Research Question

1.1  Background

Academic performance and its factors are a recurring subject in education debates and researches. Young (1998) noted that academic achievement in any school program is subjected to many different variables “including intelligence, instructor quality, curriculum quality, material presented, and the amount of time spent studying the material presented” (p.1).

Grade is known to be a primary parameter for learning, therefore it is assumed that if a student gets high grades he or she was able to learn well the subject, in the contrary, if the grades are low that indicate poor learning.

Young (1998) stated that one of the factors that impact academic performance is the amount of time studied. Study time and student’s achievement have been the subject for many researchers, Ukpong and George (2013) mentioned studies by Logunmakin (2001), Kumar (2002) and Gbore (2006), in which they agree that “study time attitude affects strong relationship with academic performance of students” (p.173). However, Plant, Ericsson, Hill and Asberg (2005) suggested that the amount of study done by college students predicts poorly academic performance.

1.2 Study

Study time means the specific time a student assigns to study in order to acquire knowledge. It doesn’t really matter if it the person study at the same time every day, if the radio or television are on while reading, or whether they use additional resources in order to study (Ukpong et al., 2013).

Ukpong et al. (2013) suggested that “quantifying the effect of study time on achievement seems important from at least two perspectives: from the perspective of the instructor, who creates classroom learning, experiences and measures learning outcomes, and finally from the perspective of the student who seeks to balance competing personal goals” (p.172).

Therefore, this study is aimed to investigate if the amount of time spent studying influence on test scores among nutrition graduate students of the University of Bridgeport. 

Research hypothesis

It may be common for some people to believe that students that spend more time on academic related activities (e.g., reading the text, completing assignments, studying, and preparing reports) are have better scores than students who spend less time on these activities. However, due to contradictory evidence of outcomes in previous researches reviewed in the literature, there is a need to re-investigate this relationship. Hence, for the purpose of this project, the relationship between hours of study and test scores will be analyzed. Thus, the hypothesis is:

H1: There is a relationship between time spent studying and test scores among nutrition graduate students of the University of Bridgeport. 

The following null hypothesis was formulated to guide the study:  

H0: There is no relationship between time spend studying and test scores among nutrition graduate students of the University of Bridgeport. 

Hence, the independent variable is minutes studied, and the dependent variable is the test score. Therefore, we predict that the more time spend studying the higher should be the test score.

Design study and methodology

3.1  Participants

The data was limited to a group of 10 graduate students from a master’s program in nutrition of University of Bridgeport, NY. All 10 participants were females, between the ages of 24 and 52. They are all from the same class of organic chemistry.

Though this is a small sample, that as a limitation could increase the likelihood of a Type II error skewing the results, which decreases the power of the study. This sample would give meaningful results for the population selected since all students of this class agreed to participate in the study.

3.2  Research Instrument

The instrument used in this study was a simple two question form where the students were asked to answer: the amount of time studied on the week before a test, and the grade obtained on that test.

3.3  Method of data analysis

In order to test this hypothesis, the Pearson product-moment correlation coefficient was used, this method was selected because it is used to test hypotheses of association, and can also provide information about the degree of association between two variables, a regression was also done in excel to get the p-value in order to determine the significance of the results.

Conducting the study/collecting numerical data

In order to answer the research question: if the amount of time spent studying influence on test scores among nutrition graduate students of the University of Bridgeport; this study was designed to collect the data anonymously.

4.1  Research Procedure

The instrument was sent via e-mail to the participants about two weeks prior to the organic chemistry midterm test. The instructions to answer the questions were very simple and objective, they were asked to compute the number of hours studied prior to the midterm test, and also report the score obtained on that same test, and send back via e-mail.

There were 10 participants in total (total number of students in this class) and all 10 returned the questionnaire. The respondents were asked to be the most honest and accurate in their responses.

 In order to control for bias the researcher did not had personal contact to any of the students of this class, all the contact was done via e-mail and all the answers were done anonymously. Therefore, there would be no reason to pretend to be a “better” student or give more hours of study time to give a “good impression”. About one week after the midterm, all answers were collected and the analysis process started.

Analyzing data

As shown on table 1, the results of the Pearson correlation coefficient indicated that there was significant positive association (r = .66, p = 0.03) between the amount of study time and test score this value is high because, as Furr and Bacharach (2014) noted, a large positive correlation will fall between .5 and 1.0, they also mentioned that “the correlation coefficient is an important part of reliability” (p.52). A regression was done in order to get the p-value, considering alpha at .05.

    Table 1. Correlation and P-value

N

r

P-value

Minutes Studied

10

0.6633133599

0.03653822064

As noted in the scatterplot below, as the number of minutes of study increase, the test scores also increase, though there are some outliers, the result indicates is a positive linear relationship. Therefore, a positive correlation exists between this two variables. Thus, the null hypothesis is rejected. Hence, we accept the alternative hypothesis that states that there is a relationship between time spent studying and test scores among nutrition graduate students of the University of Bridgeport. 

Discussion of statistical significance of results

According to Furr et al. (2014), statistical significance “is related to researcher’s confidence in a result” (p. 181). That is, if the results are significant, they can be considered as a real finding.

Therefore, based on the correlation coefficients, the hypothesis that tested direct relationship was supported, that is, the results (r = .66, p = 0.03) indicate that there is a significant relationship between time spent studying and test scores among nutrition graduate students of the University of Bridgeport. Thus, is possible to affirm that the more time spend studying the higher is the test score. 

 Supporting this results Ukpong et al. (2013) mentioned that “. If a learner earns high grades or scores high marks, it is an indication that he/she may have taken time to study well, while low grades is interpreted as using lesser time for learning” (p. 176).

 Although the results support the initial prediction, there are many extraneous variables in this study, and according to Young (1998) “it is next to impossible to control variables such as how students spend their time out of school, previous grades, motivation toward school, and the student’s home life. All of these variables have the potential to destroy the internal validity of the research study” (p. 11), and as pointed out by Furr (2014), effect size can affect statistical significance, which can lead to reliability and validity problems. However, we believe that, though the this was a small sample size, these results should be taken into consideration.

Summarizing your conclusions

After reviewing the literature, we found some contradictory results regarding the relationship between study time and test scores, for example Plant et al. (2005) that found no relationship to academic performance in a university setting. In addition, Plant et al. (2005) suggested that “the quantity of study time may only emerge as a reliable factor that determines performance when the quality of study time and the student’s SAT scores are also taken into consideration” (p. 112). Hence, we found necessary to research this hypothesis in order to draw our own conclusions.

Thus, after analyzing the data collected, provided by the nutrition graduate students of the University of Bridgeport, we found a strong correlation between the variables study time and tests scores, these results indicate that the more time the students put into studying the higher would be the score.

It is possible to suggest, that the importance of these findings for the students are a fundamental way to reassure that the time and effort put into studying has a positive outcome, in this case a higher test score, therefore this should be considered as a motivator to students.

In addition, is important to notice that this study had some limitations, such as sample size, which can affect reliability and validity of the results, though we believe that the results are significant to this study, because as noted by Plant et al. (2005), “those who engage in deliberate studying take active steps to ensure their practice time will be of high quality and encourage the improvement of performance” (p. 111).

References

Furr, R. M., &   Bacharach, V. R. (2014). Psychometrics: An introduction (2nd ed.) Thousand Oaks, CA:Sage  Publications.

Plant, E. Ashby, Anders K. Ericsson, Len Hill, and Kia Asberg (2005). “Why Study Time Does Not Predict Grade Point Average across College Students: Implications of Deliberate Practice for Academic Performance”, Contemporary Educational Psychology, v30 n1 p96­116, Jan.