3 example of descriptive research title

The different types of titles with examples

1. noun phrases that describe the topic of study ​.

Also known as descriptive or neutral, this is by far the most common type of title, especially in scientific research. Typically, a noun phrase is used to convey what the study is, without revealing its findings. It can be an effective way to cram all necessary information and keywords into a few words , and may intrigue the reader to read the rest of the article to learn about the findings. Descriptive titles are the most conservative, and arguably the most preferred, type of paper title.

• A Style-Based Generator Architecture for Generative Adversarial Networks
• The Association Between Income and Life Expectancy in the United States, 2001-2014
• The trajectory, structure and origin of the Chelyabinsk asteroidal impactor

2. Declarative stance that highlights a research finding ​

This is when you plainly state what the main finding of your study is. Declarative titles work especially well if the finding is novel or striking, and will make people want to dive into your paper to understand how you reached that conclusion. If you fear that your finding isn’t compelling enough, or that revealing it in the title might spoil the fun, then perhaps consider other types of titles.

• New elevation data triple estimates of global vulnerability to sea-level rise and coastal flooding
• Observation of J/ψp resonances consistent with pentaquark states in Λ0b→J/ψK−p decays
• More than 75 percent decline over 27 years in total flying insect biomass in protected areas

3. Interrogative sentence that presents the main research question ​

Interrogative titles are titles that are simply formulated from the research question of your study. If your study has several research questions, pick the main one for your title. Titles in the form of questions can arouse readers’ curiosity, increasing clicks and downloads of your publication. Make sure that your question is clearly worded, and that you are actually giving the answer in your paper.

• Will Gender Self-Declaration Undermine Women's Rights and Lead to an Increase in Harms?
• Does physical activity attenuate, or even eliminate, the detrimental association of sitting time with mortality?
• Will COVID-19 fiscal recovery packages accelerate or retard progress on climate change?

4. Catchy or humorous stance followed by a more informative subtitle ​

This is probably the rarest type of article title, and isn't to everybody's taste. But some readers appreciate wordplay and funny titles that make them smile and draw their attention. As you are competing for attention with millions of other journal articles out there, it might be worth considering. If you are not sure if this would be appropriate for your paper or discipline, consult your supervisor or colleagues for feedback. In any case, it is best to supplement it with a more conventional subtitle that adds information about your study.

• Systematically Improving Espresso: Insights from Mathematical Modeling and Experiment
• An Apple a Day: Which Bacteria Do We Eat With Organic and Conventional Apples?
• Sexist Games = Sexist Gamers? A Longitudinal Study on the Relationship Between Video Game Use and Sexist Attitudes

Related sources ​

Writing a good title

FAQs about writing a title

• 1. Noun phrases that describe the topic of study
• 2. Declarative stance that highlights a research finding
• 3. Interrogative sentence that presents the main research question
• 4. Catchy or humorous stance followed by a more informative subtitle
• Related sources

• Descriptive Research Designs: Types, Examples & Methods

One of the components of research is getting enough information about the research problem—the what, how, when and where answers, which is why descriptive research is an important type of research. It is very useful when conducting research whose aim is to identify characteristics, frequencies, trends, correlations, and categories.

This research method takes a problem with little to no relevant information and gives it a befitting description using qualitative and quantitative research method s. Descriptive research aims to accurately describe a research problem.

In the subsequent sections, we will be explaining what descriptive research means, its types, examples, and data collection methods.

What is Descriptive Research?

Descriptive research is a type of research that describes a population, situation, or phenomenon that is being studied. It focuses on answering the how, what, when, and where questions If a research problem, rather than the why.

This is mainly because it is important to have a proper understanding of what a research problem is about before investigating why it exists in the first place. 

For example, an investor considering an investment in the ever-changing Amsterdam housing market needs to understand what the current state of the market is, how it changes (increasing or decreasing), and when it changes (time of the year) before asking for the why. This is where descriptive research comes in.

What Are The Types of Descriptive Research?

Descriptive research is classified into different types according to the kind of approach that is used in conducting descriptive research. The different types of descriptive research are highlighted below:

• Descriptive-survey

Descriptive survey research uses surveys to gather data about varying subjects. This data aims to know the extent to which different conditions can be obtained among these subjects.

For example, a researcher wants to determine the qualification of employed professionals in Maryland. He uses a survey as his research instrument , and each item on the survey related to qualifications is subjected to a Yes/No answer. 

This way, the researcher can describe the qualifications possessed by the employed demographics of this community. 

• Descriptive-normative survey

This is an extension of the descriptive survey, with the addition being the normative element. In the descriptive-normative survey, the results of the study should be compared with the norm.

For example, an organization that wishes to test the skills of its employees by a team may have them take a skills test. The skills tests are the evaluation tool in this case, and the result of this test is compared with the norm of each role.

If the score of the team is one standard deviation above the mean, it is very satisfactory, if within the mean, satisfactory, and one standard deviation below the mean is unsatisfactory.

• Descriptive-status

This is a quantitative description technique that seeks to answer questions about real-life situations. For example, a researcher researching the income of the employees in a company, and the relationship with their performance.

A survey will be carried out to gather enough data about the income of the employees, then their performance will be evaluated and compared to their income. This will help determine whether a higher income means better performance and low income means lower performance or vice versa.

• Descriptive-analysis

The descriptive-analysis method of research describes a subject by further analyzing it, which in this case involves dividing it into 2 parts. For example, the HR personnel of a company that wishes to analyze the job role of each employee of the company may divide the employees into the people that work at the Headquarters in the US and those that work from Oslo, Norway office.

A questionnaire is devised to analyze the job role of employees with similar salaries and who work in similar positions.

• Descriptive classification

This method is employed in biological sciences for the classification of plants and animals. A researcher who wishes to classify the sea animals into different species will collect samples from various search stations, then classify them accordingly.

• Descriptive-comparative

In descriptive-comparative research, the researcher considers 2 variables that are not manipulated, and establish a formal procedure to conclude that one is better than the other. For example, an examination body wants to determine the better method of conducting tests between paper-based and computer-based tests.

A random sample of potential participants of the test may be asked to use the 2 different methods, and factors like failure rates, time factors, and others will be evaluated to arrive at the best method.

• Correlative Survey

Correlative surveys are used to determine whether the relationship between 2 variables is positive, negative, or neutral. That is, if 2 variables say X and Y are directly proportional, inversely proportional or are not related to each other.

Examples of Descriptive Research

There are different examples of descriptive research, that may be highlighted from its types, uses, and applications. However, we will be restricting ourselves to only 3 distinct examples in this article.

• Comparing Student Performance:

An academic institution may wish 2 compare the performance of its junior high school students in English language and Mathematics. This may be used to classify students based on 2 major groups, with one group going ahead to study while courses, while the other study courses in the Arts & Humanities field.

Students who are more proficient in mathematics will be encouraged to go into STEM and vice versa. Institutions may also use this data to identify students’ weak points and work on ways to assist them.

• Scientific Classification

During the major scientific classification of plants, animals, and periodic table elements, the characteristics and components of each subject are evaluated and used to determine how they are classified.

For example, living things may be classified into kingdom Plantae or kingdom animal is depending on their nature. Further classification may group animals into mammals, pieces, vertebrae, invertebrae, etc. 

All these classifications are made a result of descriptive research which describes what they are.

• Human Behavior

When studying human behaviour based on a factor or event, the researcher observes the characteristics, behaviour, and reaction, then use it to conclude. A company willing to sell to its target market needs to first study the behaviour of the market.

This may be done by observing how its target reacts to a competitor’s product, then use it to determine their behaviour.

What are the Characteristics of Descriptive Research?  

The characteristics of descriptive research can be highlighted from its definition, applications, data collection methods, and examples. Some characteristics of descriptive research are:

• Quantitativeness

Descriptive research uses a quantitative research method by collecting quantifiable information to be used for statistical analysis of the population sample. This is very common when dealing with research in the physical sciences.

• Qualitativeness

It can also be carried out using the qualitative research method, to properly describe the research problem. This is because descriptive research is more explanatory than exploratory or experimental.

• Uncontrolled variables

In descriptive research, researchers cannot control the variables like they do in experimental research.

• The basis for further research

The results of descriptive research can be further analyzed and used in other research methods. It can also inform the next line of research, including the research method that should be used.

This is because it provides basic information about the research problem, which may give birth to other questions like why a particular thing is the way it is.

Why Use Descriptive Research Design?  

Descriptive research can be used to investigate the background of a research problem and get the required information needed to carry out further research. It is used in multiple ways by different organizations, and especially when getting the required information about their target audience.

• Define subject characteristics :

It is used to determine the characteristics of the subjects, including their traits, behaviour, opinion, etc. This information may be gathered with the use of surveys, which are shared with the respondents who in this case, are the research subjects.

For example, a survey evaluating the number of hours millennials in a community spends on the internet weekly, will help a service provider make informed business decisions regarding the market potential of the community.

• Measure Data Trends

It helps to measure the changes in data over some time through statistical methods. Consider the case of individuals who want to invest in stock markets, so they evaluate the changes in prices of the available stocks to make a decision investment decision.

Brokerage companies are however the ones who carry out the descriptive research process, while individuals can view the data trends and make decisions.

Descriptive research is also used to compare how different demographics respond to certain variables. For example, an organization may study how people with different income levels react to the launch of a new Apple phone.

This kind of research may take a survey that will help determine which group of individuals are purchasing the new Apple phone. Do the low-income earners also purchase the phone, or only the high-income earners do?

Further research using another technique will explain why low-income earners are purchasing the phone even though they can barely afford it. This will help inform strategies that will lure other low-income earners and increase company sales.

• Validate existing conditions

When you are not sure about the validity of an existing condition, you can use descriptive research to ascertain the underlying patterns of the research object. This is because descriptive research methods make an in-depth analysis of each variable before making conclusions.

• Conducted Overtime

Descriptive research is conducted over some time to ascertain the changes observed at each point in time. The higher the number of times it is conducted, the more authentic the conclusion will be.

What are the Disadvantages of Descriptive Research?  

• Response and Non-response Bias

Respondents may either decide not to respond to questions or give incorrect responses if they feel the questions are too confidential. When researchers use observational methods, respondents may also decide to behave in a particular manner because they feel they are being watched.

• The researcher may decide to influence the result of the research due to personal opinion or bias towards a particular subject. For example, a stockbroker who also has a business of his own may try to lure investors into investing in his own company by manipulating results.
• A case-study or sample taken from a large population is not representative of the whole population.
• Limited scope:The scope of descriptive research is limited to the what of research, with no information on why thereby limiting the scope of the research.

What are the Data Collection Methods in Descriptive Research?  

There are 3 main data collection methods in descriptive research, namely; observational method, case study method, and survey research.

1. Observational Method

The observational method allows researchers to collect data based on their view of the behaviour and characteristics of the respondent, with the respondents themselves not directly having an input. It is often used in market research, psychology, and some other social science research to understand human behaviour.

It is also an important aspect of physical scientific research, with it being one of the most effective methods of conducting descriptive research . This process can be said to be either quantitative or qualitative.

Quantitative observation involved the objective collection of numerical data , whose results can be analyzed using numerical and statistical methods. 

Qualitative observation, on the other hand, involves the monitoring of characteristics and not the measurement of numbers. The researcher makes his observation from a distance, records it, and is used to inform conclusions.

2. Case Study Method

A case study is a sample group (an individual, a group of people, organizations, events, etc.) whose characteristics are used to describe the characteristics of a larger group in which the case study is a subgroup. The information gathered from investigating a case study may be generalized to serve the larger group.

This generalization, may, however, be risky because case studies are not sufficient to make accurate predictions about larger groups. Case studies are a poor case of generalization.

3. Survey Research

This is a very popular data collection method in research designs. In survey research, researchers create a survey or questionnaire and distribute it to respondents who give answers.

Generally, it is used to obtain quick information directly from the primary source and also conducting rigorous quantitative and qualitative research. In some cases, survey research uses a blend of both qualitative and quantitative strategies.

Survey research can be carried out both online and offline using the following methods

• Online Surveys: This is a cheap method of carrying out surveys and getting enough responses. It can be carried out using Formplus, an online survey builder. Formplus has amazing tools and features that will help increase response rates.
• Offline Surveys: This includes paper forms, mobile offline forms , and SMS-based forms.

What Are The Differences Between Descriptive and Correlational Research?  

Before going into the differences between descriptive and correlation research, we need to have a proper understanding of what correlation research is about. Therefore, we will be giving a summary of the correlation research below.

Correlational research is a type of descriptive research, which is used to measure the relationship between 2 variables, with the researcher having no control over them. It aims to find whether there is; positive correlation (both variables change in the same direction), negative correlation (the variables change in the opposite direction), or zero correlation (there is no relationship between the variables).

Correlational research may be used in 2 situations;

(i) when trying to find out if there is a relationship between two variables, and

(ii) when a causal relationship is suspected between two variables, but it is impractical or unethical to conduct experimental research that manipulates one of the variables. 

Below are some of the differences between correlational and descriptive research:

• Definitions :

Descriptive research aims is a type of research that provides an in-depth understanding of the study population, while correlational research is the type of research that measures the relationship between 2 variables. 

• Characteristics :

Descriptive research provides descriptive data explaining what the research subject is about, while correlation research explores the relationship between data and not their description.

• Predictions :

 Predictions cannot be made in descriptive research while correlation research accommodates the possibility of making predictions.

Descriptive Research vs. Causal Research

Descriptive research and causal research are both research methodologies, however, one focuses on a subject’s behaviors while the latter focuses on a relationship’s cause-and-effect. To buttress the above point, descriptive research aims to describe and document the characteristics, behaviors, or phenomena of a particular or specific population or situation. 

It focuses on providing an accurate and detailed account of an already existing state of affairs between variables. Descriptive research answers the questions of “what,” “where,” “when,” and “how” without attempting to establish any causal relationships or explain any underlying factors that might have caused the behavior.

Causal research, on the other hand, seeks to determine cause-and-effect relationships between variables. It aims to point out the factors that influence or cause a particular result or behavior. Causal research involves manipulating variables, controlling conditions or a subgroup, and observing the resulting effects. The primary objective of causal research is to establish a cause-effect relationship and provide insights into why certain phenomena happen the way they do.

Descriptive Research vs. Analytical Research

Descriptive research provides a detailed and comprehensive account of a specific situation or phenomenon. It focuses on describing and summarizing data without making inferences or attempting to explain underlying factors or the cause of the factor. 

It is primarily concerned with providing an accurate and objective representation of the subject of research. While analytical research goes beyond the description of the phenomena and seeks to analyze and interpret data to discover if there are patterns, relationships, or any underlying factors. 

It examines the data critically, applies statistical techniques or other analytical methods, and draws conclusions based on the discovery. Analytical research also aims to explore the relationships between variables and understand the underlying mechanisms or processes involved.

Descriptive Research vs. Exploratory Research

Descriptive research is a research method that focuses on providing a detailed and accurate account of a specific situation, group, or phenomenon. This type of research describes the characteristics, behaviors, or relationships within the given context without looking for an underlying cause. 

Descriptive research typically involves collecting and analyzing quantitative or qualitative data to generate descriptive statistics or narratives. Exploratory research differs from descriptive research because it aims to explore and gain firsthand insights or knowledge into a relatively unexplored or poorly understood topic. 

It focuses on generating ideas, hypotheses, or theories rather than providing definitive answers. Exploratory research is often conducted at the early stages of a research project to gather preliminary information and identify key variables or factors for further investigation. It involves open-ended interviews, observations, or small-scale surveys to gather qualitative data.

Read More – Exploratory Research: What are its Method & Examples?

Descriptive Research vs. Experimental Research

Descriptive research aims to describe and document the characteristics, behaviors, or phenomena of a particular population or situation. It focuses on providing an accurate and detailed account of the existing state of affairs. 

Descriptive research typically involves collecting data through surveys, observations, or existing records and analyzing the data to generate descriptive statistics or narratives. It does not involve manipulating variables or establishing cause-and-effect relationships.

Experimental research, on the other hand, involves manipulating variables and controlling conditions to investigate cause-and-effect relationships. It aims to establish causal relationships by introducing an intervention or treatment and observing the resulting effects. 

Experimental research typically involves randomly assigning participants to different groups, such as control and experimental groups, and measuring the outcomes. It allows researchers to control for confounding variables and draw causal conclusions.

Related – Experimental vs Non-Experimental Research: 15 Key Differences

Descriptive Research vs. Explanatory Research

Descriptive research focuses on providing a detailed and accurate account of a specific situation, group, or phenomenon. It aims to describe the characteristics, behaviors, or relationships within the given context. 

Descriptive research is primarily concerned with providing an objective representation of the subject of study without explaining underlying causes or mechanisms. Explanatory research seeks to explain the relationships between variables and uncover the underlying causes or mechanisms. 

It goes beyond description and aims to understand the reasons or factors that influence a particular outcome or behavior. Explanatory research involves analyzing data, conducting statistical analyses, and developing theories or models to explain the observed relationships.

Descriptive Research vs. Inferential Research

Descriptive research focuses on describing and summarizing data without making inferences or generalizations beyond the specific sample or population being studied. It aims to provide an accurate and objective representation of the subject of study. 

Descriptive research typically involves analyzing data to generate descriptive statistics, such as means, frequencies, or percentages, to describe the characteristics or behaviors observed.

Inferential research, however, involves making inferences or generalizations about a larger population based on a smaller sample. 

It aims to draw conclusions about the population characteristics or relationships by analyzing the sample data. Inferential research uses statistical techniques to estimate population parameters, test hypotheses, and determine the level of confidence or significance in the findings.

Related – Inferential Statistics: Definition, Types + Examples

Conclusion  

The uniqueness of descriptive research partly lies in its ability to explore both quantitative and qualitative research methods. Therefore, when conducting descriptive research, researchers have the opportunity to use a wide variety of techniques that aids the research process.

Descriptive research explores research problems in-depth, beyond the surface level thereby giving a detailed description of the research subject. That way, it can aid further research in the field, including other research methods .

It is also very useful in solving real-life problems in various fields of social science, physical science, and education.

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Home » Descriptive Research Design – Types, Methods and Examples

Descriptive Research Design – Types, Methods and Examples

Table of Contents

Descriptive Research Design

Definition:

Descriptive research design is a type of research methodology that aims to describe or document the characteristics, behaviors, attitudes, opinions, or perceptions of a group or population being studied.

Descriptive research design does not attempt to establish cause-and-effect relationships between variables or make predictions about future outcomes. Instead, it focuses on providing a detailed and accurate representation of the data collected, which can be useful for generating hypotheses, exploring trends, and identifying patterns in the data.

Types of Descriptive Research Design

Types of Descriptive Research Design are as follows:

Cross-sectional Study

This involves collecting data at a single point in time from a sample or population to describe their characteristics or behaviors. For example, a researcher may conduct a cross-sectional study to investigate the prevalence of certain health conditions among a population, or to describe the attitudes and beliefs of a particular group.

Longitudinal Study

This involves collecting data over an extended period of time, often through repeated observations or surveys of the same group or population. Longitudinal studies can be used to track changes in attitudes, behaviors, or outcomes over time, or to investigate the effects of interventions or treatments.

This involves an in-depth examination of a single individual, group, or situation to gain a detailed understanding of its characteristics or dynamics. Case studies are often used in psychology, sociology, and business to explore complex phenomena or to generate hypotheses for further research.

Survey Research

This involves collecting data from a sample or population through standardized questionnaires or interviews. Surveys can be used to describe attitudes, opinions, behaviors, or demographic characteristics of a group, and can be conducted in person, by phone, or online.

Observational Research

This involves observing and documenting the behavior or interactions of individuals or groups in a natural or controlled setting. Observational studies can be used to describe social, cultural, or environmental phenomena, or to investigate the effects of interventions or treatments.

Correlational Research

This involves examining the relationships between two or more variables to describe their patterns or associations. Correlational studies can be used to identify potential causal relationships or to explore the strength and direction of relationships between variables.

Data Analysis Methods

Descriptive research design data analysis methods depend on the type of data collected and the research question being addressed. Here are some common methods of data analysis for descriptive research:

Descriptive Statistics

This method involves analyzing data to summarize and describe the key features of a sample or population. Descriptive statistics can include measures of central tendency (e.g., mean, median, mode) and measures of variability (e.g., range, standard deviation).

Cross-tabulation

This method involves analyzing data by creating a table that shows the frequency of two or more variables together. Cross-tabulation can help identify patterns or relationships between variables.

Content Analysis

This method involves analyzing qualitative data (e.g., text, images, audio) to identify themes, patterns, or trends. Content analysis can be used to describe the characteristics of a sample or population, or to identify factors that influence attitudes or behaviors.

Qualitative Coding

This method involves analyzing qualitative data by assigning codes to segments of data based on their meaning or content. Qualitative coding can be used to identify common themes, patterns, or categories within the data.

Visualization

This method involves creating graphs or charts to represent data visually. Visualization can help identify patterns or relationships between variables and make it easier to communicate findings to others.

Comparative Analysis

This method involves comparing data across different groups or time periods to identify similarities and differences. Comparative analysis can help describe changes in attitudes or behaviors over time or differences between subgroups within a population.

Applications of Descriptive Research Design

Descriptive research design has numerous applications in various fields. Some of the common applications of descriptive research design are:

• Market research: Descriptive research design is widely used in market research to understand consumer preferences, behavior, and attitudes. This helps companies to develop new products and services, improve marketing strategies, and increase customer satisfaction.
• Health research: Descriptive research design is used in health research to describe the prevalence and distribution of a disease or health condition in a population. This helps healthcare providers to develop prevention and treatment strategies.
• Educational research: Descriptive research design is used in educational research to describe the performance of students, schools, or educational programs. This helps educators to improve teaching methods and develop effective educational programs.
• Social science research: Descriptive research design is used in social science research to describe social phenomena such as cultural norms, values, and beliefs. This helps researchers to understand social behavior and develop effective policies.
• Public opinion research: Descriptive research design is used in public opinion research to understand the opinions and attitudes of the general public on various issues. This helps policymakers to develop effective policies that are aligned with public opinion.
• Environmental research: Descriptive research design is used in environmental research to describe the environmental conditions of a particular region or ecosystem. This helps policymakers and environmentalists to develop effective conservation and preservation strategies.

Descriptive Research Design Examples

Here are some real-time examples of descriptive research designs:

• A restaurant chain wants to understand the demographics and attitudes of its customers. They conduct a survey asking customers about their age, gender, income, frequency of visits, favorite menu items, and overall satisfaction. The survey data is analyzed using descriptive statistics and cross-tabulation to describe the characteristics of their customer base.
• A medical researcher wants to describe the prevalence and risk factors of a particular disease in a population. They conduct a cross-sectional study in which they collect data from a sample of individuals using a standardized questionnaire. The data is analyzed using descriptive statistics and cross-tabulation to identify patterns in the prevalence and risk factors of the disease.
• An education researcher wants to describe the learning outcomes of students in a particular school district. They collect test scores from a representative sample of students in the district and use descriptive statistics to calculate the mean, median, and standard deviation of the scores. They also create visualizations such as histograms and box plots to show the distribution of scores.
• A marketing team wants to understand the attitudes and behaviors of consumers towards a new product. They conduct a series of focus groups and use qualitative coding to identify common themes and patterns in the data. They also create visualizations such as word clouds to show the most frequently mentioned topics.
• An environmental scientist wants to describe the biodiversity of a particular ecosystem. They conduct an observational study in which they collect data on the species and abundance of plants and animals in the ecosystem. The data is analyzed using descriptive statistics to describe the diversity and richness of the ecosystem.

How to Conduct Descriptive Research Design

To conduct a descriptive research design, you can follow these general steps:

• Define your research question: Clearly define the research question or problem that you want to address. Your research question should be specific and focused to guide your data collection and analysis.
• Choose your research method: Select the most appropriate research method for your research question. As discussed earlier, common research methods for descriptive research include surveys, case studies, observational studies, cross-sectional studies, and longitudinal studies.
• Design your study: Plan the details of your study, including the sampling strategy, data collection methods, and data analysis plan. Determine the sample size and sampling method, decide on the data collection tools (such as questionnaires, interviews, or observations), and outline your data analysis plan.
• Collect data: Collect data from your sample or population using the data collection tools you have chosen. Ensure that you follow ethical guidelines for research and obtain informed consent from participants.
• Analyze data: Use appropriate statistical or qualitative analysis methods to analyze your data. As discussed earlier, common data analysis methods for descriptive research include descriptive statistics, cross-tabulation, content analysis, qualitative coding, visualization, and comparative analysis.
• I nterpret results: Interpret your findings in light of your research question and objectives. Identify patterns, trends, and relationships in the data, and describe the characteristics of your sample or population.
• Draw conclusions and report results: Draw conclusions based on your analysis and interpretation of the data. Report your results in a clear and concise manner, using appropriate tables, graphs, or figures to present your findings. Ensure that your report follows accepted research standards and guidelines.

When to Use Descriptive Research Design

Descriptive research design is used in situations where the researcher wants to describe a population or phenomenon in detail. It is used to gather information about the current status or condition of a group or phenomenon without making any causal inferences. Descriptive research design is useful in the following situations:

• Exploratory research: Descriptive research design is often used in exploratory research to gain an initial understanding of a phenomenon or population.
• Identifying trends: Descriptive research design can be used to identify trends or patterns in a population, such as changes in consumer behavior or attitudes over time.
• Market research: Descriptive research design is commonly used in market research to understand consumer preferences, behavior, and attitudes.
• Health research: Descriptive research design is useful in health research to describe the prevalence and distribution of a disease or health condition in a population.
• Social science research: Descriptive research design is used in social science research to describe social phenomena such as cultural norms, values, and beliefs.
• Educational research: Descriptive research design is used in educational research to describe the performance of students, schools, or educational programs.

Purpose of Descriptive Research Design

The main purpose of descriptive research design is to describe and measure the characteristics of a population or phenomenon in a systematic and objective manner. It involves collecting data that describe the current status or condition of the population or phenomenon of interest, without manipulating or altering any variables.

The purpose of descriptive research design can be summarized as follows:

• To provide an accurate description of a population or phenomenon: Descriptive research design aims to provide a comprehensive and accurate description of a population or phenomenon of interest. This can help researchers to develop a better understanding of the characteristics of the population or phenomenon.
• To identify trends and patterns: Descriptive research design can help researchers to identify trends and patterns in the data, such as changes in behavior or attitudes over time. This can be useful for making predictions and developing strategies.
• To generate hypotheses: Descriptive research design can be used to generate hypotheses or research questions that can be tested in future studies. For example, if a descriptive study finds a correlation between two variables, this could lead to the development of a hypothesis about the causal relationship between the variables.
• To establish a baseline: Descriptive research design can establish a baseline or starting point for future research. This can be useful for comparing data from different time periods or populations.

Characteristics of Descriptive Research Design

Descriptive research design has several key characteristics that distinguish it from other research designs. Some of the main characteristics of descriptive research design are:

• Objective : Descriptive research design is objective in nature, which means that it focuses on collecting factual and accurate data without any personal bias. The researcher aims to report the data objectively without any personal interpretation.
• Non-experimental: Descriptive research design is non-experimental, which means that the researcher does not manipulate any variables. The researcher simply observes and records the behavior or characteristics of the population or phenomenon of interest.
• Quantitative : Descriptive research design is quantitative in nature, which means that it involves collecting numerical data that can be analyzed using statistical techniques. This helps to provide a more precise and accurate description of the population or phenomenon.
• Cross-sectional: Descriptive research design is often cross-sectional, which means that the data is collected at a single point in time. This can be useful for understanding the current state of the population or phenomenon, but it may not provide information about changes over time.
• Large sample size: Descriptive research design typically involves a large sample size, which helps to ensure that the data is representative of the population of interest. A large sample size also helps to increase the reliability and validity of the data.
• Systematic and structured: Descriptive research design involves a systematic and structured approach to data collection, which helps to ensure that the data is accurate and reliable. This involves using standardized procedures for data collection, such as surveys, questionnaires, or observation checklists.

Advantages of Descriptive Research Design

Descriptive research design has several advantages that make it a popular choice for researchers. Some of the main advantages of descriptive research design are:

• Provides an accurate description: Descriptive research design is focused on accurately describing the characteristics of a population or phenomenon. This can help researchers to develop a better understanding of the subject of interest.
• Easy to conduct: Descriptive research design is relatively easy to conduct and requires minimal resources compared to other research designs. It can be conducted quickly and efficiently, and data can be collected through surveys, questionnaires, or observations.
• Useful for generating hypotheses: Descriptive research design can be used to generate hypotheses or research questions that can be tested in future studies. For example, if a descriptive study finds a correlation between two variables, this could lead to the development of a hypothesis about the causal relationship between the variables.
• Large sample size : Descriptive research design typically involves a large sample size, which helps to ensure that the data is representative of the population of interest. A large sample size also helps to increase the reliability and validity of the data.
• Can be used to monitor changes : Descriptive research design can be used to monitor changes over time in a population or phenomenon. This can be useful for identifying trends and patterns, and for making predictions about future behavior or attitudes.
• Can be used in a variety of fields : Descriptive research design can be used in a variety of fields, including social sciences, healthcare, business, and education.

Limitation of Descriptive Research Design

Descriptive research design also has some limitations that researchers should consider before using this design. Some of the main limitations of descriptive research design are:

• Cannot establish cause and effect: Descriptive research design cannot establish cause and effect relationships between variables. It only provides a description of the characteristics of the population or phenomenon of interest.
• Limited generalizability: The results of a descriptive study may not be generalizable to other populations or situations. This is because descriptive research design often involves a specific sample or situation, which may not be representative of the broader population.
• Potential for bias: Descriptive research design can be subject to bias, particularly if the researcher is not objective in their data collection or interpretation. This can lead to inaccurate or incomplete descriptions of the population or phenomenon of interest.
• Limited depth: Descriptive research design may provide a superficial description of the population or phenomenon of interest. It does not delve into the underlying causes or mechanisms behind the observed behavior or characteristics.
• Limited utility for theory development: Descriptive research design may not be useful for developing theories about the relationship between variables. It only provides a description of the variables themselves.
• Relies on self-report data: Descriptive research design often relies on self-report data, such as surveys or questionnaires. This type of data may be subject to biases, such as social desirability bias or recall bias.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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Research Title

Ai generator.

A research title is a succinct, informative phrase that encapsulates a study’s essence. It gives readers a clear indication of the research’s focus, scope, and significance. An effective research title is concise, specific, and engaging, incorporating key terms related to the primary subject matter. Crafting a well-thought-out research title is crucial as it influences first impressions and impacts the study’s visibility and accessibility. Additionally, a strong research title enhances the title page and ensures the research paper cover letter accurately reflects the study’s content.

What is Research Title?

A research title is a concise statement that clearly and precisely encapsulates the main topic, scope, and objective of a research study. It serves as the first point of contact for readers and should effectively communicate the essence of the research in a way that is both engaging and informative. A well-crafted research title is specific, descriptive, and reflective of the study’s core focus, helping to attract interest and provide a clear understanding of the research subject at a glance.

Research Title Format

A well-crafted research title follows a specific format to ensure clarity and precision. Here’s a structured approach:

[Main Topic]: [Specific Aspect or Focus]

Example: “The Impact of Social Media on Teen Mental Health: A Comprehensive Analysis of Behavioral Changes”

Examples of Research Titles

Here are some examples of well-crafted research titles across various fields:

• “The Effects of Bilingual Education on Cognitive Development in Early Childhood”
• “Assessing the Impact of Technology Integration on Student Engagement in High School Classrooms”
• “The Role of Genetics in the Development of Alzheimer’s Disease: A Meta-Analysis”
• “Evaluating the Efficacy of Telemedicine in Managing Chronic Diseases During the COVID-19 Pandemic”
• “The Impact of Urbanization on Local Wildlife Populations: A Case Study of Central Park”
• “Assessing the Effectiveness of Renewable Energy Policies in Reducing Carbon Emissions”
• “The Influence of Social Media on Political Participation Among Millennials”
• “Exploring the Relationship Between Socioeconomic Status and Academic Achievement in Urban Schools”
• “Analyzing the Effects of Corporate Social Responsibility on Consumer Behavior”
• “The Role of Microfinance in Alleviating Poverty in Developing Countries”
• “The Development and Impact of Artificial Intelligence on Workforce Automation”
• “Assessing the Safety and Efficiency of Autonomous Vehicles in Urban Areas”
• “The Representation of Gender Roles in 21st Century Cinema”
• “Exploring the Influence of Renaissance Art on Modern Aesthetic Values”
• “The Impact of Childhood Trauma on Adult Relationships: A Longitudinal Study”
• “Exploring the Effectiveness of Cognitive Behavioral Therapy in Treating Anxiety Disorders”
• “The Effectiveness of Vaccination Campaigns in Reducing the Spread of Infectious Diseases: A Global Perspective”
• “Sustainable Farming Practices and Their Impact on Soil Health: A Comparative Study of Organic and Conventional Methods”

Research Titles for Students

• The Impact of Online Learning on Student Performance in High School
• Exploring the Relationship Between Sleep Patterns and Academic Achievement Among College Students
• The Effects of Extracurricular Activities on Student Social Skills Development
• The Influence of Peer Pressure on High School Students’ Academic Choices
• Assessing the Benefits of Early Childhood Education Programs on Later Academic Success
• The Role of Nutrition and Diet in Enhancing Student Concentration and Memory
• Examining the Effectiveness of Study Groups in Improving Academic Performance in University Settings
• The Impact of Part-Time Employment on High School Students’ Academic Achievement and Time Management
• Exploring the Relationship Between Physical Activity and Mental Health Among College Students
• The Effects of School Uniform Policies on Student Behavior and Academic Outcomes

Qualitative Research Titles

• Exploring Student Perceptions of Remote Learning During the COVID-19 Pandemic
• The Lived Experiences of First-Generation College Students: Challenges and Triumphs
• Understanding Teacher Attitudes Towards Inclusive Education in Mainstream Classrooms
• The Impact of Parental Involvement on Student Motivation and Academic Success
• Exploring the Cultural Adaptation Experiences of International Students in American Universities
• The Role of Peer Support in Coping with Academic Stress Among High School Students
• Investigating the Influence of School Climate on Teacher Job Satisfaction and Retention
• The Effects of Community-Based Learning on Student Engagement and Civic Responsibility
• Understanding the Barriers to STEM Education for Female Students in Rural Areas
• Exploring the Experiences of Students with Learning Disabilities in Higher Education
• The Impact of School Leadership Styles on Teacher Morale and Performance
• The Role of Mentorship Programs in Supporting Minority Students in STEM Fields
• Exploring the Emotional and Social Impacts of Bullying on Middle School Students
• The Influence of Extracurricular Activities on Identity Development in Adolescents
• Understanding the Perspectives of Parents on Bilingual Education Programs

Quantitative Research Titles

• The Impact of Class Size on Student Academic Achievement in Elementary Schools
• Analyzing the Correlation Between Homework Frequency and Student Performance in Mathematics
• The Effects of School Funding on Standardized Test Scores in Public Schools
• Assessing the Relationship Between Attendance Rates and Graduation Rates in High Schools
• Evaluating the Effectiveness of Flipped Classrooms on Student Learning Outcomes
• The Influence of Parental Education Levels on Children’s Academic Success
• The Impact of Early Childhood Education on Literacy Rates in Primary School Students
• Comparing Academic Performance Between Students in Single-Sex and Coeducational Schools
• The Role of Technology in Enhancing Student Engagement in STEM Subjects
• Analyzing the Impact of Nutrition Programs on Student Health and Academic Performance
• The Relationship Between Physical Activity and Academic Achievement in High School Students
• Evaluating the Success of Mentorship Programs on College Retention Rates
• The Effects of Sleep Patterns on Academic Performance Among University Students
• Assessing the Impact of Socioeconomic Status on Access to Higher Education
• The Influence of Teacher Qualifications on Student Achievement in Science

Importance of a Research Title

A research title is a critical component of any research study or academic paper. It serves multiple important functions that contribute to the overall success and impact of the research. Here are key reasons why a research title is important:

1. First Impression

The research title is often the first element a reader encounters. A well-crafted title can create a strong first impression, attracting the reader’s attention and encouraging them to explore the study further.

2. Clarity and Focus

A good research title clearly and succinctly communicates the main topic and scope of the study. It helps the reader quickly understand what the research is about and what specific aspect is being addressed.

3. Guidance

The title provides guidance to the reader about the content and direction of the research. It sets expectations and helps readers decide if the paper is relevant to their interests or research needs.

4. Searchability

In the digital age, research titles are crucial for searchability. A precise and descriptive title improves the chances of the paper being found in online searches, databases, and academic journals, increasing its visibility and accessibility.

5. Academic and Professional Recognition

A well-formulated research title contributes to the academic and professional recognition of the work. It reflects the researcher’s ability to clearly define and articulate their study, which can enhance credibility and reputation within the academic community.

Characteristics of a Good Research Title

A good research title is essential for effectively communicating the main focus and scope of your study. Here are the key characteristics that make a research title effective:

• Clear and Understandable : The title should be easily understood by a broad audience, avoiding jargon or overly complex language.
• Direct : It should convey the main topic and scope of the research without ambiguity.

2. Conciseness

• Brevity : A good title is concise and to the point, typically no longer than 10-15 words.
• Essential Information : It includes only the most relevant information, omitting unnecessary words.

3. Specificity

• Focused : The title should clearly reflect the specific aspect or focus of the research.
• Detailed : It provides enough detail to give a clear sense of what the study entails.

4. Descriptiveness

• Informative : It accurately describes the content and scope of the study.
• Comprehensive : The title should give readers a good understanding of the research without needing to read the entire paper.

5. Keywords

• Relevant Keywords : Including key terms that are central to the research topic helps with searchability and indexing.
• SEO-Friendly : Using keywords that align with what potential readers might search for increases the paper’s visibility.

6. Engagement

• Interest : The title should be engaging and interesting, encouraging readers to want to learn more about the study.
• Appeal : It should appeal to the target audience, whether they are academics, practitioners, or the general public.

How to Write a Research Title?

A well-crafted research title is crucial as it provides the first impression of your study. It should be concise, informative, and engaging to capture the reader’s attention while conveying the essence of your research. Here’s a step-by-step guide on how to write an effective research title.

1. Understand the Purpose of the Title

The title should:

• Summarize the main topic of the research.
• Indicate the scope and focus of the study.
• Reflect the methodology used (if applicable).
• Attract the target audience’s interest.

2. Identify the Key Components

To create a comprehensive title, identify the following components of your research:

• Main topic : The primary subject or focus.
• Variables : Key elements or factors studied.
• Population/sample : The group or sample studied.
• Methodology : The approach or techniques used in the research.

3. Be Clear and Specific

Avoid vague and ambiguous terms. Be precise in describing your research. For example, instead of “Study of Education Methods,” use “Effectiveness of Interactive Learning Techniques in High School Biology.”

4. Keep It Concise

A good title is typically between 10 to 15 words. It should be long enough to include essential information but short enough to be easily readable.

5. Use Descriptive Words

Use words that describe the content and aim of your research effectively. Descriptive words help in making the title informative and engaging. Examples include “effects,” “analysis,” “evaluation,” “comparison,” etc.

6. Avoid Jargon and Abbreviations

Ensure that your title is accessible to a broad audience by avoiding technical jargon and abbreviations that might not be widely understood.

7. Consider the Audience

Think about who will be reading your research. Tailor your title to meet the expectations and interests of your target audience, whether they are academic peers, professionals, or the general public.

8. Reflect the Type of Study

Indicate whether the research is a review, case study, experiment, or theoretical analysis. This helps set the context for the reader. For example, “A Case Study on Renewable Energy Adoption in Urban Areas.”

9. Include Keywords

Incorporate relevant keywords that reflect the main themes of your research. This not only helps in search engine optimization but also makes your research easily discoverable.

10. Revise and Refine

Review your title for clarity, conciseness, and accuracy. Ask for feedback from peers or mentors to ensure it effectively represents your research.

FAQ’s

How should a research title be structured.

A research title should be clear, concise, and informative, often including the main variables, methods, and context of the study.

What are the key elements of a good research title?

Key elements include relevance, clarity, specificity, and the inclusion of main keywords related to the research topic.

Can a research title be a question?

Yes, a research title can be a question if it effectively conveys the research’s focus and intrigues the reader.

How long should a research title be?

A research title should be brief but descriptive, typically between 10 to 15 words, avoiding unnecessary jargon or overly complex terms.

Should a research title include keywords?

Yes, including keywords helps in indexing and searching, making it easier for others to find your research.

Can a research title change during the research process?

Yes, it can be refined or adjusted as the research progresses to better reflect the study’s findings and scope.

Should the research title reflect the research methodology?

It can, especially if the methodology is central to the study’s uniqueness or understanding, but it’s not always necessary.

How specific should a research title be?

A research title should be specific enough to give a clear idea of the study’s focus but not so detailed that it becomes cumbersome.

What makes a research title catchy?

A catchy research title is engaging, piques curiosity, and uses intriguing language while still being clear and informative.

Can humor be used in a research title?

Humor can be used if appropriate for the subject matter and audience, but it should not compromise clarity or professionalism.

Text prompt

• Instructive
• Professional

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The Savvy Scientist

Experiences of a London PhD student and beyond

Thesis Title: Examples and Suggestions from a PhD Grad

When you’re faced with writing up a thesis, choosing a title can often fall to the bottom of the priority list. After all, it’s only a few words. How hard can it be?!

In the grand scheme of things I agree that picking your thesis title shouldn’t warrant that much thought, however my own choice is one of the few regrets I have from my PhD . I therefore think there is value in spending some time considering the options available.

In this post I’ll guide you through how to write your own thesis title and share real-world examples. Although my focus is on the PhD thesis, I’ve also included plenty of thesis title examples for bachelor’s and master’s research projects too.

Hopefully by the end of the post you’ll feel ready to start crafting your own!

Why your thesis title is at least somewhat important

It sounds obvious but your thesis title is the first, and often only, interaction people will have with your thesis. For instance, hiring managers for jobs that you may wish to apply for in the future. Therefore you want to give a good sense of what your research involved from the title.

Many people will list the title of their thesis on their CV, at least for a while after graduating. All of the example titles I’ve shared below came from my repository of academic CVs . I’d say roughly 30% of all the academics on that page list their thesis title, which includes academics all the way up to full professor.

Your thesis title could therefore feature on your CV for your whole career, so it is probably worth a bit of thought!

My suggestions for choosing a good thesis title

• Make it descriptive of the research so it’s immediately obvious what it is about! Most universities will publish student theses online ( here’s mine! ) and they’re indexed so can be found via Google Scholar etc. Therefore give your thesis a descriptive title so that interested researchers can find it in the future.
• Don’t get lost in the detail . You want a descriptive title but avoid overly lengthy descriptions of experiments. Unless a certain analytical technique etc was central to your research, I’d suggest by default* to avoid having it in your title. Including certain techniques will make your title, and therefore research, look overly dated, which isn’t ideal for potential job applications after you graduate.
• The title should tie together the chapters of your thesis. A well-phrased title can do a good job of summarising the overall story of your thesis. Think about each of your research chapters and ensure that the title makes sense for each of them.
• Be strategic . Certain parts of your work you want to emphasise? Consider making them more prominent in your title. For instance, if you know you want to pivot to a slightly different research area or career path after your PhD, there may be alternative phrasings which describe your work just as well but could be better understood by those in the field you’re moving into. I utilised this a bit in my own title which we’ll come onto shortly.
• Do your own thing. Having just laid out some suggestions, do make sure you’re personally happy with the title. You get a lot of freedom to choose your title, so use it however you fancy. For example, I’ve known people to use puns in their title, so if that’s what you’re into don’t feel overly constrained.

*This doesn’t always hold true and certainly don’t take my advice if 1) listing something in your title could be a strategic move 2) you love the technique so much that you’re desperate to include it!

Thesis title examples

To help give you some ideas, here are some example thesis titles from Bachelors, Masters and PhD graduates. These all came from the academic CVs listed in my repository here .

Bachelor’s thesis title examples

Hysteresis and Avalanches Paul Jager , 2014 – Medical Imaging – DKFZ Head of ML Research Group –  direct link to Paul’s machine learning academic CV

The bioenergetics of a marine ciliate, Mesodinium rubrum Holly Moeller , 2008 – Ecology & Marine Biology – UC Santa Barbara Assistant Professor –  direct link to Holly’s marine biology academic CV

Functional syntactic analysis of prepositional and causal constructions for a grammatical parser of Russian Ekaterina Kochmar , 2008 – Computer Science – University of Bath Lecturer Assistant Prof –  direct link to Ekaterina’s computer science academic CV

Master’s thesis title examples

Creation of an autonomous impulse response measurement system for rooms and transducers with different methods Guy-Bart Stan , 2000 – Bioengineering – Imperial Professor –  direct link to Guy-Bart’s bioengineering academic CV

Segmentation of Nerve Bundles and Ganglia in Spine MRI using Particle Filters Adrian Vasile Dalca , 2012 – Machine Learning for healthcare – Harvard Assistant Professor & MIT Research Scientist –  direct link to Adrian’s machine learning academic CV

The detection of oil under ice by remote mode conversion of ultrasound Eric Yeatman , 1986 – Electronics – Imperial Professor and Head of Department –  direct link to Eric’s electronics academic CV

Ensemble-Based Learning for Morphological Analysis of German Ekaterina Kochmar , 2010 – Computer Science – University of Bath Lecturer Assistant Prof –  direct link to Ekaterina’s computer science academic CV

VARiD: A Variation Detection Framework for Color-Space and Letter-Space Platforms Adrian Vasile Dalca , 2010 – Machine Learning for healthcare – Harvard Assistant Professor & MIT Research Scientist –  direct link to Adrian’s machine learning academic CV

Identification of a Writer’s Native Language by Error Analysis Ekaterina Kochmar , 2011 – Computer Science – University of Bath Lecturer Assistant Prof –  direct link to Ekaterina’s computer science academic CV

On the economic optimality of marine reserves when fishing damages habitat Holly Moeller , 2010 – Ecology & Marine Biology – UC Santa Barbara Assistant Professor –  direct link to Holly’s marine biology academic CV

Sensitivity Studies for the Time-Dependent CP Violation Measurement in B 0 → K S K S K S at the Belle II-Experiment Paul Jager , 2016 – Medical Imaging – DKFZ Head of ML Research Group –  direct link to Paul’s machine learning academic CV

PhD thesis title examples

Spatio-temporal analysis of three-dimensional real-time ultrasound for quantification of ventricular function Esla Angelini  – Medicine – Imperial Senior Data Scientist –  direct link to Elsa’s medicine academic CV

The role and maintenance of diversity in a multi-partner mutualism: Trees and Ectomycorrhizal Fungi Holly Moeller , 2015 – Ecology & Marine Biology – UC Santa Barbara Assistant Professor –  direct link to Holly’s marine biology academic CV

Bayesian Gaussian processes for sequential prediction, optimisation and quadrature Michael Osborne , 2010 – Machine Learning – Oxford Full Professor –  direct link to Michael’s machine learning academic CV

Global analysis and synthesis of oscillations: a dissipativity approach Guy-Bart Stan , 2005 – Bioengineering – Imperial Professor –  direct link to Guy-Bart’s bioengineering academic CV

Coarse-grained modelling of DNA and DNA self-assembly Thomas Ouldridge , 2011– Bioengineering – Imperial College London Senior Lecturer / Associate Prof –  direct link to Thomas’ bioengineering academic CV

4D tomographic image reconstruction and parametric maps estimation: a model-based strategy for algorithm design using Bayesian inference in Probabilistic Graphical Models (PGM) Michele Scipioni , 2018– Biomedical Engineer – Harvard Postdoctoral Research Fellow –  direct link to Michele’s biomedical engineer academic CV

Error Detection in Content Word Combinations Ekaterina Kochmar , 2016 – Computer Science – University of Bath Lecturer Assistant Prof –  direct link to Ekaterina’s computer science academic CV

Genetic, Clinical and Population Priors for Brain Images Adrian Vasile Dalca , 2016 – Machine Learning for healthcare – Harvard Assistant Professor & MIT Research Scientist –  direct link to Adrian’s machine learning academic CV

Challenges and Opportunities of End-to-End Learning in Medical Image Classification Paul Jager , 2020 – Medical Imaging – DKFZ Head of ML Research Group –  direct link to Paul’s machine learning academic CV

K 2 NiF 4  materials as cathodes for intermediate temperature solid oxide fuel cells Ainara Aguadero , 2006 – Materials Science – Imperial Reader –  direct link to Ainara’s materials science academic CV

Applications of surface plasmons – microscopy and spatial light modulation Eric Yeatman , 1989 – Electronics – Imperial Professor and Head of Department –  direct link to Eric’s electronics academic CV

Geometric Algorithms for Objects in Motion Sorelle Friedler , 2010 – Computer science – Haverford College Associate Professor –  direct link to Sorelle’s computer science academic CV .

Geometrical models, constraints design, information extraction for pathological and healthy medical image Esla Angelini  – Medicine – Imperial Senior Data Scientist –  direct link to Elsa’s medicine academic CV

Why I regret my own choice of PhD thesis title

I should say from the outset that I assembled my thesis in quite a short space of time compared to most people. So I didn’t really spend particularly long on any one section, including the title.

However, my main supervisor even spelled out for me that once the title was submitted to the university it would be permanent. In other words: think wisely about your title.

What I started with

Initially I drafted the title as something like: Three dimensional correlative imaging for cartilage regeneration . Which I thought was nice, catchy and descriptive.

I decided to go for “correlative imaging” because, not only did it describe the experiments well, but it also sounded kind of technical and fitting of a potential pivot into AI. I’m pleased with that bit of the title.

What I ended up with

Before submitting the title to the university (required ahead of the viva), I asked my supervisors for their thoughts.

One of my well intentioned supervisors suggested that, given that my project didn’t involve verifying regenerative quality, I probably shouldn’t state cartilage regeneration . Instead, they suggested, I should state what I was experimenting on (the materials) rather than the overall goal of the research (aid cartilage regeneration efforts).

With this advice I dialled back my choice of wording and the thesis title I went with was:

Three dimensional correlative imaging for measurement of strain in cartilage and cartilage replacement materials

Reading it back now I’m reminder about how less I like it than my initial idea!

I put up basically no resistance to the supervisor’s choice, even though the title sounds so much more boring in my opinion. I just didn’t think much of it at the time. Furthermore, most of my PhD was actually in a technique which is four dimensional (looking at a series of 3D scans over time, hence 4D) which would have sounded way more sciency and fitting of a PhD.

What I wish I’d gone with

If I had the choice again, I’d have gone with:

Four-dimensional correlative imaging for cartilage regeneration

Which, would you believe it, is exactly what it states on my CV…

Does the thesis title really matter?

In all honesty, your choice of thesis title isn’t that important. If you come to regret it, as I do, it’s not the end of the world. There are much more important things in life to worry about.

If you decide at a later stage that you don’t like it you can always describe it in a way that you prefer. For instance, in my CV I describe my PhD as I’d have liked the title to be. I make no claim that it’s actually the title so consider it a bit of creative license.

Given that as your career progresses you may not even refer back to your thesis much, it’s really not worth stressing over. However, if you’re yet to finalise your thesis title I do still think it is worth a bit of thought and hopefully this article has provided some insights into how to choose a good thesis title.

My advice for developing a thesis title

• Draft the title early. Drafting it early can help give clarity for the overall message of your research. For instance, while you’re assembling the rest of your thesis you can check that the title encompasses the research chapters you’re included, and likewise that the research experiments you’re including fall within what the title describes. Drafting it early also gives more time you to think it over. As with everything: having a first draft is really important to iterate on.
• Look at some example titles . Such as those featured above!
• If you’re not sure about your title, ask a few other people what they think . But remember that you have the final say!

I hope this post has been useful for those of you are finalising your thesis and need to decide on a thesis title. If you’ve enjoyed this article and would like to hear about future content (and gain access to my free resource library!) you can subscribe for free here:

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Writing Clear Science

Learn to write clearly and succinctly, without sacrificing the accuracy of your topic..

How to write good research paper titles

Your title is the first and most important step in engaging your reader. It should be concise, interesting and summarise the essential content of the document. Any title that is lengthy, overly complex, ambiguous or misleading can turn away prospective readers. This writing guide gives an overview of the different types of titles and explains the essential steps in designing your title.

Title structure

Titles can be sentence fragments, complete sentences or compound sentences with the second sentence typically following a colon.

To help the paper appear in search results, it is common practice to place keywords in the title. Keywords used in the title should be placed in the beginning in case only a fragment of the title appears in the search results. 

Terms used to describe types of titles

Common terms used to describe different types of research paper titles are Descriptive, declarative, interrogative, suggestive, humorous and combination titles.

Descriptive titles or indicative titles

Descriptive titles state the subject, topic, design, purpose or methods of the project. For example:

• ‘Effects of natural forest and tree plantations on leaf-litter frog assemblages in Southern Brazil.’ ( Cicheleiro et al. 2021 ).
• ‘An efficient incremental learning mechanism for tracking concept drift in spam filtering.’ ( Jyh-Jian et al. 2017 ).

Declarative or Informative titles

These titles give the main findings or result of the study. For example:

• ‘Novel flight style and light wings boost flight performance of tiny beetles.’ ( Farisenkov et al 2022 ).
• ‘Cause of hypereosinophilia shows itself after 6 years: Loa loa.’ ( Hicks et al. 2022 ).

There is some concern that presenting the results or conclusions in the title of a paper will appear presumptive: that titles containing a definitive statement or final conclusion of a study, might prove problematic if that finding is later disproved.

Some journals prefer informative titles. For example, the Journal of Clinical Epidemiology has “… an editorial policy of “more informative titles” (MITs) that crisply and concisely tell our readers what our authors found in their research. A MIT states the study type and summarizes its key findings, using the past tense for individual studies and the present tense for systematic reviews .” The idea is that titles for small individual studies should be written in past tense to allow future studies to overrule or disagree with their findings, while titles should be written in present tense for studies that are unlikely to be over-ruled by later studies: i.e. literature reviews. Some research has also demonstrated that “articles with short titles describing the results are cited more often.” ( Paiva et al. 2012 ).

Interrogative titles

Interrogative titles or titles phrased as a question. The use of questions in titles can create interest by making the reader immediately wonder what the answer might be. It is also a concise way of presenting the research topic.

For example:  

• ‘Does adding video and subtitles to an audio lesson facilitate its comprehension?’ ( Zheng et al. 2022 ).
• ‘Microbial defenses against mobile genetic elements and viruses: Who defends whom from what?’ ( Eduardo et al. 2022 ).

Suggestive titles

These are titles that are slightly ambiguous or overly brief to hint or suggest what the findings might be, presumably to create suspense to entice the reader to find out what the answer is. For example:

• ‘Drawing to improve metacomprehension accuracy’. ( Thiede et al. 2022 ).
• ‘The puzzle of high temperature superconductivity in layered iron pnictides and chalcogenides.’ ( Johnston 2010 ).

Humorous or colloquial title

These are titles that hope to attract interest through humour or common-use sayings, colloquialism or metaphors. These types of titles can be used to good effect. However, be mindful that colloquialisms might not make sense to readers from different language or cultural backgrounds.

For example:

• ‘miR miR on the wall, who's the most malignant medulloblastoma miR of them all?’ ( Wang et al 2018 ).
• ‘One ring to multiplex them all’ ( Torres-Company 2017 ).
• ‘Sauropod farts warmed the planet.’ ( Marshall 2012 ).

Combination titles

Combination titles are those that include a combination of different types listed above.

The following example uses a colloquialism in the key title with the findings mentioned in the sub-title:

• ‘Standing out in a crowd: Intraspecific variability in dorsal patterning allows for photo-identification of a threatened anuran.’ ( Gould et al. 2021 ).

The following example has the following structure: ‘Topic: results of study’

• Plastic Pollution in the World's Oceans: More than 5 Trillion Plastic Pieces Weighing over 250,000 Tons Afloat at Sea ( Eriksen et al. 2014 ).

Which type is better?

There are conflicting views which type of title is better. There are arguments for and against different types, with research findings presenting the pros and cons of different types of title. Before you decide which is best, first look at how titles are commonly structured in recently published journals within your discipline.

Essential steps in designing your title

The following steps will help you design your document title.

1. Read the Instructions to Authors

Once you have selected a journal, review the types of titles recently published and read the Instructions to Authors to learn what the journal requires for paper titles. Instructions regarding titles are often brief. For example:

- Elsevier’s Guide for Authors “Title - Concise and informative. Titles are often used in information-retrieval systems. Avoid abbreviations and formulae where possible.”

- Plos One Submission Guidelines state that titles should be “…Specific, descriptive, concise, and comprehensible to readers outside the field.” and “…written in sentence case (only the first word of the text, proper nouns, and genus names are capitalized). Avoid specialist abbreviations if possible. For clinical trials, systematic reviews, or meta-analyses, the subtitle should include the study design.”

2. Consider your audience

Although the expected audience is broadly set by the scope of the journal, you still need to identify who will be interested in your paper. Who is your target audience? Are they scientists who mostly work in your field or will they include researchers from other disciplines? Consider what aspects of your project would attract your target audience and whether or not you can include these in your title.

3. Decide what aspects of your study to include in your title

As outlined above (Types of titles) decide whether you want to describe the process (descriptive) the result (informative) the research question or problem (integrative) or a combination of these factors.

Description of methods and study design

Titles of research papers, reports and conference proceedings often contain standard research methods. For example:  

• ‘Plant-based diets and incident cardiovascular disease and all-cause mortality in African Americans: A cohort study.’ ( Weston et al. 2022 ).
• ‘Using scale modelling to assess the prehistoric acoustics of Stonehenge.’ ( Cox et al. 2020 ).
• ‘The use of chronosequences in studies of ecological succession and soil development.’ ( Walker et al 2010 ).

Description of study subjects and location

Titles often just describe the key study subject, and also often including habitat or location. For example: 

• ‘Making (remote) sense of lianas.’ ( van der Heijden 2022 ).
• ‘The vulnerability of native rangeland plant species to global climate change in the West Asia and North African regions’ ( Ouled Belgacem & Louhaichi 2013 ).

How specific or general should your title be?

Your title should be unique to your project. Hopefully, no one else is writing a paper exactly the same as you, and your title should reflect this. If your title is too broad or general, then you may give the impression that the study is larger than it is or that it is a literature review.  This is when it is important to make a distinction between ‘topic’ (general) and ‘title’ (specific). Unless you are writing a literature review or presenting a large-scale study, don’t give your research topic as your title.

Including information on the scope of the study will also help the reader understand the magnitude of your study and from this, the importance and implications of the findings. In the following example, “in highway bridges” gives the scope of the study:

• ‘Finite element based fatigue assessment of corrugated steel web beams in highway bridges.’ ( Wang & Wang 2015 ).

Avoid making your title too long with too much specific detail. For example, perhaps this title is too long:

• ‘Use of open-text responses to recode categorical survey data on postpartum contraception use among women in the United States: A mixed-methods inquiry of Pregnancy Risk Assessment Monitoring System data.’ ( Richards et al, 2022 ).

4. Consider your reader’s behaviour

Assume your reader only has a short time to decide if your title is relevant and that they will only review the abstract if the title interests them. Titles that include standard procedures, common cause-effect scenarios or well-known research topics, might be overlooked in preference for titles describing unique approaches or interesting findings.

5. Check that your title is clear and easy to read 

Your main message must be clear. Your titles don’t have to be grammatically-complete sentences, but make sure they make sense, especially if you have tried to shorten them by cutting out words. Don’t sacrifice clarity for brevity by making your title obscure.

Beware of using adjectival-noun strings in your titles. This is when authors try and be more concise by placing too many adjectives in front a single noun making it difficult to decipher whether each adjective is actually modifying the root noun or another word in the adjectival-noun string. Take an example from a student report: ‘ Australian insecticide control failure .’ (Anon.) This might be interpreted as:

• The failure of insecticide to control something in Australia.
• The failure of Australian insecticide to control something somewhere else.
• The failure to control [the use of] Australian insecticide.

Another unclear example: ‘Post head emergence spring radiative frost damage of winter cereals.’ (Anon.) It could be made even longer: ‘Winter cereal post head emergence spring radiative frost damage.’ 

6. Check your title length  

The shorter the title, the easier it will be to read but only to a certain point. Too short and you risk sacrificing your meaning. Also, If you leave out too much detail, the title may appear too general and mislead the reader. If the reader has to guess what the meaning, you increase the chance of losing them. Check that your title is not too ambiguous, cryptic or inadvertently misleading. An ambiguous media release example:

• ‘Lupins show healthy potential for increased human consumption.’ ( Australian Food News 2008 ).

7. Check that your title is concise

Titles can be made more concise by removing unnecessary repetition and detail. Common research phrases can be removed without affecting the meaning or structure of the title. Examples of these research phrases include ‘The influence of...’, ‘The role of..’, ‘Effects of..’, ‘Observations of..,’ ‘Studies on...’

For example: ‘Annual variation in the distribution of summer snowdrifts in the Kosciuszko alpine area, Australia, and its effect on the composition and structure of alpine vegetation.’  ( Edmonds et al. 2006 ) [25 words] could be reduced to: “Distribution of summer snowdrifts influences composition and structure of Kosciuszko alpine vegetation, Australia” [13 words].  

8. Ways to make your title more interesting

Ask a question

By writing a title in the form of a question you are immediately inviting the reader to think. For example:

• ‘Whose shoulders is health research standing on? Determining the key actors and contents of the prevailing biomedical research agenda.’ ( Testoni et al. 2021 ).

Be humorous or focus on the unusual or unexpected

Mildly humorous titles immediately engage the reader while unusual or unexpected tiles create curiosity.

• ‘On human odour, malaria mosquitoes, and Limburger cheese.’ ( Knols 1996 ).

Final considerations

My key advice is, ensure your title is concise, easy to read (for your target audience), not too long and adequately reflects your study’s design or purpose (not too general or too specific).

• Is it hard to read?
• If it is a question, does it make your reader wonder what the answer is?
• If it is a summary of your methods, are these methods unique or reveal a fresh approach or are they just standard and well-known and therefore unlikely to stand-out?
• If it is the answer or conclusion to your problem, are you risking letting the reader think they now don’t need to read the paper? Or might your conclusion-title be a way to hook your reader into finding out more about your study?
• Does it create interest or curiosity?

© Dr Marina Hurley 2022 www.writingclearscience.com.au

Any suggestions or comments please email  [email protected] 

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