Introduction
To conduct this research I will use a between-subjects design. In this method, I will divide the sample into two groups. One of the groups will be a control group. The control group will not be allowed to use calculators while working on mathematical problems. The use of between will require a comparison of the score for each group of students. Each of the participants will have a unique score. Since each of the participants has a separate score, this design is often called independent measure design. The use of this design will have several advantages to the general research procedure. In the first place, the participant’s scores will not be influenced by factors such as repeated practice since he or she only performs the task once. The participants will also not be influenced by contrasting effects that result from treatment. However, this design will also have its shortcomings. It would be difficult to measure individual differences. Individual differences include things such as different intelligence quotients among students. These differences can become confounding variables in research thus decreasing the authenticity of the results.
This research will entail measuring four very important variables. The variables to be measured include proficiency measure without the use of a calculator and the proficiency measure with the use of a calculator. I will measure the two variables using the percentage each of the students obtains in a mathematical test. The average score for each group will be calculated and compared between the two groups under study. The other variables I will measure are; accuracy and speed of completion. Accuracy will be measured in terms of how the students present the answers in their tests. The number of questions that the students answer correctly will determine the accuracy of his or her work. Speed on the other hand will be measured using the time taken to complete the test. The lesser time a student takes to complete the test the faster the student.
Subjects
Research on the moderating effects of calculators in the fashion merchandising industry will provide insight into how the use of mathematical calculator change the properties of a mathematical test score (Henson, 2001). However, the choice of a sample to study is really important. In determining the sample determining the target population is very important. In this case, the target population is the students enrolled in the fashion merchandising industry program. The next step after the determination of the target population will be to determine the sample size. It is statistically logical that a small sample may reflect the characteristics of the group from which it is drawn. A larger sample will reflect the target group more precisely. A point to note about sampling is that the precision increases as the sample size increases. The decision of choosing the sample will vary depending on the budgetary allocation for the project, availability of time, willingness of the participants and the degree of precision. This research requires a high degree of precision. However, the research methods used for this project do not encourage participation unless there is an incentive. Taking this into account plus the budgetary allocation, the sample size for this project will be about 40 participants. To attract the participants, I will offer an incentive in the form of money for every test paper completed. However, each participant can only complete one paper at any given time.
All the participants in this project must be fashion merchandising students. In addition to this, the sample selected must avoid any form of bias. Excluding bias completely from a sample is extremely hard. However, by using quotas there may be the elimination of bias that may arise in a sample. To avoid the bias of gender allocation I will ensure that the ratio of the male and female participants in the sample reflect the ratio exhibited in the target population. Another bias that may arise is the bias caused by individual differences. To avoid this bias all the students picked for the study will need to have attained grades that are almost equal in magnitude. This will assist in reducing the risk of confounding variables that arise due to individual differences.
Study Measures
Measures are components in research to which the participants will need to give a response (Pelham and Blanton, 2006). For example, measures may include interviews, questionnaires, surveys questions and tests. All the questionnaires, interviews and tests must be relevant to the topic. Moreover, they should not be time-consuming and should be able to capture the attention of the participants. Several design elements will be taken into account to ensure the study is effective. Study measures will include:
- Taking into account the character of the participants.
- All the questions in the test will be constructed in a manner that will allow all the participants to understand them.
- No questions are supposed to be leading to ensure that the participants give answers according to their understanding of the question.
- All the questions in the questionnaire will be brief so that the test takes the shortest time possible.
- All the questions will be non-ambiguous.
- The test will contain multiple questions that will allow testing the accuracy, speed and proficiency.
Reliability and validity
The use of these measures will ensure that the research conducted maintains a degree of integrity. Measures limit the degree of bias in a study. For example, by taking into account the character of the participants I will be reducing the risk of getting non-serious participants thus increasing the reliability of the study. The content validity is a subjective measure that analyses whether the measures taken encompasses the whole domain of the content. To measure the validity the relevance of the measures are checked against the topic of study. Measures that will be taken in this study will ensure that the research remains within a relevant range. Therefore, the measures used will enhance the research process.
Material and Apparatus
The research will require the use of several materials. Included in the list are pencils for students to use while undertaking the test. Calculators are also necessary since they will be used by the non-control group. Working papers where students can perform their calculations are required. Moreover, the research would require erasers and question papers.
Procedure
All the participants will be exposed to a classroom setting. Before this activity, all the participants will be assigned specific tests and separated into the control group and the experimental group. The experimental group will be given calculators to assist them in completing the arithmetic test. Participants will be informed to treat the test like any other test. Each of the groups will have thirty minutes to complete their test. Both the groups must complete the test under the watch of a supervisor to avoid bias that may arise if the students were left alone. Time taken by each student to complete the test will be recorded by the supervisors.
Data Analysis
All the tests will be marked out of 100 per cent. These results will be analyzed using ANOVA to see if any difference occurs between the two groups of students. SPPS will be used to simplify the process of data analysis and to generate all the required graphs.
Limitations
Various limiting factors will exist in this study. To begin with, financial constraints may be a major limitation to this study. The cost incurred to purchase approximately twenty scientific calculators, forty pencils and forty erasers will be high. Therefore, to solve these problems participants will be required to work on their tests at different times. This will to the consumption of more time than is required. Moreover, it may encourage cheating since the participants may pass information about the test to others. Another limitation of this study is the fact that participants may not take the test seriously. Therefore, the results exhibited may not reflect the results that are expected. Another limitation to this study is that it may not provide a test of how the use of calculators may affect alterations in disciplines. This means that once the research has been performed in the fashion merchandising industry it becomes difficult to measure how the results can be used in case a student changes his or her discipline of study.
References
- Henson, R. K. (2001). Understanding Internal Consistency Reliability Estimates: A Conceptual Primer on Coefficient Alpha. Measurement and Evaluation in Counseling and Development, 34 (1), 177-189.
- Pelham, B. W. and Blanton, H. (2006). Conducting Research in Psychology: Measuring the Weight of Smoke, London: Wadsworth Publishing