Research Methods: Experimental or Quasi-Experimental Study Research Paper

How the application of the designs differ

In this study, the first aspects of the design involved identification of variables. The quasi independent variable was the use of iPad technology. The study was focused on determining how the use of iPad technology among children in kindergarten affected early literacy skills.

The use of the quasi experimental design used in this study deferred with some of the conventional approaches in many ways. The researcher had absolute control over the assignment to treatment condition (Cubelic & Larwin, 2014). This makes the study prone to errors associated with bias. The design also lacked random assignment elements.

The sampling: rationale and techniques

The sampling method used in this study involved non-random selection of the subject. The study sample involved 16 kindergarten classrooms that were selected in schools (Cubelic & Larwin, 2014). Each district was assigned two classrooms. The rationale for this sampling design was that there was a form of uniformity in the selected groups of students in the entire region.

Using random sampling method would hinder the process of selecting individual subjects in each of the groups. The design was focused on ensuring that the final sample group will be a true reflection of the desired population of the study group.

Data collection techniques

Data was collected from the schools that were willing to participate in the eight districts. Each of the participating schools was assigned five iPad tablets (Cubelic & Larwin, 2014). The participants were categorized into eight control groups, and eight intervention groups. The eight control groups had eight teachers and 164 students, while the other eight intervention group had eight teachers and 169 students. The researchers collected data from these two groups in order to facilitate their study. Each of the groups was assigned equal values.

Levels of measurement of the variables

Some of the variables in this study were ignored because their impact was negligible. The study paid special attention to demographic variables such as gender of the participants, their socio-economic status, and race. Their impact was considered significant in this study.

For instance, it was believed that male children would be more aggressive when using iPad technology in the classroom. It was also believed that students from rich families would find it easier to use the iPad because their parents own these gadgets. In measuring the variables, the study used a multivariate analysis of variance (Cubelic & Larwin, 2014). The study also factored in the experience of the teacher.

Types of statistics used to analyze the data and generate results

The researchers used DEBELS score to analyze data and produce results. The study selected eight control groups with eight teachers and 164 students, while the intervention group had eight teachers and 169 students (Cubelic & Larwin, 2014).

However, actual number of participants that were in generating data for analysis results fewer than the initial number of participants that were 333 kindergarten students. Only the data from 281 were use in this quasi experimental research. The statistics used was descriptive in nature. The researchers believed that descriptive data will be able to address the issue under investigation appropriately.

Inferences that can be drawn from the results

From the results obtained in this study, it was evident that integration of iPad 2 technology in a classroom learning for kindergarten students improved their skills and ability to master what they are taught. Students at this stage are very curious and need a learning approach that is backed by technology to improve their understanding.

This study observes that this approach eliminates the idea that learning is a boring process. It introduces entertainment in the learning process. The study also concluded that socio-economic factors, gender, and race affected learners’ ability to use iPad technology in class work.

Special considerations: validity, reliability, generalizability

Some researchers have claimed that, validity in most of the quasi studies may not be easily determined because of the nature of selecting the subjects.

Quasi experiments allow a researcher to select a sample group based on their own discretion. This means that they are prone to some errors. In this study, the researchers used Cronbach’s Alpha to determine the reliability of the data. This made it possible to make a generalization of the phenomenon observed in the sample, to the entire population.

Ex Post Facto Study

How the application of the designs differ

In this study, the methodology was based on ex post facto research design. According to Pense, Beebe, Leising, Wakefield and Steffen (2006), ex post facto study is crucial when conducting research where the variables are studied in their natural environment without any manipulations.

This research design is considered different from other common research designs which allow the researcher to manipulate variables in order to suite his or her interests. In this study design, the researcher must purpose to ensure that the variables are studied in their natural environment without introducing any agent that may hinder their normal behavior.

The sampling: rationale and techniques

The study used a sample of 202 twelfth grade students that were selected using a random sampling method (Pense, Beebe, Leising, Wakefield & Steffen, 2006).

The researchers first identified two regions as urban or suburban areas, and rural areas. In the two clusters, simple random sampling was used to select three rural schools and two urban or suburban schools. In the individual schools, simple random sampling was used to select participants in this study. The rationale of this method was to eliminate any form of errors when selecting participants.

Data collection techniques

Data collection was based on the scores of the learners in Agriculture as one of their subjects. The collection of data was done in end year semester of 2004-2005 examinations (Pense, Beebe, Leising, Wakefield & Steffen, 2006).

It is important to observe that the emphasis was laid on the fact that the participants were not to be informed of the study. This means that they behaved normally when addressing this examination, without the knowledge that they were under investigation. The results from the participants from the selected schools were collected after they were marked.

Levels of measurement of the variables

In this study, there were several levels of measurement of variables that had direct or indirect impact on the performance of the student in this subject.

The relationship between the teacher and students, teacher training experiences, the environment within which the education is taking place, and the actual process of teaching were some of the variables that affected the outcome of the students’ performance. This differed in the different schools that participated in this research.

Types of statistics used to analyze the data and generate results

This study used descriptive statistics in order to develop a generalization on the issue that was under investigation. The researchers used the Statistical Package for the Social Scientists (SPSS) in order to generate frequencies, standard deviation, and mean in the data collected.

Some of the participants left the study for various reasons, including those who transferred and did not sit for the exams for one reason or the other. 90% of the participants were involved in collecting the final data.

Inferences that can be drawn from the results

From this study, the inference that can be drawn from the result is that students in rural schools performed better in agriculture than their counterparts in urban or suburban schools. This was largely associated with the learning environment.

Students in rural schools are exposed to the practical aspect of what they are taught in the classroom, unlike their urban counterparts. Factors such as knowledge of the teachers, teacher-student relationship, and levels of student intelligence also played a role in defining this performance.

Special considerations: validity, reliability, generalizability

The validity of the research was determined using Cronchbach’s Alpha. The study had a high level of validity, especially on the instruments used. There was no direct interference with the subjects during data collection process. Bias in selection participants was also eliminated. This means that the results can be reliable when used to make a generalization on the entire population.

Correlational Study

How the application of the designs differ

In this study, the researchers used correlational research design. It involved close comparison of different variables in order to determine their relationship. The researchers were focused on testing for any statistical relationships that existed between the variables (Antoine, Miller & Chanda, 2003).

Unlike other studies, this research was focused on close comparison of various variables in the research. It is important to note that, unlike ex post facto study, correlational study engages the participants directly so that they are aware that the research process is in progress.

The sampling: rationale and techniques

The study sampled participants from two regions. The sampling was done in a group of secondary agriculture teachers in Virginia and North Carolina using simple random sampling. The desired sample population was 242 participants.

However, the researcher predicted that about 35% of the participants may fail to participate in the study after being selected. For this reason, 380 participants were sampled. The rationale of doing this was to ensure that if this parentage fails to respond to the question mailed to them, the study will have enough participants to take part in the research.

Data collection techniques

Data collection was done with the help of questionnaires that were sent to the participants in the selected learning institutions. A series of questions focused on the areas of interest were developed to help capture the required information. The respondents in these institutions were expected to respond to the questions and mail back the questionnaires back to the researchers.

Levels of measurement of the variables

This study identified a number of variables that were measured at different levels. The first level of measuring the variables involved analyzing the relationship that existed between instructional technology variable and gender (Antoine, Miller & Chanda, 2003). The second level was to determine the relationship between instructional technology variable and the age of the participants.

The third was to determine the relationship between instructional technology variable and higher degrees of the participants. Other variables that were compared closely with instructional technology variable included teaching experience of the tutors, program enrolment, program membership, access to a computer at home, and internet accessibility.

Types of statistics used to analyze the data and generate results

The statistics obtained were analyzed in order to determine the correlational analysis between selected variables mentioned. There was a need to determine instructional technology variables were affected by various other independent variables in the study.

The researchers used quantitative statistics to generate data. A correlational analysis was conducted using the Statistical Package for Social Scientists. It was considered appropriate when dealing with quantitative data.

Inferences that can be drawn from the results

In this study, the focus was to determine the ability of the participants to use technology to improve their teaching capability. To do this, they had to be able to understand instructional technology characteristics. The results obtained from the participants in North Carolina and Virginia indicated that technology played a major role in improving the performance of high school teachers.

However, various issues were affecting the ability to use technology in their teaching practice. This meant that a section of the participants had better capacity to use technology than the other based on various environmental factors

Special considerations: validity, reliability, generalizability

Reliability was given a lot of concern because there was a need to generalize the findings of this research to the entire population. In order to determine the validity of all the instruments used in this study, the researchers analyzed the reliability face and content of the data obtained. The approach used ensures internal and external validity makes the findings of this study reliable enough to make a generalization out of it.

References

Antoine, A., Miller, W. & Chanda, E. (2003). A Correlational Analysis of Instructional Technology Characteristics in North Carolina and Virginia Secondary Agricultural Education Curricula. Journal of Southern Agricultural Education Research, 53(1), 140-152.

Cubelic, C. & Larwin, K. (2014). The Use of iPad Technology in the Kindergarten Classroom: A Quasi-Experimental Investigation of the Impact on Early Literacy Skills. Comprehensive Journal of Educational Research, 2(4), 47- 59.

Pense, S., Beebe, J., Leising, J., Wakefield, D. & Steffen, R. (2006). The Agricultural Literacy Of Urban/Suburban And Rural Twelfth Grade Students In Five Illinois High Schools: An Ex Post Facto Study. Journal of Southern Agricultural Education Research, 56(1), 5-205.