Evolution of the Problem Statement: From Arriving at it to Solidification

Research involves a number of activities. 

  • The first step is to identify a problem statement. This should be clear, concise, and accurate; it should also include the question that you want to answer.

  • The second step is to define the scope of your research. This means defining the limits of your study, including the population you are studying and any other relevant limits. For example, if you are conducting a survey, you need to make sure that you are only surveying people who live in your area.

  • The third step is to design the research. This involves planning out how you will collect data, analyze results, and write up your findings. It also involves choosing the appropriate method(s) for collecting data and deciding whether or not to use an experiment or observational study. These decisions can be based on a variety of factors, such as cost, time, amount of participants required for the study, feasibility, ethics considerations, etc.

  • The fourth step is to conduct the research. This involves actually collecting data and analyzing it once it has been collected. You will also need to write up your findings in a report or article that includes all relevant information.

A problem statement is the thesis’s introductory sentence that states the thesis’s overall purpose. It should be focused, concise, and unambiguous. While it can be a topic sentence (as in the case of a book review), it doesn’t have to be.

It should encapsulate the main argument or insight of your thesis and, ideally, be able to stand on its own. It should also capture the reader’s attention by opening with an interesting hook or strong statement of purpose.

The problem statement sets a clear goal for your research, which will guide your writing process and keep you focused on what matters most: presenting your findings in an engaging manner.

Arriving at the Problem

The foremost concern of any researcher’s quest is to find and delineate exactly what the researcher wants to solve and the questions he or she should answer to arrive at a solution. In other words, the research problem provides for a concern or a gap in the existing body of knowledge that brings out intriguing questions and is pertinent enough to be investigated in order to find a solution or address the problem, hence, it is the primary reason why you are pursuing the research. 

  • Cause and effect: The research problem should consist of a cause and an effect. The   statement could describe a loss or a missed opportunity and indicate a cause for the loss and the missed opportunity. The problem statement should describe the cause of the problem and the effect that has been caused. This means it should contextualize the reason why the problem exists in the first place and the researcher should opt for the reason that seems the most likely or compelling and how this particular cause affects the environment of study. The researcher should be aware of the various causes that might produce the same effect which is why an astute reference to research literature is necessary to focus on the right relationship between that cause and the effect. 

  • Guidelines: The problem statement selection should be guided by some essential aspects – the research problem should be something that the researcher is interested in and it should be possible to be efficiently and effectively pursued. The problem you have undertaken could have an earlier setting, in which case you should ensure that it either rectifies an issue in the earlier problem or brings out a new aspect of the problem unexplored hitherto. 

  • What it should do: The problem statement should be able to address a gap in knowledge and while addressing the gap should contribute to the existing body of knowledge. The problem statement should be able to provide scope for future research and can be of utility to policy formulation in your domain of study, this will pique interest in your research. The research problem should also ensure that data is available on the matter that it concerts and is promptly available or accessible. The problem should address ethical issues that could arise in its study and how your research will redress the concerns in pursuit of the problem. 

Evolving and solidifying of the problem

The statement of the problem briefly addresses the question – “What is the problem that the research will address”?”

How the researcher should evolve it – the problem statement should be molded into a concise sentence(s) that is a targeted and well-defined statement which can be easily understood and explored with understanding of its significance to what is being studied. It should practically provide the reader with a clear purpose if the research you are pursuing. 

  • Contextualize the problem: The problem should be formulated with a clear, concise and insightful background of the problem dealing with answers to questions like how the problem has been created (cause), what is the effect of the problem (effect) and has there been any practical approach to solving the problem earlier, if so detail the extent of its success and how it can be improved. 

  • The definition of the problem: The problem should effectively be described in a few lines, in a manner that the reader can understand the problem by reading the statement.
  • Relevance of the problem or why it should be addressed: This part of the problem statement should clarify the research into this problem is a necessary to the study domain of your research – the researcher should be aware that it is not necessary that the problem you are trying to research is ground-breaking or going to herald in an unfounded exploration into a topic in your field, what is more important is that it is practical, valid, feasible and relevant to your field of research. 

  • The problem statement should also be able to address the problem and should delve into an intro to methodology and how you plan to pursue the problem in your thesis. The research objectives are further elaborated from this which presents how you will achieve this.

Chaptering Your Research Paper: Writing the Discussion Section

The discussion section is the last part of a research paper, in which an author describes, analyzes, and interprets their findings, explaining their significance and connecting everything back to the research questions by focussing on the results and outcomes of your study. It usually follows the chapters on methodology and results and comes prior to the final chapter or conclusion. The discussion section also answers the question regarding the meaning, importance, and relevance of your results in the light of the literature that was already explored and discusses the new insights about the research problem that you have obtained from the findings of your research.

Constituents of the discussion chapter

At the beginning of each discussion, remember to recap the introduction and review the literature in detail, but don’t just repeat it; rather, use the discussion to explain how your study has moved the reader’s understanding of the research problem forward by expanding on your outcomes in the results or findings section and how it has helped shape the understanding of the research problem. The discussion comprises a list of essential ingredients which are to be effectively included to write the perfect discussion section for your research paper. 

The discussion section includes 

  • The most important findings of your research which is a summary of the major findings and a recap of your research problem and link research findings with the research questions

  • The significance of these findings where you will have to provide your interpretations and identify the patterns, principles, and relationships shown by each major findings and place them in proper perspective in relation to your collected data and place these findings in context by analyzing your literature review to understand and evaluate how your results from the study aligns with the earlier research you have reviewed.  

  • When detailing your findings and its relationship to existing literature, you have to highlight any unexpected results and clearly explain them to help the reader understand why such findings might have been produced and is it relevant to the research problem directing the scope of research, if yes, explain the significance. 

  • When explaining the implications of your research, connect it to the existing literature and explain how your findings are relevant to the body of knowledge and what are the new insights that your research has uncovered which has been previously overlooked or unfounded and how this contribution is beneficial to the discipline of study.

  • Researchers often use this section to underline the limitations of their research and also the strengths. The primary reason is that a researcher who acknowledges justifiable limitations improves the credibility of the work and shows that the avenue was not left unexplored or unknown but was intentionally omitted. Avoid using an apologetic tone; however, be honest and self-critical as it shows that you are critically aware of what your study can and cannot do. The researcher should also make clear that despite the explained limitations, why the study would be a valid research on solving the stated problem.

  • Towards the end of the discussion section provide a brief understanding of potential avenues within the research study that can be further explored by future researcher studies and can also elaborate on how this investigate study can be carried out. The ideas for future research should be concise and targeted at maybe one or two issues because it will not be appealing to uncover multiple plot holes in your research as it may affect the validity of your findings

  • The researcher can also provide an understanding of his or her ideas of practical implementation of their research work and explain why you believe the findings and conclusions of your study are important. 

Why is it important

Apart from the various constituents of the discussion section described above which adds to the quality of your research work, the discussion section is considered an integral part of your research as it assess you as a researcher because it directly demonstrates your ability to think critically, interpret and verify data and develop solutions to address problems that have directed the course of your research. This section helps the readers understand your researcher in detail and covers the most important part of how your researcher adds to the body of knowledge and how successful it has been in exploring the problem you have identified from the research gap that has existed. The discussion section provides you the opportunity to explore your research in depth by addressing the implications of your study. It provides the readers and researchers in your field with a critical overview of how your research can be further improved and provides a trajectory for future research.

This section highlights the importance of your research and how it has contributed to exploring the research gap you have identified in the beginning of your research. While stating this contribution, the researchers should be careful as to not reiterate everything they have already elaborated in the research findings but only state how your findings have analyzed the gaps in research that existing literature failed to address. The other major prominence it has over its relatively similar sections in the data analysis section is that it is not a platform to merely present data but rather provide evidence-based interpretations of the findings that have been uncovered thus providing a meaning to what your research has explored. 

What should I avoid?

The discussion chapter holds a great deal of importance in your research paper and the researcher should be aware of common mistakes and possible pitfalls that can be avoided while framing this section

  • Rewriting the results section: You should be careful when framing the section of your discussion and avoid rewriting your analysis and findings, the focus should be on interpretations instead of merely summarizing the findings , in case you do need to refer to a finding that will be discussed in the section, use “bridge sentences” that relate the result to the interpretation.
    • How to use bridge sentences: Example- “In investigating the availability of freshwater in the households of sector A, the findings suggest that at least 3/4th of houses…” – and continue with explaining the finding from there  

  • Include new arguments or evidence not previously discussed. The researcher should not bring in any new information that has not already been collected, confirmed and analyzed in the earlier sections of the research chapters. 

  • Drawing boundaries: the researcher should be able to deduct from the information available and derive explanations backed up by results which have been evidenced in your research paper and should stay within the confines of your subject discipline in all aspects of the discussion.

  • Guide the narrative flow with a precise structure,  clearly demarcate between the discussion and conclusion section. Researchers often write limitations section after the discussion in the conclusion, clearly structure the sequence prior to formulating the chapter. 

  • If presenting limitations and/or strengths in the discussion section itself, the researcher should be aware to not fundamentally corrupt the validity of the research and always be sure to back your research methodology and credibility of data and its analyzes. 

  • In the same way, a researcher should also not be hesitant to be honest and clear in stating the true nature of the limitations that the study has faced, avenues it has not explored – intentionally or because it did not have the resources to do so. Uncover potential bias, threats to internal or external validity and such issues that could affect the study design without coating it. 

  • When presenting the discussion, the researcher should also present the findings that have not been helpful or results that are unfavorable and present only those that support your research questions. The researcher should also be careful in identifying the importance of the study so as to not make grand statements of your research study’s capabilities to solve issues that are not necessarily in the realm of your research. 

Threats to Internal Validity – PhD Research Design Assistance

We will now consider several potential threats to the internal validity of a study. The confounds described here are those most encountered in psychological research; depending on the nature of the study,other confounds more specific to the type of research being conducted may arise. The confounds present here will give you an overview of some potential problems and an opportunity to begin developing the critical thinking skills involved in designing a sound study. These confounds are little problematic for nonexperimental designs but may also pose a threat to experimental designs. Taking the precautions described here should indicate whether or not the confound is present in the study.

 Nonequivalent control group. One of the most basic concerns in an experiment is that the subjects in a control and experimental groups are equivalent at the beginning of the study. For example, if you wanted to test the effectiveness of a smoking cessation program and you compared a group of smokers who voluntarily signed up for the program to a group of smokers who did not,the groups would not be equivalent . They are not equivalent because one of the group chose to seek help , and this makes them different from the group of smokers who didn’t seek help.They might be different in a number of ways. For example they might be concerned with their health . The point is that they differ, and thus, the groups are not equivalent. Using random sampling and random assignment are not used ,subject selection or assignment problems may result. In this case we would have a quasi-experimental design(discussed in chapter 13), not a true experiment.

History. Changes in the dependent variable may be due to historical events that occur outside of the study,leading to the confound known as history effect.These events are most likely unrelated to the study but nonetheless effects of a certain program on stress reduction in college reduction. The study covers a 2 month period during which students participate in your stress-reduction program. If your posttest measures were taken during midterm or final exams, you might notice an increase in stress even though subjects were involved in a program that was intended to reduce stress. Not taking the historical point in the semester into account might lead you to an erroneous conclusion concerning the stress-reduction program. Notice also that a control group of equivalent subjects would have helped reveal the confound in this study.

 Maturation.In the research in which subjects are studied over a period of time, a maturation effect can frequently be a problem. Subjects mature physically,socially and cognitively during the course of study. Any changes in the dependent variable that occur across the course of the study, therefore,may be due to maturation and not to the dependent variable are due to maturation;if they are, the subjects in the control group will change on the dependent variable during the course of the study even though they did not receive the treatment.

Testing.In studies in which are measured number of times , a testing effect may be problem-repeated testing may lead to better or worse performance. Many studies involve pretest and posttest measures. Other studies involve taking measures on an hourly, daily ,weekly or monthly basis. In these cases, subjects are exposed to the same or similar “tests” numerous times. As a result, changes in performance on the test may be due to prior experience with the test and not to the independent variable.If, for example, subjects took the same math test before and after participating in a special math course, the improvement observed in scores might be due to the participants’ familiarity with and practice on the test items.This type of testing confound is sometimes referred as a practice effect.Testing can also result in the opposite of a practice effect, a fatigue effect(sometimes referred to as a negative practice effect).Repeated testing fatigues the subjects, and their performance declines as a result .Once again having a control group of equivalent will help to control for testing confounds because researchers will be able to see practice or fatigue effects in a control group.  

Regression to the mean. Statistical Regression occurs when individuals are selected for a study because their scores at some measures were extreme either extreme high or extreme low. If we study students that scored in the top 10% on the SAT and we retested them on SAT, then we would expect them to do well again.Not at all,however,would score as well as they did originally because of  Statistical Regression.often referred to as  regression to the mean – a threat to internal validity in which extreme scores,upon retesting , tend to be less extreme, moving towards the mean. In other words, some of the students did well the first time due to chance or luck. What is going to happen when they are going to take the test the second time?They will not be as lucky, as their scores will regress toward the mean.

 Regression to the mean happens in many situations other than research studies. Many people think that a hex is associated with being on the cover of Sports Illustrated and that an athlete’s performance will decline after appearing on the cover.This can be explained by regression of mean.Athletes most likely appear on the cover of sports illustrated after a very successful season or on the peak of their carrier. What is most likely to happen after athletes perform exceptionally well over a period of time? They are likely to regress toward the mean and perform in amore average manner(Cozby,2001). In a research study having an equivalent control group of subjects with extreme scores will indicate whether changes  in the dependent measure are due to regression  to the mean or to the effects of the independent variable.

Instrumentation. An instrumentation effect occurs when the measuring device is faulty. Problems of consistency in measuring the dependent variables are most likely to occur when the measuring instrument is an human observer.The observer may become better at taking measures during the course of the study or may become fatigued with taking measures. If the measures taken during the study are not taken consistently, then any change in the dependent variable may be due these measurement changes and not to the independent variable. Once again having a control group of equivalent subjects will help to identify the confound.

Mortality or attrition.Most research studies have a certain amount of Mortality or attrition(dropout).Most of the time, the attrition is across experimental and control groups. It is a concern to the researchers, however, when attrition is not equal across the groups. Assume that we begin a study with two equivalent groups of participants.If more subjects leave one group than the others, then the two groups of subjects are most likely no longer equivalent, meaning the comparisons cannot be between groups. Why might we have differential attrition between the groups?Imagine we are conducting a study to the effects of a program aimed at reducing smokes. We randomly select a group of smokers and then randomly assign half to the control group and half to the experimental group. The experimental group participants in our program reduce smoking, but the heaviest smokers just cannot take the demands of a program and quit the program. When we take a posttest measure on smoking, only those participants who were originally light to moderate smokers are left in the experimental group. Comparing them to the control group would be pointless because the groups are no longer equivalent. Having a control group to determine whether there is differential attrition across the groups.

Diffusion of treatment .When subjects in a study are in close proximity to one another, potential threat to internal validity is diffusion of treatment– observed changes in the behaviors of subjects may be due to the information received from other subjects. For example, college students are frequently used as participants in research studies. Because many students live near one another and share classes, some students discuss an experiment in which they participated . If the other students were planning to participate in the study in the future, the treatment has now been compromised because they know how some of the subjects were treated during the study. They know what is involved in one or more of the conditions in the study, and this knowledge may affect how they respond in the study regardless of the condition to which they are assigned. To control for this confound, researchers might try to test the subjects in a study in large groups or within a short time span so they do not have time to communicate with one another. In addition, researchers should stress to the subjects the importance of not discussing the experiment with anyone until it has ended.

Experimenter and Subject effects.When researchers design experiments, they invest considerable time and effort in endeavor.Often this investment leads the researcher to consciously or unconsciously affect or bias the results of the study. For example,a researcher may unknowingly smile more when subjects are behaving in the predicted manner  and frown or grimace when subjects are behaving in a manner undesirable to the researcher. This type of experimenter effect is also referred to as experimenter bias or expectancy effects (see chapter 4) because the results of the study are biased by the experimenter’s expectations.

Guide to ‘causal-comparative’ research design: Identifying causative relationship between an independent & dependent variable

Most often, in experimental research, when a researcher wants to compare groups in a more natural way, the approach used is causal design. On the other hand, in a non-experimental setting, if a researcher wants to identify consequences or causes of differences between groups of individuals, then typically  causal-comparative design is deployed.  

Causal-comparative, also known as ex post facto (after the fact) research design, is an approach that attempts to figure out a causative relationship between an independent variable & a dependent variable. It must be noted that the relationship between the independent variable and dependent variable is a suggested relationship and not proven as the researcher do not have complete control over the independent variable.

This method seeks to build causal relationships between events and circumstances. Simply said, it determines to find out the reasons/causes of specific occurrences or non-occurrences. Based on Mill’s canon of agreement and disagreement, causal-comparative research involves comparison in contrast to correlation studies which looks at relationships. 

For example, you may wish to compare the body composition of individuals who are trained with exercise machines versus individuals trained only free weights. Here you will not be manipulating any variables, but only investigating the impact of exercise machines and free weights on body composition. However, since factors such as training programs, diet, aerobic conditioning affects the body composition, causal-comparative research will be assessed scrupulously to determine how the other factors were controlled. 

This research design is further segregated into:

  • Retrospective causal-comparative research –  In this method, a research question after the effects have occurred is investigated. The researcher aims to determine how one variable may have impacted another variable.  
  • Prospective causal-comparative research – This method begins with studying the causes and is progressed by investigating the possible effects of a condition. 

How to conduct causal-comparative research? 

The basic outline for performing this type of research is similar to other researches. The steps involved in this process are: 

  1. Topic selection – Identify & define a specific phenomenon of interest and consider the possible consequences for the phenomenon. This method involves the selection of two groups that differ on a certain variable of interest. 
  2. Review the literature – Assess the literature in order to identify the independent and dependent variables for the study. This process lets you figure out external variables that contribute to a cause-effect relationship.
  3. Develop a hypothesis – The hypothesis developed must define the effect of the independent variable on the dependent variable.
  4. Selection of comparison groups – Choose groups that differ in regards to the independent variable. This enables you to control external variables and reduce their impact. Here, you can use the matching technique to find groups that differ mainly by the presence of the independent variable. 
  5. Choosing a tool for variable measurement variables and data collection – In this type of research, the researcher need not incorporate a treatment protocol. It is a matter of gathering data from surveys, interviews, etc. that allows comparisons to be made between the groups.
  6. Data analysis – Here, data is reported as a frequency or mean for each group using descriptive statistics. This is followed by determining the significant mean difference between the groups using inferential statistics (T-test, Chi-square test). 
  7. Interpretation of results – In this step carefully state that the independent variable causes the dependent variable. However, due to the presence of external variables and lack of randomisation in participant selection, it is probably ideal to state that the results showcase a possible effect or cause.  

Flow chart 

So, when should one consider using this research design? 

Typically, causal-comparative research design can be considered as an alternative to experimental design due to its feasibility, cost-affordability and easy to perform the research. 

However, in causal-comparative design, the independent variables cannot be manipulated, unlike experimental research. For example, if you want to investigate if ethnicity affects self-esteem, you cannot manipulate the self-esteem of the participants’. The independent variable here is already selected, and hence, some other method needs to be utilised to determine the cause.

Threats to the internal validity of the research 

In this type of research, since the participants are not randomly selected and placed in the groups, there is a threat to internal validity. Another threat to internal validity is its inability to manipulate the independent variable. 

In order to counter the threats and strengthen the research, impose selection strategies of matching utilising ANCOVA or homogeneous subgroups. 

Causal-comparative design includes basic features such as:

  • Involves selection of two comparison groups (experimental & control group) to be studied
  • Includes making comparisons between pre-existing groups in regards to interested variables 
  • Studies variables which cannot be manipulated for practical or ethical reasons
  • Consumes reduced amount of time and cost

Although this approach gives an opportunity to analyse data on the basis of your personal opinion and come out with the best conclusion, while predicting the relationship, you might fall to post hoc fallacy. Therefore, pay extra attention while predicting the relationship and then arrive at a conclusion.

5 ways how research in particle physics is transforming the world around us

The research in particle physics not only pushes the boundaries of science but looks forward to benefiting society by generating knowledge as well as by developing unexpected and transformative applications. 

Particle physics is often referred to as High Energy Physics (HEP). This is so because the probing of matter on the smallest distance scales would require the application of the highest particle collision energies. 

Particle physics seeks to understand the evolution of the Universe in terms of a small number of fundamental particles and forces after its birth in the Big Bang; the processes that led to our existence. 

Today, particle physics is at an exciting threshold. The intellectual curiosity embedded in particle physics is at the foundation of art, philosophy, and other scientific disciplines, which have shaped the modern world. 

Modern particle physics has its origins in theoretical developments and discoveries that have shaped the modern science. Several advances in molecular biology, chemistry, genetics and materials science, etc were predicated on the basis of discovery of the electron, quantum theory, analytical probes including X-rays and nuclear-based techniques. Particle physics experiments  generate new technical approach and are in demand in terms of equipment design. 

 The discovery of novel, long-lived charged particles that catalyses magnetic monopoles, or nuclear fusion, to catalyse proton decay, have the potential to offer an unlimited supply of high energy. As particle physics experiments explore natural environment under extreme conditions, they need innovative technologies which finds its application in transforming the way we live. 

  1. Accelerator application – Particle accelerator has been considered as a key tool in medicine for more than three decades. Today, there are more than 10,000 accelerators operating in medical research facilities and various hospitals worldwide. Driven by the demands of experiment in this field, innovations in accelerator design continues to find medical applications. 
  2. Computing application – Latest computing technique is an integral part of all basic research, especially in physics. They normally deal with systems that are quite complex and can be applied to complex systems in the life sciences as well.
  3. Medical imaging – Plenty of latest silicon devices, including the Medipix hybrid pixel detector produced by a CERN collaboration will lead to faster CT-scanning and X-ray imaging. Here we can obtain clearer images at relatively lower X-ray doses and can be utilised to observe cancer therapy in real time. Although charge coupled devices (CCDs), originally created for applications in particle physics and astronomy, are now used in dental X-ray machines. Being developed for the ILC (p7), the new generation of large-area X-ray detectors can be employed to image the heart, etc. In addition, gas-filled particle detectors can be implemented in a new whole body PET scanner, which is considered to be significantly quicker and cheaper than the current PET systems. 
  4. Electronics – The need for rapid data accumulation in a high-radiation environment has led to significant collaborations with electronics manufacturing. This in turn, has resulted in major improvements in chip designs. For instance, highly parallel, radiation-hard, three-dimensional chips, and connectors that enable data acquisition and fast read-out.
  5. National security – Particle detectors can be utilised to monitor nuclear reactor cores as well as determine if the weapons-grade enriched uranium or plutonium are present. In addition they can be used to detect radioactive elements at airports and other entry points into the country. 

Researchers are working on particle physics to exploit it to the fullest. Some of the latest research in this field include: 

  • Testing the standard model – Electroweak theory describing the weak forces, the gauge theory of the strong force, electromagnetic, and quantum chromodynamics, together form the standard model. This model offers an organising framework for the purpose of classification of the known subatomic particles. It can be measured by means of present technology. However, several elements are still under experimental verification or clarification.
  • Testing supersymmetry – With several researches being conducted in particle physics, the major experiment that has gained immense attention is focus is testing of supersymmetry. This test reveals the impact that lies outside the standard model, in particular, those that are a result of supersymmetry. This study also include measurements based on millions of Z-particles. 
  • Investigating neutrinos – Researchers are conducting experiments detect the masses of three neutrinos. The outcome of the experiment has given no sign of mass of specific neutrino. Other researches have measured neutrino mass indirectly by inspecting if the neutrinos can change from one type to another. 

Other present research includes the search for a new state of matter known as the quark-gluon plasma. 

What is new & unique to particle physics is the scale of the science. That is the size,complexity not only of detectors & accelerators but also of scientific collaborations.

World has always gained crucial advantages both directly & indirectly from the pursuit of particle physics. The challenges of this field are unprecedented and stimulating to develop new ideas, technologies leading to quantifiable improvements.