Reflection on Presentation 3: Instrumentation Part 1 (Questionnaires)

On August 12, 2010, we entered the world of “Instrumentation” presented by Zubaidah Abdul Ghani, Norela Elias and Roslina Ahmed Tajuddin which covered largely on Questionnaire. The presentation was straightforward and informative. The examples given by the presenters managed to shed some light to my understanding on Instrumentation.  

The definition of data, instrumentation, validity, reliability, objectivity and usability is summarized in the table below:

 

As discussed in the class, there are three (3) methods for obtaining information, which are (1) Researcher instrument (2) Subject instrument and (3) Informants instruments. Researcher instrument (RI) is obtained by directly or indirectly assessing the subjects of a study. For example, in a Statistics class, a researcher observes students, examine students’ records, and noting the frequency of oral assessments. Subjects instrument (SI) is obtained through a self-report data that are provided by the subject of the study themselves. For instance, a researcher might have to request students’ products (essays) for evidence or interview the students.  Another method of obtaining data is Informants instrument (II) which is data provided by other people about the subjects of a study. For example, a researcher interviews teachers or students and assess each student’s thinking skills based on their prior experience.

The instruments for Researcher-Completed Instruments and Subject-Completed Instruments are as in the table below:

 

Generally, most of quantitative data obtained are reported in the form of scores. There are two scores namely Raw Scores and Derived Scores.

Raw Scores – Refers to the initial score obtained. It can be the total number of items an individual gets correct or answers in a certain way on a test. However, assessing an individual raw score is difficult to interpret and has little meaning. Examples of raw scores would be a student’s marks: Bahasa Malaysia (90), English (53), Science (89) and Mathematics (91).

Derived Scores – Refers to the data obtained by taking raw scores and then convert them into more useful scores on some type of standardized basis. It is able to indicate a particular individual’s raw score in relation to other raw scores in the same distribution and able to help the researchers compare scores between individuals taking the same test. The three examples of derived scores are (1) Age & Grade-Level Equivalent Scores (2) Percentile Ranks Scores and (3) Standard Scores.

As what has been discussed in the classroom, when we want to use the scores, we must ensure that the reference group make sense. For instance, it is quite misleading if we want to compare girls’ and boys’ performance on Mathematics subject. The group that used to determine derived scores is called the norm group and instruments that provide such scores are referred to as norm-referred instrument. Another example is: Semester 2 students of Educational Leadership & Management (Norm Group) and Statistics Test (Norm-Referenced Instruments).

Another alternative to performance or achievement instrument is Criterion-Referenced Instruments. It focuses more on instruction rather than evaluating learner’s progress through gain scores. Yet, it is based on specific goals or target for each learner to achieve. So, why use this test? The main reason would be to determine whether or not the candidate has the demonstrated mastery of a certain skill or set of skills. For example, consider a student of Education program going for a practical training at school for 3 months. The result would be either pass or fail the assessment.

In the class, I recall that Measurement Scale is the foundation of scientific investigation. Measurement is the assignments of numbers to objects. The 4 types of measurements are Nominal (groups and label the data only and reports frequencies or percentages), Ordinal (ranks data, use number only to indicate ranking), Interval (assumes that equal differences between scores mean equal differences in the variable measured) and Ratio (a ratio scale that has a true zero point and does not have negative value).

Lastly, as discussed in the presentation, the data must be prepared for analysis consistently in order to generate accurate conclusion. The data is normally coded and tabulated in Computer Software such as SPSS and ANOVA.

Till then, thanks for reading! To get the Power Point slides, click "Instrumentation Part I- Questionnaire".

Reflection on Presentation 2: Sampling

On August 5, 2010, a topic on "Sampling" was presented by Normazhazlin Alzahari, Azlyn Sarafina A. Hamid and also Hanim Othman. All the three presenters have managed to present the topic clearly and answer the questions from the audience. Sampling is another branch in doing research and I believe it is important to understand and grasp the idea of sampling, population and et cetera before making the appropriate and suitable sampling methods for our research. 

I summarized whole broad idea about “Sampling” in the figure below:

 

There are two main types of sampling, which are Random Sampling and Non-Random Sampling. Let’s look at what the types of sampling are all about in the table below:

Basically, the idea of Random Sampling method is easy to catch as there are many examples that fall under this method. For instance, consider  a personnel from the Ministry’s office wishes to find out how many Secondary School Principals in Perak is keen to have Mandarin taught in as one of their subject. So, she will have to place all 100 names of secondary school, mix them thoroughly, and then draw out the names of 25 names of schools to be interviewed.

Another type of sampling is Non-Random Sampling:

Again, I would like to give the example provided by the presenters on Non-Random Sampling. Consider the Ministry wishes to send its personnel to find out how many secondary school principals in Perak is keen to have Mandarin taught in as one of their subject. There are 5 jr. Personnel in the department. They need to select only 3. Thus, 3 personnel’s were selected based on some criteria, (1) must be permanent staff and (2) at least have 5 years serving the Ministry. I thought of it as a simple and straightforward example on Non-Random Sampling  :D

 

As discussed in the class, since Purposive Sampling is largely based on the researcher’s judgement, it tends to contribute to an error of observations such as bias.

Another sub-topics discussed under “Sampling” are as below:

In doing research, it is better for us to follow the recommended sample size and we must take note that any sample that is less than 20 is too small, yet not encourage to do so. I still remember vividly Dr. Teoh said that in selecting sample size, we must ensure that we have enough energy and time to collect data. Simply say, as researchers, we should try to obtain as large as sample that we reasonably can. Pretty make sense, isn’t? 

 

Other than that, there are times when Random Sample are not been used. There are 2 reasons for this question.

First: The educational researchers are not aware of the hazards involved in generalizing where there is no random sample available.

Second: Sometimes, it is not feasible for the researcher to invest the time, money and other resources necessary to obtain a random sample. 

Till then, thank you for reading! To get the Power Point slides, click "Sampling". 

Reflection on Presentation 1: Types of Educational Research - Quantitative and Qualitative Research Methodologies

The presentation of Research Methodology's class starts with the first presentation by our group (Me, Agalitha and Marliana) on the topic entitled "Types of Educational Research - Quantitative and Qualitative Research Methodologies" which is largely extracted from the book of How to Design and Evaluate Research in Education by Fraenkel and Wallen.

Presentation 1: Types of Educational Research - Quantitative and Qualitative Research Methodologies

Presenters: Nur Zahira, Agalitha and Marliana

Our presententation started with the introduction of quantitative and qualitative research. To review, quantitative research generates statistics through the use of large-scale survey research, using methods such as questionnaires or structured interviews. This type of research reaches many more people, and the contact with those people is much quicker than it is in qualitative research. In contrast, qualitative research is more into the explorations of attitudes, behaviours and experiences through such methods as interviews or focus groups. It attempts to get an in-depth opinion from participants. As it is attitudes, behavior and experiences which are important, fewer people take part in the research, but the contact with these people tends to last a lot longer. Under the umbrella of qualitative research there are many different methodologies.

Under the umbrella of quantitative research, there are 5 methodologies namely Experimental, Single-Subject, Correlational, Causal Comparative, and Survey. While for qualitative research, the various methodologies are Phenomenology, Case studies, Observations & Interviews, Ethnographic and Historical.

The powerpoint slides for our presentation is here.

Happy reading all !!!