INTRODUCTION

After decades of inquiry, the crucial role of motivation in second language (L2) learning seems to be beyond doubt. Traditionally, motivation was simply conceived of as a stable and fixed trait of L2 learners that steadily drives them towards their long-term goals (Dörnyei, 2020). However, with the advent of theories, novel views of motivation have been adopted postulating that L2 motivation goes beyond an individual difference. Rather, it should be considered as part of a more inclusive and dynamic system (Dörnyei & Ushioda, 2021). This means that motivation is in constant interaction with a plethora of cognitive, affective, social and situational variables, hence subjected to temporal and contextual fluctuations even within a single individual (Ushioda, 2019). Consequently, scholars began to investigate L2 motivation, as a situated phenomenon in various timescales of development (Dörnyei, 2020).

One of the consequences of the shift to situated perspectives was a propensity to focus on task motivation. Tasks provide researchers with a manageable unit of analysis and enable them to connect the study of L2 motivation to instructed second language acquisition (SLA) (Kormos & Dörnyei, 2004). So far, several aspects of task motivation have been investigated: differences between general motivation and task motivation (Dörnyei, 2002; Dörnyei & Kormos, 2000), task-related factors and L2 motivation (Ghasemi et al., 2021; Naseri et al., 2021; Poupore, 2013, 2014), learner choice and task motivation (Kormos & Préfontaine, 2017; Lambert et al., 2017; Mozgalina, 2015), the effect of task motivation on task performance (Dörnyei & Kormos, 2000; Kormos & Dörnyei, 2004), the interaction of social factors and task motivation (Azkarai & Kopinska, 2020; Fukada et al., 2019; Guo et al., 2020; Poupore, 2016 ), and temporal and dynamic variation in task motivation (Dörnyei &Tseng, 2009; MacIntyre & Serroul, 2015).

The majority of the studies on task motivation have generally concentrated on researching the inherently motivational characteristics of tasks, or examining the direct impact of task motivation on L2 learners’ performance and achievement. However, there is a dearth of knowledge about the potential effect of task motivation on the transfer of learning from one task to other subsequent tasks, a fact that warrants further scrutiny (Jeon, 2021; Kormos & Wilby, 2019). Thus, the present study aims to investigate whether varying degrees of task motivation toward a specific L2 task can influence the transfer of knowledge to another L2 task.

LITERATURE REVIEW

Task Motivation

The inception of L2 task motivation research dates back to as far as three decades ago when Jülkunen (1989), drawing on cognitive theories, conceptualized task motivation as a blend of trait motivation and state motivation. In fact, he construed task motivation as an individual’s trait motivation crystalized in a specific situation. Later, Dörnyei (2002) criticized Jülkunen’s model for oversimplifying task motivation and emphasized the dynamic complexity of the construct. According to his process-based view, numerous interplaying factors are at work and the culmination of their combined effects determines the motivational power of any task. Learners’ appraisal of the task, task execution, and using action control strategies are the major elements underlying task motivation (Khatib & Dehghankar, 2018; Dörnyei, 2002; Dörnyei & Kormos, 2000; Dörnyei & Tseng, 2009). Despite all the endeavors to delineate task motivation, the concept still evades a discrete definition. Dörnyei (2019, 2020) believes that this can be ascribed to the multitude of variables that must be taken into account including learner, situational, task-related, and other miscellaneous factors (e.g., distractions).

Despite the difficulty of capturing and characterizing task motivation, scholars have recently attempted to shed some light on how it interacts with other learner variables and influences or is influenced by them. Regarding how characteristics of tasks might affect motivation, Poupore (2014) found that task content, topic interest, and text features can significantly predict the motivational potential of tasks and learners’ engagement in related activities. He concluded that life themes, personal topics and story-based tasks are the most interest-provoking of all content-related topics. In the same vein, Lambert et al.’s (2017) study showed that personalized content about life issues and experiences are positively associated with task motivation.

Dörnyei (2019) believes that task ownership and the degree of perceived control over the task play an important role in regulating task motivation. In an experimental study, Mozgalina (2015) manipulated writing task choice by providing his learners with three different levels of option for deciding about the task content and procedure. It was found that totally free choice was relatively detrimental whereas a fixed content with relative procedural freedom evoked the highest level of task motivation. According to Lambert et al. (2017), too, personalized topics and self-relevant content induce more control, engagement and interest. Moreover, task complexity seems to impact motivation (Skehan, 2014). Kormos and Préfontaine (2017) investigated the effect of learners’ appraisals of oral tasks on their fluency. The participants’ subjective rating and questionnaire data indicated that cognitive demands affect task motivation and performance. Their findings showed that unclear task structure, high cognitive load and responsibility were implicated in increased anxiety and diminished motivation. Likewise, MacIntyre and Serroul (2015) maintain that task difficulty, topic familiarity, and vocabulary and grammatical challenges are implicated for motivational inconsistencies. By the same token, in a study on Iranian L2 learners’ performance on writing tasks, medium complexity tasks were observed to energize learners with positive emotion and task motivation (Azizi & Gholami, 2020).

Another notable dimension of task motivation relates to social factors. Some studies have focused on the role of interlocutors, interacting peers or task partners and suggest that task motivation is co-constructed when learners work in dyads or groups, something that is common in task execution (Dörnyei, 2000; Kormos & Dörnyei, 2004). This led to an ongoing surge of investigation into the nature and function of group work dynamics, defined as feelings of acceptance and comfort, “genuine sense of warmth, trust, cheerfulness, and accomplishment within the group” (Poupore, 2016, p. 724). Findings of such studies lend support to the positive impact of healthy group dynamics and connections on improving L2 learners’ task motivation and performance and abatement of their anxiety (e.g., Guo et al., 2020; Azkarai & Kopinska, 2020; Leaming, 2021; Poupore, 2016).

Several scholars have reported task motivation to affect learner performance, involvement and learning outcomes, regardless of learners’ general motivational profile (Dörnyei, 2019; Dörnyei & Kormos, 2000; Kormos & Dörnyei, 2004; Wang & Li, 2019). They highlight the necessity of choosing appropriate tasks with sufficient motivational energy to keep learners on track in their subsequent learning activities and performances. Supporting this position, Masrom et al. (2015) held the view that robust task motivation positively affects syntactic and lexical complexity of L2 learners’ written products. Similarly, Azkarai  and Kopinska (2020) argue that a motivating task would persuade learners to take part in more interactive episodes and engage in learning opportunities. Accordingly, Kormos and Préfontaine (2017) state that if learners develop a promising evaluation of task success and motivation, they will tend to engage in similar tasks in the future.

Transfer of Learning

Transfer of learning is one of the most elusive concepts in the realm of learning and teaching (Long, 2015). The transfer takes place “when learning in one context or with one set of materials impacts on performance in another context or with another set of materials” (Perkins & Salomon 1994, as cited in James, 2018, p. 330). In fact, the value of instruction lies in the transfer of knowledge and learning; otherwise, there is no point in teaching and learning activities (Jeon, 2021). The concept of transfer is getting increasingly salient in task-based language teaching (TBLT) because achieving a comprehensible and practical understanding of the concept can pave the way to the efficient selection, planning and assessment of language learning tasks (Benson, 2016). As Long (2015) asserts, the major goal of TBLT is to enable L2 learners to use their acquired knowledge and skill in other communicative settings. Definitely, this aim may not be attained without the capacity of transferring the acquired knowledge to other situations. Nevertheless, there is little consensus regarding how the transfer of learning should be understood. Research has failed to provide enough evidence of transfer and there is ample disagreement on the factors which affect or predict transfer of learning (James, 2018; Larsen-Freeman, 2013).

Scholarly works on transfer of learning highlight several cognitive, emotional, motivational, contextual, and social variables and conditions that affect the transfer of learning. For example, it has been stated that transfer is more likely to happen between tasks of similar content domains (Benson, 2016; Spada et al., 2014). They assert that memory best serves transfer when encoding processes in working with the first task match retrieval processes in the second. Benson (2016) also foregrounds the importance of contextual similarities and memory demands in achieving effective transfer.

Some other scholars found that learners’ perception of relevance, meaningfulness, and usefulness of tasks has a bearing on the transfer of learnt items. As an illustration, Green (2015) believes that learners’ perception of task relevance and enjoyment can impact transfer. James (2012), too, remarks on the importance of value that learners place on a task and its contribution to transfer of learning. Following a similar individual focus, a number of studies have concentrated on the effects of motivational and attitudinal elements on transfer. For instance, some researchers suggest that a strong motivational base in a learning activity is the key to deep understanding which, ultimately, culminates in transfer of knowledge across different occasions (Haskell, 2001; James, 2012). Similarly, Pugh and Bergin (2006) found that motivation positively influences transfer by improving the quality of initial learning, cognitive engagement, initiation of effort, and increasing learners’ persistence. They state that task motivation can be raised if learners consider the task at hand to be useful and relevant. Billing (2007), too, believes that motivation promotes transfer of learnt materials through activating self-regulatory learning mechanisms, prompting cognitive and metacognitive strategies such as self-monitoring and self-reflection.

Furthermore, cognitive capacities have been highlighted to play a part in the successful transfer of learning. As a case in point, attention and noticing seem to promote transfer of learning (Billing, 2007; Saito, 2013). Amount of practice and provision of a variety of practice opportunities in multiple contexts are believed to improve transfer as well (Chang & Millet, 2016; James, 2018; Larsen-Freeman, 2013; Okuno & Hardison, 2016; Shintani & Ellis, 2014). Some of the scholars who have worked on these aspects insist that fruitful transfer of L2 knowledge, especially of form, warrants that learners do not internalize narrowed or localized rules; instead, they should acquire principles via induction and abstraction (Larsen-Freeman, 2013).

PURPOSE OF THE STUDY

A review of literature on task motivation makes it clear that the potential effects of task motivation on transfer of leaned materials from one task to other tasks have not been dealt with and demand thorough investigation. Therefore, in order to scrutinize this subject, the following research questions have been addressed:

1. Does L2 learners’ task motivation affect their learning transfer in terms of the English definite article use across tasks?
2. What are the different learning behaviors of L2 learners with high or low task motivation that affect transfer of learning?

METHOD

Design

Following Ary et al. (2019), this study was a mixed-methods research that followed an explanatory sequential design. First, quantitative data were collected using a test, a questionnaire and two tasks. Then, a few participants were recruited for the qualitative part and the data were obtained via interviews. Analysis and comparison of both data types result in complementarity and richer insight.

Participants

The present study involved a convenience sample of 82 Iranian intermediate EFL learners (male = 37, female = 45) who were learning English at two private language institutes in Mazandaran. The sample was drawn from an initial pool of 102 individuals. After the pre-test was administered, those test-takers who fell within one standard deviation above and below the mean score (n= 86) were selected to form the sample, and the remaining 20 students were excluded from the study. Furthermore, four other students were later excluded from the sample due to the mortality effect. They were absent in one or more data collection sessions. Thus, their results were also removed from the final dataset and the finalized sample comprised 82 participants. According to the placement mechanisms of the institutes, all participants were at intermediate level of proficiency. They attended language classes twice a week with each session lasting about 90 minutes. The ages of the participants ranged from 16 to 30 (Mean= 19.66, SD= 3.33). The first language of the participants was Persian. The students were taught by four teachers (female= 2, male= 2) in separate classes (a total of seven classes run by the four teachers). All the teachers held master’s degrees in TEFL from Iranian universities and none of them had less than five years of teaching experience.

Instrumentation

Task Motivation Questionnaire

The major measurement instrument of the study was a self-report task motivation questionnaire which was adopted from Poupore (2016). The questionnaire was based on cognitive theories of motivation, particularly self-determination and expectancy-value theory. The instrument consisted of two sections. The first one contained nine five-point Likert-type items classified into four sub-scales including: task enjoyment (3 items), reported effort (three items), result assessment (two items), and task relevance (one item). The sum of the scores on all categories divided by the number of categories provides a measure of respondents’ task motivation. The second section of the questionnaire included a few questions about respondents’ names, ages, and gender. At the bottom of the page, there was a note in boldfaced letters which assured the students of the confidentiality of their information and obtained their consent to use the questionnaire data.

Test of the Definite Article

The learning point of interest in the present study was related to the use of the English definite article (the). This is an area of knowledge where students experience great difficulty and quite often produce erroneous utterances (Lee et al., 2018). In order to measure participants’ knowledge of the definite article, a test was developed by the author. It contained 21 multiple-choice items. There were three choices after each stem. Test takers were prompted to choose an option from among a/an, the, or nothing to complete the stem, as illustrated in the following example:

I wished Thomas an enjoyable and safe journey for his next trip to ______ Alps.

1. a/an
2. the
3. nothing

The instances of the definite article use were intentionally selected to cover seven areas or categories where there is a rule to be applied to how the definite article is used. They included 1) names of countries with political terms (e.g., The USA, The Republic of Ireland), 2) unique entities (e.g., the sun, the equator), 3) geographical names of rivers, mountain ranges etc. (e.g., the Alps, the Red Sea), 4) names representing a general class or inventions (e.g., the telephone, the elephant), 5) musical instruments (e.g., the piano, the violin), 6) plural names of countries and islands (e.g., The Netherlands, The Maldives), and 7) names of cities, countries, lakes, mounts, abstract nouns etc. where the definite article should be avoided (e.g., Japan, football). Every category was represented by three test items.

The final version of the test was subjected to content validity analysis. Three CELTA certified teachers of English with at least 16 years of experience read through the items and confirmed their suitability. Then, the test was administered to a group of 12 intermediate English learners. They took the test and answered the items without any misunderstanding, making sure that the content was suitable for learners of that level. The reliability of the test was calculated by using KR-21 yielding an estimate of .80 which indicates good reliability.

Tasks

Two tasks were used in the present study: a consciousness-raising task and a picture story writing task. They are fully described below.

Consciousness-raising Task: A reading passage of about 400 words entitled “Wonderful natural beauties of the world” was purposefully composed to incorporate sufficient instances of the definite article use or avoidance. Care was taken to give enough room to all seven categories of the definite article. The content centered around four natural wonders including Mount Everest, the Amazon River, The Aurora Australis, and the Angel Oak. A total of 20 instances, where the definite article was correctly used or avoided, were printed in bold and underlined so as to attract students’ attention for the form-focused part of the task.

The task begins with a few warm-up questions and a meaning-focused purpose is set. The goal of reading is to decide which one of the four phenomena is more wonderful or amazing than the others and is worth being on one’s to-visit list. Thus, brief discussion and exchange of personal opinions after the reading phase are necessary. After the meaning-focused phase is accomplished and the outcome is achieved, students’ attention is drawn towards the boldfaced words and phrases, most of which include the definite article (15 out of 20) and five of them lack one. Then, the students are encouraged to work in groups or pairs (depending on class size) to extract rules governing the application of the definite article and formulate them inductively. In the meantime, the teacher moves around the room and provides feedback and help when necessary. Finally, the extracted grammatical rules are shared and finalized by students.

Picture Story Writing Task: This task called “Donny’s travels and experiences” was especially designed by the author for the present study to assess how participants use their acquired knowledge of the definite article in composing new sentences. A sizeable colorful map of the world was prepared for the task. On the map, several items were enlarged and made salient. They were drawn disproportionately larger; for example, a kangaroo, as the national animal of Australia or the flag of Japan covered half of the surface of their respective countries. The items of interest comprised various natural, cultural, political and geographical entities (e.g., rivers, mountain ranges, some animals, countries, cities, famous organizations like the UN, a few cultural items such as musical instruments, some geographical features, etc.). A few isolated content words or phrases were written next to each item to provide information to help students in generating relevant sentences. For instance, the words pacific ocean, largest, world appeared on the Pacific Ocean, or the words peacocks, heavy tail, fly appeared next to a peacock on India. No definite articles or other function words were provided. The students are also made aware that the content words must be strung together by using grammatical words or functional morphemes from their own so that finally, they come up with a complete and correct sentence. There were 10 starting and ending points marked around the edges of the map.

To implement the task, students are supposed to pick a starting point of their own choice and then draw a line across the map to connect it to one of the ending points on the other side. Then, they should guide Donny, the imaginary character, through the designated points along the drawn path that takes Donny across the world. The objective is to write a short narrative about the places Donny visits and the things he experiences and learns. Students are instructed to write at least three sentences for each one of the illustrated points that Donny meets: one sentence reporting his movement, arrival, or departure (e.g., Donny arrived in India), another sentence describing something he gets involved in (e.g., He saw a beautiful peacock), and a third one explaining factual information about the specific item (e.g., Despite their heavy tail, peacocks can fly). Nevertheless, they are free to write more sentences or form any sentences that fulfill the task goal.

Focus-group Interview: A focus-group interview was used as the qualitative data collection instrument. A total of 16 participants were invited to take part in focus group interviews. The sample was purposefully recruited to incorporate two groups of extreme cases: eight learners with the highest mean scores for task motivation (male= 4, female= 4), and eight learners who had the lowest mean scores on the same scale (male= 5, female= 3). Initially, the aim of the interview was explained to the participants and their consent was received. The two groups were interviewed separately to ensure respondents’ comfort. The major objective of the interviews was to identify the different ways by which learners, affected by varying levels of task motivation, approach tasks and transfer the acquired knowledge to the following tasks. Thus, during the interviews, the researcher asked a few prompt questions about the participants’ specific feelings and experiences with the tasks, their encounter with them, their perception of task enjoyment and relevance, their expended effort to involve in learning, their strategies to deal with the tasks and the way they engaged in learning and transferring the learning content. Both interview sessions were conducted and audio-recorded by the author, and each took around 90 minutes to finish. The language used was Persian to allow maximum expression of thoughts.

Procedure

As a mixed-methods project, this study contained two phases of data collection: a quantitative phase followed by a qualitative one. Prior to data collection, the schedule and procedure were shared with the participating teachers. They were briefed on the details of the work, task goals and contents. The quantitative phase of the study was carried out in four steps that took around two weeks to complete. At the outset, the test of the definite article was administered as the pre-test. Results of the test were used to homogenize the participants as to their knowledge of the definite article. The second step was taken during the following week when the consciousness-raising task (Task 1) was performed in all the classes. This task was intended to provide L2 learners with knowledge of the content domain. According to the teachers’ reports, Task 1 was implemented in 40 minutes on average. The third step was administering the task motivation questionnaire immediately after Task 1 was completed. The participants filled in the questionnaires and expressed how motivated they felt about the task they had just executed. Around a week later, the fourth step was taken when the picture story writing task (Task 2) was performed. This task took about 20 minutes to finish. The purpose of the second task was to assess the quality of transfer of learning from the first task. Two days after the first phase of data collection was accomplished, the interview was done.

Data Analysis

Each individual participant had three independent measures: (a) a pre-test score (0-21), (b) a task motivation mean score denoting their motivation on the first task (1-5), and (c) a score representing accuracy on Task 2. Accuracy on the task was computed and reported in percentage points. This was done by dividing the number of instances where the definite article was correctly used or avoided by the total number of cases where knowledge of the definite article should have been applied (in the seven categories under investigation). The resulting number was then multiplied by 100 to be converted into a comparable percentage value. The quantitative data were subjected to analysis by using SPSS version 20. Based on their task motivation mean scores, the participants were divided into three groups of low task motivation (LTM) (Mean = 1-2.33), medium task motivation (MTM) (Mean = 2.34-3.67), and high task motivation (HTM) (Mean = 3.68-5). Then, by running an analysis of variance (ANOVA), performances of the three groups on Task 2 were compared to see whether learners’ level of task motivation determines how well they transfer knowledge to the succeeding task.

The qualitative data were analyzed through thematic coding analysis with a semantic approach (Braun & Clarke, 2006). The interviews were transcribed and carefully read through several times to establish familiarization. Then, units of meaning and meaning-carrying elements were highlighted and assigned a code for achieving data reduction. Next, tentative categories were developed by combining related codes that could be accumulated under the same category. After that, categories were mindfully examined and where possible, they were linked to other categories to form themes. Throughout the whole process, constant comparison and iterations were utilized to find potential similarities and differences between codes and categories and to crosscheck whether formed combinations and melds were consistent with the data.

RESULTS

Quantitative Data

Descriptive statistics of the pre-test are presented in Table 1. As already described, all the scores fell within one standard deviation above or below the mean hence, leaving no outliers.

Table 1: Descriptive Statistics of the Pre-test

Table 2 summarizes the questionnaire data. As mentioned before, for better comparison and analysis, the participants were categorized into three groups on the basis of their performance on the questionnaire. Thus, each group included a different number of learners (LTM= 24, MTM= 31, HTM= 27). Their mean scores on each sub-scale are separately provided in Table 2. However, since the sum of each participant’s scores on all sub-scales makes up their task motivation index, the overall index is considered as the major indicator of task motivation. Evidently, there is great variation among the groups. The LTM group (Mean = 1.15, SD= 0.31) gained a low mean score. The MTM group (Mean= 2.70, SD= 0.35) was clearly set off from the LTM group by a wide margin. Finally, the HTM group (Mean= 3.73, SD= 0.38) obtained the highest means on all measures and experienced the highest level of task motivation. The overall measure of the participants taken together is also given in the last column of Table 2.

Table 2: Descriptive Statistics of the Task Motivation Questionnaire

Note. TM= task motivation, TMQ= task motivation questionnaire, HTM= high task motivation, LTM= low task motivation, MTM= medium task motivation

In order to see whether the participating groups, with varying degrees of task motivation, have performed differently on the following task, their mean scores on Task 2 were compared. Table 3 presents the descriptive statistics of Task 2 performance. The average accuracy rates of the learners after the initial exposure are presented. The descriptive statistics suggest that on Task 2 the HTM group outperformed the other groups, and the MTM group outperformed the LTM group.

Table 3: Descriptive Statistics of the Three Groups’ Performances on Task 2

Note. HTM= high task motivation, LTM= low task motivation, MTM= medium task motivation

To see whether the observed differences were statistically significant a one-way ANOVA was conducted. The normality of the data was checked with the Kolmogorov-Smirnov test, producing a significance value of 0.08 which indicated that the data were normally distributed. Also, the result of Levene’s test ensured the homogeneity of variances (sig= 0.19). After running the ANOVA, it was found that there was a statistically significant difference among the performances of the three groups on Task 2 [F(_2,79)= 60.29, p< .000, η²= 0.47] (see Table 4). The eta squared suggests a large effect size. Thus, the magnitude of the observed difference was substantial.

Multiple comparisons of means shed further light on the observed differences. As illustrated in Table 5, Post-hoc comparisons by using Tukey HSD test demonstrated that the mean score for the HTM group (Mean = 58.41, SD= 7.09) was significantly higher than both the MTM group (Mean = 50.15, SD=9.17) and the LTM group (Mean = 38.44, SD=6.69) at p= 0.000. Moreover, the mean score for the MTM group was significantly higher than that of the LTM group at p= 0.000. This means that there were significant statistical differences between all the groups with the MTM group outdoing the LTM group, and the HTM group outdoing both of them.

Table 4: One-Way ANOVA for Task 2

Table 5: Task 2 Multiple Comparisons

Qualitative Data

After the completion of data analysis, four major themes emerged which are presented in the following section. These themes represent the differences between LTM and HTM learners. Excerpts from respondents’ statements are chosen to exemplify the themes and bring them to life. Pseudonyms are used instead of individuals’ real names to guarantee their anonymity.

Positive Task Appraisal

Learners’ perception of the task seemed to be a significant element differentiating the HTM and LTM groups. Being a sparse concept in statements of the latter group, task appraisal proved to be a crucial component of the former groups’ behavior. Motivated learners confirmed to have had a positive view of the task in terms of its relevance, functional value and necessity. Mina, one of the motivated learners, commented:

[The definite article] is an essential grammatical point, yet hard to capture. I have always had a tough time trying to get to grips with it. However, you need to know it well, otherwise… your speaking and writing will be sloppy and flawed. So, when I learned that we were to work on the [definite article] I had my own reasons to attend carefully.

Interestingly, four of the motivated learners emphasized that they had the intention to learn and internalize the rules of the definite article and were already looking for such opportunities. This is illustrated in what Rastin said:

My teachers and friends believe that I am a fluent speaker and a good writer. Nevertheless, I have had a mixed feeling… there has been an imbalanced development. My fluency and communicative abilities have grown, but some delicate grammatical nuances, especially the… fail and frustrate me. I was aware that… I needed practice. So, I did it with full devotion.

Peer Effect

Peers were reported to exert remarkable motivational influence during pair or group work. There were reports that energetic and enthusiastic learners inspired their partners by imparting excitement and enjoyment. Conversely, a few respondents believed that their partners’ lack of diligence created an air of indifference or reluctance that caused their initial motivation and enthusiasm to subside. As an illustration, Parisa, from the LTM group, asserted that:

I can’t say that I was working with determination. Nevertheless, I … had been concentrating on the materials. After I got paired with Mahsa, … she seemed not to care about the task and showed me a funny drawing on his book cover… that put an end to my concentration … instead we began muffling our giggles. I lost the track. Now I can say that I just forgot about the whole activity.

Hooman, an HTM learner, experienced peer effect differently. He described his teamwork with an earnest classmate who takes work seriously:

A good partner is a must in language learning. I always join Khosrau in group activities because of his disciplined manner. During our group work… He started to draw a grid … or table to classify the words... when you see his organized work, you think if you … don’t work the same way, you are going to miss something critical and fall badly behind.

Effort and Extra Work

The third major theme was about expending effort and spending time on practicing the newly learnt materials. All the motivated learners affirmed that doing several rounds of practice and engaging in extra exercises had been an indispensable part of their encounter with the new lesson. They maintained that the in-class part of the task was merely a starting point which led to further independent and persistent practice to rehearse the rules and automatize their application. None of the LTM group learners mentioned any out-of-class self-practice. Shirin, an HTM learner, narrated her persistent and autonomous practice:

Habitually, when something is valuable and important, I keep on [learning] even after the class is finished, especially when there are rules or regulations that must be committed to memory. Three times, I referred to my notes… from the first task and composed several… sentences and phrases on my own to give myself further exercise.

Likewise, Shadi talked about his diligent engagement with new information and mentioned that he had practiced it in other contexts:

I did quite well on Sunday [i.e., on Task 2]. After the first encounter in the classroom, I reviewed the rules in… English Grammar in Use and did the related exercises. Also, I visited two language learning websites that offered free grammar practice, found the related exercises… and worked with them. Thus, I had a fresh and alert mind on Task 2.

Deploying Self-regulation Strategies

In motivated learners’ statements, frequent examples of self-regulation strategies showed up. Their accounts of their learning behavior indicated deployment of self-assessment, self-reflection, and some learning strategies (e.g., note-taking, rehearsal, and organization). The following quotes are quite revealing in this regard. For example, Hooman, a motivated learner, asserted that:

I made a simple plan to learn the principles… First, I summarized the rules, classified them, and did some exercise at home by using a self-study website. After every five or six [items], I checked the answers and evaluated myself. This procedure always works for me.

LTM learners, too, showed understanding of self-regulation. Nonetheless, they seemed not to apply such strategies in this study. In response to a question about their self-managed learning behavior, one of them called Kayvan used such strategies in dealing with learning tasks he liked:

I invest time and arrange responsible work… not with grammar or such staff… for example, I listen to English songs. I work on two songs every week, listen several times, focus on words, and look up the unknown words and sometimes search the lyrics on the internet. Songs are my favorite part of learning English… and I guess, even for learning grammar, songs are better than grammar lessons.

DISCUSSION

The first aim of the present study was to investigate the potential impact of L2 task motivation on learners’ transfer of knowledge of English definite article from one task to another. Analysis of the quantitative data by using ANOVA demonstrated that task motivation significantly affects the transfer of learning across tasks. L2 learners with higher measures of task motivation appeared to outdo their less motivated counterparts in transferring the grammatical rules of the definite article from the first task, where they were exposed to the input, to the second task, where they were required to apply the rules. Though no other study has been observed in the literature to investigate the link between task motivation and transfer of learning, the finding can find support in a number of studies that ascribe positive learning outcomes and effective task performance to higher levels of task motivation (Azkarai & Kopinska, 2020; Dörnyei, 2019; Dörnyei & Kormos, 2000; Haskell, 2001; Kormos & Dörnyei, 2004; Kormos & Préfontaine, 2017; Masrom et al., 2015; Pugh & Bergin, 2006; Wang & Li, 2019).

The second research question sought to see what specific dispositions or learning behaviors differentiate L2 learners with robust task motivation from those who have a low level of task motivation. Analysis of the qualitative data suggested that there were major differences between them. It was revealed that highly motivated learners demonstrate special learning habits tendencies that pinpoint how task motivation exerts influence over performance, engagement, and consequently, transfer of learning to another task. Also, the results of the qualitative data analysis corroborate and complement the quantitative results. The qualitative and quantitative results converge in that they substantiate the crucial role of task motivation in task performance and transfer of learning. The interview data showed that high task motivation has a robust capacity to influenceL2 learners’ learning behavior and task engagement, leading to evident and conspicuous outcomes which are discussed in the following paragraphs.

The main purpose of the focus group interviews was to find out the mechanisms by which high or low task motivation affect L2 learners’ learning behavior and transfer. The first theme that partially characterizes the issue is positive task appraisal i.e., viewing the task in a positive light. Learners who have strong task motivation seemed to evaluate the task as relevant, beneficial, instructive and necessary, and therefore, approach it with heightened attitude and interest. This explanation can be supported by the findings of Poupore (2014) and Lambert et al. (2017) who contend that L2 learners’ appraisal of task relevance and interest is associated with task motivation. Moreover, it has been confirmed that learners’ perception of task meaningfulness, usefulness and relevance increases their task motivation (Billing, 2007; Green, 2015; James, 2012).

The second theme emerging out of the data was peer effect which pertains to social dimensions of task motivation. The interviewees stressed the role of partners or peers in their rising or falling task motivation levels. It is suggested that hardworking and motivated interlocutors engender similar moods in their partners. This finding is consistent with Kormos and Dörnyei (2004) and Poupore’s (2016) contentions that task motivation is co-constructed through cooperation in dyads or groups. Other researchers, similarly, bore witness to the significance of peer effect in enhancing motivational dispositions and reducing negative emotions (Kopinska & Azkarai, 2020; Leaming, 2021). Furthermore, the conclusions of Guo et al. (2020) can corroborate the present findings. They found that inter-individual variability in task motivation at the group level can result in great fluctuations in individual learners’ task motivation and willingness to communicate.

It appears that effort and extra work characterize the learning behavior of highly motivated learners. Obviously, HTM learners invested more energy for practicing the learning materials and doing extra self-assigned exercises. It is a known fact that motivated individuals work harder to achieve their goals. Likewise, analyzing learners’ accounts in the current study revealed that frequent practice and persistent engagement constitute a distinctive behavioral characteristic of highly motivated learners. The literature on transfer of learning is replete with supporting evidence. A large number of studies confirm that quantity of practice is a decisive factor in transfer of learning (e.g., Billing, 2007; James, 2018; Saito, 2013). Apart from amount of practice, L2 learners’ reports contained evidence of their attempts to practice the definite article use in multiple settings by drawing on different sources. This observation accords with several other studies which have suggested that the effectiveness of practice is amplified if conducted in a variety of contexts and situations (Chang & Millet, 2016; Larsen-Freeman, 2013; Okuno & Hardison, 2016; Shintani & Ellis, 2014).

Another crucial concept that was identified in the participants’ narrations pertains to using self-regulation strategies. As the results indicate, learners with either high or low task motivation were adept and skillful at applying various self-regulation strategies to their learning activities. However, it seems that they use their inventory of strategies when they are motivated and interested in the task at hand. Thus, the deployment of strategies may be a direct consequence of task motivation. It can be contended that task motivation exercises its power over learning and transfer through activating or eliciting self-regulation strategies that facilitate learning and improve learning efficiency (Oxford, 2017). Additionally, self-regulation is actively controlled and operated by individual learners. Therefore, they may enhance concentration and engagement which further contributes to deeper understanding, and subsequently, to transfer of knowledge. These interpretations can find support in some previous studies (e.g., Billing, 2007; Dörnyei, 2002; Dörnyei & Tseng, 2009).

In contrast to the existing literature on transfer of learning, a few concepts were almost absent in the data. First, unlike the findings of Billing (2007) and Saito (2013), there was no mention of improved attention and noticing made by task motivation. This can be attributed to the fact that the consciousness-raising task is inherently form-focused; hence, task motivation could have not stimulated further attention or awareness of form than the task did. Moreover, contrary to suggestions of Benson (2016) and Spada et al. (2014), the present study did not identify any reference to task similarities and differences as facilitating or inhibiting transfer of learning. A probable justification for this discrepancy may be found in the fact that only two tasks, which bore structural resemblances, were used in the study. Therefore, the participants did not have any opportunity to compare the potentially variant impacts of task similarity or difference.

CONCLUSION AND IMPLICATIONS

This study was an attempt to investigate the effects of task motivation on L2 learners’ transfer of learning across tasks. Taken together, the results indicate that task motivation significantly affects transfer of learning among L2 learners. Probably, the influence of peers and group dynamics along with a positive appraisal of tasks give rise to task motivation, and then, heightened task motivation may bring about increased effort and engagement, and more efficient activation of self-regulation strategies.

This combination of findings provides some implications for teachers. First, teachers and planners should mind learners’ perception of task value and usefulness. This can be accomplished on two levels: planning courses and lessons to deliver materials when learners are most prepared, and building a rudimentary foundation for lesson presentations so to stimulate learners’ interest and self-relevant questions about the task at hand. Furthermore, teachers are advised to take grouping schemes more seriously for the crucial role of peer effect. Keeping fixed pairs and groups of learners might function to the detriment of some students. Trying interchangeable combinations is thus recommended to teachers.

The present study faced a number of limitations that could be addressed by other interested researchers. For example, future research should include more tasks in a single study especially to see the long-term impact of task motivation on transfer. Additionally, the present study focused on individual tasks only, whereas TBLT is meant to promote communication. Thus, it is suggested that collaborative task motivation be studied so that social impacts of group dynamics and peer effect can be dealt with in action. Also, in this study, learners’ task motivation on the second task was not measured. Future researchers may want to measure learners’ motivation on all given tasks to pave the way for analyzing how motivation on the second task can influence transfer of learning especially when tasks are of different kinds (e.g., form-focused or meaning-focused). Finally, as engagement and effort proved effective factors arising from task motivation, researchers should scrutinize task engagement as the concrete manifestation of task motivation and consider actual behavioral representation of this construct.

Disclosure statement

No potential conflict of interest was reported by the authors.

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