nursing homes, chronic mental patients
• When a person expects a treatment or experience to change her/him, the person changes, even when the "treatment" is know to be inert or ineffective
• Medical research
• "The bedside manner", or the power of suggestion
• Pygmalion effect - self-fulfilling prophecies of e.g. teachers' expectancies about student achievement
• Experimenters may prejudge their results - experimenter bias
• Double blind experiments
• Both the researcher and the research participant are "blind" to the purpose of the study.
• They don't know what treatment the participant is getting
• Instruments with low reliability lead to inaccurate findings/missing phenomena
• e.g. human observers become more skilled over time (from pretest to posttest) and so report more accurate scores at later time points
• Studying extreme scores can lead to inflated differences, which would not occur in moderate scorers
• Selection subjects for the study, and assigning them to E-group and C-group
• Look out for studies using volunteers
• Sometimes called experimental (or subject) mortality
• If subjects drop out, it creates a bias to those who did not
• e.g. comparing the effectiveness of family therapy with discussion groups for treatment of drug addiction
• addicts with the worst prognosis more likely to drop out of the discussion group
• will make it look like family therapy does less well than discussion groups, because the "worst cases" were still in the family therapy group
• When subject can communicate to each other, pass on some information about the treatment (IV)
• In real life, people may feel sorry for C-group who does not get "the treatment" - try to give them something extra
• e.g. compare usual day care for street children with an enhanced day treatment condition
• service providers may very well complain about inequity, and provide some enhanced service to the children receiving usual care
• C-group may "work harder" to compete better with the E-group
• Opposite to compensatory rivalry
• May feel deprived, and give up
• e.g. giving unemployed high school dropouts a second chance at completing matric via a special education programme
• if we assign some of them to a control group, who receive "no treatment", they may very well become profoundly demoralized
• Can the findings of the study be generalized?
• Do they speak only of our sample, or of a wider group?
• To what populations, settings, treatment variables (IV's), and measurement variables can the finding be generalized?
• Mainly questions about three aspects
• Research participants
• Independent variables, or manipulations
• Dependent variables, or outcomes
• Says nothing about the truth of the result that we are generalizing
• External validity only has meaning once the internal validity of a study has been established
• Internal validity is the basic minimum without which an experiment is uninterpretable
• Our interest in answering research questions is rarely restricted to the specific situation studied - our interest is in the variables, not the specific details of a piece of research
• But studies differ in many ways, even if they study the same variables
• operational definitions of the variables
• subject population studied
• procedural details
• Generally bigger samples with valid measures lead to better external validity
• Subject selection - Selecting a sample which does not represent the population well, will prevent generalization
• Interaction between the testing situation and the experimental stimulus
• When people have been sensitized to the issues by the pre-test
• Respond differently to the questionnaires the second time (post-test)
• Operationalization
• We take a variable with wide scope and operationalize it in a narrow fashion
• Will we find the same results with a different operationalization of the same variable?
• "natural" - e.g. disaster research
• Static-group comparison type
• Non-equivalent experimental and control groups
• Manipulating the IV
• Sorting out extraneous variables
• Articifiality - a generalization problem
• Limited range of questions
• Donald Campbell often cited Neurath's metaphor
• "in science we are like sailors who must repair a rotting ship while it is afloat at sea. We depend on the relative soundness of all other planks while we replace a particularly weak one. Each of the planks we now depend on we will in turn have to replace. No one of them is a foundation, nor point of certainty, no one of them is incorrigible"

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