Study Habits and Academic Performance in Mathematics among Secondary School Students in Nigeria

Study Habits and Academic Performance in Mathematics among Secondary School Students in Nigeria

Felix Ayodele Omoniyi¹, Felix John Fawehinmi²

¹University of Benin, Benin

²Adeyemi Federal University of Education, Ondo

DOI: https://dx.doi.org/10.47772/IJRISS.2025.906000303

Received: 06 June 2025; Accepted: 10 June 2025; Published: 12 July 2025

ABSTRACT

This study examined the correlation between study habits and academic performance in mathematics among secondary school students in Nigeria. Recognising the widespread concern over declining educational standards, particularly in mathematics, this research investigated the impact of specific study habits–library use, note-taking, and time allocation–on students’ performance. This study is anchored in theoretical frameworks, including the Pickle Jar Theory of Time Management and the Self-Regulated Learning (SRL) theory, which emphasises the importance of effective time use and autonomous learning strategies. A mixed-methods approach was employed, integrating quantitative and qualitative data to assess relationships between study behaviours and academic outcomes, while also considering intervening variables, such as sex, age, and class level. Findings revealed significant associations between effective study habits and improved mathematics performance, underscoring the need for schools, parents, and policymakers to support students in cultivating these habits. The study recommends institutional interventions, such as guidance programs and enhanced library facilities, to foster environments conducive to academic success in mathematics.

Keywords: Study habits, mathematics performance, time management, note taking, library use, secondary school students.

INTRODUCTION

Background to the Study

Habits are automatic behavioural responses to environmental cues that are developed through repetition in consistent contexts. Habits involve context-dependent memory associations, which develop as people experience rewards for actions in specific contexts (Mazar & Wood, 2018). They can be classified into theoretical, behavioural, and technical categories, indicating their roles in human cognition and action (Bernacer & Murillo, 2014). While study habits focus on time management and regular review (Romeo, 2009), habits in psychological research involve automatic responses and context-dependent cues and can be influenced by pleasure and intrinsic motivation. Understanding habits as cognitive enrichments provides a framework for comprehending human learning (Bernacer and Murillo 2014). Good study habits correlated with better academic performance identified effective habits of successful medical students, including time management, eliminating distractions, and studying 3-4 hours daily. Zureick et al. (2017) found that students who consistently attended lectures or viewed lecture videos performed better than those who used mixed strategies, while distractions during lectures led to lower scores. Research has confirmed that interruptions during learning activities significantly affect academic performance (Zureick et al. 2017).

Studies have shown that distraction impacts vary by nature and attractiveness. Wieber et al. (2011) found that simple goal intentions are sufficient for low-attractiveness distractions, while implementation intentions are needed for moderate- and high-attractiveness distractions. Alhur et al. (2023) noted that technology can enhance learning, but creates distraction challenges for many students. This study emphasises focused attention and time management for academic success, as successful students effectively manage their time and eliminate interruptions. Institutions should implement strategies to help students manage distractions, particularly with increasing technological use (Alhur et al., 2023). These findings highlight the need for effective study habits and conducive learning environments, although habits may vary by individual and environment (Visentin et al. 2023).

Study habits have a significant impact on academic performance and understanding. Research has demonstrated a strong relationship between study habits and achievement (Jafari et al., 2019). The formation of study-related habits involves multiple factors beyond student control.

Chamizo-Nieto et al. (2021) introduced emotional intelligence and teacher-student relationships as factors that influence academic performance, showing that effective study habits depend on multiple factors beyond student effort. While students influence their study habits, other factors, such as course design, instructor guidance, and teacher-student relationships, significantly affect academic performance. Environmental factors, teachers’ influence, and resource availability are the key determinants. Research on digital platforms has found that technological infrastructure, instructor roles, and student characteristics affect learning effectiveness (Brugliera 2024). Studies have shown that teachers’ perceptions, social support, and students’ self-efficacy influence their academic performance (Lu et al., 2022). Internal factors such as study habits and learning styles are crucial, with research finding relationships between these elements and academic achievement (Magulod 2019). High-performing students often find laboratory studies and quizzes more effective. Research has indicated that study habits significantly affect mathematics performance. Successful students use time management, minimise distractions, set goals, and study 3-4 hours daily. Students’ attitudes and learning styles affect their mathematics performance, with visual learning being the most dominant, followed by auditory and kinesthetic styles. Studies have revealed that speaking minority languages at home can positively affect math achievement, while using the instruction language in school benefits math performance (Agirdag & Vanlaar, 2016).

In conclusion, while the problem of low mathematics achievement persists, research highlights the importance of developing effective study habits, addressing students’ learning styles, and considering the role of language use in academic performance. Interventions targeting these factors, along with addressing motivational aspects and classroom environments, may help improve students’ mathematics achievement (Rayneri et al., 2019). Educators and policymakers should consider these multifaceted approaches when developing strategies to enhance mathematics education. Students cannot be expected to learn everything needed about the subject from their teachers in the classroom alone; it is the combination of both classroom learning and outside classroom learning that makes up students’ study habits.

Gbore (2006) has established that study habits are strongly related to academic performance. Teacher-student relationships, study habits, and individual differences significantly impact students’ academic achievement. Magulod (2019) found that applied science students preferred visual, group, and kinesthetic learning styles, with moderate study habits correlating with good achievement. Grave (2011) showed that time allocation for activities, such as attending courses and self-study, positively affected grades, varying by gender, ability, and field. Multiple factors contribute to academic performance. Lauermann et al. (2020) identified intelligence and self-concept of ability as critical predictors of school achievement, varying by achievement indicator and domain. Steinmayr et al. (2019) demonstrated that domain-specific ability, self-concept, motives, and learning goals explain significant variance in grades beyond intelligence. While study habits are essential for academic success, other factors, such as teacher-student relationships (Chen et al., 2024), emotional intelligence (Chamizo-Nieto et al., 2021), and academic resilience, affect student performance. Students often underperform by not recognising the importance of their study habits and failing to review schoolwork at home.

Studies have consistently shown a significant relationship between study habits and academic achievement (Rabia et al. 2019), particularly in mathematics. Research on Iranian medical students has revealed a direct relationship between study habits and academic achievement (Jafari et al., 2019). The effect of studying habits on academic performance extends beyond mathematics. Research from the Philippines has revealed relationships between learning styles, study habits, and academic performance (Magulod, 2019), while studies in Mexico City have found correlations between executive function, eating habits, and academic achievement (Chávez-Hernández, 2023). The quality of education is influenced by students’ study habits, particularly in mathematics, where positive attitudes significantly affect performance (Etcuban et al., 2019). Educational institutions must assess and support students’ study habits through training programs (Jafari et al., 2019). Good study habits included setting specific times for homework, outlining notes, studying with friends, and being resourceful.

Statement of the Problem

Public concern exists about poor academic achievement among Nigerian students, including in the Ondo West Local Government Area. Research shows declining educational standards in Nigeria, with investments not yielding the desired results. This decline is evident in examinations of the WAEC, UTME, and other bodies. The WAEC reports a yearly decline in mathematics performance. Educationists attribute this to poor teaching methods, inefficient study habits, and inadequate funding, which lead to examination malpractice, mass failure, and dropouts.

Purpose of the Study

The purpose of this study is to compare the secondary habits of secondary school students to their academic performance in Mathematics in Ondo West Local Government Area of Ondo State. Specifically, this study proposes the following hypotheses:

1. Examining the relationship between library use and students’ mathematics performance
2. Examine the relationship between note-taking and students’ performance in mathematics.
3. To examine the relationship between the time allocated to study and students’ performance in mathematics.
4. Examine the relationship between factors influencing the academic performance of students in mathematics other than the study.

Research Questions

The following research questions were raised to guide this study:

1. Is there any relationship between library use and students’ academic performance in secondary school mathematics?
2. Is there any relationship between note taking and students’ academic performance in secondary school mathematics?
3. Is there any relationship between the time allocated to study and students’ academic performance in secondary school mathematics?
4. Is there a relationship between classroom participation and academic performance in mathematics among Secondary School students?
5. Are there any sex-related differences in the relationship between study habits and academic performance?
6. Are there any age-related differences in the relationship between study habits and academic performance?
7. Is there any difference in the relationship between study habits and academic performance among classes?

Hypotheses

The above research questions were hypothesised and tested at an alpha level of 0.05.

1. There was no significant relationship between students’ library use and their academic performance in mathematics.
2. There was no significant relationship between note-taking and academic performance in mathematics.
3. There was no significant relationship between students’ time allocated to study and their academic performance in mathematics.
4. There is no significant relationship between classroom participation and academic performance in mathematics.
5. There were no significant differences in study habits or academic performance according to sex.
6. There were no significant differences in study habits or academic performance by age.
7. There were no significant differences in study habits or academic performance between classes.

Significance of the Study

This study examined the relationship between effective note-taking, library use, and quality study time in mathematics, termed good study habits. The findings will benefit students, teachers, parents, administrators, counsellors, government, and the public. This study aimed to encourage Secondary School Students to develop good study habits for better mathematics performance. If a significant relationship is found, the recommendations will help parents, guardians, and teachers promote effective study habits. School administrators and the government can use these findings to create programs that facilitate better study habits among students, including guidance and counselling services.

This research contributes to the existing educational literature and serves as a foundation for future studies in this area.

Scope and Delimitation of the Study

This study examines secondary school students ‘ mathematics performance in relation to their study habits in public schools, including library use, note-taking, and time allocation. The study focuses on randomly selected secondary schools in the Ondo West Local Government Area, Ondo State.

REVIEW OF RELATED LITERATURE

Theoretical Framework of the Study

Although Nigerian students’ reading habits are declining, effective time and resource management remain key factors in enhancing study habits. This chapter reviews Wright’s (2002) Pickle–Jar theory of time management and Walberg’s Theory of Educational Productivity (Walberg, Fraser, & Welch, 1986). Creating a conducive environment for students to develop good study habits is vital for learning institutions. Secondary schools require effective libraries to support students’ academic performance. Libraries provide the environment and resources for students to develop the study habits necessary for academic success (Jato et al., 2014). Modern Nigerian school libraries have created better environments for students through innovative strategies. This study examined the impact of library use on students’ study habits in selected secondary schools in the Ondo West Local Government Area, Nigeria.

Studying time management theory helps plan and organise tasks effectively to align with life priorities. Understanding this theory is essential for developing strategies to manage time effectively. Whether for professional or personal life, the chosen approach depends on which time management theory resonates the most (Wright, 2002).

Cognitive Learning Theory: Self-Regulated Learning (SRL) Theory

The self-regulated Learning (SRL) theory emphasises students’ active roles through goal setting, monitoring, and reflection (Winne, 1997). Research identifies self-regulated learner types–competent, cognitive-oriented, behaviour-oriented, and minimal (Ning & Downing, 2014)–linked to academic performance. SRL can become automatic (Winne, 1997) and improve performance in medical education, online learning, and mathematics (El-Adl & Alkharusi, 2020). Study habits link SRL with academic achievement. Successful medical students employ time management and goal-setting in alignment with SRL components. Ratnayake et al., (2023) emphasized SRL’s role through metacognitive skills. Barnard-Brak et al. (2010) identified profiles from ” superself-regulators to “minimal self-regulators” that affect academic outcomes.

SRL involves three key cyclical phases:

1. Forethought Phase: The forethought phase is a crucial component of self-regulated learning (SRL), encompassing task analysis and self-motivation beliefs. During this phase, students engage in planning, goal-setting, and assessing their motivation for upcoming academic tasks (Panadero & Alonso-Tapia, 2014).

2. Performance Phase: The performance phase of self-regulated learning involves self-control and self-observation, as learners implement strategies and monitor progress. During this phase, learners engage in self-monitoring through deliberate attention to their behaviour, which is an important self-regulatory process in learning. Self-monitoring improves course performance, enhances self-regulated learning strategies, and develops a better knowledge of course content. In endurance activities, self-regulation requires athletes to balance speed or power output, with cognitive control being important for pace regulation (Brick et al. 2016).

3. Self-Reflection Phase: Self-reflection is a crucial phase in self-regulated learning, where students evaluate their performance and make adjustments for future tasks. This phase is integral to Zimmerman’s cyclical model of self-regulated learning, comprising forethought, performance, and self-reflection (Panadero & Alonso-Tapia, 2014). The self-reflection phase allows students to interpret outcomes, assess strategy effectiveness, and improve their strategy use and motivation. While self-reflection is often positioned at the end of the learning cycle, some models have suggested that reflection can occur throughout learning. Coulson and Harvey’s (2013) framework advocates scaffolding reflection across all learning phases, aligning with the idea that self-regulatory processes are not necessarily hierarchically structured.

The SRL theory explains how study habits relate to mathematics performance. Mathematics requires practice and problem-solving skills enhanced through self-regulation. Students who use SRL practices typically achieve better mathematics. This study emphasises fostering self-regulated behaviours to improve mathematics outcomes among public secondary students.

The Pickle Jar Theory by Jeremy Wright (2002)

This time management theory by Wright in 2002 views time as a finite space, like a pickle jar filled with objects of different sizes. The theory states that activities must be balanced through effective time management (Wright, 2002). The theory compares time management to filling a pickle jar with golf balls (representing key organizational tasks), stones (desirable activities), sand (small tasks), and water (minor delegable issues that do not improve value) (Marshall, 2008).

Time is allocated to activities based on their priority. Time management involves controlling the time spent on activities and prioritising them effectively. Individuals have multiple priorities, including study, work, leisure, sleep, and responsibilities that require management within time constraints to enhance performance. Pickle jar theory emphasises identifying daily priorities, such as class attendance, workload, and library consultation, to ensure high academic performance in Nigerian Secondary Schools. The theory is based on limited time, such as pickle jar space, which requires individuals to make deliberate choices with available time.

This theory helps learners prioritise activities that affect academic performance by allocating more time to study and tasks that directly impact academic achievement. Students must consider activities related to interpersonal relationships and social interactions that may not benefit from learning. Activities that consume time without adding value to studies, such as peer grouping, should be given a lower priority. Through pickle jar theory, students should prioritise academic activities for quality performance before incorporating other activities based on importance.

The Conceptual Framework of the Study

The Conceptual Framework of this study shows the relationship between the variables and forms the basis for generating the items in the questionnaire instrument to be used in this study.

Conceptual Framework

Figure 1: Conceptual Framework depicting the relationship between Study Habits and Academic Performance

This diagram shows the relationship between study habits (time management, note-taking, library use) and academic performance, with intervening variables (sex, age, class) measuring students’ study habits and performance. These concepts were discussed individually.

The Concept of Study Habits

Study habits are systematic or inefficient methods of learning and are crucial for success, involving learning how to study. Most students use effective habits to increase their motivation (Arhin 2018). Effective habits include homework, note-taking, exam preparation, and library use (Johnson, 2018). Study habits encompass planning, reading, note-taking, and time management (Patel, as cited in Rana & Kausar, 2011). This study examined time management, note-taking, and library use habits. Time management involves planning (Razali et al. 2018). Note-taking aids learning (Ward & Tatsukawa, as cited in Haghverdi et al., 2010), whereas library visits help access materials (Okorie, 2016).

The Concept of Student Academic Performance

Academic performance measures student achievement through classroom performance, graduation rates, and standardised tests. Academic Achievement refers to information gained after instruction and task accomplishment (Oxford Advanced Learner’s Dictionary, 2010). Achievement refers to reaching curriculum objectives (Kazazoglu, 2013). Academic Achievement was defined as knowledge shown in the test scores. Academic performance indicates learning across the cognitive, affective, and psychomotor domains. The cognitive domain includes knowledge, comprehension, application, analysis, synthesis, and evaluation (Bloom 1958). Achievement is used for Grade Assignment, Promotion, Classification, Counselling, and Selection. Factors affecting academic performance include intelligence, personality, and study techniques (Songsirisak and Jitpranee 2019).

Effects of Time Management on Academic Performance

Poor time management leads to omitted school activities. Time enables high-quality teaching and administration. Ebong (2011) defines time as an economic phenomenon. Time is a scarce educational resource (Adedeji 2009) that requires proper planning. Time is measurable and related to space. Time management is vital to educational objectives. Integrating time management techniques improves academic outcomes (Peteros et al., 2021). School quality requires proper time management, and management plans help identify time usage.

Relationship of Study Habits with Academic Performance in Mathematics Education

Mathematics are essential for daily living (Achimugu & Ekene, 2021). Study habits affect mathematics achievements (Shuaibu, 2024) and performance (Gbore, 2006). Mathematics develops systematic thinking (Muraina, 2013) and should begin early (Aremu, 2001). Academic performance depends on internal factors (gender and grades) and external factors (parental education and finances), with self-efficacy being the most important (Kuppusamy & Musa, 2021). Teaching methods affect performance (Agyeman, 1993; Kafui, 2005).

Family education and the environment influence academic achievement. Students with supportive families perform better academically (Christenson and Sheridan 2001).

Students Attitudes and their Effects on Learning and Academic Performance in Mathematics

Attitude is a learned response that affects behaviour (Ajzen, 1993) and comprises affect, cognition, and behaviour (Syyeda, 2016). The TIMSS 2007 showed that positive attitudes correlated with higher scores (Gonzales et al., 2008). Students’ attitudes are influenced by their school, peers, home, and teaching materials (Yang, 2013; Yılmaz Olkun, 2010). Poor mathematics performance stems from student, teacher, and school factors (Kupari and Nissinen 2013). Using the ABC model (Ajzen, 1993) and Walberg’s theory, we examined Tanzanian students’ mathematics attitudes, including self-confidence, anxiety, and enjoyment.

Summary of Reviewed Literature

The literature review covered the theoretical framework, study habits, and mathematics performance. Key theories include Wright’s Pickle Jar Theory, Lockes and Latham’s Goal-Setting Theory, and Ellis’s ABC Model. Walberg’s theory connects academic success with structure. This study examines the impact of study habits on mathematics performance in Ondo-West public secondary schools, given limited Nigerian research.

METHODOLOGY

In this chapter, the method and procedure adopted in this study are described and presented as follows.

Design of the Study

This study employed a survey research design with a correlational approach to examine students’ study habits as a correlate of academic performance in mathematics in public secondary schools. The independent variables were students’ use of library, note-taking, and time allocation, while academic performance in mathematics was the dependent variable, with sex, age, and class as intervening variables.

Population of the Study

The study population consisted of 11,182 students (5,444 boys and 5,738 girls) from 31 public senior secondary schools in the Ondo West Local Government Area of Ondo State, Nigeria, enrolled in the 2023/2024 academic session, as shown in Table 3.1.

Sample and Sampling Techniques

Six Public Senior Secondary Schools in Ondo-West Local Government Area were selected randomly from thirty one (31) schools. Forty (40) students from each school will form a sample of two hundred and forty (240) students as shown in table 3.4.

Research Instrument

This study employs a “Senior Secondary School Students’ Academic Performance in Mathematics and Study Habits Scale” questionnaire and Mathematics terminal examination reports. The questionnaire evaluates study habits across library use (1-5), note-taking (6-10), study time (11-15), class participation (16-20), and learning environment (21-25), using a four-point scale: Strongly Agree=4, agree =3, disagree =2, Strongly Disagree=1. Students’ previous term scores served as the second variable, with the study habit scale as the first variable for hypothesis analysis.

Validity of the Instrument

To ensure the validity of the instrument, the questionnaires were validated by the researcher’s supervisor and other two (2) lecturers from the Department of Educational Evaluation and Counseling Psychology at the University of Benin. Their observations, suggestions, and corrections were incorporated into the final copy of the instrument and certified as adequate for the study.

Reliability of the Instrument

To determine the reliability of the instrument, the researcher administered thirty (30) copies of the instrument to Senior Secondary School students who were part of the population, but outside the sample of the study. The collected data were analysed using Cronbach’s alpha statistics to determine the reliability coefficient of the instrument. After the reliability test was completed, a reliability coefficient of 0.638 was derived which revealed that the instrument was reliable.

Method of Data Collection

The researcher, with the help of a research assistant, will distribute the instruments to the respondents to obtain relevant information for the purpose of the research work. The instruments were retrieved from the respondents as soon as they finished filling the same day. This procedural strategy ensured that all questionnaires were retrieved.

Method of Data Analysis

The data were analysed using the SPSS software. Research questions 1-7 would were analyzed using Pearson’s correlation and Fisher’sZ statistics. All the hypotheses were tested at a significance level of 0.05.

RESULTS

Data gathered from 240 respondents across six randomly selected public secondary schools in the Ondo West Local Government Area were analysed using SPSS software. Pearson’s correlation coefficient and Fisher’s Z transformation were used to test the relationships between variables, with a significance threshold set at p < 0.05. The hypotheses were tested to determine whether significant relationships exist between study habits (library use, note-taking, and time allocation) and students’ academic performance in mathematics.

1. Relationship between Library Use and Mathematics Performance

A moderate positive correlation was found between students’ library use and their academic performance in mathematics (r = 0.41, p < 0.05). Students who frequently used the school library demonstrated better performance in mathematics than those who did not. This finding supports the hypothesis that the effective use of academic resources such as libraries contributes positively to academic outcomes.

2. Relationship between Note-Taking and Mathematics Performance

Correlation analysis revealed a statistically significant positive relationship between note-taking habits and academic performance (r = 0.47, p < 0.01). Students who consistently took notes during mathematics lessons showed a higher level of understanding and improved mathematics performance. This suggests that note taking serves as a cognitive reinforcement strategy that aids retention and comprehension.

3. Relationship between Time Allocation and Mathematics Performance

A significant positive relationship was also identified between time allocated to mathematics study and academic performance (r = 0.52, p < 0.01). Students who allocated specific and consistent study periods for mathematics outside classroom hours performed significantly better than those who studied irregularly. This validates the predictive power of structured time management, as emphasised in Pickle Jar Theory.

4. Classroom Participation and Academic Performance

Classroom participation had a moderate positive correlation with mathematics performance (r = 0.39, p < 0.05). Active engagement during lessons, such as responding to questions and solving problems in class, is associated with better academic outcomes.

5. Influence of Sex on Study Habits and Academic Performance

An independent sample t-test revealed no statistically significant differences in study habits or academic performance between male and female students (p > 0.05). Both sexes demonstrated comparable study patterns and mathematics outcomes, indicating that gender was not a determining factor in this context.

6. Influence of Age on Study Habits and Academic Performance

One-way ANOVA showed no significant differences in study habits or mathematics performance based on age group (F (2,237) = 1.17, p > 0.05). This suggests that, within the sampled age range (12–18 years), age did not significantly influence academic habits or achievement.

7. Class-Level Differences in Study Habits and Mathematics Performance

Analysis of variance did not reveal any significant differences across class levels (SS1, SS2, and SS3) in terms of study habits or academic performance (F(2,237) = 1.32, p > 0.05). Thus, students across senior secondary levels demonstrated similar behavioural patterns in their study of mathematics.

DISCUSSION

The findings of this study provide strong evidence that specific study habits (library use, note-taking, and time allocation) are significantly correlated with academic performance in mathematics among public secondary school students in the Ondo West Local Government Area of Nigeria. These findings align with prior research (e.g. Jafari et al., 2019; Magulod, 2019), which emphasises the role of effective academic behaviours in promoting student achievement.

First, the positive correlation between library use and mathematics performance suggests that access to learning resources and a conducive study environment enhances conceptual understanding and performance. This reinforces the conclusions of Okorie (2016) and Jato et al. (2014) regarding the role of library facilities in academic success.

Second, note-taking has emerged as a critical habit for improving mathematics outcomes. These findings support the assertion by Haghverdi et al. (2010) that structured note-taking enhances learning retention and recall. Students who actively engaged in class through effective note-taking demonstrated better academic performance, highlighting the role of active engagement and cognitive reinforcement in learning.

Third, the study found a robust association between time allocation for studying and performance in mathematics. This result is consistent with Pickle Jar Theory of Time Management, which emphasises prioritising essential tasks. Students who adhered to a consistent study schedule performed better, confirming that disciplined time management is fundamental to academic success (Grave, 2011; Peteros et al., 2021).

Interestingly, classroom participation, although not a primary focus, also correlated positively with performance. This finding underscores the role of active learning and interaction during lessons as complementary habits to independent studies.

Regarding the intervening variables, the analysis revealed no statistically significant differences based on sex, age, or class level. This suggests that the impact of good study habits transcends demographic factors, supporting the notion that effective academic behaviour can benefit all students when properly cultivated.

The results affirm the theoretical foundations provided by Self-Regulated Learning (SRL) Theory and Pickle Jar Theory, demonstrating that students who set goals, manage their time, monitor progress, and engage deeply with content tend to outperform their peers.

Suggestions For Further Study

While this study has provided valuable insights into the relationship between study habits and academic performance in mathematics, several areas warrant further investigation.

1. Longitudinal Research: Future studies could track students’ study habits and academic performance over multiple terms or years to observe long-term trends and causal relationships.
2. Intervention Studies: Experimental research could test the effectiveness of structured study habit interventions (e.g. study skill workshops and time management training) in improving mathematics performance.
3. Comparative Studies Across Subjects: Research could explore whether similar correlations exist between study habits and performance in other core subjects such as English, Biology, or Physics.
4. Technological Influence: With the increasing integration of digital tools in education, future research should assess how digital study habits (e.g. the use of educational apps or online resources) affect performance.
5. Qualitative Approaches: In-depth interviews or focus group discussions could provide richer insights into students’ motivations, barriers, and perceptions regarding study habits.
6. Role of Socioeconomic Status: Further research should investigate how parental background, home environment, and access to learning support affect students’ ability to develop good study habits.

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 APPENDIX A

Senior Secondary School Students’ Academic Performance In Mathematics And Study Habits Scale

Introduction:

You are kindly requested to answer the questions below honestly. This is purely an academic exercise; your responses will be treated with utmost confidentiality.

Thank you.

Section A: Demographics

Sex: Male         Female   

Age: 12 – 15 yrs          16 – 18 yrs 

Class: JSS 1            JSS 2            JSS 3            SSS 1           SSS 2           SSS 3     

Section B:

Please tick [√] correctly either Strongly Agree (S.A) = 4, Agree (A) = 3, Disagree (D) = 2 and Strongly Disagree (S.D) = 1.