Study On Academic Performance And Learning Strategies Of Tertiary Level Students

Abstract

Considering the interaction between the strategies of learning and academic performance is vital in teaching and learning environment. The purpose of the present study is to investigate whether there is a statistically significant correlation between students’ learning strategies and their academic performance in learning business and accounting courses. The Learning Strategies Scale was adapted from the Motivated Strategies for Learning Questionnaire (MSLQ). This instrument includes 31 items concerning students’ use of different cognitive and metacognitive strategies and 19 items regarding student management of different resources. Students’ academic performance was measured by their Cumulative Grade Point Average (CGPA). A total of 312 business and accounting undergraduate students participated in this study. Based on the correlational analysis, the results showed that effort regulation was positively correlated to their academic performance. Nevertheless, there was no relationship between other subscales of the learning strategies and students’ academic performance. This study offers insights on the relationship between learning strategies and academic performance which could assist to develop instructional strategies in enhancing students learning skills.

Keywords: Learning strategiescognitive strategiesmetacognitive strategiesresource managementacademic performance

Introduction

Learning strategies are one of the essential elements to be successful in higher education institutions. Nevertheless, not all educators and students are aware of the importance of understanding learning strategy. In improving the academic achievements, the main priority is to comprehend the educational complications (Khan & Rasheed, 2019). Educator especially in the tertiary education have to be very responsive of their teaching approaches in imparting information and knowledge towards the students as the learning process will determine the students’ academic performance. Hence, in helping the students to unleash their potential and progress holistically, teaching philosophies need to be concentrated in producing students learning outcome (Hanin et al., 2013). Based on this foundation, educators would be able to identify the students learning strategy so they can facilitate academic weaknesses and suggest better strategy and approach to suit the students learning ability. Workable learning strategies could help the students to cope and adapt to their learning requirement in higher education institutions. Besides, students are to be responsible in their own learning so they can unleash their full potential and consequently performed better in their education. Applying appropriate strategy in their learning experience will reward the students with better performance academically.)

Problem Statement

As different individual has different characteristics and preferences in studying, so do their learning strategies. There is little evidence on the relationship between learning strategies and academic achievement among students in tertiary education in Malaysia. Hence, the focus of this study is to explore learning strategies among undergraduate students in business management and accounting programs and how the learning strategies are correlated to academic performance. Identifying various types of learning strategy with regard to its relationship to academic performance is important as an effort to further understand how cognitive and metacognitive components are related to academic performance. Besides, Malaysian students have been identified to be lack in certain skills such as English communication, professional and technical skills (MOHE, 2012). This issue could possibly due to the deficiency of understanding learning strategy and approach to enhance teaching and learning in education institutions. The study strategy’s formulation has made the learning more meaningful is part of vital phase in education development of any learners (Khan & Rasheed, 2019). Therefore, this study is not only crucial for integrating the existing theories of individual differences but also as a fundamental for shedding light on understanding the learners’ differences of learning at tertiary level. Both educators and learners play an important role to identify the differences of learning strategies to improve academic achievement.

Literature Review

Research Questions

The main question of this study wants to address undergraduate students’ learning strategies and

its relationship with academic performance.

Purpose of the Study

The current study is aimed to examine undergraduate students’ learning strategies and its relationship with academic performance. The results of this study could be effective in terms of its contribution to trigger awareness among educators and students particularly at tertiary institutions in relation to learning strategies.

Research Methods

Findings

The mean (M) and standard deviations (sd) for all items in the nine learning strategies subscales are presented in Table 2 .

A descriptive analysis was performed to identify the means and standard deviation of the nine subscales of learning strategies as presented in Table 2 . To recapitulate, the views regarding the subscales were rated on a Likert scale ranging from “strongly disagree” (1) to “strongly agree” (7). Based on the descriptive statistic, the highest mean score (M=5.2756) was for rehearsal strategy. The findings also show that the item with the highest mean for rehearsal is “memorize key words to remind me of important concepts in this class” (M=5.5705, sd=1.2634) while the lowest mean is “practice saying the material to myself over and over” (M=4.9551, sd=1.37194).

The second highest occurrence of learning strategy (M=5.0705) was organization strategy. The result also indicated that “outline the material to help me organize my thoughts” (M=5.3205, sd=1.25258), is the highest score of the subscale while “make simple charts, diagrams, or tables to organize course material” (M=4.5577, sd=1.77963) is recorded as the lowest score of organization learning strategy. In contrary, time/ study environment management strategy has the second lowest mean score (M=4.7612). The item with the highest score for time/ study environment management learning strategy is “study in a place where I can concentrate on my course work” (M=5.5000, sd=1.25008) while “I rarely find time to review my notes or readings before an exam” (M=3.3782, sd=1.67195) has the lowest score.

Finally, the lowest mean score of the subscales (M=4.6843) was effort regulation strategy. The highest mean for effort regulation strategy is “I manage to keep working until I finish” (M=5.3269, sd=1.19033) while “I either give up or only study the easy parts” (M=4.1667, sd=1.77816) has the lowest mean. Table 3 summarizes the correlation between the nine subscales of learning strategies and academic performance.

Table 3 presents the correlation between students’ learning strategies and academic performance. Based on the findings there was a positive correlation between effort regulation learning strategy and academic performance, r = 0.127, N=312, p =0.005. A low strength of association was noted between the variables. Nevertheless, there was no correlation between academic performance and other learning strategies. Effort regulation strategy is one of the subscales under resource management strategy. Among the strategies in effort regulation is being persistence in the face of difficult or boring tasks, handling challenging activities or tasks, and the capacity and ability to remain persevere when confronted with academic challenges.

Mixed results were found in previous studies with regard to effort regulation strategy. Effort regulation is one of the strategies that correlated with academic performance as noted by Broadbent and Poon (2015). This study found that four learning strategies have significant relationship with academic performance namely effort regulation, time management, metacognition and critical thinking. In the same vein, other studies have also found positive relationship between effort learning and academic performance (i.e., Carson, 2011; Cho & Shen, 2013; Puzziferro, 2008). On the contrary, Chan Lin (2012) in her study found that the relationship between effort regulation and academic performance is not significant.

Furthermore, the current study discloses that although effort regulation strategy is the only learning strategy associated with academic performance, effort regulation is also the learning strategy with the lowest mean (M=4.7612). In addition to that, further descriptive analysis of the students leaning strategy subscales shows that “I manage to keep working until I finish” (M=5.3269) has the highest score of mean followed by “I work hard to do well in this class” (M=5.000) as the second highest score. This is the followed by “I often feel so lazy or bored when I study” (M=4.6795) and “I either give up or only study the easy parts” (M=4.1667) as lowest and second lowest scores of mean.

This finding is also aligned with Kim et al. (2015) who explored the differences between high-achiever and low-achiever students. The study reveals that high-achiever students who could sustain higher level of effort regulation throughout the semester will eventually have higher academic performance. In a systematic review of 59 research papers to identify the role of self-efficacy and performance among university students, Honicke and Broadbent (2016) concluded that effort regulation appears to at least partially facilitates academic performance. Students with a higher effort regulation are more likely to adjust the amount of effort spent on a learning task, hence, will result in higher level of academic performance.

In addition, prior research has found that effort regulation is important in facilitating academic performance (Kassab et al., 2015; Komarraju & Nadler, 2013). These studies have also discussed effort regulation in relation to self-efficacy trait. Students with higher self-efficacy will perform higher academic achievement due to the combination of cognitive and effort regulation strategies. Similarly, Robbins et al. (2006) have proposed effort persistence as one of the predictors of academic performance.

Based on the study conducted, it is noted that the students can perform well in their academic performance although they faced academic encounters. Having perseverance and retaining effort to confront the challenges will not make them fail, but eventually will lead the students to gain benefit in relation to their academic performance. It is possible that students with greater effort regulation strategies perform at a higher level because they can cope more efficiently with academic challenges. This could also due to the ability of the students to remain positive, increase effort, and assemble relevant self-regulating strategies in facing difficult tasks so that they can survive and become successful students.

Conclusion

The main objective of this study is to examine the relationship between undergraduate students’ learning strategies and academic performance. Findings from this study indicated that there is a significant and positive relationship between effort regulation and academic performance. This finding shows that the respondents tend to apply effort regulation as their learning strategy to obtain the current academic performance. Learners with higher academic performance exhibits more effort regulation strategy in their learning in comparison to the students with lower performance.

This study has several limitations. First, the participants of the study could be considered as bias due to the participants’ background that is only from business and accounting programs. This is because students in different fields of study might have different learning strategy. Furthermore, the relatively small number of students participated in this study. Even though random assignment would have been best, it was not a viable option. Nonetheless, further research should be conducted whereby larger number of students involving other institutions is studied.

Second, as this study only serves to examine the association between learning strategies and academic performance, further research that consider other individual differences such as learner motivation, self-efficacy and other individual traits could be conducted. Longitudinal study could be carried out in investigating how and in what way these individual difference traits inhibit or exhibit the learning process.

From these findings, a more dynamic picture of how learning strategies could be geared among undergraduate students is possible. The results suggest that academic performance could be boosted by applying effort regulation strategy in learning. Being able to improve academic performance would be beneficial for educators and students at various levels.

Moreover, to maintain the student’s academic performance, everyone in the organization needs to give full commitment and supports to ensure the goal can be achieved. Therefore, to assist students to understand and apply relevant learning strategies, the institution needs to organize programs such as workshops or seminars so that greater awareness could be enhanced. Furthermore, educators should encourage their students to be more flexible to understand the importance of understanding and applying learning strategies.

The findings offer implications for research on teaching at tertiary institutions. Understanding how students’ apply learning strategies during their learning experience provides information of how useful certain learning strategies could be in facilitating teaching and learning process. Using these results, instructors can identify students who may be having trouble in learning and provide additional study skills assistance. The empirical evidence provided by this study could also offer future direction particularly to university students for creating potentially effective support and relevant approaches in accommodating strategies they apply in learning to improve the quality of academic achievement.

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