Learning Strategies in Language Learning Influence of Resource Management in Language Learning

Learning Strategies in Language Learning Influence of Resource Management in Language Learning

Norliza Che Mustafa, *Norhayati Idris, Saidah Ismail, Haslinda Md Isa, Nurul Amirah Khairul Amali, Noor Hanim Rahmat

Akademi Pengajian Bahasa, University Technology MARA Cawangan Shah Alam

*Corresponding Author

DOI: https://dx.doi.org/10.47772/IJRISS.2025.909000679

Received: 04 June 2025; Accepted: 11 June 2025; Published: 25 October 2025

ABSTRACT

Learning and mastering a new language can be immensely helpful for cognitive health and can also aid learners to stay relevant and competitive in the global work market. However, without a proper learning strategy, the task of acquiring a new language can be challenging. This quantitative study was conducted to investigate how learners perceive their use of learning strategies in acquiring a new language. This study is rooted in Wenden and Rubin (1987), Learning Strategies Theory, which consists of three main elements: cognitive, resource management, and metacognitive strategy. The instrument used is a 5-point Likert scale survey. The survey has 4 sections. Section A contains items related to the demographic profile. Section B has 19 items on cognitive components. Section C has 11 items on metacognitive strategies. Section D has 11 items on resource management. A total of 110 students from two clusters, science and social science and humanities, at a public university in Malaysia participated in this study. Data were analysed using SPSS frequency statistics. The findings showed that all three components, cognitive, resource management, and metacognitive strategy are equally important in learners learning strategy in acquiring a new language. The correlation reveals that there is a strong positive correlation between resource management and cognitive components and also the relationship between resource management and metacognitive self-regulation. These findings suggest that foreign language teachers should be aware of different learning strategies used by learner and consider resource management when assisting learners in their learning process, as it significantly influences learners’ learning strategies.

Keywords: LLS, cognitive components, metacognitive strategies, resource management

INTRODUCTION

Background of Study

People acquire languages for a variety of reasons, such as education, career advancement, and personal development. Furthermore, speaking multiple languages is becoming crucial in today’s society due to globalization. When learning a new language, a language learner uses variety of strategies that work for them to plan, monitor, and evaluate their progress.

Numerous studies have shown that language learning is influenced by various factors. Sometimes, one factor may be more dominant than others. In order to make classroom teaching and learning effective, the teacher or researcher needs to understand: (a) the learner, (b) the learning process to be used in the classroom, and (c) the learning situations and strategies used (Rahmat, 2019).

According to Oxford (2001) Learning strategies is a specific behaviours or thoughts learners use to enhance their language learning. Using the right learning strategies that suits learners learning style will influence learner’s ability to learn in a particular instructional framework. They will also be motivated to study, knowing there is a solution to their learning challenges (Zakaria et al.,2024).

Although language learning strategies have been studied for years, research on the connection between resource management and the use of language learning strategies appears to be lacking. Resource management, as mentioned by Pintrich et al. (1991) encompasses of self-regulation of cognition, time management, study environment, and effort regulation. Effort regulation refers to the ability of students to maintain their effort and attention in the face of interruptions and uninteresting tasks.

Hence, in an attempt to address this gap, the present study tried to answer the following research questions: How do learners perceive resource management, cognitive components, and metacognitive self-regulation in learning? and is there a relationship between all components in learning strategy?

Statement of Problem

In the present day, the focus on learner-centred methodologies in language teaching is increasing. Nevertheless, many students still encounter difficulties with learning methods that could improve their language acquisition. According to Hardan (2013), language learning strategies can assist students to become successful language learners. Students can excel and acquire foreign languages efficiently if they implement and use the correct learning strategies.

Educators can also improve the instructional practices and learner outcomes by understanding how learners perceive and implement various learning strategies such as resource management, cognitive processing, and metacognitive self-regulation.

However, there are limited studies that explored the interrelationship between these elements in the second or foreign language acquisition.

This study examines learners’ perceptions of the three key strategies established by Wenden and Rubin (1987) and also explores whether there are relationships between these three components. It will provide insights into how strategic learning behaviours affect language learning successes.

Objective of the Study and Research Questions

The objective of this study is to investigate learners’ perceptions of resource management in their learning processes. Specifically, this study is done to answer the following questions;

• How do learners perceive resource management in learning?
• How do learners perceive cognitive components in learning ?
• How do learners perceive metacognitive self-regulation in learning?
• Is there a relationship between all components in learning strategy.?

LITERATURE REVIEW

Theoretical Framework

General Learning Strategies

This section explains how researchers have studied second/foreign language learning strategies. In the 1970s, Rubin (1975) studied what makes good language learners successful in her work What ‘The Good Learner’ Can Teach Us?. Griffiths (2015) expanded on Rubin’s ideas in What Have We Learned from ‘Good Language Learners’?, showing that strategies can be taught. She suggested that instructors include specific lesson techniques to help learners practice, reflect, and improve their learning methods.

Earlier, O’Malley et al. (1985) created a system for classifying strategies to help learners study and remember languages better. They focused on mental processes (cognitive and metacognitive strategies), which this study will explore further. By the late 1980s, Oxford (1990) developed the Strategy Inventory for Language Learning (SILL), a popular tool for studying language learning strategies because of its broad approach.

In the 2000s, researchers introduced the idea of self-regulated strategies, where learners manage their learning.

This approach, introduced by Tseng, Dörnyei, and Schmit (2006), offered a new way to study language learning. Rose et al. (2018) and others (e.g., Teng & Zhang, 2020; Öztürk & Çakıroğlu, 2021) have since learned how self-regulation can improve learning.

Today, self-regulation is an important part of learning strategies. It depends on a learner’s habits and how well they use these strategies. There are still challenges, but there is a lot to explore, especially in understanding individual differences and improving teaching methods. This includes using online platforms, which are now a big part of education.

Resource Management

Resource management is a key factor in students’ learning strategies. In achieving targeted degree of academic learning by students, resource management strategy is regarded as a vital element (Ahmed & Khanam, 2014). Furthermore, according to Pintrich et al. (1991), resource management is not only limited to self-regulation of cognition, it also covers time and study environment, effort regulation, peer learning and help seeking. Time management includes good use of study time utilisation, and coordinating attainable goals. Meanwhile, study environment management represents a student’s setting in which they complete their class task. Next, effort regulation is the capability of students in maintaining their effort and attention upon facing interruption and uninteresting tasks. Besides that, it is found that peer learning such as collaborating with fellow students upon learning results in positive effects on academic achievement. Other than that, it is essential for students to manage the support of peers and educators. Similar explanations regarding resource management components can also be found in Ahmed & Khanam (2014).  In conclusion, resource management strategies are indeed a major part of students’ learning strategies.

Cognitive Component

Weinstein & Mayer (1983) defined cognitive components as rehearsal and elaboration. In their study, rehearsal strategies are split into two cognitive aims. One is selection which is guiding students to focus on important aspects of study material. Next is acquisition, ensuring that the material studied is conveyed into working memory. Examples of such strategies include copying, underlining and shadowing materials learned in the classroom. The regular practice for rehearsal strategies will be notetaking. As for elaboration, the main objective of this strategy is to integrate dispensed information with retrospective knowledge. This can be achieved by practising tasks such as paraphrasing, summarising, or describing how novel information connects with present knowledge. A noteworthy practice for elaboration will be outlining key chapters in study material.  Meanwhile, Rubin (1981), interprets cognitive components as stages or operations employed in learning or problem solving. A total of six main cognitive learning was recognized by Rubin (1981) including clarification, guessing, deductive reasoning, practice, memorisation and monitoring. Considering all this, cognitive learning is interpreted into different strategies by different researchers. However, these processes have similar nature in executing learning strategies by students.

Metacognitive Self-Regulation

According to Pitrich (1991), metacognition relates to different phases of self-regulation; awareness, knowledge and control of cognition. Metacognitive self-regulatory exercises mentioned by Pitrich (1991) include planning, monitoring and regulating. Zimmerman (1998) however suggested different self-regulation metacognitive aspects. These aspects comprise forethought, performance or volitional control, and self-reflection. All exercises mentioned by both Pitrich (1991)  and Zimmer (1998)  are indeed interrelated with each other. Hence, it is ought to say that with proper practice of self-regulation application, students are able to thrive in their academic environment.

Past Studies

Learning Strategies

Research on second or foreign language learning has increasingly focused on self-regulated learning strategies (SRL), particularly in modern, technology-assisted learning contexts. Several studies highlight the effectiveness of SRL strategies in improving language skills. For instance, Öztürk and Çakıroğlu (2021) examined the use of SRL strategies in a flipped English course in Turkey. Their quasi-experimental study involved an experimental group using SRL strategies and a control group following traditional methods. The results showed significant improvements in speaking, reading, writing, and grammar for the experimental group. However, there was no notable progress in listening skills, indicating that SRL strategies may vary in effectiveness depending on the skill being targeted.

In another study, An et al. (2021) investigated how Chinese university learners used technology-assisted SRL strategies to enhance their English language skills. The findings revealed that learners moderately applied SRL methods, often relying on technology for tasks like vocabulary learning. Enjoyment and self-efficacy were closely linked to the use of these strategies, which ultimately improved learning outcomes. The study also emphasized the importance of encouraging social language learning activities, raising awareness about motivational regulation, and providing training for instructors to better integrate SRL strategies into teaching practices.

Teng et al. (2020) focused on SRL strategies in writing interventions and explored how they influenced learners’ writing performance, strategy use, and self-efficacy. The study compared a group receiving SRL-focused instruction with a control group following a standard writing course. Results showed that SRL strategies significantly improved writing outcomes, encouraged active strategy use, and increased confidence in managing their academic performance. The study highlighted the need to consider individual differences, integrate social and motivational strategies, and adapt teaching methods to optimize results.

Overall, these studies underscore the growing importance of SRL strategies in second and foreign language learning. Self-regulated strategies not only promote active engagement and strategic learning but also align with the needs of digital-native learners by incorporating technology. This shift in focus reflects the evolving demands of education, where personalized and technology-assisted approaches play a critical role in fostering effective learning.

CONCEPTUAL FRAMEWORK

Successful learners need to have the ability to manage their resources well. Learning resources include text documents, images, infographics, video, and many other forms of materials that facilitate learning.  Resource management involves learners making plans. It also involves the learners utilizing their resources to achieve their learning goals. Resource management is only one type of strategy learners use to maximise learning. According to Rahmat (2018), the use of strategies help learners use learning materials to facilitate their learning. Figure 1 shows the conceptual framework of the study. According to Wenden and Rubin (1987), there are three main learning strategies. The first one is cognitive components and this component is supported by sub-strategies such as rehearsal, organization, elaboration, and critical thinking. The second strategy is resource management and this is supported by sub-strategy such as environment management, effort management and help-seeking. The last strategy is metacognitive strategy and involves learners making plans.

Figure 1- Conceptual Framework of the Study Influence of Resource Management in Language Learning

METHODOLOGY

This quantitative study is done to explore motivation factors for learning among undergraduates. A purposive sample of 110 participants responded to the survey. The instrument used is a 5 Likert-scale survey and is rooted from Wenden and Rubin (1987) to reveal the variables in table 1 below. The survey has 4 sections. Section A has items on demographic profile. Section B has 19 items cognitive components. Section C has 11 items on metacognitive strategies. Section D has 11 items on resource management.

Table 1- Distribution of Items in the Survey

Table 1 also shows the reliability of the survey. Individual analysis was done on each variable. The Cronbach alpha for Cognitive components is .925. for Metacognitive Self-Regulation is .828 and for Resource Management is .828. The overall analysis of all 41 items shows a Cronbach alpha of .944, thus, revealing a good reliability of the instrument chosen/used. Further analysis using SPSS is done to present findings to answer the research questions for this study.

FINDINGS

Findings for Demographic Profile

Table 2- Percentage for Q1 Gender

Table 2 presents the percentages of respondents in this study based on gender. From 110 respondents, the findings revealed that 42% males and 58% females participated in the studies.

Table 3- Percentage for Q2 Course

Table 3 presents the percentages of respondents in this study based on course. From 110 respondents, the findings revealed that 26% were level 1 students, 39% were level 2 students and 34% were level 3 students.

Table 4- Percentage for Q3 Discipline

Table 4 presents the percentages of respondents in this study based on discipline. From 110 respondents, the findings revealed that 51% of the respondents were from science discipline and 49% of the respondents were from social sciences discipline.

Findings for Resource Management

This section presents data to answer research question 1- How do learners perceive resource management in learning? In the context of this study, this is measured by (i) environment management, (ii) effort management and (iii) help-seeking.

Table 5- Mean for (i) Environment Management (5 items)

Table 5 shows the mean for (Environment Management). The highest mean (m=4.4) is for item (I attend the classes regularly in this program). Second highest mean (m=4) is or item, (I usually study in a place where I can concentrate on my course work). Item 2 (I make good use of my study time for the courses in this program), item 3 (I have a regular place set aside for studying) and item 4 (I make sure that I keep up with the weekly readings and assignments for the courses) scored the same mean of (m=3.7)

Table 6- Mean for (ii)Effort Management (4 items)

Table 6 shows the mean for Effort Management. The highest mean (m=3.9) is for item number 2 (I work hard to do well in the classes in this program even if I do not like what we are doing) and item number 4 (Even when course materials are dull and uninteresting, I manage to keep working until I finish) with a mean of (m=3.9) each. Meanwhile, item number 4 (when the coursework is difficult, I either give up or only study the easy parts) has the lowest mean (m = 2.7).

Table 7- Mean for (iii) Help-Seeking (2 items)

Table 7 shows the mean for Help-seeking. The highest mean (m=4), is for item number 2 (I try to identify students in the classes whom I can ask for help if necessary) and the mean for item number 1 (When I cannot understand the material in a course, I ask another student in the class for help is (m=3.9).

Findings for Cognitive Components

This section presents data to answer research question 2- How do learners perceive cognitive components in learning?

In the context of this study, this is measured by (i) rehearsal, (ii)organization, (iii) elaboration and (iv) critical thinking.

Table 8- Mean for (i) Rehearsal (4 items)

Table 8 shows the mean for Rehearsal. The highest mean (m=3.8) is for the item, (Memorize key words to remind me of important concepts in this class). The lowest mean (m=3.5) is for the item, (When studying for the courses, I read my class notes and the course readings over and over again)

Table 9- Mean for (ii)Organization  (4 items)

Table 9 shows the mean values for Organization. The highest mean (m=3.9) is for item, (When I study for the courses, I go through the readings and my class notes and try to find the most important ideas). The lowest mean score (m=3) is for item,(I make simple charts, diagrams, or tables to help me organize course materials in this program)

Table 10- Mean for (iii) Elaboration (6 items)

Table 10 shows the mean scores for Elaboration. The highest score,(m=3.8) is for item, (When reading for the courses, I try to relate the material to what I already know). The second-highest score, (m=3.7) is for item (I try to understand the material in the classes by making connections between the readings and the concepts from the lectures). The lowest mean score, (m=3.3), is for item (I try to relate ideas in one subject to those in other courses whenever possible).

Table 11– Mean for (iv) Critical Thinking (5 items)

For Table 11, the highest mean score for Critical thinking is (m=3.7), for item (I often find myself questioning things I hear or read in the courses to decide if I find them convincing). The statement (I try to play around with ideas of my own related to what I am learning in the courses) score the second highest mean of (m=3.6). The lowest score, (m=3.4), is for the statement (When a theory, interpretation, or conclusion is presented, I try to decide if there is good supporting evidence).

Findings for Metacognitive Self-Regulation

This section presents data to answer research question 3- How do learners perceive metacognitive self-regulation in learning?

Table 12- Mean for Metacognitive Self-Regulation

Table 12 presents the mean score for Metacognitive Self-Regulation. Based on all 11 items, the mean scores range from 3 to 3.9. The highest mean score (M=3.9) is for item (When I become confused about something I am  reading for the classes, I go back and try to figure it out). Three items shared the same mean score (m=3.7), item (If course readings are difficult to understand, I change the way I read the material), (I ask myself questions to make sure I understand the material I have been studying in this program) and item (When studying for the courses in this program I try to determine which concepts I do not understand well). The lowest score (m=3) is for item (During class time, I miss important points because I am thinking of other things).

Findings for Relationship between

This section presents data to answer research question 4- Is there a relationship between all components in learning strategy.?

To determine if there is a significant association in the mean scores between all components in learning strategy, data is analysed using SPSS for correlations. Results are presented separately in table 13, and 14 below.

Table 13– Correlation between Resource Management and Cognitive Components

Table 13 shows there is an association between resource management and cognitive components. Correlation analysis shows that there is a high significant association between resource management and cognitive components (r=.588**) and (p=.000). According to Jackson (2015), coefficient is significant at the .05 level and positive correlation is measured on a 0.1 to 1.0 scale. Weak positive correlation would be in the range of 0.1 to 0.3, moderate positive correlation from 0.3 to 0.5, and strong positive correlation from 0.5 to 1.0. This means that there is also a strong positive relationship between resource management and cognitive components.

Table 14- Correlation between Resource Management and Metacognitive Self-Regulation

Table 14 shows there is an association between resource management and metacognitive self-regulation. Correlation analysis shows that there is a high significant association between resource management and metacognitive self-regulation (r=.649**) and (p=.000). According to Jackson (2015), coefficient is significant at the .05 level and positive correlation is measured on a 0.1 to 1.0 scale. Weak positive correlation would be in the range of 0.1 to 0.3, moderate positive correlation from 0.3 to 0.5, and strong positive correlation from 0.5 to 1.0. This means that there is also a strong positive relationship between resource management and metacognitive self-regulation.

CONCLUSION

Summary Of Findings And Discussions

The study findings revealed interesting insights on how learners perceive their use of learning strategies. First, the findings on resource management show that, in order to succeed, the students make an effort to attend class regularly and work hard to complete a given task even if the course materials are uninteresting. As mentioned by Pintrich et al. (1991) resource management encompasses not only self-regulation of cognition but also time management, study environment, and effort regulation. Effort regulation refers to the ability of students to maintain their effort and attention in the face of interruptions and uninteresting tasks. Next, students actively seek out peers who can assist them in their learning process. As mentioned by Ahmed & Khanam (2014), peer learning, such as collaborating with fellow students, results in positive effects on academic achievement.

Second, the findings on cognitive components indicate that students memorize keywords for significant concepts and organize their studies by reviewing their class notes and identifying key ideas.  As mentioned by Weinstein & Mayer (1983) rehearsal strategies are split into two cognitive aims. Selection guides students to focus on important aspects of the study material, while the other aspect ensures the transfer of the studied material into working memory. Next, findings on elaboration reveal that students often relate new material to their existing knowledge. This finding is supported by Weinstein & Mayer (1983) the main objective of the elaboration strategy is to integrate dispensed information with retrospective knowledge.

Last, the findings on Metacognitive Self-Regulation. The item, “When I become confused about something I am reading for the classes, I go back and try to figure it out” scored the highest mean. This shows that students will self-regulate their learning strategies in the learning process. As mentioned by Pintrich (1991), Metacognitive self-regulatory exercises include planning, monitoring and regulating.

The finding for correlation between all components in learning strategy show that there is a strong positive relationship between resource management and cognitive components and also relationship between resource management and metacognitive self-regulation

Pedagogical Implications and Suggestions for Future Research

There are 2 perspectives in language learning strategies: learners and teachers. For students, the ability to identify a strategy that suits their learning style will tremendously help them understand the subject matter. Zakaria et al. (2024). For teachers, knowing the different strategies used by students is crucial, as it will help them adapt their teaching to the learners’ needs, thus optimising the learning experience and knowledge gained. As mentioned by Oxford (2001), teachers should help their students to develop an awareness of learning strategies and enable them to use a wider range of appropriate strategies. Therefore, we recommend future studies to examine teachers’ awareness and readiness in language learning strategies.

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