Category Archives: Empirical Research

Researches based on observed and measured phenomena.

Market Analysis: The Pizza Study

What is market analysis? How is it done? This article describes how market analysis works using data on a pizza study.

After having defined marketing research in my previous post and giving an example conceptual framework for a pizza study, I decided to get into the details of market analysis using a standard multivariate statistical analysis tool. I saw the need of writing this article upon reading several articles on market analysis. There is a need to demonstrate what is market analysis.

Before everything else, the concept “market analysis” should be defined first.

What is market analysis and how is it used?

Market Analysis Defined

Marketing strategies work best when founded on a systematic evaluation of consumer preferences. What do consumers want? How do they respond to a product or service? Marketing research provides answers to these questions.

Hence, market analysis can be defined as the process of evaluating consumer preferences using a systematic approach such as marketing research, among others. Market analysis is a detailed examination of the elements or structure of the market.

Why is a market analysis done? An analysis is done to draw out important findings for interpretation, discussion and finally, a decision on what steps to make.

The Pizza Study

Once again, the conceptual framework given in the pizza study is given below to serve as a reference in the following discussion.

market analysis of a pizza study
Conceptual framework of the pizza study.

To find out what customers want, let us have a sample data of feedback from 200 pizza shop customers. To understand how analysis works, you need to read the article on variables as these are important units of analysis. If you already understand what variables are, then proceed to read the rest of the discussion.

Coding the Variables for Market Analysis

Let us have the following measures for the variables in this study namely pizza taste, service speed, and waiter courtesy:

Pizza Taste

1 – Very bad
2 – Bad
3 – Moderate
4 – Good
5 – Very good

Service Speed
1 – Satisfied
0 – Not satisfied

Waiter Courtesy
1 – Courteous
0 – Not courteous

Level of Satisfaction
Let us assume that the following Likert scale applies to the customer’s level of satisfaction:

1- Not at all satisfied
2 – Slightly satisfied
3 – Moderately satisfied
4 – Very satisfied
5 – Extremely satisfied

If for example, the customer is satisfied with pizza taste, service speed, and waiter courtesy; he rates everything “5.” If he is not satisfied with courtesy, then he might rate it a “0.”

Multiple Regression Analysis

Below is a data set representing the response of 200 pizza customers that serves as input to multiple regression analysis (you may try the data set if you know how to compute using multiple regression):

You may skip this table by clicking the link below:

Jump to the Results of Analysis.

A table summarizing the results of the pizza survey.

Customer #SatisfactionTasteSpeedCourtesy
15511
25411
34411
44411
54411
63500
75511
84511
95511
104411
114410
124411
134311
145311
154311
163401
174411
185411
195410
205410
214411
223501
234511
244411
253401
264511
275511
285411
294411
303401
313501
323501
333401
344411
354311
364210
375411
385311
395311
404311
414411
425411
434411
445311
454411
465411
474511
485511
494511
505511
514511
525411
534411
545411
554410
565511
573501
583501
593501
604411
614410
624410
634400
645511
655511
665511
675511
685411
695411
705411
714411
724411
734411
745311
754311
765311
774411
784411
794411
804511
814511
824510
835511
844411
854411
864411
874511
884511
894511
903501
914511
924411
934411
945411
954411
964411
974410
983401
993401
1003401
1013401
1024311
1034411
1044411
1054410
1064511
1074511
1084511
1095511
1104511
1114411
1124411
1135411
1144411
1154411
1164411
1175511
1185511
1195510
1205511
1215511
1225411
1235411
1245411
1255411
1265411
1275411
1284411
1294411
1304410
1314411
1324511
1334511
1344511
1354511
1364511
1375411
1385411
1395411
1405311
1414411
1424411
1434411
1444411
1454410
1464411
1474311
1484311
1494311
1503401
1514411
1524411
1534411
1543401
1554411
1564511
1574511
1584511
1595511
1605511
1615510
1625510
1635511
1645511
1654511
1664511
1674510
1684510
1694511
1704411
1715411
1725411
1735411
1745411
1754411
1764511
1774511
1784511
1794511
1804511
1815511
1825511
1835511
1845511
1854511
1864511
1874511
1884411
1893401
1904411
1914411
1924411
1934411
1945411
1955411
1965410
1974511
1984411
1994411
2003401

Result of the Regression Analysis

The following table presents the results of the multiple regression analysis using a simple spreadsheet software application with regression capability – Gnumeric. The first part shows the general relationship between the dependent and independent variables. The second part shows the details of the relationship between satisfaction score and pizza taste, service speed, and waiter courtesy.

Part 1. Regression Statistics
Multiple R0.66
R^20.44
Standard Error0.47
Adjusted R^20.43
Observations200
Part 2. Details
CoefficientsStandard Errort-Statisticsp-Value
Intercept2.91920.269110.84860.0000
Taste0.03260.05260.62080.5355
Speed1.32450.107612.31000.0000
Courtesy−0.01610.1098−0.14690.8834

Notice that the overall relationship has R values. Among these R values, the most important for interpretation is the Adjusted R^2 value. This value represents the relationship between variables of the study. The value obtained here is 0.43. This means 43% of the variation in satisfaction score is accounted for by the three variables.

Closer scrutiny of the details in Part 2 reveals that service speed significantly relates to satisfaction score. The red font indicates this significant relationship (for better understanding, please read the post on how to determine the significance of statistical relationships).

Interpretation of the Results

Based on the results of the statistical analysis, we can say with confidence that among the variables studied, service speed relates significantly to customer satisfaction. If you look closely at the entries in the data set, for every 5 or 4 satisfaction score, a 1 corresponds to service speed, meaning, the customer is satisfied with service speed. Take note, however, that this interpretation holds true only to the particular location where the study transpired.

Given this result, the marketing manager, therefore, should focus on the improvement of service speed to satisfy customers. This simple information can help the pizza business grow and gain a competitive edge. Market analysis guides decision-making and avoids incurring the unnecessary cost associated with the hit-and-miss approach.

Cite this article as: Regoniel, Patrick A. (May 21, 2016). Market Analysis: The Pizza Study. In SimplyEducate.Me. Retrieved from http://simplyeducate.me/2016/05/21/market-analysis-pizza-study/

Marketing Research Conceptual Framework

What is marketing research? How do you come up with your conceptual framework on marketing research? This article defines the concept and provides a simplified example.

One of the readers of my article on how to develop a conceptual framework asked if I could provide an example conceptual framework on marketing research. I am quite interested in applying the principles of marketing research on my entrepreneurial venture such as in creating and running this website.

It so happened I came across a book on marketing research in BOOKSALE while looking for textbooks on statistics. The book is on sale, so I pulled out my wallet and shelled out a little investment for my hungry brain. The title of the book is a straightforward “Essentials of Marketing Research” by William Zikmund.

I set aside 15 minutes to read the book right after my jogging session. I did this thinking that my mind could actively absorb the contents of the highly academic book after pumping a lot of oxygen during vigorous exercise. In fact, Hillman (2008) noted the beneficial effect of aerobic exercise to cognition. Exercise not only improves physical health but also academic performance.

To come up with a conceptual framework for marketing research, I find it necessary to define marketing research first.

Marketing Research Defined

Zikmund (1999) defines marketing research as a systematic and objective process of generating information to aid in marketing decisions. This process includes specifying what information is required, designing the method for collecting information, managing and implementing the collection of data, analyzing the results, and communicating the findings and their implications.

The most important thing in this definition is that marketing research, as in any research venture, helps business owners or marketing managers make decisions. Marketing research sheds light on customer’s preferences, the long-range profitability of business operations, and other product-oriented concerns.

Successful companies like Google, Microsoft, IBM, among other well-known businesses must be employing excellent marketing research activities to keep their edge. Decisions related to their products and services are not haphazardly done. Managers decide with calculated risks.

Example Conceptual Framework on Marketing Research

One of the popular marketing research activities focuses on product quality and services. I illustrate product and service research with a personal experience below.

A few years back, I answered a simple questionnaire soliciting my feedback on the product and services of a pizza shop. The questionnaire sought my rating of pizza taste, service speed, and the courtesy of the server.

We can plot the paradigm of the study as follows:

marketing research example
The paradigm of the pizza study showing the independent and the dependent variables.

The paradigm above shows the conceptual framework of the study. It is an abstract representation of what the pizza manager or consultant has in mind. It shows the variables that the researcher shall examine to determine which of the three variables correlate most with customer satisfaction.

Why were the three independent variables namely pizza taste, service speed, and waiter courtesy selected? A review of the literature on customer satisfaction may have revealed that these variables are determinants of customer satisfaction. But in the particular location where the pizza restaurant operates, any of these variables may be more important than the other. A study found out that customer preferences vary geographically. This finding implies that clients in one place may prioritize courtesy over taste. In one location, customers may put a premium on service speed. In another location, customers may not mind much either the speed or courtesy but the taste.

So how will the marketing manager use the findings of the study in the given example? If for example, customers in the location I’m in prioritizes service speed, then the appropriate action should be to improve the speed of pizza delivery without compromising taste and courtesy.

This example illustrates the importance of marketing research in making decisions that can help businesses grow. Research findings guide marketing managers on what steps to take to improve their business operations.

Reference

Hillman, C. H., Erickson, K. I., & Kramer, A. F. (2008). Be smart, exercise your heart: exercise effects on brain and cognition. Nature Reviews Neuroscience, 9(1), 58-65.

Zikmund, W. (1999). Essentials of marketing research. Dryden Press. 422 pp.

Cite this article as: Regoniel, Patrick A. (May 20, 2016). Marketing Research Conceptual Framework. In SimplyEducate.Me. Retrieved from http://simplyeducate.me/2016/05/20/marketing-research/

The Yaya Dub Phenomenon: Why Videos Go Viral

Yaya Dub is one of the intriguing phenomena that ever happened in the digital age. Who is Yaya Dub and how did she become so popular within a short period? Why is she getting so much attention among netizens and television viewers not only in the Philippines but also in other countries?

This article applies the scientific approach in trying to understand why a dubber became an overnight celebrity and why she gained so many followers in youtube, and recently, on television.

I was so intrigued by the Yaya Dub phenomenon as virtually everyone I meet knows about it. The mere mention of the phrase evokes familiarity.

I tried to find out in Google’s Keyword Planner what is the monthly search statistics for just the term “Yaya Dub.” The keyword gained 22,200 searches in July and 49,500 in August. I have set the United States as the target country. However, youtube reaches virtually all countries in the world, so I clicked on All Locations as the target for the keyword. It showed 301,260 in July, and 550,980 in August.

But, what about the Philippines where the youtube videos about Yaya Dub originated? Again, I reset the location to the Philippines. The statistics showed 246,210 in July and 451,310 in August. It goes to say that Filipinos account for most of the traffic.

Why this so much traffic for the apparently simple activity such as dubbing? Do viewers obtain benefit from those videos? The ultimate answer in this case presumably is pure entertainment.

What does the literature say about viral or popular videos? What prompts people to share Yaya Dub’s antics?

What scientists say about viral videos

In her dissertation, Izawa (2010) found out that those who had shared or would share the viral videos felt stronger emotions than those who did not share them. These are emotions of happiness, humor, surprise, fear, sadness, and anger.

Upon sharing the videos, those who shared expect the receiver to feel the same way they did. Southgate et al. (2010) confirmed this observation. Since many people use youtube in sharing videos, the platform facilitated the sharing process.

Yaya Dub Videos: The Emotional Content

See the following viral videos of Yaya Dub. Discern which emotions appealed to you most that made you think of sharing the content to your friends.

The videos showed a diversity of emotions aptly expressed by the comedienne. Did it in any way prompt you to share it with your friends? What could have been the motivation of viewers for sharing what they have seen? Do you agree with the findings of the scientists?

Your comments will help affirm or refute the findings.

References

Izawa, M. (2010). What Makes Viral Videos Viral?: Roles of Emotion, Impression, Utility, and Social Ties in Online Sharing Behavior. PhD thesis, Johns Hopkins University.

Southgate, D., Westoby, N., and Page, G. (2010). Creative determinants of viral video viewing. International Journal of Advertising, 29(3):349–368.

Cite this article as: Regoniel, Patrick A. (September 25, 2015). The Yaya Dub Phenomenon: Why Videos Go Viral. In SimplyEducate.Me. Retrieved from http://simplyeducate.me/2015/09/25/yaya-dub-phenomenon/

Statistical Sampling: How to Determine Sample Size

How do you determine the sample size required for your specific study? This is an important question considering that the answer determines how much effort you should devote to your research as well as how much money you have to allocate for it. This article explains how sample size should be estimated to obtain the optimal sample size.

As you would not want to sacrifice accuracy for convenience, and to make your research worthwhile, having the correct sample size makes your research more credible. If you sample too little, your results may not be reliable. If you sample too large a size, you will also be spending too much.

Sampling is especially true to quantitative studies, as it tries to define or describe a population by studying a part of it. But how many should be enough?

Here are important considerations when estimating the correct sample size.

4 Measures Required to Estimate Sample Size

Statisticians agree that you have to be familiar with at least four things before you draw a sample from your population. These are enumerated and described below.

1. Size of the Population

As a researcher, you should be familiar with your target population’s size. It is therefore necessary that you define your population so that you can approximate or find ways to estimate the total population and get the optimal size possible.

Let’s say you would want to find out the tourists’ average willingness to pay to access or see a natural park in view of estimating the value of the natural park’s aesthetic value. This means that your population should be the number of tourists who visit the park in one year if you are discussing an annual turnout of visitors. You can get this number from the tourism office especially if park access is for a fee.

Since you cannot interview all of the tourists, a sample may be drawn at a certain point in time which you will determine yourself, bearing in mind the peak and the off seasons to avoid bias. Familiarity with your population, therefore, is a must.

2. Margin of Error or Confidence Interval

Margin of error refers to the range of values that is acceptable to you as you estimate of the population’s mean or average value. What is the percentage of error that you will allow to give you the level of confidence you need? Whatever value you get in estimating say, the mean of your population is not an absolute number. You should allow for little deviations that are statistically acceptable and serve your purpose.

An analogy to illustrate the margin of error is like a hunter trying to hit a deer with his arrow. He aims for the heart but in the process hits the areas within 3 inches of the heart, either below, above, at the left or at the right. That is okay, because what he really wants is to be able to bring the deer home for his meal. Hitting the parts surrounding the heart serves the purpose of going home with the booty. Hitting the lungs or the other internal parts next to the heart can immobilize it.

3. Confidence Level

Confidence level is a little bit confused with margin of error. This is your level of certainty that your estimated mean (the statistic) will fall within the confidence interval that you have set for the estimate.

Again, back to the analogy of hitting the deer with an arrow. The question is “How confident is the archer in hitting the areas surrounding the heart?” If he is really a very good archer, he might say that out of 100 arrows, he is certain that 95 of this would hit the area within 3 inches of the heart. That’s his confidence level or percentage of certainty.

In statistics, the convention is to have a confidence level of either 95% or 99%. The former is a commonly used standard.

Assuming that your population has a normal distribution, the confidence level corresponds to a value of the z-distribution. A z-distribution is a standard normal distribution, meaning, the population approximates a bell-shaped curve.

4. Standard Deviation

The standard deviation is how spread out the numbers are from the mean. To make this concept clear, let’s go back to the hunter example.

Let’s say the hunter shot a target with a bullseye 500 times. As he is a very good archer, most of the arrows would have landed near or at the center but for sure, not always at the center. Those arrows that missed the bullseye are similar to the deviations from the mean. The way the arrows spread from the center indicates deviations from the average.

So how far will the arrows released by the hunter deviate from the center? We don’t know unless we measure the distance of each of the arrows from the center. But we don’t have time to measure all of the 500 arrows he released so we might as well take a sample, say 20 arrows. Those 20 arrows might show that the deviation from the bullseye is within 4 inches. So this value can be used to predict the deviation of the 500 arrows consequently released.

Getting the population standard deviation from 20 samples is analogous to a pilot study of the population. A portion of the population may be studied to estimate the population standard deviation. If it is not possible to do so, it is common practice that a standard deviation of 0.5 is used in estimating sample size.

The population standard deviation is computed by getting the square root of the variance. The variance is the average of the squared differences from the mean. This is denoted by the formula given below:

population standard deviation
Fig. 1 Population standard deviation.

Using Confidence Level, Standard Deviation and Margin of Error to Estimate the Sample Size

If you are now ready with at least three measures to estimate sample size, i.e., margin of error, confidence level and standard deviation, then you are now ready to estimate the sample size you need. For example, let’s have the following data:

Given:
Confidence level: 2.326 (the corresponding value in the z table indicating 99% of the population is accounted for)
Standard deviation: 0.5 (assuming that the population standard deviation is unknown)
Margin of error: 5% or 0.05

The following equation is used to compute the sample size:

estimating sample size
Fig. 2. Formula to estimate sample size.

Substituting given values to the equation:

Sample size = ((2.326)² x 0.5(0.5))/(0.05)²
= (5.4103 x 0.25)/ 0.0025
= 1.3526/0.0025
= 541.04 ~ 542 (always round up to the higher integer number)

Therefore, if your research requires interviewing people, the estimated number of interviewees is 542.

References

Niles, R. (n.d.). Standard deviation. Retrieved on 18 February 2015 from http://www.robertniles.com/stats/stdev.shtml

Smith, S. (2013). Determining Sample Size: How to Ensure You Get the Correct Sample Size. Retrieved on 19 February 2015 from http://www.qualtrics.com/blog/determining-sample-size/

©2015 February 22 P. A. Regoniel

Qualitative Interviewing: 4 Reminders about Question Construction

The goal of the interview is to collect whole answers from the interviewee. Question formulation and delivery are critical in this process.

Interviewees respond not only to the kind of question that is context dependent but also to the way the question is asked. The wording, ordering, and kind of language used affect the context (e.g. perception of the interviewee) of the question. Even your tone, enunciation, gestures, and facial expressions as interviewer affect the direction of the interviewee’s answers.

A question could be closed-ended or open. A closed-ended question could be answered by a yes or no, or a list of choices is provided where the interviewee may choose his/her answer. Otherwise the question is open-ended when answers depend on the participant’s own categories and opinions.

It is said that closed-ended questions are hard to construct but easy to use in data gathering while open-ended is the opposite. Actually, both types are hard to formulate since both need rapport and both are prone to errors when not properly prepared.

So when preparing your questionnaire, there are important things to consider in question construction and delivery.

4 Reminders About Question Construction

1. Start with the easiest question.

An interview schedule (whether for structured or semi-structured setting) should always start with the easiest, most comfortable question to establish rapport for a one-shot setting or maintain the rapport for a multilevel setting. Depending on the culture, the interviewer should be cognizant on what subtopic or question would the interviewee consider as the easiest and most comfortable. Usually, questions about basic personal information seem the least threatening and thus, the most uncomplicated.

2. There is proper ordering of questions.

The ordering of the questions affects the entire interview process. Whether you choose the deductive (from general to specific) or the inductive (specific to broad) arrangement, questions are always in a network. That is, the subsequent question should be linked to the one it follows. This is to help the interviewee in organizing the information that she/he is going to share.

Unless inevitably necessary, questions should not be isolated from one another. When you ask questions randomly, as if they are just popping out of nowhere, you will definitely confuse the interviewee.

3. Remember that questions are connected.

Since questions are linked together, a preceding question may significantly affect the interviewee’s answer to the subsequent question. Bradburn, Sudman, and Wansink (2004) cited a study that illustrates how the ordering of questions about advertising affects the women’s answers. Women’s attitudes (answers) when asked about their opinions toward advertising were more positive when questions about dress advertising preceded the general questions about advertising than when it was the other way around.

Given this tendency, you may opt to carefully arrange the questions in such a way that the unnecessary effect of the preceding question will be minimized and will not be carried over to the next. That is why, a pilot interview is always recommended to evaluate your prepared schedule.

lots of questions

4. Learn how to probe.

However efficiently formulated your questions are, always expect that the interviewee’s answers may not always be complete. Reasons could be that the questions are not clear, the interviewee is reluctant to answer or there is problem with the retrieval of the information needed. If this is the case, probe.

If questions are misunderstood or unclear, just rephrase the question and immediately ask again or you may just ask again later. The interviewee may hesitate due to uncertainty of what more information is needed.

If this is the case, ask for more by paraphrasing his answers followed by prompts e.g. “What else?”, “Why?”, “What do you mean?, “In what way?, or “How?”

Prompts also are important to aid recall when interviewee has difficulty in remembering. You may give examples to serve as retrieval cues or to clarify the needed information (Dawson, 2007).

References

Bradburn, N.M., Sudman, S., & Wansink, B. (2004). Asking questions: The definitive guide to questionnaire designs – for market research, political polls, and social and health questionnaires. CA: Josey-Bass: A Wiley Imprint.

Dawson, C. (2007). A practical guide to qualitative research: A user friendly manual in mastering research techniques and projects. Oxford: How To Content.

©2015 February 10 J. G. Pizarro

Qualitative Interviewing: 3 Mistakes to Avoid in Question Formulation

There are common mistakes that are often committed by an interviewer who is new in the field. Even the seasoned ones sometimes inadvertently overlook these errors. To avoid these mistakes, a carefully prepared and tested set of questions is the key.

One classic example given by Bradburn, Sudman, and Wansink (2004) to illustrate the criticality of proper construction of questions is the difference between the two questions namely, “Is it a sin to smoke while praying?”, and “Is it a sin to pray while smoking?”. The inquiry brought about by an argument between two priests is to find whether it is a sin to pray and smoke at the same time.

When both asked each other’s superior, the first question (of the first priest) got a ‘yes’ answer while the latter (question of the second priest) got a ‘no’. The difference in the answers is not due to conflicting opinions but due to the disparity in the context.

In the first question, there is the assumption that the individual is already praying when he/she opted to smoke along with praying. While the second implies the opposite, that is, the individual is already smoking when he opted to pray (maybe to ask for strength to resist the vice). This reminds us that a slight change in the wording of a question changes its meaning and context.

The following are six reminders on the common mistakes to be avoided when preparing and asking questions for interview.

3 Common Mistakes to Avoid in Question Formulation

1. Avoid underestimation, overestimation, and over-assumption.

Underestimation. Use simple words but not too simple. Do not underestimate your interviewee’s capacity to understand. Doing so might offend her. Unless necessary, slang language should be minimized not because it is informal but because some slang words cannot be easily understood. Jargons too should be simplified.

Overestimation. You should not overestimate as well. Do not ask questions beyond the interviewee’s ability to comprehend and also do not over-assume that the interviewee is knowledgeable as this situation is prone to social desirability bias. This bias refers to the interviewee’s motivation to appear “good” like being smart or morally good in front of the interviewer. Thus, even if he does not totally understand the question, or has no knowledge regarding the topic of the question, he might attempt to answer it to appear knowledgeable.

Over-assumption. One example of over-assumption is when you assume that an interviewee who has a driver’s license automatically has experience in driving an SUV. Without the preceding question “Do you happen to have driven an SUV?” the question “How does it feel driving an SUV?” is an over-assumption.

2. Avoid double-barreled questions.

Do not confuse the interviewee by asking double-barreled questions. This may result to vague answers since the interviewee gets confused to the question that contains two (or more) concepts (or objects) that are put together needing two (or more) different opinions but asks only one answer. There are actually two (or more) questions compounded together.

For example, “Are your teachers morally good and kind?” and “Do you support homosexuality and gender equality, or do you support heterosexuality and freedom of religion?”

In the first question, being morally good is different from being kind. The two concepts should be separated to formulate two questions asking for two different answers. The second question contains four different concepts that should ask four different opinions.

3. Avoid leading questions.

Social desirability bias may also be at work if leading questions are delivered. These are questions that influence the direction of the interviewee’s answers either to correspond with what the interviewee thinks as socially desirable answer or as the answer expected of her by the interviewer (Seidman, 2006). These could be in the form of predisposing questions, leading probes, or loaded questions.

Predisposing Questions. There are questions that predispose the interviewee to provide a socially desirable answer. The question “Do you jog?” for example, may seem neutral and not leading at first. But to some interviewees, this may become predisposing since jogging is considered as fashionable and good. The interviewee is prone to provide an answer that appears good. Researchers suggest the use of the word “happen” in “Do you happen to jog?” since it neutralizes the question implying that it is not expectant of a positive answer from the interviewee (Bradburn et al., 2004).

The question “What is the opinion of an honor student like you on cheating?” will likely elicit a socially desirable answer since including the phrase “honor student like you” is leading the interviewee to desire to be seen as good. The question should start with “What do you think is the general opinion of students on cheating?” which could then be followed by “How about your opinion?”.

Leading Probes. Asking leading probes is like subtly shoving the answers into the interviewee’s mouths. For example, the probe question “Are you saying that you are already in love with him?” when you want to clarify what she means by the statement “Well, I think I miss him now”, is leading because it creates an idea that may not be originally present in the interviewee’s mind. The probe should be open-ended like “Why?”, “How?” or “What do you mean by that?”

Loaded questions. These are worded in such a way that they will get answers expected or desired by the interviewer. These questions contain loaded words which could be emotional like “apathetic” and “problematic” or political like “trickery” and “defraud.”

The question “Do you think your teachers are too burdened and apathetic to help you in your academic concerns?” is loaded in such a way that it will likely elicit a biased answer. The use of the loaded words implies that the writer of the question have biases against teachers. It should be rephrased into “Do you think your teachers help you in your academic concerns?”

In his early surveys on workers, Karl Marx asked the question “Does your employer or his representative resort to trickery in order to defraud you of your part of your earnings?” (Bradburn et al., 2004). He was clearly an advocate of the working class given his loaded question leading the interviewees to provide a biased opinion against the capitalist employers. The question should be asked “Does your employer treat you fairly when it comes to your earnings?” to get the real answers of the interviewees.

References

Bradburn, N.M., Sudman, S., & Wansink, B. (2004). Asking questions: The definitive guide to questionnaire designs – for market research, political polls, and social and health questionnaires. CA: Josey-Bass: A Wiley Imprint.

Seidman, I. (2006). Interviewing as qualitative research: A guide for researchers in Education and Social sciences (3rd ed.) New York: Teachers College Press.

© 2015 February 8 J. G. Pizarro

Qualitative Interview Designs

The critical part of a research process is the data collection procedure. Even if you have an apt and interesting topic with an appropriate framework, if the corresponding data collection method is a slapdash, the results would be unreliable and weak. Research is scientific, that is, it should follow a carefully planned methodology.

Interview, for one, is not just going into the field and starting the conversation after obtaining the consent of the participant, and preparing a set of questions and recording tools. It should be designed.

How many levels should it take? How will the interaction flow? What should be the medium of dialogue? The answers should always correspond to the objectives of the research.

Setting Style

One-shot. For baseline exploratory design, this one setting interview would be enough. If the goal is just to provide an initial reference for a specific inquiry, then a follow-up may not be necessary. All the inquiries could be compressed in one short time. Rapport could be built within the first part of the interview. This is ideal for less sensitive and/or simple topics that do not require extensive data.

Multi-tiered. For emergent design and/or in-depth inquiry, a multilevel setting interview is recommended. When topics are more sensitive, more complicated, and more prone to biases and prejudice, a strong rapport is needed to encourage the full disclosure of the participant. This implies longer time for rapport building. You may set the first level for establishing the needed relationship and for preparing the participant for the next level/s. For example, you may start with the easiest and most comfortable topics and may ask the general questions in this level. This deductive arrangement will guide and help the participant retrieve, organize and share the information needed. If the approach is emergent, the next levels will provide opportunity for clarifications and confirmation as a result of preliminary analysis.

Interaction Design

Structured (Narrow Setting). This design is formal and is strictly on the script which could be a highly organized questionnaire set or a standardized interview schedule (Best & Kahn, 1995). The interviewer follows the protocol in uniformity so as to have maximum control of the setting to minimize extraneous variables such as the possibility of researcher influence like gender, age, biases, emotions, preconceptions, assumptions, and the like. Extraneous variables are those which may contaminate the data from the participants. For example, an interview with women participants, if the interviewer is a woman, the interviewee might be more accommodating and open. In another interview of the same topic and participant, if the interviewer is a man, the interviewer’s gender may influence the way the participant provides the answer.

Semi-structured. This design requires a prepared guide question (schedule) that is flexible but retains continuity with spontaneity and fluidity of the conversation process. If the conversation slightly deviates from the topic, the interviewer allows it but tactically returns to the topic to maximize resources. This is usually recommended if the inquiry may allow other important information that may emerge and thus may enrich the data (Dawson, 2007).

Unstructured (Free-flowing Conversation). In Filipino indigenous method, this is known as pakikipagkwentuhan. There is no need for a guide question or list of topics here. The interviewer has only the topic and allows wherever the conversation flows with little directional influence from him/her. The interviewer subtly emphasizes the topic to serve as cue (for the participant) to put into the surface all the elements of the data that the researcher wants to extract from the participant. Interviewer may ask questions sometimes to clarify some information and to retain the conversation process. This design is ideal for in-depth studies like life history and phenomenological research (Marvasti, 2004).

Medium of Dialogue

Face-to-face. This is the most common medium since this allows collection of other details like behavioural and context observation. This is ideal for in-depth study since in this kind of inquiry, trust is critical for rapport.

Phone Interview. This is suggested if distance will not allow a face-to-face interaction and/or the goal is for the participant to answer few simple questions for structured or semi-structured design. This is an alternative to face-to-face interview if the verbal data are the only source for analysis and behavioural and context observation like facial expression and physical setting are no longer necessary for the research.

Online. This could be a video call or internet chat. Chatting is ideal for interviews that allow anonymity of the participants and/or interviewer. This could also be useful in minimizing extraneous variables to reduce bias (Jupp, 2006). While a video call could be a substitute to face-to-face interview.

References:

Best, J.W. & Kahn, J.V. (1995). Research in education. New Delhi: Prentice-Hall of India Private Limited

Dawson, C. (2007). A practical guide to qualitative research: A user friendly manual in mastering research techniques and projects. Oxford: How To Content.

Jupp, V. (2006). The Sage dictionary of Social Science research methods. Thousand Oaks: Sage Publications

Marvasti, A.B. (2004).Qualitative research in Sociology: An introduction. Thousand Oaks: Sage Publications.

© 2015 February 1 J. G. Pizarro

Peer Coaching: A Sample of Professional Development Plan

This article describes how the findings of a dissertation can be applied in coming up with a plan to develop teachers professionally. Specifically, it deals with professional development for teachers using peer coaching as a tool.

Read on and find out how you can plan for your own professional development by reading the article below.

How can you develop yourself professionally? This can be done by undertaking steps which you can do by yourself.

However, aside from self-directed activity as described in my previous article titled “Reflective Journal: A Sample of Professional Development Plan,” you may also use a school-based activity to come up with your professional development plan. Among those approaches you could use is “peer coaching” since this is a common school activity applied by teachers.

Steps in Peer Coaching to Develop Pronunciation Skills

Since peer coaching falls under the school-based category, how can you make use of this approach? As an example, here are steps in order to improve your pronunciation skills if you find that you need to develop your skill along this line:

1. Look for a partner or a friend who is good at pronunciation and is willing to serve as your coach. If you find one, set a specific time to engage in this activity on a regular basis.

2. During the scheduled time, you may discuss a particular topic or problem in pronunciation and ask for the coach’s suggestions on how to improve on it.

3. You must do the suggestions for a prescribed period of time. Perhaps, the session could last for two weeks, or maybe a month. After practicing for some time, you may request your coach to evaluate your pronunciation skills after using his/her suggested activities.

Example Dialogue of Peer Coaching

Below is an example of a dialogue between an expert (the peer coach) and a group of teachers.

Teachers: Sir, we know that you are good in pronouncing words. Can you help us improve our pronunciation skills?

Peer Coach: Thank you. Yeah, I’m willing to help you, but I am too busy. Anyway, we can schedule it during my free time. Is it okay with you? My free time is every Friday afternoon, from 2-4pm.

Teachers: Yes, Sir. We can meet you up at that time.

During the Meeting with the Peer Coach

Teachers: Sir, we have noticed that we cannot pronounce well the words with /f/. We pronounce father as “pather.” How can we pronounce the word correctly?

Peer Coach: (He can give as many suggestions as he can).

Teachers: (They listen to the peer coach and apply the suggested activities).

During the Evaluation

Peer Coach: Now, let’s try to see if you have improved your pronunciation.

Teachers: (They do the evaluation techniques given by the peer coach).

Basically, peer coaching as a professional development activity is designed to improve student performance. It is in this activity that teachers form small groups in order to share, reflect on, and refine their teaching practices to address their students’ needs.

However, in the Customized Professional Development Model, any professional activity can be used and customized to address the specific needs of the teachers. Therefore, any activity that is originally designed for students can be used by teachers to improve their own professional skills.

Reference

Louisiana Department of Education Initiatives: Best Practices (2006). Examples of Job Embedded Professional Development. Retrieved 3 July, 2010 http://www.wbrschools.net/curriculum/sip/LaDOE%20Best%20Practices.ppt

2015 January 25 M. G. Alvior

A Sample of Conceptual Framework with Statement of the Problem

This article shows how a conceptual framework, along with the corresponding statement of the problem, is organized and written in a dissertation. Take a look at the example on how it is done and try to make one for your paper. You may also use this in your thesis.

You may be thinking about too many theories to base your study on. However, a conceptual framework in built on a theory that serves as the basis for your study. Once you have decided which theory to adopt, try to figure it out if the phenomenon, with all the associated variables in your study, can be best explained by that theory. The example below illustrates how this works.

Example of a Conceptual Framework

This study zeroes in on the professional development activities for teachers by espousing the idea that the classroom performance of teachers is a critical factor for student academic performance. The researcher based her assumption from Weiner’s Attribution Theory that external and internal factors can improve performance.

For example, students may attribute their academic performance to their teachers (external factor) while the teachers may attribute their teaching performance to in-service trainings (external factor) and perhaps, to their teaching efficacy, job satisfaction, and attitude towards the teaching profession (internal factors). These relationships are illustrated in Figure 1.

conceptual framework
Figure 1. Paradigm showing the relationships among the variables in this study.

Statement of the Problem

The purpose of this study is to provide baseline data on in-service training for English, Mathematics, and Science Fourth Year High School teachers from School Year 2006 up to 2010. Also, a professional development model for teachers is proposed.

Specifically, this study sought answers to the following questions:

1. What are the most familiar in-service training activities among teachers? And what are their insights about these activities as to: (a) applicability in the classroom, (b) importance in the teaching profession, and (c) impact on student performance?

2. What feedback do teachers have of the in-service training programs attended in terms of (a) perception, and (b) satisfaction?

3. What are the teachers’ level of teaching efficacy, job satisfaction, and attitude towards the teaching profession?

4. What is the performance of the fourth year high school students in their Subject Achievement Tests in three subject areas: English, Mathematics, and Science during the first semester of SY 2010-2011?

5. Are the teachers’ perception and satisfaction regarding the in-service training programs predictors of their levels of teaching efficacy, job satisfaction, and attitude towards the teaching profession?

6. Are the teachers’ levels of teaching efficacy, job satisfaction, and attitude towards the teaching profession predictors of their student performance in the Subject Achievement Tests?

7. What enhanced professional development model for teachers can be developed on the basis of the results of this study?

Now, you have learned how a theory is used, and how the questions in the statement of the problem are formulated. Take note that the questions in the statement of the problem are arranged according to the flow of conceptual framework. First, it has questions on inventory of in-service training activities, followed by the feedback. The next question is about teacher factors, then results of student performance. The last question relates to the development of the enhanced professional development model.

Can you make it? Yes, you can!

© 2015 January 19 M. G. Alvior

The Economic Loss of Rice Farms Due to Sea Level Rise and Farmer Adaptations

How are research topics arrived at? One of the ways on how to identify a phenomenon worthy of research investigation is to go out on field and ask questions.

This article discusses how research topics in environmental science can be generated through interaction with community members as clients of the research outputs. Specifically, it examined the issue of sea level rise as a pressing issue threatening the rice production capacity of a community living next to Malampaya Sound, a marine biodiversity rich body of water located northeast of Palawan Island. It was once dubbed the ‘fish bowl’ of the Philippines.

The trip yesterday to Abongan, a farming community in the municipality of Taytay located 167 kilometers northeast of Puerto Princesa, Palawan (Figure 1), was a fruitful one. I discovered an environmental issue that could be a good research topic to explore. The rice farmers in that community experience the negative effects of sea level rise – a manifestation of climate change. This issue arose as our research team conducted a focus group discussion with agriculture stakeholders.

sea level rise
A map showing the location of sea level rise affected farmlands in Abongan (Map source: Wikimapia.org).

Salt water inundated and changed a portion of the farmlands into mangrove stands. The phenomenon started way back in 1994, according to the barangay chairman of Abongan.

Reminded of the environmental economics perspective on evaluating environmental issues, a question popped in my mind: “How much in terms of money is the value lost by farmers each year because of the advancing sea waters?”

The Economic Loss of Rice Farms Due to Sea Level Rise

To objectively examine the issue discussed earlier, let us enumerate and assume the value of the different variables at play in this phenomenon:

  1. Area of farmland affected by sea level rise: 200 hectares
  2. Number of cavans of unhusked rice grains (palay) produced per hectare: 100
  3. Percentage of rice (bigas) produced in a cavan of palay: 25% or 1/4
  4. Price per kilogram of rice: PhP42 or $0.92
  5. Kilograms of rice per cavan: 50
  6. Number of croppings per year: 2
  7. Percentage of return from farm investment: 50%

The net loss of income on annual basis, therefore, can be computed by converting the net income from rice produced per hectare to the number of hectares affected. This is obtained by multiplying the number of kilos of rice produced per hectare to current price. This is equal to 25 cavans or 1,250 kilograms times PhP42 ($0.92); that gives a total of PhP52,500 ($1,150) per hectare.

If 200 hectares are affected by sea level rise each year, the total value of rice yield per hectare will be PhP10,500,000 ($48,300) per cropping season. Since there are two cropping seasons per year, total annual loss in income will be double this amount.

The annual loss in income of farms in Abongan, therefore, will be PhP21,000,000 or $96,600. Since the percentage of return from investment is roughly 50%, the annual loss in net income is half this final value which is the same value obtained for one cropping season, i.e., PhP10,500,000 ($48,300).

The value given above assumes that the area of affected farmland is the same. But farmers observed that saltwater goes further inland each year. This causes anxiety among farm owners especially those whose land lie next to rivers.

Adaptation of Rice Farmers to Sea Level Rise

Currently, some of the farmers build dikes to prevent saltwater from flowing into their farms. There’s also a plan to increase the flow of freshwater from the watershed to their farms.

Further reflecting on the issue, three questions came to my mind:

  1. What species of mangroves successfully settled in the upper reaches of the river next to farms?
  2. What are the other adaptations measures did farmers make to mitigate the advancing waters aside from dikes and increased freshwater flow?
  3. What is the salinity of river water next to farms?

Now, can you appreciate the value of having to go out in the field and identify environmental issues that hound communities? In the process of finding answers to questions, the outcome of your study will be helpful inputs that will empower communities.

Figuring out your research topic in the four corners of the classroom will offer you less ideas to pursue. Get up and explore the world.

©2015 January 11 P. A. Regoniel