psychology research paper

RESULTS

Descriptive Analysis

To understand the dynamics of the results attained one needs to understand the characteristics of the participants. This was done using descriptive where the mean, median, standard deviation to name a few were calculated. The sample size used was 232 with an equal distribution between those who do not have study groups and those who do. The participants who had no study group accumulated a mean of 61.8362, SD= 4.45059 with a minimum of 48.00 and a maximum of 69.00. Those who had study groups had a mean of 84.9828, SD=4.65503 at a minimum of 74.00 and a maximum of 98.00. They resulted in M=73.4095, SD=12.45670 with a skewness of 0.008.

Table 1: Descriptive Statistics

	No	Yes	Overall
N	116	116	232
Mean	61.8362	84.9828	73.4095
Median	63.0000	85.0000	71.5000
Std Deviation	4.45059	4.65503	12.45670
Variance	19.808	21.669	155.169
Minimum	48.00	74.00	48.00
Maximum	69.00	98.00	98.00

Independent T test

In respect to the objectives of the study. The following hypotheses were derived to aid achieve set research questions:

Null Hypotheses(H0): There exists no significant difference between participants who have study groups and those who do not in exam scores

Alternative Hypotheses(H1): There exists a significant difference between participants who have study groups and those who do not in exam scores.

As seen in table 2, an independent t test was used as it is the most appropriate to examine the differences between groups. It was conducted to compare the exam scores between the group of participants who have study groups and the group of participants in who do not. There was a significant difference in exam scores between Group 1-those who have no study groups (M = 61.8362, SD = 4.45059) and Group 2-those who have study groups (M = 84.9828, SD = 4.65503), t(DF) =-38.709, 0.000 < .05. As a result, the null hypothesis was rejected, and the alternative hypothesis was accepted.

The effect size for the analysis (d = 0.59796) was found to be exceed Cohen’s (1988) convention for a medium effect (d = 0.50). Levene’s test for equality of variances was not violated for the present analysis, F(DF) = 0.00, p =0.000. These results suggest that when participants who do not have study groups will have lower exam scores. Specifically, our results indicate that participants who have study groups will have higher levels of exam scores than those who choose not to.

Table 2: Comparison of exam scores in study groups
	Levene's Test for Equality of Variances	t-test for Equality of Means
	F	Sig.	T	df	Sig. (2-tailed)	Mean Difference	Std. Error Difference	95% Confidence Interval of the Difference
								Lower	Upper
Examscore	Equal variances assumes	.000	.996	-38.709	230	.000	-23.14655	.59796	-24.32474	-21.96837
	Equal variances not assumes			-38.709	229.538	.000	-23.14655	.59796	-24.32475	-21.96835

DISCUSSION

Results derived from analyses show that there was a difference in exam scores between those who were in study groups and those involved in none. This was seen with the difference in mean at 23.1466 which had exceeded the medium effect at 0.6. The individuals that were involved in study groups managed to score a higher exam mean at 84.9828% while those with none had a mean score of 61.8362%. In general, this means that there is a slightly more than medium effect on exam scores in involvement of study groups. This supports scholars such as Altman & Miller(2017) on collaborative studying enhancing understanding of topics. The results show that the effect is more than medium enhancing the need to promote study group involvement of students. Moreover, Gillies & Boyle (2011) suggested that collaborative work not only promotes academic achievement but also collaborative abilities. They noted it helped regardless of age or curriculum for individuals to be more open to sharing ideas, learning to inquire, clarifying differences, problem-solving, and construction of new understandings.

Contrary, few studies show that some groups are declared redundant as enthusiasm for group work is affected by type of task, as well as the group’s members. This presents a gap as it suggests that just being in a group will not automatically help in the increase of a student’s performance. Moreover, Faroq et al., (2011) put forward that it did not matter what kind of learning technique a student uses, but majorly on the student’s social economic status. This was from research done in Pakistan that revealed that social economic status was a significant predictor of a student’s performance besides school factors. This shows that other derivatives should be considered while examining the performance of students. However, it is also noted that exam scores do not show understanding of a topic. Karpicke(2009) noted that learning can only take place when students are able to retrieve the information learnt twice. Therefore, it is efficient to study the learning techniques of the study groups to examine whether the techniques used are effective in learning topics successfully.

The study is limited to data collected only on scores and not also on other factors such as time spent in the study groups and interaction of students within the group. This would have aided in examining the correlation between exam scores and the dynamics of the study group.

In conclusion, further data driven research is needed to understand the study group dynamics and how it affects exam scores. Also, research can be done before and after scores of students who were not in study groups but later joined to help cement the notion on effectiveness of groups.

REFERENCES

Farooq, M. S., Chaudhry, A. H., Shafiq, M., & Berhanu, G. (2011). Factors affecting students’ quality of academic performance: a case of secondary school level. Journal of quality and technology management, 7(2), 1-14.

Gillies, R. M., & Boyle, M. (2010). Teachers' reflections on cooperative learning: Issues of implementation. Teaching and teacher Education, 26(4), 933-940

Karpicke, J. D. (2009). Metacognitive control and strategy selection: Deciding to practice retrieval during learning. Journal of Experimental Psychology: General, 138(4), 469.

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