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Busted: 5 Academic Writing Myths You Must Know About

Academic writing, much like any other form of writing, is a demanding endeavour that requires patient and diligent hard work. It can take the average scholar up to two or three years to learn and sharpen the various skills and intellectual proficiencies associated with good academic writing.

Now, although polished academic writing skills and techniques can only be developed and mastered over time, there are a few practical guidelines that can help you accelerate this process. With this in mind, here are 5 of the biggest academic writing myths that you must absolutely steer clear of:

Myth #1: Academic writing is a linear process

There is much discussion about good academic writing practices, with many scholars and educators often talking about the various merits and demerits of a certain writing process. In fact, a quick internet search can fetch you numerous results that proclaim to teach you ‘everything you need to know about academic writing’. However, many writers still find themselves stumped when it comes to writing their academic papers. The reason for this is pretty simple – writing is not a linear process.

Unfortunately, there is no explanatory diagram or step-by-step flowchart that you can follow in order to become a seasoned academic writer. Instead, the actual writing process involves constantly modifying your work, jumping between multiple sections of your paper in order to make it more coherent. So, if you ever find yourself editing and re-editing your thesis statement midway through writing your paper, fret not – you are not the only one.

Myth #2: Writing skills are more important than reading and researching skills

Writing skills go hand-in-hand with reading and researching skills. To improve upon one of these areas, you will invariably have to improve upon the others too. Even if you possess good writing skills, it does not necessarily mean that you will become a good academic writer in case your reading and research skills are not up to the mark. After all, you first need to be able to fully understand what you are reading in order to interpret it and paraphrase it successfully.

So, a good idea is to always begin by understanding the aim and scope of a given academic assignment, followed by researching it thoroughly. Once you have understood the general idea and have sufficient and relevant matter at hand, it will be easier to intuit and write the rest of the assignment with common sense, practice and some helpful guidance on good academic writing practices.

Myth #3: An introductory writing course is enough instruction

Some scholars, and even educators, for that matter, believe that an introductory writing course is enough to arm oneself with the required know-how towards writing an academic paper. However, nothing could be further from the truth.

Writing is a lifelong endeavour that involves constant learning and improvement. Assuming that a mere introductory course will make you a better academic writer is just folly on your part. A certain instruction course might be able to help you with a specific assignment, but this does not mean that it will provide relevant assistance with your next assignment too. So, be prepared to work hard on every assignment that you receive over the course of your academic tenure, rather than wrongfully assuming that you have learnt everything by attending a single introductory writing course.

Myth #4: Good grammar is good writing

Some individuals are convinced that drilling grammar into their assignments is an easy fix towards attaining desired outcomes. While grammatical correctness is indeed important, it is definitely not the ‘be-all’ and ‘end-all’ of academic writing. After all, good writing is about more than just good grammar. Most importantly, it is about achieving a desired effect upon the target audience. A well-written academic paper should be able to clearly communicate its intended message to the reader.

So, concentrate on your grammar to a fair extent, ensuring that your academic paper is devoid of glaring mistakes that would render it incoherent. However, equal attention should be paid towards assessing the assignment tasks and guidelines appropriately, and conducting your research accordingly.

Myth #5: Writing perfect first drafts

Many scholars are guilty of having too many expectations from early drafts. However, it is unrealistic to expect that you will write a perfect academic paper on your very first attempt. If you try to do so, chances are high that you will either overwork yourself trying to achieve the near-impossible task of creating an immaculate first draft, or you will get frustrated and give up altogether.

Remember, there is hardly anyone who writes perfect first drafts. The sheer scope of subjects, genres and fields of study present means that writing different academic papers requires a different approach each time. For instance, a scholar who has written an exceptionally good academic paper on English Literature might not necessarily turn in a well-written paper on Psychology too. So, do not beat yourself up if that first draft is not up to the standards you have set for yourself. With concentrated effort and study, you will gradually improve as an academic writer indeed.

Conclusion

Ultimately, academic writing can appear to be quite intimidating for most to even begin with. Moreover, the aforementioned myths can hinder scholars from appreciating and learning this art to an even bigger extent. Ideally, this article should be successful in debunking these harmful myths to give you a more comprehensive understanding of academic writing – and how you can excel at it.

Working Title, Selecting topic for PhD Research

Before considering what literature to use, first identify a topic to study and reflect on whether it is practical and useful to undertake the study. The topic in the subject or subject matter of a proposed study. Such as “faculty teaching,” “organizational creativity,” or “psychological stress.” Describe the topic in a few words or in short phrases. The topic becomes the central idea to learn about or to explore.

There are several ways that researchers gain some insight into their topics when they are initially planning their research (my assumption is that the topic is chosen by the researcher and not by an adviser or committee member). One way is to draft a brief working title to the study. I am surprised at how often researchers fail to draft a title early in the development of their projects. In my opinion, the working or draft title becomes a major road sign in research-a tangible idea that the researcher can keep refocusing on and changing as the project goes on (see Glesne & Peshkin, 1992). It becomes an orienting device. I find that in my research, this topic grounds me and provides a sign of what I am studying, as well as a sign useful for conveying to others the central notion of my study. When students first provide their research project idea to me, I often ask them to supply a working title if they do not already have one written down on paper.

How to keep your thoughts organized while writing a thesis?

When it comes to academic writing, the main purpose of the writer is to deliver an impression on the reader that confirms his intellect as well as the comprehensibility of the writer. Academic writing could sound to be more than a headache for some students, and this is where the academic writing services can help them secure the level of grades they are looking for. It takes time in developing an understanding as to the requirements of a thesis.

Here are some helpful tips that can enhance your focus during thesis writing:

The first step to writing the perfect thesis is analyzing the materials you already have. It means that you need to take a good look at all of the information you have on your subject, including your textbook materials, lecture notes, and course handouts. Your instructor will usually point out exactly what is expected of you. Students tend to neglect this and, as a consequence, they feel stressed out.

Secondly, you need to develop an understanding about the topic of your research paper. It means that you should know what the main topic of your thesis is and how it sounds to you. Moreover, the thesis should be interesting to you so that you could work hard in researching for the same. Another critical factor to include is the originality that never should be gone without.

Now, the next thing is the amount of evidence required to assert your thesis. You should have collected and documented a sufficient amount of evidence regarding your thesis so that you could create a valid impression with those who disagree with you. It involves choosing your evidence with utmost care after confirming its validity to assert your point.
Referencing and quoting is an essential element of an academic paper. The paper should never be filled with lots of quotations otherwise it would sound quite fluffed.Giving less than the required amount of quotations might lead you to lower grades as it indicates that you haven’t carried out extensive research.

There are tons of resources to research information from aside from the Internet. Look for previous research papers that are usually available in the library. Or check out magazine and journal databases, newspaper and newslists, blogs, among others which you find convenient and useful. You must stick to your mind that what you will gather should support your thesis and build a case about your point of view. Never forget to cite the source.

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.

Experimental Design Research Methodology – Between-Subjects Experimental Designs

In a between-subjects design, the subjects in each group are different; that is, different people serve in the control and experimental groups. The idea behind experimentation, is that the researcher manipulates at least one variable (the independent variable) and measures at least two groups or conditions. In other words, one of the most basic ideas behind an experiment is that there are at least two groups to compare. We typically refer to these two groups or conditions as the control group and the experimental group. The control group is the group that serves as the baseline or “standard” condition. The experimental group is the group that receives some level of independent level. Although we describe the two groups, an experiment may involve the use of two experimental groups with no control group. In other words, there can be multiple experimental groups in experiments.

Experimentation involves control. First, we must control who is in the study. We want to have a sample that is representative of the population about whom we are about to generalize. Ideally, we accomplish these pates in each condition in each condition, so we should use random assignment of subjects in two conditions. By randomly assigning participants to conditions, we are trying to make two groups as equivalent as possible. In addition to controlling all of this, we observe behavioural changes when the independent variable is manipulated, we can then conclude that the independent variable caused these changes in dependent variable.

Let’s consider the example of smoking and cancer to examine the difference between correlational research and experimental research. Remember, we said that there are positive correlational between smoking and cancer. We also noted that no experimental with human supported a causal relationship between smoking and cancer. Why is this case? Let’s think about trying to design an experiment determine whether smoking causes cancer in Humans. Keep in mind potential ethical problems that might arise as we design this experiment.

Let’s first determine the independent variable. If you identified smoking behaviour as the independent variable, you are correct. The control group would be a group that does not smoke, and the experimental group would be the group that does smoke. To prevent confounding of our study by previous smoking behaviour, we could only see non-smokers. We would then randomly assig them into either of the smoking or non-smoking group. In addition to assigning a subject to one of the two conditions, we would control all other aspects of their lives. This means that all participants in the study must be treated exactly the duration of the study, expect the half of them would smoke on a regular basis (we would decide when and how much) and half of them would not smoke at all. We would then determine the length of time for many years for us to access any potential differences between groups. During this time, all aspects of their lives that might contribute to cancer would have to be controlled-held constant between the groups.

FIGURE 9.1 Experimental study of the effects of smoking on cancer rates

What would the dependent variable be? The dependent variable would be the incidence of cancer. After several years had passed, we would begin to take measures on the two groups to determine whether there were any differences in cancer rates. Thus, the cancer rate would be the dependent variable. If the control was maximized, and the experimental group and control group were treated exactly the same expect for the level of independent variable that they received, in any difference observe between the groups in cancer rate would have to be due to the only difference that existed between the groups- the independent variable of smoking. This experimental study is illustrated in Figure 9.1.

You should begin to appreciate the problems associated designing a true experiment to test the effects of smoking and cancer. First, it is not ethical to determine for people whether they smoke. Second, it is not feasible to control all aspects of these individual, lives of the period that is needed to conduct this study indicating that smoke causes cancer in humans.

It is perfectly feasible, however, to conduct experimental studies on other topics. For example, if we want to study the effect of a certain type of mnemonic device (a study strategy) on memory, we could have one group use the device while studying. We could then give each person a memory test and look for a difference between performance in two groups. Assuming would have to be due to the independent variable. If the mnemonic group performed better, we could conclude the mnemonic device caused memory to improve.

The memory study is also known as simple post-test-only control group design. We start with a control group and experimental group made up of equivalent subjects; we administrator the treatment (mnemonic or no mnemonic); and we take a post-test (after treatment) measure. It is very important that the experimental groups and control groups are equivalent because we want to be able to conclude that any differences observe differences observed between the two groups are due to the independent variable and not to some other difference between groups. We help to ensure equivalence of groups by using random assignment.