Data Collection Instrument. By Temtim Assefa

Transcription

1 Data Collection Instrument Design By Temtim Assefa

2 Instruments Instruments are tools that are used to measure variables There are different types of instruments Questionnaire Structured interview Observation checklists Dairy Archival documents Photographs, etc

3 Questioners Most frequently used measurement instrument in organization studies Includes sets of questions to which the subject responds It is used to measure: Attitude Opinions Demographic characteristics of the subjects

4 1. Questionnaires Common design of questionnaires are checklists and rating scales Check listis a list of behaviors, characteristics or other entities that a researcher is investigating Either the researcher or participants simply check(s) items from the list What are features of user friendly software 1. Graphical interface 2. Clear navigation direction 3. Immediate feedback 4. Other specify

5 Questionnaire A rating scale is more useful when a behavior, attitude, or other phenomena of interest needs to be evaluated on a continuum scale It is designed with the following scales 1. inadequate to excellent, 2. never to always or 3. strongly disapprove to strongly approve

6 Example of Questionnaire People who visit the park by private car creates heavy traffic congestion around the park. The park manager arranges buses for visitors in the purpose of reducing the traffic. A study is made to assess the people s reaction to the buses 1. Why did you decide to use the bus system (checklist) a) Thought it was required b) Environmental and aesthetic reasons c) To save time and or gas d) To avoid or lesson traffic e) Easier to park f) Other specify 2. In general, what is your opinion of public bus use in national parks as an effort to reduce traffic congestion and park problems? (rating scale) Strongly Approve Neutral Disapprove Strongly Approve disapprove

7 Guideline for Questionnaire 1. Keep it short What do I do with the information? Is it absolutely essential to have this information to solve part of the research problem 2. Use simple, clear, unambiguous language 3. Check for unwarranted assumptions implicit in your questions How many cigarette do you smoke each day? Good to add a choice <5 None 4. Word your questions in ways that don t give clues about preferred or more desirable responses What strategies have you used to try to quit smoking? Leads him to list strategies he did not try

8 Guide line Check consistency that leads to give contradictory answer for two questions Determine in advance how you will code the response Keep the respondents task simple Provide clear instructions Make the questionnaire attractive and professional looking Conduct a pilot test Give for half a dozen friends to see they have difficulty understanding any items Scrutinize the almost final product carefully to make sure it address your needs

9 Data collection Train data collectors if you hire data collectors Follow the data collectors on the site Check filled questioners for immediate correction in the field Data collectors may fill false data without going to the selected sample Check filled questionnaires with randomly selected respondents

10 Advantage of Questionnaire Easily to collect data from large number of people, including those who live thousands of miles away Can be administered by unskilled data collectors Presents a uniform stimulus to all subjects Can be collected online or through mail Researcher does not have contact with the respondents The anonymity of the respondents helps respondent to provide more truthful information than they would be in personal interviews, especially on sensitive and controversial issue

11 Draw back of questionnaire Majority of people may not return, if it is mailed the return rate is not more than 50% Returned responses may not be a true representative of the originally selected samples Cannot be used with illiterate or persons who cannot read Most questioners are inflexible, respondents answer by choosing only from the given lists

12 Interviews Interviews are meetings in which the interviewers directs questions at the interviewee and records the obtained responses It is direct face to face interactions Can be undertaken through telephone Help to captured more detailed information than questioners Allow to include the respondents views

13 Design of Interview Can be structured and unstructured Unstructured interview is designed with open ended questions The researchers asks and the responds reply to the questions The same questions may not be asked for different respondents Examples Can you list down the benefit of the new software for your organization? What are the main drawbacks of the new software? What do you suggest to improve software to solve the current problems?

14 Structured interviews The researcher asks standard set of questions and nothing more In semi structured interview, the researcher may follow the standard questions with one or more individually tailored questions to get clarification or probe a persons reasoning In structured interview, you can have checklist of responses Example What are the benefits of LAN in the organization a. Facilitates communications among employees b. Improves information access c. Improves relationship with customers d. Other specify What kind of the support the management provides to the success of the Intranet system

15 Conducting Interview 1. Make sure that the interviewees are representative of the population 2. Find suitable location 3. Get written permission 4. Establish and maintain rapport 5. Focus on the actual rather than the abstract and hypothetical 6. Don t put words in people s mouths 7. Keep your reaction to your self 8. Good to use also Recording devices like Sony Voice recorder

16 Advantages of Interview Interview is formal and emotionally neutral Help to develop hypothesis at early stage of the research than testing hypothesis It has a distinct advantage of establishing rapport with potential participants and gain cooperation Has higher response rate Flexible to include additional views and opinions Has better validity, the researcher can further ask probing questions on some biased response

17 Disadvantage It is generally expensive than other data collection methods The researcher is the main interviewer otherwise training of interviewer is very expensive and time taking The interviewer presents the questions in different manners that lead to different responses affects the validity and reliability of the data Characteristics of the respondents (age, sex, ethnicity, etc) may the value of measured variables Respondents may not free on some controversial issues

18 SAMPLING

19 Sampling Sampling is a process of selecting a representative fraction of the large population Assume the population to be studied is 3 million Difficult to collect data about all population Select a subset or a sample of the population Makes conclusion from the sample about the population Sample must be true representative of the population Refers to the external validity of a research study

20 Sample Design Probability sampling, and Type of Sampling Non probability sampling

21 Probability Sampling The researcher can specify in advance that each segment of the population will be represented in the sample The sample is selected by a process known as random selection Each member of the population has an equal chance of being selected Assume we have a beaker that contains 100ml of water and the other 10ml concentrated acid. After mixing the two, if extracted 1ml, from any part of the solution, and find that sample contains precisely 10 parts water and 1 part acid

22 Cont d The same is assumed to be true if the sample is selected from a population who have considerably variability in race, wealth, education, social standing, and other factors - But this is practically impossible

23 How Samples are selected There are different methods Assign each person in the population a different number and use an arbitrary method of picking certain numbers Drawing numbers out of a hat Using computer random number generator application SW like Spreadsheet and Microsoft works has a random number generator module

24 How A tried and true and widely used method of selecting a random sample is to use a table of random numbers From the table, the researcher picks one number randomly Take a birr number from your wallet and take the first two digits to determine the entry rows and columns Use coins to decide which will be raw and a column

25 TABLE OF RANDOM NUMBERS

26 Type of Random Samples Simple random sampling Stratified sampling Cluster sampling A combination of the above methods

27 1. Simple Random Sampling The least sophisticated one Applicable for small and all members of population is known e.gif we study the competency of teachers in Addis Ababa University Procedure: number the units in the population from 1 to N decide on the n (sample size) that you want or need K = N/n = the interval size, where N total population, n is sample size K is the sample interval randomly select an integer between 1 to k Then take every K th unit Not recommended for large and unknown population size

28 Example Divide 100 by 20, you will get 5. Randomly select any number between 1 and five. Suppose the number you have picked is 4, that will be your starting number. So student number 4 has been selected. From there you will select every 5th name until you reach the last one, number one hundred. You will end up with 20 selected students.

29 2. Stratified Random Sampling Also sometimes called proportional or quota random sampling, Dividing population into homogeneous subgroups and then taking a simple random sample from each subgroup. Objective: Divide the population into nonoverlapping groups (i.e., strata) N1, N2, N3,... Ni, such that N1 + N2 + N Ni = N. Then do a simple random sample of K = n/n from each strata.

30 cont d We select the required sample from each of the strata It guarantees equal representation of each strata Good if each strata has equal population size If male 60%, Female 40% and your sample should reflect this proportion

31 Advantage & Disadvantage Advantage focuses on important subpopulations but ignores irrelevant ones improves the accuracy of estimation efficient sampling equal numbers from strata varying widely in size may be used to equate the statistical powerof testsof differences between strata. Disadvantage can be difficult to select relevant stratification variables not useful when there are no homogeneous subgroups can be expensive requires accurate information about the population, or introduces bias.

32 Cluster Sampling When the population is spread out to a larger geographical area, it may not feasible to make up a list of every person living within the area and select a sample for the study using random procedures Steps: divide population into clusters (usually along geographic boundaries) of similar characteristics Randomly select sampled clusters measure allunits within sampled clusters If we use telephone and mailed questionnaire, you may not consider cluster sampling

33 Sample Size As a guide to determine your sample size, use this formula Depends on level of sampling error How about Non-response? S= S min X S r % Where S Actual sample size S min is the minimum (adjusted) sample size S r % is the expected response rate in percentage

34 Non Probability Sampling The researcher has no way of forecasting or guaranteeing each member of the population has equal change of being selected in the sample There are three types: 1. Convenience sampling 2. Quota sampling 3. Purposive sampling

35 Convenience sample A is used when you simply stop anybody in the street who is prepared to stop, or when you wander round a business, a shop, a restaurant, a theatre or whatever, asking people you meet whether they will answer your questions. In other words, the sample comprises subjects who are simply available in a convenient way to the researcher. There is no randomness and the likelihood of bias is high. can't draw any meaningful conclusions from the results you obtain. However, this method is often the only feasible one, particularly for students or others with restricted time and resources, and can legitimately be used provided its limitations are clearly understood and stated.

36 Quota sampling is often used in market research. Interviewers are required to find cases with particular characteristics. They are given quota of particular types of people to interview and the quota are organized so that final sample should be representative of population. Stages Decide on characteristic of which sample is to be representative, e.g. age Find out distribution of this variable in population and set quota accordingly. E.g. if 20% of population is between 20 and 30, and sample is to be 1,000 then 200 of sample (20%) will be in this age group

37 A purposive sample is one which is selected by the researcher subjectively. The researcher attempts to obtain sample that appears to him/her to be representative of the population and will usually try to ensure that a range from one extreme to the other is included. Often used in political polling -districts chosen because their pattern has in the past provided good idea of outcomes for whole electorate.

38 Snowball sampling With this approach, you initially contact a few potential respondents and then ask them whether they know of anybody with the same characteristics that you are looking for in your research. For example, if you wanted to interview a sample of vegetarians / cyclists / people with a particular disability / people who support a particular political party etc., your initialcontacts may well have knowledge (through e.g. support group) of others.

39 DATA COLLECTION