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Park: Exploring the Differences in Learning Strategy Use Between Online and Offline Classes


The purpose of this study was to explore whether there is a difference between online and offline classes in the degree of learning strategies that learners use for learning outcomes and whether there is a connection between learning strategies used in online and offline classes. A total of 81 college students, taking liberal arts English classes—Reading and Writing Practice, TOEIC Beginner, Let’s Know Two-Word Verbs, and ESP Reading and Writing—answered questions based on the learning strategies scales from the Motivated Strategies of Learning Questionnaire (MSLQ) by Pintrich et al. (1991). There was a total of 30 questions related to rehearsal, elaboration, organization, critical thinking, and metacognitive self-regulation. The results showed that there was no significant difference between online and offline classes in learning strategies used. It was further found that there were highly significant relationships among the learning strategies used in online and offline classes. Although there was no difference in strategy use between online and offline learning, this current study found out that the level of the strategy uses and the relationship between strategies used was significant. This study emphasizes that the use of learning strategies should be presented according to the context and learning environment.


In order to learn English, EFL learners have to face and solve a number of challenging and difficult tasks such as words, pronunciation, grammar, and language systems (Varasteh et al., 2016). Pintrich et al. (1994) stated that learners’ academic motivations are related to their learning strategies to solve these learning areas. These worries are no longer unique to classroom instruction as online learning has become common after the development of the Internet. Regarding learners’ active learning attitudes, strategies, or motivations, many scholars have studied and emphasized a lot not only in traditional learning (Pintrich et al., 1993) but also in online learning (Barrnett, 2009; Gardner & Lambert, 1972; Rahardjo & Pertiwi, 2020; Smith, 2012).
As distance education has become more popular, places and tools have diversified to the extent that this distance education can be referred to according to the application base and environment for education called electronic learning, mobile learning, and ubiquitous learning. In addition, many learning processes have been created based on this web. Learners also get more learning opportunities because these learning has made it possible for them to learn without major spatial, physical, and temporal restrictions.
In addition to those advantages, this distance education requires autonomous learning attitudes and strategies for learners while studying to achieve efficient and good learning outcomes (Adam et al., 2017). In fact, classroom instruction and online instruction have different characteristics. In traditional classroom instruction, instructors can control students’ learning and plans, but in remote instruction, learners must control their own classes and implement regular and autonomous learning (Broadbent, 2017). Rather, some scholars have mentioned that learners’ use of selfregulated strategies in online learning plays a more important role in the achievement of learning than in face-to-face instruction (Broadbent & Poon, 2015; Serdyukov & Hill, 2013).
Considering previous studies, it is important to use strategies well in both online and face-to-face classes, and choosing an appropriate strategy to achieve good learning outcomes is important for both instructors and learners regardless of whether online or offline is (Donker et al., 2013; Zhou & Wang, 2021). In addition, learners’ consciousness and willingness to use effective learning strategies can also affect learning outcomes. Although many studies, as mentioned earlier, explore the influence or effectiveness of strategy use in distance learning and face-toface classes, there are not many studies on whether there is a difference in the strategies that learners use in online and face-to-face classes each. Therefore, based on the current situation, first, this study examines the degree to which students use learning strategies with the Motivational Strategies of Learning Questionnaire (MSLQ) from Pintrich et al. (1991), which is used in many areas online and offline. Second, it explores whether there are differences between online and offline classes when students use strategies. Lastly, it investigates whether there is a correlation among learning strategies.


1. Learning Strategies in Learning

Learning strategies are referred as a necessary or useful techniques for effective learning and existence of the information and skills (Chamot & Kupper, 1989). Many studies have argued that successful learning strategies play a decisive role in learning, affecting learners’ academic satisfaction or achievement in a skill-mediated learning environment (Artino, 2008; Greene & Azevedo, 2009). Also, researchers stated that learning strategies are important factors for academic achievements in online learning and are the process of generating, organizing, and changing data (Neroni et al., 2019; Zhou & Wang, 2021). With the rise of importance, there have been various models and classifications of learning strategies (Pintrich et al., 1991; Zimmerman, 2000). The model of Pintrich et al. (1991) is composed of the factors concerning self-regulation and the role of context. It contains more specific sub-processes based on motivation and learning strategies. Zimmerman’s model is based on the social cognitive theory and describes the three aspects: forethought, performance, and self-regulation specially related to motivation on self-regulation.
Avila and Genio (2020) studied how much the level of motivation affects online learning due to COVID-19 pandemic. It turned out that the results were not related to motivation and learning achievement. Rather, it was found that the learning strategy affects the speed of self-directed learning of learning.
Duncan and McKeachie (2005) stated that metacognitive regulation is the learner’s ability to control, plan, and reflect on the learning process while learning. In another study, Puzziferro (2008) explored how students’ class satisfaction and grades work in online courses with a total of 815 students taking liberal arts online courses. According to the results, students with high desire for achievement tend to be more satisfied with metacognitive regulation than students with low achievement. Besides, students with high grades gave higher scores to questions related to strategy use (Puzziferro, 2008).
In particular, it is said that it is very useful for learning to connect well with the mission when learning a foreign language, to fit the strategy according to the learner’s own preference, and to effectively link the selected strategy to other strategies (Ehrman et al., 2003). Lin et al. (2017) also stated that high strategy use scores in learning are related to high academic achievement. They surveyed 466 students of high school level using learning materials used in the virtual school to measure motivation, intrinsic motivation, extrinsic motivation, satisfaction with online-learning strategies, and perceived learning progress. The result showed that online learning strategy use can work as a moderate level in course of language learning.
Barbour and Reeves (2009) stated that learners with strong motivation and various learning strategies do better in online learning than learners with low motivation and less learning strategies. Students with better English proficiency use learning strategies more autonomously than students with lower ability and know how to use strategies appropriate for the continuation of learning (Tsuda & Nakata, 2013). In their study, they suggested that students have internal factors such as learning strategies and motivations that influence English learning and the teacher argued that we should understand these internal factors well.

2. The Motivated Strategies of Learning Questionnaire in Learning

Pintrich (2000) stated that learners must make efforts to control their own learning and use cognitive self-regularization strategies to achieve good learning outcomes. According to the classification, there are three sections: motivation scales, learning strategies scales, and resource management. Among learning strategies related to the current study, rehearsal is related to basic cognitive strategies to measure behaviors the use of repeating words over and over. Elaboration includes paraphrasing, summarizing and organization is to measure behaviors such as outlining, creating tables. Critical thinking is related to strategies that students apply previous knowledge to new situations or make critical evaluations of ideas. Finally, metacognitive self-regulation covers setting goals, monitoring, or regulating.
Zarei and Gilanian (2014) examined the relationship between Strategies Inventory for Language Learning (SILL) from Oxford and learning strategies (rehearsal, elaboration, organization self-regulated learning, and critical thinking) from the MSLQ from Pintrich et al. (1991). They found the meaningful results. First, the memory strategies were the best predictor of rehearsal and metacognitive, affective, and memory strategies had predictive power on elaboration. Additionally, the result revealed that there were significant relationships between meta-cognitive and cognitive strategies and organization self-regulated learning.
Anthonysamy et al. (2020) searched a total of 239 and finally, reviewed 14 papers. According to the results, they found that research examined the strategies such as metacognitive knowledge, resource management and motivational belief strategies, and motivational beliefs for learning outcomes, while engagement strategies were the least investigated. Therefore, they argued that the quality of learning is low due to the lack of strategy use in digital learning and using self-regulated learning strategies well in blended learning leads to a positive effect on learners’ learning outcomes.
Assuming that learning outcomes are poor if self-directed learning is insufficient, Anthonysamy et al. (2021) explored the effect of using learning strategies in online learning for Malaysian students. Then, they found that these three factors, cognitive engagement, resource management, and motivating lives, influenced students’ recognition of learning outcomes. Based on their results, they stated that it is important for students to have self-regulated learning strategies and it makes them successfully improve their learning performance.
Considering the previous studies mentioned related to learning strategies, it means that students can achieve good learning performances if both teachers understand the learning strategies their students use and train them to use the shortcomings. If students also perceive their strategy use by themselves, learning efficiency should be improved. Therefore, under these arguments, this study investigates the degree of the use of learning strategies in online and offline. Then, it examines whether there are significant differences between the use in online and offline. Lastly, this current study explores where there is the relationship among the learning strategies.


1. Participants

A total of 81 students participated in the survey of this study. Students took four courses run by researchers among English classes opened at the liberal arts university: English Reading and Writing Practice, TOEIC Beginner, Let’s Know Two-Word Verbs, and ESP Reading and Writing. Since it is a liberal arts class, students have a total of 17 majors. Participants’ major information is shown in Table 1.
The average age of the participants was 24.5 and consisted of 38 female students and 44 male students. The grades were 12 first graders, 38 second graders, 23 third graders, and 8 fourth graders. These are students who have experienced both online and offline classes because they have experienced the COVID-19 pandemic, so they responded based on their learning experiences. The response to questions using strategies was based on regular school classes. Concerning the English proficiency of the participants, since not all students had official English grades such as TOEIC, TOEFL, or OPIc, they were asked to submit their English test scores from National Entrance Exam for University (NEEU). The proficiency of the participants in the current study was not high with an average of 4.5 out of a total of 9 grades on the NEEU.

2. Measures

MSLQ of Pintrich et al. (1991) was administered in this study to find out how students use the same strategy in online and offline classes. MSLQ is designed not only to focus on the course level, but also to analyze the various and detailed situations that occur during the course. It has translated into multiple languages and globally used by many researchers or instructors throughout the world (Duncan & McKeachie, 2005).
MSLQ consists of a total of 81 items and is divided into two sections: motivation and learning strategies. The learning strategies of MSLQ are composed of the scales of the three types, including cognitive, metacognitive, and resource management. This study employed cognitive and metacognitive strategy scales among the three ones. Cognitive strategies include rehearsal, elaboration, organization, and critical thinking related to the ones that students basically use for the processing of information from the learning. The metacognitive scales are connected to strategies that students control and regulate their own cognition. The question response scale was set as a seven-point scale system ranging from 1 (not at all true of me) to 7 (every true of me) according to the original inventory.

1) Rehearsal

Rehearsal is the most basic cognitive strategy and is associated with repetitive actions by reciting items of learned things or saying names. This scale is most often used for a simple task or action of learning to get to long-term memory. In other words, it is assumed to affect the repetitive actions such as word memorization, or concentration (Pintrich et al., 1991). Cronbach’s alpha for Rehearsal was .79 in online and .81 offline. The items are shown in Table 2.

2) Elaboration

Elaboration is to measure more complex strategies used by students. For example, this includes actions such as paraphrasing, summing, or generative note-taking. This helps learners store information in long term memory. Learners who use this strategy well know how to integrate new and previous information (Pintrich et al., 1991). Cronbach’s alpha for Elaboration was .81 in online and .80 offline. The five items were seen in Table 3.

3) Organization

Organization strategies, like Elaboration, are also intended to measure more complex strategies, including outlining, selecting main idea, or creating tables. It is also a measure of whether the learner can select and build the appropriate things from the learned information. This strategy is to be active, requires a commitment of effort, and seeks better achievements (Pintrich et al., 1991). Cronbach’s alpha for Organization was .76 in online and .75 offline. Table 4 shows the items.

4) Critical Thinking

Critical Thinking is to measure whether learners can apply existing knowledge to new knowledge and make a decisive evaluation of ideas. It is a measure of the degree to which learners can apply and report old knowledge and new situations to solve problems, make decisions, and make decisive evaluations (Pintrich et al., 1991). Cronbach’s alpha for Critical Thinking was .79 in online and .79 offline. Table 5 shows the items.

5) Metacognitive Self-Regulation

This part consists of meta-cognitive control strategies, which are strategies used to help learners control and regularize their cognition on their own. It consists of a total of 12 items. These items include planning (setting goals), monitoring (of one’s compliance), and regulating (e.g., adjusting leading speed dependent on the task, Pintrich et al., 1991). Cronbach’s alpha for Metacognitive Self-regulation was .72 in online and .82 in offline class. Each item is displayed in Table 6.


1) Rehearsal

Descriptive statistics, including mean and standard deviations of each used to find out how degree learners use the rehearsal strategy in the learning, were listed in Table 7. In Rehearsal, the overall mean showed (M = 4.68, SD = 1.26) in online and (M = 4.89, SD = 1.30) in offline. The results revealed no statistically significant difference in strategy use, both online and offline class although they look different from the numbers.
More specifically, the results show that among the four items of Rehearsal, item 46 (When studying for this course, I read my class notes and the course read over and over again.) strategies were the most frequent (M = 5.03, SD = 1.53) in online class. and item 59 (I memorize key words to remind me of import concepts in this class.) were higher (M = 5.20, SD = 1.44) in offline class. These results show that learners do not want to miss out on an important part of learning.

2) Elaboration

According to the results, the overall average of the Elaboration showed (M = 4.54, SD = 1.29) in online and (M = 4.80, SD = 1.16) in offline. Table 8 shows the results of each item.
The results show that there is no significant difference when students use the same strategy of Elaboration in online and offline class. Nevertheless, among the five items, item 64 (When reading for this class, I try to relate the material to what I already know.) showed a slightly higher frequency than other items. Regarding item 64, the study of Pintrich et al. (1991) also showed that this item had a slightly higher average than other items (M = 5.56, SD = 1.28) based on offline class. This means that students have some difficulty in incorporating their previous knowledge with new instructions.

3) Organization

In organization, the overall average showed (M = 4.30, SD = 1.22) in online and (M = 4.49, SD = 1.24) in offline. The average of each item is shown in Table 9.
Prominently, item 49 (I make simple charts, diagrams, or tables to help me organize course material.) numerically is the lowest in both online and offline class as seen in table 9. In the results of Pintrich et al. (1991), item 49 (M = 3.04, SD = 1.94) were the lowest compared to other items as in this study (M = 3.40, SD = 1.64). This seems students to think that tables or diagrams are not factors that directly affect learning.

4) Critical Thinking

According to the results, the overall average of the Critical Thinking showed (M = 4.49, SD = 1.13) in online and (M = 4.67, SD = 1.10) in offline. Table 10 shows the results of Critical Thinking.
Each item of Critical Thinking showed an average of 4 points in both online and offline, and students responded neither negatively nor positively. Among them, the highest average is 4.91 (SD = 1.46) in offline from item 66 (I try to play around with ideas of my own related to what I am learning in this course.). This shows that learners are more active in thinking activities in offline classes.

5) Metacognitive Self-Regulation

The overall average for Metacognitive Self-regulation was 4.40 (SD =.88) in online and 4.59 (SD = .90) in offline. The results obtained show that there is no significant difference when students use the same strategy in online and offline class, respectively. Descriptive statistics for each of the 12 items related to Metacognitive Self-regulation are shown in Table 11.
Synthetically, the results to find out the degree to which learners use learning strategies in offline and online, it was found that the degree of strategy used offline class was generally similar to that of previous studies (Cho & Shen, 2013; Pintrich et al., 1991). Numerically, the degree of the use of strategies in offline is a little higher than that of online. However, there was no statistically significant difference between online and offline when using strategies.

6) The Relationship Among Learning Strategies in Online

Correlation analysis to find out whether the strategies used in online learning are related to each other showed that all items were highly correlated, as shown in Table 12. Interestingly, all relationships were correlated ranging from .66 and .79. As seen in the table above, the highest score is .79 between Rehearsal and Elaboration. The relationship between Critical Thinking and Metacognitive Self-regulation was the lowest with .66.

7) The Relationship Among Learning Strategies in Offline

The results correlations among learning strategies in offline, as shown in Table 13 also showed that all strategies were highly correlated with each other. Prominently, the correlation between Organization and Critical Thinking was the lowest score with .63. The coefficient score between Rehearsal and Elaboration was the highest with .82 as the one of online result.
The results for online showed that students in this study most frequently used the strategies related to Rehearsal with the average 4.68 (SD = 1.26), compared to Elaboration. Interestingly, it turns out that students use Rehearsals most often, even offline like online. Organization (M = 4.30, SD = 1.22), Critical Thinking (M = 4.49, SD = 1.13), and Metacognitive Self-regulation strategies (M = 4.40, SD = .88).
This shows that students are using strategies well, as it is an iteration, which is an advantage of online instruction. Interestingly, it turns out that students most frequently use Rehearsal strategies (M = 4.89, SD = 1.30) in even offline classes as shown in the results of online. The following highest is Elaboration with the mean 4.80 (SD = 1.16). Critical Thinking is 4.67 (SD = 1.10), Metacognitive Self-regulation with (M = 4.59, SD = .90), and Organization with (M = 4.49, SD = 1.24). According to the results, students in this study most often use Rehearsal strategies. It means that they are well aware of the basic strategies. More specific descriptive statistics are followed.


This study was to find out whether Korean university students use learning strategies differently online and offline. In order to obtain the results of the study, we surveyed the learning style questions from MSLQ of Pintrich et al. (1991). As mentioned in previous studies, many previous studies have argued that the use of strategies is important because it affects learners’ learning outcomes and have studied their relevance (Anthonysamy et al., 2020, 2021; Delen et al., 2013; Donker et al., 2014; Pintrich et al., 1991).
Strategies are important in digital learning but also in offline learning. Most studies are focused on online (Adam et al., 2017; Anthonysamy et al., 2020). So, this study investigated whether there is a difference in learners’ strategy use between online and offline, respectively. There was no difference in the results of this study. Rather, it was found that the subjects of this study had a high degree of strategy use.
Looking at the overall average, Rehearsal averages were 4.68 (SD = 1.26) in online, and 4.89 (SD = 1.30) in offline, Elaboration averages were 4.54 (SD = 1.22) in online, and 4.80 (SD = 1.16) in offline, Organization averages were 4.30 (SD = 1.22) in online, and 4.49 (SD = 1.24) in offline, Critical Thinking averages were 4.49 (SD = 1.13) in online, and 4.67 (SD = 1.10) in offline, and Metacognitive Self-regulation averages were 4.40 (SD = .88) in online and 4.59 (SD = .90). As seen in the results, it was found that there was no difference in the degree to which learners used strategies online and offline.
Although there is no difference in learners’ strategy use between online and offline, it was revealed that the degree of strategy use of learners was not lower than that of subjects offline by the study of Pintrich et al. (1991). Although the online result of this current study was not compared to previous online research, it was found that our learners used strategies that were only as large as offline even online.
Addtionally, the fact that the degree of use of learning strategies is not low means that the students who participated in this study are conscious of using strategies. In future studies, it is suggested that the research with self-report needs to explore whether learning strategy use affects learning outcomes such as grades or performances.
In terms of the relationship among strategies, it was found that the correlation among the uses of the learning strategies was high in both online and offline. The correlation in online was seen ranging from .66* and .79*. The highest correlation was revealed between Rehearsal and Elaboration and the lowest one was between Critical Thinking and Metacognitive Self-regulation. Interestingly, the lowest score in offline was revealed between Organization and Critical Thinking with .69*. The results showed that the strategies used by the students of this study were significantly connected to each other. Regardless of these positive results, the limitation of the study is that since the responding students are composed of only the students of the researcher of the current study, the results are not apt to be generalized.
However, in conclusion, it turned out that the participants of the current study are actively using strategies both online and offline, and the relationship between strategies is somewhat high. This study suggests that since learners need to be aware of using strategies and instructors should understand the degree of strategy use of learners and guide them to make good use of sufficient strategies so that learners can boost learning effects. The results of the study are pedagogically meaningful in that learners do not overlook strategies. For future research, it is necessary to explore whether it is related to the responded questionnaire and actual learners’ academic outcomes as well as it is necessary to explore them with various and more students.

Table 1.
The Department of the Participants
Department n Department n
Game Content 9 Convergence Soft 10
Tourism 6 Chinese Language 2
Digital Media 1 Physical Education 3
Russian Language 3 Computer Science 6
Beauty Medical 1 Piano 1
Smart City 9 Marine Bio 17
Food Nutrition 3 Physical Education 3
Practical Music 3 Environmental Energy 2
Early Childhood Education 2
Table 2.
Rehearsal Scales
39. When I study for this class, I practice saying the material to myself over and over.
46. When studying for this course, I read my class notes and the course readings over and over again.
59. I memorize key words to remind me of important concepts in this class.
72. I make lists of important items for this course and memorize the lists.
Table 3.
Elaboration Scales
53. I treat the course material as a starting point and try to develop my own ideas about it.
62. I try to relate ideas in this subject to those in other courses whenever possible.
64. When reading for this class, I try to relate the material to what I already know.
67. When I study for this course, I write brief summaries of the main ideas from the readings and my class notes.
69. I try to understand the material in this class by making connections between the readings and the concepts from the lectures.
Table 4.
Organization Scales
32. When I study the readings for this course, I outline the material to help me organize my thoughts.
42. When I study for this course, I go through the readings and my class notes and try to find the most important ideas.
49. I make simple charts, diagrams, or tables to help me organize course material.
63. When I study for this course, I go over my class notes and make an outline of important concepts.
Table 5.
Critical Thinking Scales
38. I often find myself questioning things I hear or read in this course to decide if I find them convincing.
47. When a theory, interpretation, or conclusion is presented in class or in the readings, I try to decide if there is good supporting evidence.
51. I treat the course material as a starting point and try to develop my own ideas about it.
66. I try to play around with ideas of my own related to what I am learning in this course.
71. Whenever I read or hear an assertion or conclusion in this class, I think about possible alternatives.
Table 6.
Metacognitive Self-Regulation Scales
33. During class time I often miss important points because I’m thinking of other things. (REVERSED)
36. When reading for this course, I make up questions to help focus my reading.
41. When I become confused about something I’m reading for this class, I go back and try to figure it out.
44. If course readings are difficult to understand, I change the way I read the material.
54. Before I study new course material thoroughly, I often skim it to see how it is organized.
55. I ask myself questions to make sure I understand the material I have been studying in this class.
56. I try to change the way I study in order to fit the course requirements and the instructor’s teaching style.
57. I often find that I have been reading for this class but don’t know what it was all about. (REVERSED)
61. I try to think through a topic and decide what I am supposed to learn from it rather than just reading it over when studying for this course.
76. When studying for this course I try to determine which concepts I don’t understand well.
78. When I study for this class, I set goals for myself in order to direct my activities in each study period.
79. If I get confused taking notes in class, I make sure I sort it out afterwards.
Table 7.
The Results of Rehearsal
Item Online Offline
M (SD) M (SD)
39 4.27 (1.49) 4.65 (1.54)
46 5.03 (1.53) 5.02 (1.70)
59 5.01 (1.53) 5.20 (1.44)
72 4.42 (1.72) 4.67 (1.80)
Total 4.68 (1.26) 4.89 (1.30)
Table 8.
The Results of Elaboration
Item Online Offline
M (SD) M (SD)
53 3.43 (1.71) 3.81 (1.745)
62 4.06 (3.52) 3.91 (1.85)
64 5.25 (1.60) 5.33 (1.44)
67 3.83 (1.45) 4.17 (1.57)
69 3.53 (1.44) 3.53 (1.38)
Total 4.54 (1.29) 4.80 (1.16)
Table 9.
The Results of Organization
Item Online Offline
M (SD) M (SD)
32 4.56 (1.56) 4.91 (1.58)
42 4.90 (1.55) 5.07 (1.57)
49 3.40 (1.64) 3.43 (1.74)
63 4.34 (1.66) 4.53 (1.64)
Total 4.30 (1.22) 4.49 (1.24)
Table 10.
The Results of Critical Thinking
Item Online Offline
M (SD) M (SD)
38 4.38 (1.41) 4.37 (1.41)
47 4.55 (1.47) 4.81(1.47)
51 4.37 (1.49) 4.60 (1.48)
66 4.69 (1.62) 4.91 (1.46)
71 4.49 (1.63) 4.64 (1.63)
Total 4.49 (1.13) 4.67 (1.10)
Table 11.
The Results of Metacognitive Self-Regulation
Item Online Offline
M (SD) M (SD)
33R 3.43 (1.71) 3.81 (1.75)
36 4.06 (3.51) 3.91 (1.85)
41 5.25 (1.59) 5.33 (1.44)
44 4.99 (1.47) 5.14 (1.35)
54 4.37 (1.55) 4.64 (1.60)
55 4.21 (1.45) 4.42 (1.49)
56 3.83 (1.45) 4.17 (1.57)
57R 3.53 (1.44) 3.53 (1.38)
61 4.68 (1.39) 4.86 (1.38)
76 5.17 (1.43) 5.47 (1.33)
78 4.60 (1.63) 4.80 (1.54)
79 4.71 (1.60) 4.96 (1.63)
Total 4.40 (.88) 4.59 (.90)
Table 12.
The Relationship Among Learning Strategies in Online
Items Rehearsal Elaboration Organization Critical thinking
Elaboration .79**
Organization .75** .75**
Critical thinking .72** .77** .69**
Metacognitive self-regulation .73** .73** .74** .66**

**. . Correlation is significant at the 0.01 level.

Table 13.
The Relationship Among Learning Strategies in Offline
Items Rehearsal Elaboration Organization Critical thinking
Elaboration .82**
Organization .75** .73**
Critical thinking .75** .76** .63**
Metacognitive self-regulation .78** .74** .71** .71**

**. . Correlation is significant at the 0.01 level.


Adam, N.L., Alzahri, F.B., Cik Soh, S., Abu Bakar, N., & Mohamad Kamal, N.A. (2017). Self-regulated learning and online learning: A systematic review. In In : H. B. Zaman & P. Robinson & A. F. Smeaton & T. K. Shih & S. Velastin & T. Terutoshi & A. Jaafar & N. M. Ali (Eds.), In: Advances in visual informatics: 5th International Visual Informatics Conference, IVIC 2017; Bangi, Malaysia. November 28-30, 2017; Proceedings. pp 143-154. Springer: Cham:https://doi.org/10.1007/978-3-319-70010-6_14.
Anthonysamy, L., Koo, A. C., & Hew, S. H. (2020). Self-regulated learning strategies and non-academic outcomes in higher education blended learning environments: A one decade review. Education and Information Technologies, 25, 3677-3704. https://doi.org/10.1007/s10639-020-10201-8.
Anthonysamy, L., Koo, A. C., & Hew, S. H. (2021). Investigating self-regulated learning strategies for digital learning relevancy. Malaysian Journal of Learning and Instruction, 18(1), 29-64. https://doi.org/10.32890/mjli2021.18.12.
Artino, A. R. (2008). Motivational beliefs and perceptions of instructional quality: Predicting satisfaction with online training. Journal of Computer Assisted Learning, 24(3), 260-270. https://doi.org/10.1111/j.1365-2729.2007.00258.x.
Avila, E. C., & Genio, A. M. G. J. (2020). Motivation and learning strategies of education students in online learning during pandemic. Psychology and Education Journal, 57(9), 1608-1614. https://doi.org/10.17762/pae.v57i9.506.
Barbour, M. K., & Reeves, T. C. (2009). The reality of virtual schools: A review of the literature. Computers & Education, 52(2), 402-416. https://doi.org/10.1016/j.compedu.2008.09.009.
Barrnett, J. (2009). Aptitude, personality and motivation tests. Kogan Page.
Broadbent, J. (2017). Comparing online and blended learner’s self-regulated learning strategies and academic performance. Internet and Higher Education, 33, 24-32. https://doi.org/10.1016/j.iheduc.2017.01.004.
Broadbent, J., & Poon, W. L. (2015). Self-regulated learning strategies & academic achievement in online higher education learning environments: A systematic review. The Internet and Higher Education, 27, 1-13. https://doi.org/10.1016/j.iheduc.2015.04.007.
Chamot, A. U., & Kupper, L. (1989). Learning strategies in foreign language instruction. Foreign Language Annals, 22(1), 13-22.
Cho, M. H., & Shen, D. (2013). Self-regulation in online learning. Distance Education, 34(3), 290-301. https://doi.org/10.1080/01587919.2013.835770.
Delen, E., Liew, J., & Willson, V. (2014). Effects of interactivity and instructional scaffolding on learning: Selfregulation in online video-based environments. Computers & Education, 78, 312-320. https://doi.org/10.1016/j.compedu.2014.06.018.
Donker, A. S., de Boer, H., Kostons, D., Dignath van Ewijk, C. C., & van der Werf, M. P. C. (2014). Effectiveness of learning strategy instruction on academic performance: A meta-analysis. Education Research Review, 11, 1-26. https://doi.org/10.1016/j.edurev.2013.11.002.
Duncan, T. G., & McKeachie, W. J. (2005). The making of the motivated strategies for learning questionnaire. Educational Psychologist, 40(2), 117-128.
Ehrman, M. E., Leaver, B. L., & Oxford, R. L. (2003). A brief overview of individual differences in second language learning. System, 31, 313-330. https://doi.org/10.1016/S0346-251X(03)00045-9.
Gardner, R. C., & Lambert, E. (1972). Attitudes and motivation in second language learning. Newbury.
Greene, J. A., & Azevedo, R. (2009). A macro-level analysis of SRL processes and their relations to the acquisition of a sophisticated mental model of a complex system. Contemporary Educational Psychology, 34(1), 18-29.
Lin, C. H., Zhang, Y., & Zheng, B. (2017). The roles of learning strategies and motivation in online language learning: A structural equation modeling analysis. Computers & Education, 113, 75-85. https://doi.org/10.1016/j.compedu.2017.05.014.
Neroni, J., Meijs, C., Gijselaers, H. J. M., Kirschner, P., & de Groot, R. H. M. (2019). Learning strategies and academic performance in distance education. Learning and Individual Difference, 73, 1-7. https://doi.org/10.1016/j.lindif.2019.04.007.
Pintrich, P. R. (2000). The role of goal orientation in self-regulated learning. In M. Boekaerts & P. Pintrich & M. Zeidner (Eds.), Handbook of self-regulation. pp 451-502. Academic Press.
Pintrich, P. R., Roeser, R. W., & de Groot, E. A. M. (1994). Classroom and individual differences in early adolescents’ motivation and self-regulated learning. The Journal of Early Adolescence, 14(2), 139-161. https://doi.org/10.1177/027243169401400204.
Pintrich, P. R., Smith, D. A., Garcia, T., & McKeachie, W. J. (1991). A manual for the use of the motivated strategies for learning questionnaire (MSLQ) (ED338122). ERIC, https://files.eric.ed.gov/fulltext/ED338122.pdf.
Pintrich, P. R., Smith, D. A., Garcia, T., & McKeachie, W. J. (1993). Reliability and predictive validity of the motivated strategies for learning questionnaire (MSLQ). Educational and Psychological Measurement, 53(3), 801-813. https://doi.org/10.1177/0013164493053003024.
Puzziferro, M. (2008). Online technologies self-efficacy and self-regulated learning as predictors of final grade and satisfaction in college-level online courses. The American Journal of Distance Education, 22, 72-89. https://doi.org/10.1080/08923640802039024.
Rahardjo, A., & Pertiwi, S. (2020). Learning motivation and students’ achievement in learning English. Journal of English Language Teaching and Literature, 1(2), 56-64. https://jurnal.stkipmb.ac.id/index.php/jelita/article/view/65.
Serdyukov, P., & Hill, R. (2013). Flying with clipped wings: Are students independent in online college classes? Journal of Research in Innovative Teaching, 6(1), 54-67.
Smith, R. C. (2012). Situational language teaching. ELT Journal, 2(4), 71-79.
Tsuda, A., & Nakata, Y. (2013). Exploring self-regulation in language learning: A study of Japanese high school EFL students. Innovation in Language Learning and Teaching, 7(1), 72-88. https://doi.org/10.1080/17501229.2012.686500.
Varasteh, H., Ghanizadeh, A., & Akbari, O. (2016). The role of task value, effort-regulation, and ambiguity tolerance in predicting EFL learners’ test anxiety, learning strategies, and language achievement. Psychological Studies, 61, 2-12. https://doi.org/10.1007/s12646-015-0351-5.
Zarei, A. A., & Gilanian, M. (2014). On the relationship between cognitive self-regulated learning and language learning strategies. Journal of Social Issues & Humanities, 2(12), 200-209.
Zhou, Y., & Wang, J. (2021). Psychometric properties of the MSLQ-B for adult distance education in China. Frontiers in Psychology, 12, https://doi.org/10.3389/fpsyg.2021.620564.
Zimmerman, B. J. (2000). Self-efficacy: An essential motive to learn. Contemporary Educational Psychology, 25(1), 82-91. https://doi.org/10.1006/ceps.1999.1016.
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