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Figure 6. Mean values across factors for continuing (cont.) and discontinuing (disc.) students and quitters Standard deviation values suggest that continuing students generally responded more similarly to the five-point Likert scale items belonging to the three factors than discontinuing students and quitters (see Figure 7). In particular, discontinuing students indicated a larger range of responses in E, factor at the meso level and the the second semester, especially in regard to the influence of the LI SCE factor at the macro level on their motivation. For the purpose of this article, the data analysis is structured in three levels which correspond to three factors as presented in previous sections. Differences between students who stated they would continue learning an L2 from one semester (S) to the other (continuing students) (7 = 593 in $1 and 167 in S2) and students who stated they would discontinue learning an L2 from one semester to the other (discontinuing students) (7 = 126 in S1 and 39 in S2 respectively) are analyzed. In addition, responses provided by 85 students who did not enroll in an L2 course in the second semester but completed a section of the second questionnaire are also analyzed. The latter are here labelled “quitters,” drawing upon Martin et al.’s (2016) study distinction among (a) committed students, (b) doubters, and (c) quitters. No data regarding quitters from semester two to semester three are collected. Means of students’ responses to the five-point Likert scale items of each factor show that continuing students were more motivated on average by all three factors than discontinuing students, since their mean values were on average close to 2 (in a range of five points, 1 stands for strongly agree and 5 for strongly disagree; see Figure 6). Quitters were less demotivated than discontinuing students at the micro and meso levels of analysis in semester one only, as quitters were not enrolled in semester two.

Figure 6 Mean values across factors for continuing (cont.) and discontinuing (disc.) students and quitters Standard deviation values suggest that continuing students generally responded more similarly to the five-point Likert scale items belonging to the three factors than discontinuing students and quitters (see Figure 7). In particular, discontinuing students indicated a larger range of responses in E, factor at the meso level and the the second semester, especially in regard to the influence of the LI SCE factor at the macro level on their motivation. For the purpose of this article, the data analysis is structured in three levels which correspond to three factors as presented in previous sections. Differences between students who stated they would continue learning an L2 from one semester (S) to the other (continuing students) (7 = 593 in $1 and 167 in S2) and students who stated they would discontinue learning an L2 from one semester to the other (discontinuing students) (7 = 126 in S1 and 39 in S2 respectively) are analyzed. In addition, responses provided by 85 students who did not enroll in an L2 course in the second semester but completed a section of the second questionnaire are also analyzed. The latter are here labelled “quitters,” drawing upon Martin et al.’s (2016) study distinction among (a) committed students, (b) doubters, and (c) quitters. No data regarding quitters from semester two to semester three are collected. Means of students’ responses to the five-point Likert scale items of each factor show that continuing students were more motivated on average by all three factors than discontinuing students, since their mean values were on average close to 2 (in a range of five points, 1 stands for strongly agree and 5 for strongly disagree; see Figure 6). Quitters were less demotivated than discontinuing students at the micro and meso levels of analysis in semester one only, as quitters were not enrolled in semester two.

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Figure. 1. Types and number of data for Chowsie, K, and Rhonda
Figure. 1. Types and number of data for Chowsie, K, and Rhonda
Storying is a Literacy
Storying is a Literacy
Figure 1. The three-level model
Figure 1. The three-level model
Figure 2. Categories of demotivators belonging to the PLL factor Intrinsic Demotivation encompasses students’ lack of interest in learning an L2 over time (Ushioda, 1998). Sakai and Kikuchi (2009) define this category of demotivators as “learners’ loss of interest” given to the lack of relevance of the L2 in the learner’s life. A lack of desire to be in contact with L2-speaking people and be immersed in an L2-speaking environment was labelled as Integrative Demotivation, drawing upon prior studies on motivation (e.g., Gardner, 2001).
Figure 2. Categories of demotivators belonging to the PLL factor Intrinsic Demotivation encompasses students’ lack of interest in learning an L2 over time (Ushioda, 1998). Sakai and Kikuchi (2009) define this category of demotivators as “learners’ loss of interest” given to the lack of relevance of the L2 in the learner’s life. A lack of desire to be in contact with L2-speaking people and be immersed in an L2-speaking environment was labelled as Integrative Demotivation, drawing upon prior studies on motivation (e.g., Gardner, 2001).
Teacher-specific Demotivational Components are related to the teaching style and approach of instructors, and the relationship between teacher and students (cf. Kikuchi, 2019; Yadav & BaniAta, 2013). Teachers’ personalities and character also appeared to demotivate students in previous studies (Song & Kim, 2017). Course-specific Demotivational Components include the material chosen for a course, topics covered in class and the class environment (cf. Thorner & Kikuchi, 2020). Sakai and Kikuchi (2009) discovered four out of six categories related to the class environment, material, topics and approaches dominating an L2 class. Figure 3. Categories of demotivators belonging to the LE factor
Teacher-specific Demotivational Components are related to the teaching style and approach of instructors, and the relationship between teacher and students (cf. Kikuchi, 2019; Yadav & BaniAta, 2013). Teachers’ personalities and character also appeared to demotivate students in previous studies (Song & Kim, 2017). Course-specific Demotivational Components include the material chosen for a course, topics covered in class and the class environment (cf. Thorner & Kikuchi, 2020). Sakai and Kikuchi (2009) discovered four out of six categories related to the class environment, material, topics and approaches dominating an L2 class. Figure 3. Categories of demotivators belonging to the LE factor
Figure 4. Categories of demotivators belonging to the SCE factor Instrumental Demotivation is caused by the scarce utility of an L2 in terms of job opportunities according to students’ goals and career preferences. In Australia, the increasing pressure on students to learn Asian languages, given economic and diplomatic ties between Asian countries and Australia (cf. Baldwin, 2019; Lo Bianco, 2016; Mascitelli & O’Mahony, 2014), discourages some students from learning European languages. Such a prominent need to improve the learning of Asian languages was reiterated by the national government’s Australia in the Asian Century White Paper (Commonwealth of Australia, 2012).
Figure 4. Categories of demotivators belonging to the SCE factor Instrumental Demotivation is caused by the scarce utility of an L2 in terms of job opportunities according to students’ goals and career preferences. In Australia, the increasing pressure on students to learn Asian languages, given economic and diplomatic ties between Asian countries and Australia (cf. Baldwin, 2019; Lo Bianco, 2016; Mascitelli & O’Mahony, 2014), discourages some students from learning European languages. Such a prominent need to improve the learning of Asian languages was reiterated by the national government’s Australia in the Asian Century White Paper (Commonwealth of Australia, 2012).
Table 2. ANOVA results across three student cohorts for the three factors in the first semester In the second semester, an independent sample’s Atest detected much smaller differences between continuing and discontinuing survey students’ average responses, which were statistically significant only for the PLL factor at the micro level and the LE factor at the meso level. No quantitative data about quitters were collected in the second semester (see Table 3).
Table 2. ANOVA results across three student cohorts for the three factors in the first semester In the second semester, an independent sample’s Atest detected much smaller differences between continuing and discontinuing survey students’ average responses, which were statistically significant only for the PLL factor at the micro level and the LE factor at the meso level. No quantitative data about quitters were collected in the second semester (see Table 3).
Figure 7. Mean values across factors for continuing and discontinuing students and quitters The analysis of variance (ANOVA) was conducted to estimate the differences between average responses provided by the three student cohorts. In the first semester, data confirm that the mean differences across the three cohorts for all three factors were statistically significant (see Table 2).
Figure 7. Mean values across factors for continuing and discontinuing students and quitters The analysis of variance (ANOVA) was conducted to estimate the differences between average responses provided by the three student cohorts. In the first semester, data confirm that the mean differences across the three cohorts for all three factors were statistically significant (see Table 2).
Table 3. t-test results across two student cohorts for the three factors in the second semester The PLL factor at the micro level was the most motivating factor for continuing students in both semesters under consideration, where low means represent high levels of students’ motivation (M = 2.06 and 2.02 respectively). Discontinuing students were not particularly motivated by this factor, since the mean values are not very low in both semesters (M = 2.43 and 2.32 respectively). This suggests that more discontinuing students than continuing students experienced negative psychological reactions and/or poor performances during their L2 learning process. Such a result was confirmed by higher standard deviations for discontinuing students than for continuing students in both semesters (SD = 0.53 and 0.55 and 0.46 and 0.46 respectively). More quitters were demotivated by the PLL, given the mean of 2.24 and the higher standard deviation compared to continuing students. Such noticeable differences were validated by the highest F value for this factor in the first
Table 3. t-test results across two student cohorts for the three factors in the second semester The PLL factor at the micro level was the most motivating factor for continuing students in both semesters under consideration, where low means represent high levels of students’ motivation (M = 2.06 and 2.02 respectively). Discontinuing students were not particularly motivated by this factor, since the mean values are not very low in both semesters (M = 2.43 and 2.32 respectively). This suggests that more discontinuing students than continuing students experienced negative psychological reactions and/or poor performances during their L2 learning process. Such a result was confirmed by higher standard deviations for discontinuing students than for continuing students in both semesters (SD = 0.53 and 0.55 and 0.46 and 0.46 respectively). More quitters were demotivated by the PLL, given the mean of 2.24 and the higher standard deviation compared to continuing students. Such noticeable differences were validated by the highest F value for this factor in the first
Table 4. Pearson correlations between the three factors in the first and second semesters
Table 4. Pearson correlations between the three factors in the first and second semesters
Within the PLL, demotivated survey participants and interviewees underlined that the L2 learning process was considered a very hard task. Discontinuers and quitters confirmed that learning an L2 takes a lot of time and effort. Some of them encountered more difficulties in memorizing words and concepts than continuing students, which confirms quantitative data analysis outcomes. Poor L2 performances, both in and out of the class environment, discouraged all three categories of students, who originally deemed a European L2 learning path an easy task. Hence, negative emotions hindered students who doubted their aptitude for learning L2s and received negative marks. Stress, anxiety, fear of failing, and discouragement were reported. These emotions emerged more often in the second phase of the data collection, which appeared to be more difficult than in the first semester, especially for discontinuing students. Consequently, the latter started to dislike the challenge stemming from an L2 learning process. Figure 8. Most frequently recurring themes for the PLL factor at the micro level
Within the PLL, demotivated survey participants and interviewees underlined that the L2 learning process was considered a very hard task. Discontinuers and quitters confirmed that learning an L2 takes a lot of time and effort. Some of them encountered more difficulties in memorizing words and concepts than continuing students, which confirms quantitative data analysis outcomes. Poor L2 performances, both in and out of the class environment, discouraged all three categories of students, who originally deemed a European L2 learning path an easy task. Hence, negative emotions hindered students who doubted their aptitude for learning L2s and received negative marks. Stress, anxiety, fear of failing, and discouragement were reported. These emotions emerged more often in the second phase of the data collection, which appeared to be more difficult than in the first semester, especially for discontinuing students. Consequently, the latter started to dislike the challenge stemming from an L2 learning process. Figure 8. Most frequently recurring themes for the PLL factor at the micro level
At the meso level, most of the themes’ recurrences were linked to Course-specific Demotivational Components. Research participants considered the pace of their classes too rapid and the amount of material studied too large. Demotivated students, mainly discontinuing students and quitters, could not keep up with the L2 course program. These demotivators became more influential in the second semester when the course workload increased and students encountered higher levels of difficulty, as observed at the micro level of analysis. As a result, they obtained lower marks, which triggered test anxiety. The choice of materials and topics was a demotivator when students were not interested in the content delivered during L2 classes and expected to improve their L2 oral skills to use in daily-life settings. Figure 9. Most frequently recurring themes for the LE factor at the meso level
At the meso level, most of the themes’ recurrences were linked to Course-specific Demotivational Components. Research participants considered the pace of their classes too rapid and the amount of material studied too large. Demotivated students, mainly discontinuing students and quitters, could not keep up with the L2 course program. These demotivators became more influential in the second semester when the course workload increased and students encountered higher levels of difficulty, as observed at the micro level of analysis. As a result, they obtained lower marks, which triggered test anxiety. The choice of materials and topics was a demotivator when students were not interested in the content delivered during L2 classes and expected to improve their L2 oral skills to use in daily-life settings. Figure 9. Most frequently recurring themes for the LE factor at the meso level
Figure 10. Most frequently recurring themes for the SCE factor at the macro level
Figure 10. Most frequently recurring themes for the SCE factor at the macro level
Screen plot extracted by the principal component analysis
Screen plot extracted by the principal component analysis
Table 1. An Overview of Selected Phrases with Transliterations The Editor’s Translingual Practices
Table 1. An Overview of Selected Phrases with Transliterations The Editor’s Translingual Practices
Table 2. Positive Comments to the Translingual Practices*
Table 2. Positive Comments to the Translingual Practices*
Responses to the Editor’s Mistakes: Requests Table 2 showed how the joy of reading creative transliteration and feeling proud of their own wtiting system were shared among some users. However, these positive comments disappeared as users got accustomed to the practice and pointed out mistakes. Table 3 shows comments of a few users who were disturbed by a lack of fluency and the editor’s mistakes, which invoked their requests for clarification or correction. Some suggested alternatives. Among the comments that disapproved of exaggerating sounds or mixing two alphabets, the author of comment 11 questioned the efficacy of the transliteration, saying that it was harder to read than the English phrase. Comment 12 showed how the lack of reading fluency in the transliterations made users question translingual practices or, more significantly, distrust the editor’s information (13, 16, 18 below). Even more directly, comments 13 and 14 called for adherence to traditional transcription symbols, demonstrating their knowledge of inguistics, which was recontextualizing to claim an advantageous footing for their claim. Some users (13, 14, 16), following their general understanding of communication and rhetorical norms, mitigated their challenges with such courteous comments as I don’t want to blame you, please, might be better and the use of ellipses. Many comments were not mitigated to the same extent, which was not uncommon in online contexts, less concerned about a risk of losing or threatening face. A user’s persuasive intent for improvement was shown in comment 14, I¢ 7s not the first time, implying that the editor repeatedly made mistakes across posts. Instead of letting the mistakes go or reprimanding the editor, the user asked for accurate information (also comments 13, 16, 17). These comments suggested that there were users who were returning to the posts, acknowledging the value of the information but bothered by
Responses to the Editor’s Mistakes: Requests Table 2 showed how the joy of reading creative transliteration and feeling proud of their own wtiting system were shared among some users. However, these positive comments disappeared as users got accustomed to the practice and pointed out mistakes. Table 3 shows comments of a few users who were disturbed by a lack of fluency and the editor’s mistakes, which invoked their requests for clarification or correction. Some suggested alternatives. Among the comments that disapproved of exaggerating sounds or mixing two alphabets, the author of comment 11 questioned the efficacy of the transliteration, saying that it was harder to read than the English phrase. Comment 12 showed how the lack of reading fluency in the transliterations made users question translingual practices or, more significantly, distrust the editor’s information (13, 16, 18 below). Even more directly, comments 13 and 14 called for adherence to traditional transcription symbols, demonstrating their knowledge of inguistics, which was recontextualizing to claim an advantageous footing for their claim. Some users (13, 14, 16), following their general understanding of communication and rhetorical norms, mitigated their challenges with such courteous comments as I don’t want to blame you, please, might be better and the use of ellipses. Many comments were not mitigated to the same extent, which was not uncommon in online contexts, less concerned about a risk of losing or threatening face. A user’s persuasive intent for improvement was shown in comment 14, I¢ 7s not the first time, implying that the editor repeatedly made mistakes across posts. Instead of letting the mistakes go or reprimanding the editor, the user asked for accurate information (also comments 13, 16, 17). These comments suggested that there were users who were returning to the posts, acknowledging the value of the information but bothered by
Table 4. Comments to Negotiate Table 4 shows less common comments that corrected the editor’s mistakes. Three types of errors that users addressed were (a) pronunciation errors (17, 18); (b) faulty expressions (19-22); and (c) culturally inappropriate expressions (23-27). In these comments, users employed various interactional and recontextualization strategies to support their corrections, involving active negotiation of their footings from the initial one-directional knowledge flow. Such active attempts at negotiation were possible due to the lack of hierarchy in the online space. The most common strategy was to express intimate knowledge of the target culture(s), and less frequently to refer to knowledge of English linguistics (phonetics and grammar) or familiarity with accepted transcribing methods. Strategies used to negotiate showed users’ lack of translingual attitudes toward diversity, based on the
Table 4. Comments to Negotiate Table 4 shows less common comments that corrected the editor’s mistakes. Three types of errors that users addressed were (a) pronunciation errors (17, 18); (b) faulty expressions (19-22); and (c) culturally inappropriate expressions (23-27). In these comments, users employed various interactional and recontextualization strategies to support their corrections, involving active negotiation of their footings from the initial one-directional knowledge flow. Such active attempts at negotiation were possible due to the lack of hierarchy in the online space. The most common strategy was to express intimate knowledge of the target culture(s), and less frequently to refer to knowledge of English linguistics (phonetics and grammar) or familiarity with accepted transcribing methods. Strategies used to negotiate showed users’ lack of translingual attitudes toward diversity, based on the
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