Relationship between College Students Aptitude Test and Algebra - Research Paper Example

Quantitative Research Design on the Relationship between College Aptitude Test and Algebra Submission Date: Quantitative Research Design on the Relationship between College Students Aptitude Test and Algebra Introduction Most students enter college and other institutions of higher learning with predetermined courses and subject areas they want to read. Others also go into these institutions with yet several unanswered questions about exactly want to they want to achieve in life. In either case, Mishra (2007) found a fundamental issue where it is important for students to be guaranteed that whether they have predetermined choices or are unaware of their choices they can be assured that whatever course they read in the long run will be suitable for their academic competence. Based on this understanding, a number of principles and concepts as to how students can determine their academic competence in specific areas of studies have come up. Commonly, these principles and concepts tend to take an area of a students’ life that is very easy to measure or assess and uses this to correlate with previous academic outcomes (Murat, 2009). At other times when the results are not based on the student’s own history, they are based on conclusions of research with similar variables that are being measured as that of the student in question. Purpose of study The purpose of the study is to find the correlation that exists between college students’ aptitude test and performance in algebra. As stated in the introduction, taking decisions about students’ competence based on another aspect of their life is not a new practice. This study is therefore based on similar study as was conducted by Olson (2003) on the topic of “Predicting undergraduate mathematics success: an analysis of UCDHSC placement methods and the ACCUPLACER exam”. The current study builds on the previous research in two major ways. The first is to widen the population of the study by putting college students into a generalized context. The second is to be specific about the variables for measurement, which in this case are aptitude test and algebra. At the end of the current study, it will contribute knowledge to education by aiding students and academic faculties in making more informed decisions when it comes to the assignment and placement of students for courses. This is expected to be done with the use of aptitude test, especially for students who are to read algebra. Where algebra is a compulsory course to be read, faculty will be aided on how they can identify weak students to assist them based on their aptitude test scores. Hypothesis The study’s purpose is stated in the form of a hypothesis, given the fact that the study is generally a correlational one, whereby a given hypothesis must be justified or rejected. The study will therefore seek to deal with the following forms of hypotheses: Null hypothesis: college students’ aptitude test does not impact on algebra Alternative hypothesis: college students’ aptitude test impacts on algebra. Because this is not the first study of its kind, there are a number of existing theoretical frameworks that this study relates to. One of these is the classical methods for predicting long-term college success, used in Olson (2003). In this framework, success in mathematics is taken to be an interdependent concept, which is influenced by a number of life achievement factors. Some of these achievement factors must however be related to cognition such as verbal scores, math score and extra-curricular activities. The current study therefore relates to this framework and actually builds on it by focusing all the achievement factors into the college aptitude test. This study is a quantitative research and so there will not be the use of grounded theory approach. As far as theory is concerned, the study relates to the social cognitive theory, which seeks to link such social factors found with aptitude test as self-efficacy to academic achievement (Cabrera, Castañeda, Nora & Hengstler, 1992). Literature Search The study will depend very heavily on existing research, so as to guarantee the empirical nature of the primary data collection to be performed. In line with this, a literature search will be performed to select the best articles that address the topic at hand. A total of 24 articles will be targeted, which will be spread across four (4) major themes for the study. The descriptions to be used in the search will therefore come from key words in the themes. The themes are thus given as follows: i. Social variables that make the aptitude test ii. How social variables in aptitude test relate to concepts in algebra iii. Achieving effective course placement with aptitude test scores iv. Improving student performance in algebra based on their aptitude test score Based on the themes given above, the key words to be used in the search will include social variables, aptitude test, algebra, course placement, and student performance. These descriptions and key words shall be used with reference to five major academic databases which are ERIC, Academic Search Premier, PROQUEST, Google Scholar, and PsycINFO. It is expected that from these databases also, a search will be performed for literature reviews published in this study area. Research Design The study will be performed as a quantitative correlational design, which will seek to measure the relationship between college student aptitude test and algebra. As a quantitative study, a lot of attention will be given to hypotheses, based on which variables shall be identified and tested with the use of the research instrument (Dellinger & Leech, 2007). Hakim (2010) however warned that whiles doing this, a number of threats can be posed to internal validity. One of these threats is testing, whereby a repeated participation in similar study may cause a respondent to gain experience in this area and thus influence responses. This will be minimized by screening participants to be sure that they are all first time participants. The second threat has to do with instrumentation, whereby the instrument may fail to be consistent with what the study intends to measure (Adams and Schvaneveldt, 2011). This will be overcome by forming a mock sample that is first used to measure cause-effect relationship. To maximize generalizability of the findings, emphasis shall be given to fairness in the sampling process so that the findings can be as widely representative as possible. Sampling The study is expected to be carried out in a college setting. Students in the second year and reading algebra as a compulsory or core subject are to be used as the population. It is expected that there will be over 100 students in all forming the population. The rationale for using core algebra instead of elective algebra is that in the elective algebra, there are higher chances that most students will have high competence in the subject and so measuring academic performance may be very limited. What this more, using the elective algebra will limit the number of respondents and thus affect generalizability of the outcomes negatively (Green, Johnson and Adams, 2006). With this said, a sample size will be constructed from among the population, which will be expected to be made up of students with many different academic competence in algebra. The sample size shall be 50. The sampling procedure to be used will be a random sampling technique for the reason that it guarantees fairness and avoids biases in the selection process. 50 is found to be appropriate for the sample size as it gives a very large representation of the total population whiles avoiding the temptation of handling too many people than can really be catered for by the researcher. There will be no subgroups but a mock sample made up of the students in the researcher’s class shall be used. Limitation with the study will be with the total elimination of generalizability issues as only one school will be involved. Variables The variables of the study are directly set from the hypotheses that were formed earlier. In line with this, the hypotheses are stated again as follows: Null hypothesis: college students’ aptitude test does not impact on algebra Alternative hypothesis: college students’ aptitude test impacts on algebra. From the hypotheses, the following variables are identified: Independent variable: aptitude test score Dependent variable: achievement in algebra Methods of data collection Data collection shall data place by the use of primary data collection procedure, which means that the researcher shall be physically present at the site where the data will be collected (He and Opposs, 2012). Data collection will take place through the use of a test checklist specially developed as a measure or instrument for data collection. As a checklist, what the instrument will seek to do will be to find out the outcomes with students aptitude tests and compare this will major test outcomes performed in various topics in algebra. For the semester, there shall be four major topics that will be selected in algebra, for which student outcomes will be measured. The variation in topics will be used so that it will be possible to relate specific traits within the aptitude test to different topic areas in algebra. After this, a second instrument that will involve students more directly in the form of questionnaire shall be prepared. The questionnaire shall be delivered onsite to the students after the inputs of the questionnaire have been explained to them. The purpose of the questionnaire will be to sample views and opinions from students on how they feel their aptitude affects their learning in algebra and how they could be better assisted in improving their learning of algebra. The role of the researcher in all of this will therefore to be a facilitator, who does not directly influence the outcomes with the study but implements the data collection process to ensure that the goals of the study are achieved. Data analysis procedures After data have been collected, a statistical quantitative analysis procedure shall be used in establishing the relationship between student aptitude test and algebra. This statistical quantitative procedure shall involve the use of Pearson correlation. The rational for selecting the Pearson correlation is because the variables being tested in this study are normally distributed and linear (Dorn et al., 2013). This is because there is only one dependent variable which will be tested against one independent variable. This correlation will therefore make it possible to determine if the scores obtained in various aspects of the aptitude test has any correlation with achievement in algebra. Another important thing that the Pearson correlation will do is that it will give the researcher the opportunity of measuring how strong the various correlations to be established are (Gall, Gall & Borg, 2006). Ethics and human relations As part of this academic exercise, there will be a number of ethical considerations that will be made. These ethical considerations are particularly important, given the fact that there will be human participation in the study. In the first instance, the researcher shall ensure that an official permission is granted from the research setting, which will be the school where data collection is expected to take place. After the permission has been granted, a consent form will be prepared for all respondents. This consent form will state the purpose of the study, why it is important for the respondents to be part of the study, as well as the role expected to be played by the respondents. After this, the researcher shall ensure that during the actual data collection process, the confidentiality and anonymity of respondents is guaranteed. One way to ensure this will be to avoid the use of any form of identity for the respondents, such as their names. Finally, respondents will be given the freedom to exit the study at any point that they find convenient. It is expected that the official letter to be prepared will help the researcher gain access to the research site whiles the consent form will make it easier to solicit participant cooperation. Conclusion To conclude, it will be reiterated that the importance of giving students the right placement or assistance with their academic achievement is very important for the overall success of the students. It is for this reason that all available means by which factors influencing students’ achievement must be identified (Mzumara and Shermis, 2001). The research that has been planned will become an important avenue for establishing the relationship between aptitude test scores and algebra. As aptitude tests are very common with most colleges, it is expected that an additional advantage will be found with this test when the correlation it has with algebra are clearly spelt out at the end of the study. References Adams, G. and Schvaneveldt, J. (2011). Understanding Research Methods. New York: Longman. Cabrera, A., Castañeda, M., Nora, A. & Hengstler, D. (1992). The convergence between two theories of college persistence. The Journal of Higher Education, 63(2), 143-164. Dellinger, A. B. & Leech, N. L. (2007). "Toward a Unified Validation Framework in Mixed Methods Research". Journal of Mixed Methods Research; Vol. 1, No. 4, pp. 309–332. Dorn et al. (2013). Longitudinal Reliability of Self-Reported Age at Menarche in Adolescent Girls: Variability across Time and Setting. Developmental Psychology, 49(6), p1187-1193 Gall M. D., Gall J. P. & Borg W. R. (2006). Educational Research An Introduction (8th ed.). Boston, MA: Pearson Green, B. N., Johnson, C. D., and Adams, A. (2006) "Writing Narrative Literature Reviews for Peer-Reviewed Journals: Secrets of the Trade". Journal of Chiropractic Medicine; 5(3), pp. 101–114. Hakim, C. (2010). Research Design: Successful Designs for Social and Economic Research. London: Routledge. He, Q and Opposs, D. (2012). The Reliability of Results from National Tests, Public Examinations, and Vocational Qualifications in England. Educational Research and Evaluation, 18(8), p779-799 Mishra SG (2007). Teaching Attitude Score a criterion for Admission in colleges of education. Edutracks, February 2007, Vol.6 – No.6 pg.25-27 Murat P. (2009). Pre-Service Teachers’ Teaching Anxiety about Mathematics and Their Learning Styles. Eurasia Journal of Mathematics, Science & Technology Education, 2009, 5(4), 335-345 Mzumara H. R. and Shermis M. D. (2001). Predictive validity of placement test scores for course placement at IUPUI. Technical Report 317-274-2620, Indiana University Purdue University Indianapolis, 2001. Olson G. A. (2003). Predicting undergraduate mathematics success: an analysis of UCDHSC placement methods and the ACCUPLACER exam. Retrieved October 25, 2014 from http://math.ucdenver.edu/graduate/thesis/olson_gary.pdf Read More