Emergency remote teaching adaptation of the anonymous multi–mediated writing model

Abstract

Covid-19 related transfer of instruction to digital platforms has heightened the complications involved in teaching writing, including assessment problems regarding the increased risk of academic misconduct incidents. This study aimed at scrutinizing how the revised anonymous multi–mediated writing model fits emergency remote teaching (ERT), ensuring the promotion of academic integrity. The revised model was implemented throughout a two–semester freshmen “Writing Skills” course via a mixed methods triangulation research design in the ELT department of a university in Türkiye. Quantitative data came from writing assignments and peer feedback analyses, whereas qualitative data were retrieved through reflection papers and interviews. Students' ERT scores were compared to pre-Covid face-to-face (F2F) learning scores, revealing no significant differences; confirming that students’ performances were similar in F2F or ERT without any increase in academic misconduct in ERT. The AMMW model worked well in ERT by enabling scaffolding through asymmetrical and symmetrical asynchronous online feedback, with the integration of a rubric as the learning tool. Qualitative findings revealed the limitations of online teaching, especially regarding the importance of teacher–student(s) interaction. As an anthology of L2 writing practice amid the Covid-19 outbreak, this study may help other academics to cope with cases resembling those presented here.

1. Introduction

The move of instruction to digital platforms due to Covid-19 first seemed like a massive transformation of education from face-to-face (F2F) classes to distance education. Yet this was indeed an implementation of “emergency remote teaching” (ERT) that did not follow the principles of distance or online education. This practice demanded immediate action incorporating digitalization of the course, including the design of remote classes and assessment practices. Although the obstacles involved in teaching remote classes might be tolerated to some extent, problems with formative assessment were worse, since the uncertainty increased the risk of academic misconduct incidents.

This unprecedented situation magnified the complications involved in teaching writing. Pre-Covid era literature reported the importance of scaffolding learners through systematic teacher1 or peer feedback. However, unless planned carefully, feedback implementation may not work well. Besides, increased plagiarism concerns in online teaching, although regarded as a research myth in the pre-Covid era (Eaton, 2018), amplified complaints in teaching writing. The “anonymous multi–mediated writing (AMMW) model” (Razı, 2016, Razı, 2017) was developed with the hope of providing a solution to the problems involved in exchanging feedback in writing classes, in addition to instituting a culture of academic integrity.

The AMMW model uses the writing process approach (e.g., Curry & Hewings, 2003; Wette, 2015) as a foundation by following steps such as prewriting, planning, drafting, and revision originating from the teacher, peer, and self–feedback before final submission on a digital platform. The main incentive in developing the model was motivating students to complete their writing assignments by receiving feedback from multiple sources, including teacher, peers, and self–feedback during the writing process so that they think carefully at each step to increase creativity (Razı, 2017). After receiving teacher feedback on their earlier drafts, students submit revised versions. Each revised assignment is matched with three peers; one from each of the previously labelled “good,” “moderate” and “weak” categories describing peers’ proficiency in writing to assure a balanced delivery of asymmetrical and symmetrical feedback (Hanjani & Li, 2014) and peers exchange feedback anonymously to ensure more critical feedback (Lu & Bol, 2007); otherwise, they might be reluctant to criticize their peers/friends. After receiving feedback from their peers, students revise and resubmit their papers. Before the final submission, students self–review their papers. Assessment rubric is used as a learning tool to provide any type of feedback throughout the process. Considering its innovativeness, the AMMW model was awarded the “Turnitin Global Innovation Award 2015,” then listed as good practice for preventing academic misconduct by the “Australian Government Tertiary Education Quality and Standards Agency” (Bretag, 2017).

The AMMW model enables anonymous asynchronous online feedback in a digital environment to encourage a balanced distribution of asymmetrical and symmetrical feedback. The former refers to feedback exchange among learners who differ in their language skills, whereas the latter addresses exchanging feedback between learners who possess similar language skills (Hanjani & Li, 2014). I made some minor modifications to the model as my response to the “disrupted teaching” (Gao & Zhang, 2020, p. 12) so that it worked smoothly in ERT. Gao and Zhang's study highlights that carefully planned remote teaching may contribute to the objectivity of assessment. Considering this warning, I mainly aimed to establish academic integrity, especially avoiding plagiarism. Gao and Zhang carefully described the worries of EFL teachers at the very beginning of the pandemic. I was not an exception and consulted other scholars, who were in a similar situation, via online events (e.g., Plagiarism across Europe and Beyond Conference and SSLWebinars) and realized that the issues were global; and brainstorming sessions at these meetings helped in revision of the model. At SSLWebinars Matsuda (2020), for example, highlighted the contribution of peer feedback. The model already addressed Matsuda's expectations by enabling a combination of peer and tutor feedback to encourage learners to become more autonomous with the development of self–regulation skills. The model also aimed to enable a more reliable assessment of learners' progress in writing by paying attention to their performance in providing peer feedback.

Although there are studies reporting on peer feedback exchange practices during Covid-19 (e.g., Xu, 2021), to my knowledge, there are no studies comparing students’ achievements in ERT writing to F2F writing. Considering the digitalization of teaching, the present mixed–methods triangulation research design (Creswell & Plano Clark, 2007) as exploratory action research revisited the AMMW model and reported the outcomes of implementing the model in an ERT setting “Writing Skills” course for freshmen, relating both to controlled and free academic writing tasks to check how the revised AMMW model fitted the ERT setting and worked in practice. The following three RQs were formed.

RQ1

How did the learners perform in the Writing Skills course in ERT compared to F2F teaching?

RQ2

What was the learners' perception of the AMMW model implementation in ERT?

RQ3

How frequent were the suspicious cases violating academic integrity standards in ERT and F2F?

2. Literature review

2.1. Feedback in writing

As an essential tool (Hyland & Hyland, 2006), feedback helps individuals in EAP (English for Academic Purposes) writing classes as an important component in the teaching of academic writing (Morton et al., 2015). “Feedback […] includes comments/commentary/response as well as corrective feedback (CF), which focuses on formal aspects of learners' language and is provided with the intent to improve linguistic accuracy” (Ene & Upton, 2018, pp. 1–2), whereby learners get the opportunity to notice their errors and correct them (Bitchener & Knoch, 2010). Feedback might be “summative”— referring to assessment practices—or “formative,” aiming at improving learners' writing skills by giving “descriptive, diagnostic information” (Lee, 2020, p. 2). The relevant literature takes a positive view of the pedagogical merits of feedback (Shvidko, 2020). Crosthwaite et al. (2020, p. 4) provide a taxonomy of the various types of feedback, firstly direct feedback, where learners are presented with the correct form, and secondly indirect feedback that informs learners about errors, if they exist, by locating them on paper. Thirdly, metalinguistic feedback is codes or linguistic expressions signifying errors. Fourthly, they discriminate unfocused feedback, where learners receive feedback on all errors, from focused feedback, which deals with just a few error types. Finally, electronic feedback is addressed, where teachers use hyperlinks to indicate errors. Out of this taxonomy, teachers tend to prefer focused feedback to avoid cognitive overload (Cheng & Zhang, 2021).

There is evidence that teacher feedback assists with scaffolding student writing (e.g., Zhang, 2013) but despite its pivotal role in writing classes, researchers still question its contribution to the development of writing skills (Hyland & Hyland, 2006). Considering technological developments, we can provide more effective feedback (K. Hyland, 2003) and have more options to blend feedback in our syllabus digitally. The choices are greater for digital feedback as can be generated by humans or electronic devices automatically and delivered either synchronously or asynchronously (Ene & Upton, 2018).

One way of implementing feedback is delivering low–stakes assignments. These provide several benefits by increasing students' awareness about their achievements. Frequently delivered low–stakes assignments enable students to see what they are doing well and what needs to be improved; thus, they encourage them to interact with others to refine their papers. Yu (2020) warns teachers to better understand their students’ needs so that they can maximize the profits of feedback. Such draft assignments can also benefit from simpler grading, such as “pass/fail” or “complete/incomplete” (Matsuda, 2020). Teachers may use a rubric as a learning tool in low–stakes assignments by asking students to exchange self or peer feedback; thus, students are more involved in the evaluation of their own learning process.

Peer feedback, based on the social constructionist theory of learning (Hanjani & Li, 2014), is where peers exchange feedback with others to accomplish a writing task. Peers are expected to spot awkward facets in each other's assignments (Ruecker, 2011). Such a practice should contribute to the development of writing skills for both those who give or receive feedback (Berggren, 2015; Fan & Xu, 2020; Vinagre and Muñoz, 2015; H. Zhao, 2014), despite some potential problems (Berggren, 2015; Ruecker, 2011; H. Zhao, 2014). Before implementation of peer feedback, learners' preparedness is essential (Ferris, 2003) because it changes the roles of the source of information in the classroom (Berggren, 2015). However, unless planned carefully, such interaction may lead students to be involved in academic misconduct, such as “collusion”—illegal collaboration with peers, or “contract cheating”—buying assignments from essay mills. Therefore, teachers should clearly explain the aim of each draft assignment by drawing a clear line between collaboration and collusion, and then provide opportunities for scaffolding through feedback. In addition to contributing to the development of writing skills, exchanging peer feedback in the AMMW model in a legitimate way under the control of the teacher is expected to prevent students from being involved in misconduct such as collusion.

2.2. AMMW model

The model benefits from several other theories apart from the sociocultural theory, providing the basis for Vygotsky's (1978) zone of proximal development (ZPD) and scaffolding (Bruner, 1978) with the integration of feedback. ZPD highlights the importance of interacting with others who are more knowledgeable. Boggs (2019) revealed a significant contribution of scaffolding to the improvement of writing skills; yet, she interprets the results with caution, as they were not valid for all participants. However, completing a peer review task should help learners turn input into intake, as illustrated in Schmidt’s (1990) noticing hypothesis. As the AMMW model encourages the completion of multiple peers' papers, this provides an opportunity to repeat the transformation from input to intake several times.

ZPD encourages matching learners of various proficiency levels with each other so that the weaker ones might be scaffolded by more knowledgeable ones and they become autonomous learners (Lim & Renandya, 2020). Receiving feedback from multiple peers requires careful analysis due to probable contradictions among the reviewers. This is an advantage of the AMMW model compared to direct corrective feedback exchange, in which learners do not necessarily approach feedback critically (e.g., Ferris, 1995; Shintani & Ellis, 2015). Thus, the model encourages the student–author to be more careful when taking necessary actions regarding the revision; and the development of metacognitive skills as the learners receive feedback from several peers, thereby calling for substantial analysis (Razı, 2016, 2017). When learners are responsible for the management of a task, then they are involved in metacognitive experiences (Abbott, 2006), which requires the involvement of higher order thinking skills alongside self–regulation skills, contributing to students becoming autonomous learners (Barfield, 2016; F. Hyland, 2000), because peer feedback contributes to the development of form–focused cognitive processing and results in the employment of metacognitive revising strategies (Nishino & Atkinson, 2015).

Instruction by the writing teacher as well as information from the relevant literature are considered as “input”; exposure of a receptive skill in the “input hypothesis” (Krashen, 1985), whereas students' draft essays are regarded as “output.” Processed input is also called “intake” (Sharwood Smith, 1993), since writing an essay requires production. In the AMMW model, students approach the received feedback from several peers in a critical manner by checking its relevance and accuracy; thus, addressing and processing feedback critically and revising it accordingly can be regarded as “uptake” in accordance with Lyster and Ranta (1997). This is considered as “learned language” by Sharwood Smith (1993). Processing feedback and acting on it requires high–level analysis, as illustrated in Dekeyser's (2007) skill acquisition theory, by enabling declarative knowledge to become procedural knowledge, resulting in an autonomous learner. The AMMW model contributes learners to become autonomous, which is considered as an essential step in the prevention of academic misconduct such as plagiarism since plagiarizers, writing in a L2/FL, regard language barrier as a reason to be involved in academic misconduct (Razı, 2015b).

The AMMW model enables a smooth transition from teacher to peer feedback, as suggested by Hanjani (2016), either in controlled or free academic writing; therefore, it prepares learners “for more participatory forms of feedback” (p. 296). For any feedback exchange, the model encourages meeting five principles, namely, “providing positive comments, avoiding appropriating student writing, responding as a reader, involving students in the revision process, and minimizing student frustration” in addressing interpersonal teacher feedback (Shvidko, 2020, p. 35). Therefore, the model is expected to encourage the development of Howard and Jamieson's (2021) “rhetorical intertextuality,” defined as “a way of labelling and gesturing toward an approach to source use that is dialogic, generative, and attentive to the interactive relations between writers, their sources, and their audiences” (p. 388). The AMMW model allows room to establish good rapport between teacher–learners and learners–learners, as suggested by Wette (2014).

2.3. Promoting academic integrity in writing

Establishing a culture of academic integrity to counter infringements of academic standards has received more attention recently because of increased concerns about plagiarism, mainly due to the availability of an enormous range of digital sources. Prevention of plagiarism requires cooperation among stakeholders, including teachers and students; therefore, understanding the reasons behind plagiarism and developing appropriate pedagogical approaches contributes more than endorsing sanctions. Plagiarism can be broadly categorized into two groups, accidental and deliberate, depending on the intention and motivation of students. Accidental plagiarism requires more pedagogical support before making “a simple accusation of plagiarism” (Pennycook, 1996, p. 226). Howard's (1992) “patchwriting” relating to unacceptable paraphrasing by changing only a few words could be an example of this. However, infringements involving deliberate plagiarism may be considered as an ethical issue (Pecorari, 2015), and usually associated with sanctions in addition to pedagogical support. Bearing this in mind, “collusion,” illegal agreements with peers, or “contract cheating” with third parties for the completion of an assignment are all regarded as examples of deliberate plagiarism. Yet, students may change over time and develop proper academic writing skills after being accused of plagiarism (Pecorari, 2015). Therefore, writing classes play an essential role in establishing a culture of academic integrity, with the onus borne by writing teachers.

Practising citation skills may even be insufficient in preventing plagiarism since the development of such skills is associated with other factors such as language proficiency, identity, and background knowledge (Chandrasoma et al., 2004). Writing classes should incorporate reliable, transparent, and consistent teaching and assessment methods that encourage the growth of academic integrity by considering probable socio–cultural differences (e.g., Hu & Lei, 2016; Wheeler, 2009) among students. This helps institutions to develop more effective policies to promote academic integrity by going beyond the boundaries of detective or reactive strategies. By integrating reliable, transparent, and consistent teaching and assessment methods, the AMMW model seems as a good fit for teachers in search of pedagogic, preventive, and proactive academic integrity policies.

Technological developments have been accused of triggering plagiarism due to the ease of copying and pasting on digital platforms; however, these high–tech advances may also help students to develop better writing skills and for teachers to detect and prevent plagiarism. There are now digital tools available for students to manage citations and organize knowledge so that they minimize the risk of accidental plagiarism. Text–matching software may assist teachers not only in detecting plagiarism but preventing it (Razı, 2017); although it must be said that some text–matching systems attract students’ attention by promising free so–called “plagiarism reports” and channelling them to third–party essay–mills. Therefore, teachers need to plan carefully before implementing such tools. The AMMW model gives enough room for students to practise their similarity report interpretation skills enabling the use text–matching software as a learning tool.

3. Methods

3.1. Setting

I collected the data in a two–semester Writing Skills course in the ELT department of a state university located in western Türkiye. In the fall semester, both in F2F and ERT, students submitted three written assignments on topics I had assigned, accompanied by relevant referencing sources that I had distributed which I call as “controlled writing” practices. The main aim of these relatively short controlled assignments was to give students an opportunity to focus all their attention on developing their academic writing skills as quickly as possible without being worried about topic selection and finding relevant reliable sources to support their claims. Otherwise, asking them to find a writing topic and relevant sources would make the task too complicated and time–consuming for the time being. Upon the completion of these three controlled assignments, students were supposed to be ready to choose their individual writing topic and find reliable sources for referencing in the spring semester, which this time I call as “free writing” practices. In both semesters, they received feedback from various sources in line with the AMMW model. Turnitin was used as a digital environment given that it provided opportunities for feedback exchange along with text–matching similarity reports for the detection of possible plagiarism. I implemented the AMMW model online both in F2F and ERT; however, after Covid-19 swept through the country, F2F classes were replaced with ERT. Therefore, the students enrolled in Writing Skills 2 during the spring semester of 2019/20 academic year and those attending in Writing Skills 1 during the fall semester of the 2020/21 academic year were instructed in ERT. Their achievements in giving feedback and writing assignments were compared to those who received the course as F2F, before the Covid-19 outbreak, in the 2018/19 spring and 2019/20 fall semesters to reveal whether ERT makes any difference in their achievements.

3.2. Participants

As Covid-19 affected the type of instruction, converted from F2F to ERT by March 2020, ERT implementation of the model started first with Writing Skills 2 (free writing) during the spring semester of the 2019/20 academic session. Considering the pandemic circumstances, I used the convenient sampling method. I tested ERT implementation of the AMMW model on controlled academic writing practices with Writing Skills 1 during the fall semester of the 2020/21 academic session. Therefore, the model was tested with different participants in each semester. Students enrolled in the Writing Skills course for the related four semesters constituted the participants as illustrated in Fig. 1 . Participants’ consents were taken before the data collection via reflection papers and interviews. Seventy–five students submitted “Reflection 1” after receiving audio–recorded teacher feedback on their first drafts, 63 students submitted “Reflection 2” after giving peer feedback, and 65 students submitted “Reflection 3” after submitting their final drafts. Three students were invited for follow–up interview sessions by considering gender representation and their achievements either in F2F or ERT.

Fig. 1.

Distribution of participants.

3.3. Instruments

3.3.1. Fundamentals of the academic writing rubric (FAWR)

I used the Fundamentals of Academic Writing Rubric (FAWR, see Appendix A for the rubric) as a simplified version of the transparent academic writing rubric (TAWR) (Razı, 2015a). There are 20 items in FAWR categorized under five groups, namely, introduction, citation, academic writing, idea presentation, and mechanics. Each item carried 5 points (total score 100). The students used FAWR to exchange peer feedback for their controlled academic writing assignments.

3.3.2. TAWR

TAWR (Razı, 2015a, see Appendix B for the rubric) was developed to score students’ review papers for free writing practice. There were 50 items covering various aspects of review papers. These were organized within five categories, namely, introduction, citations, academic writing, idea presentation, and mechanics. Each item carried 2 points (total score 100), with three labels: “poor,” “acceptable,” and “excellent.” Construct validity, covering discriminant and convergent validity, was already established by means of a multi–trait multi–method matrix for TAWR. The students used TAWR to exchange peer feedback for their free academic writing assignment.

3.4. Scoring peer feedback

I used the five categories in FAWR and TAWR as a basis to score peer feedback. There were 20 items in FAWR and I assigned 5 points to any student who managed to provide at least one valid feedback for that item. Valid feedback refers either to a problematic issue that should be addressed by the student–author or a good practice sample as encouragement. This was a precaution to encourage students to provide feedback on different aspects of the paper; otherwise, some students might find it easier to give feedback only on grammatical accuracy. As there were 50 items in TAWR, I expected a contribution to at least four items under each of the five categories. Any student who managed to provide correct constructive feedback for 20 items—four items in each category—received 100 points.

3.5. Interview sessions

I invited three students for follow–up interview sessions online on Microsoft Teams by considering gender representation and their achievements either in F2F or ERT regarding the grades in our institutional grading system that were AA (90–100, excellent), BA (85–89, very good), BB (80–84, good), CB (70–79, satisfactory), CC (60–69, satisfactory), DC (55–59, conditional pass), DD (50–54, conditional pass), FD (40–49, fail), FF (0–39, fail), and DS (dropout). The first interviewee (ERT1) was a female student who received AA for F2F Writing Skills 1 and AA for ERT Writing Skills 2. The second interviewee was a repeating male student (ERT2) who failed F2F Writing Skills 2 the previous year but managed to receive AA in ERT. The third interviewee (ERT3) was a male student who passed F2F Writing Skills 1 but failed ERT Writing Skills 2. By doing so, I was able to ensure homogeneity by interviewing a student who performed similar in F2F and ERT in addition to students who performed either better or worse in ERT.

3.6. Inter–rater reliability

I have been teaching writing skills in the same department for more than 15 years and scored all assignments myself using the aforementioned rubrics at the end of each semester. Since there were several writing and peer tasks in this study, this should have helped to eliminate measurement error. Yet, to avoid any rater–related measurement error relating to the quantitative data, I asked an independent rater to score 10% of the peer tasks and writing assignments. After scoring the writing assignments and peer tasks myself, I identified samples from students at various levels. I selected 50 students (n _Fall–ERT = 11, n _Fall–F2F = 12, n _Spring–ERT = 15, n _Spring–F2F = 13) from the four semesters and trained the rater to use FAWR and TAWR. To maximize intra–rater consistency, I asked the rater to finish scoring them in a week. Kendall's tau-b correlation revealed strong, positive significant correlations between the two raters' scores on peer feedback (τ _b = 0.90, p < .001) and writing assignments (τ _b = 0.93, p < .001); thus, inter–rater reliability was established for the quantitative data.

The rater also helped avoid any bias in the investigation of plagiarism cases. By using sample assignments from previous years, I trained the researcher to interpret text–matching software similarity reports, with specific emphasis to plagiarism detection. Then, I shared similarity reports (n = 60) assignments constituting of plagiarized (n = 41) and plagiarism–free assignments (n = 19). The rater first discriminated plagiarized assignments from plagiarism–free ones. The results revealed 100% match with my labels. Then, the rater discriminated accidental and deliberate plagiarism cases and once again the results revealed 100% match with my categorization.

An independent researcher reviewed initial codes and categories to ensure inter-coder reliability for the qualitative data.

3.7. Procedures for data collection

I collected the data throughout a two–semester freshmen Writing Skills course, each lasting for 16 weeks including exam period. The Council of Higher Education in Türkiye made the decision to replace classroom education with ERT by March 2020. Therefore, in the spring semester of 2020/21 academic year I delivered the Writing Skills 2 course as ERT. The students who were enrolled on that course had been instructed in Writing Skills 1 as F2F in the fall semester. In ERT, I delivered 2-h synchronous lectures weekly via Microsoft Teams. Quantitative data were gathered from analyzing writing assignments and peer feedback, whereas qualitative data were retrieved through reflection papers and interview sessions.

In Writing Skills 1 (see Appendix C for the syllabus), students practised in–text citation rules to write safely by blending other sources (Pecorari, 2013) and avoiding either accidental or deliberate plagiarism. They benefited from text–matching tool similarity reports for the draft assignments which ensured the use of such tools for pedagogical aims rather than detecting academic misconduct (Bretag, 2016; Davies & Howard, 2016).

Throughout the semester, students submitted three 700–word writing assignments on topics I assigned by citing the sources I provided (see Appendix D for assignment instructions). I encouraged them to find alternative outline options considering the drawbacks of 5–paragraph essays (Caplan & Johns, 2019). To control their in–text citation practice skills, I asked them to blend only the sources that I provided. I noted problematic issues and good examples in the first drafts and used these anonymous samples to give students conference feedback before distributing the papers for peer review. I preferred conference feedback (Yu, 2020) since the writing tasks were conducted in a controlled manner. Such a practice could be considered as a precaution to ensure a gradual shift from teacher to peer feedback (Hanjani, 2016).

For each assignment, they exchanged feedback by using FAWR with three peers that I assigned; then they revised their papers considering the feedback and resubmitted them. For each assignment, they had one week to submit the first draft, another week to exchange peer feedback, and a third week to revise and resubmit. All revised assignments were submitted both with and without tracking changes on MS Word documents. They used FAWR as a checklist, which enabled self–feedback before final submission. Writing assignments had a weight of 60% and I scored them by means of FAWR. I also scored the quality of the peer feedback they provided, which counted for 40% of their grades. Fig. 2 illustrates the procedure followed for controlled writing tasks in the fall semester.

Fig. 2.

Controlled writing process throughout fall semester: Writing skills 1.

In Writing Skills 2 (see Appendix E for the syllabus), I asked students to write an ELT–related paper of their choice, approximately 2000 words in length, excluding the abstract and references (see Appendix F for assignment instructions). They provided peer feedback by using TAWR on three papers that I assigned and submitted revision assignments. Their assignments counted for 60% and were scored through TAWR. I also scored the quality of the peer feedback they provided, contributing 40% of their grades. I provided feedback on their earlier drafts on three occasions. The draft submission was mandatory as a precaution to prevent possible collusion and/or contract cheating. Their earlier drafts were subject to pass/fail scoring; those who could not receive two pass scores out of three were unable to submit the final version. Earlier drafts were low–stakes assignments enabling students to see what they were doing well and what needed to be improved with the help of formative feedback without worrying about being graded.

They submitted their outlines and received their first audio–recorded teacher feedback. Then, they added approximately 15 (∓ 3) sources to their outlines by compiling a prospective reference list and received second audio–recorded teacher feedback. After the first draft submission, they received the third teacher feedback, this time on MS Teams at individual meeting sessions. They also submitted a reflection paper as a response to my feedback.

I introduced TAWR as a tool for exchanging peer feedback with guidelines to exchange effective feedback and modelled how to do it using TAWR. I asked them to provide positive, clear, and concise feedback. They made suggestions as to how their peers could improve clarity, concision and the overall quality of the paper without editing the paper for English but highlighting problematic issues.

After they submitted their second drafts, they were assigned three peer papers to exchange feedback with. After completing this stage, they submitted a reflection paper judging the peer feedback exchange process. They listed what they had changed after receiving peer feedback, and gave their responses about the peer feedback they did not take into consideration. They submitted the final version of their assignment by using TAWR as a checklist functioning as self–feedback and uploaded digital versions of sources they used as a precaution against contract cheating.

In conclusion, such a procedure, as illustrated in Fig. 3 , is in line with the principles of Wette's (2015) process approach as it encourages learner creativity; Cumming et al.’s (2018) expectations from a writing class to practise skills such as searching for relevant information and note–taking; and Rogerson's (2017) assessment process to detect academic misconduct.

Fig. 3.

Free writing process throughout spring semester: Writing skills 2.

3.7.1. Revisions of the AMMW model

Transforming education into the ERT context increased security concerns in assessment when checking whether the students met the course outcomes or not. I made a few modifications in the model evoked by ideas discussed at the SSLWebinars organized by Matsuda (2020) to ensure that it fitted the expectations of the ERT situation.

The first modification was about the tutorial sessions. I made the attendance to these sessions compulsory. Before the ERT, I could meet my students in person, either in lectures or tutorials. As an institutional regulation, attendance to lectures was optional in ERT, and I wanted to maintain my contact with them by means of compulsory tutorial sessions. I provided teacher feedback in ERT by delivering 3-min audio–recorded feedback for draft outlines and annotated outlines. I met them individually on MS Teams to provide feedback on their first drafts and questioned them to check whether any collusion and/or contract cheating involvement had taken place. In ERT, their earlier drafts were subject to pass/fail scoring to ensure that they kept working throughout the semester with integrity.

The second modification was asking students to submit revision assignments both with and without track changes on MS Word documents. This enabled me to identify all revisions made on the paper and assess the improvements (or vice versa) easily. This was also an opportunity for the students to recognize their own developments with their papers.

The third modification was asking students to upload all e-sources they had used to write their papers into a drive folder as a PDF document. In the case of sources not being available as PDF, they uploaded other proof of their efforts, such as screenshots of the relevant pages. This encouraged them to review the related literature thoroughly while discouraging them from creating fictitious references.

A final modification was related to the distribution of peers. As Turnitin disabled a previous feature of designating teacher–assigned multiple reviewers, the peers were randomly assigned. However, this still enables scaffolding through asymmetrical and symmetrical asynchronous online feedback.

3.8. Procedures for data analysis

The study included both quantitative and qualitative data. I triangulated the quantitative data from assignment and peer scores with the qualitative data derived from reflection papers and follow–up interview sessions.

Descriptive statistics, Mann–Whitney U tests, and Chi Square test of independence were run for the quantitative data using SPSS Version 25. I used a non–parametric test since the data violated the Kurtosis value to ensure normal distribution both for controlled and free writing cases.

The qualitative data from reflection papers were analysed thematically by combining inductive and deductive approaches for coding. In the first round, descriptive coding was used with reference to the items of TAWR. In the second round, I turned these codes into themes. I sent these initial codes and themes to an independent researcher for review. We used deductive thematic analysis to re–examine them and reached a consensus. Finally, these codes and themes were used to construct the final narrative.

The themes from the reflection papers were used to construct interview questions. I followed an edited transcription procedure for the scripts. After transcribing, I sent them back to the interviewees for confirmation. I used deductive content analysis to triangulate reflection papers and interviews for a more detailed description of the ERT process.

4. Results

4.1. ERT performance compared to F2F

To answer RQ1, I used scores from both controlled and free writing. I compared free writing ERT scores in the 2020/21 fall semester to F2F scores in the 2019/20 fall semester and also compared ERT scores in 2019/20 spring semester to F2F scores in 2018/19 spring semester.

Considering the controlled writing skills, the results on peer review scores of ERT (Mdn = 76.50) and F2F (Mdn = 77.00) did not indicate significant differences, U(n _ERT = 116, n _F2F = 115) = 6360.00, z = −0.61, p > .05. The results on the writing scores of ERT (Mdn = 83.50) and F2F (Mdn = 79.00) did not indicate significant differences either, U(n _ERT = 116, n _F2F = 115) = 5932.00, z = −1.45, p > .05.

I also ran a Chi–Square test of independence to check whether the students’ grades (peer feedback score 40% + writing task score 60%) either in the ERT or F2F Writing Skills 1 course differed significantly. The initial Chi–Square test of independence results revealed an expected count less than 5 in 8 cells (40.00%); thus, I merged DC with DD as conditional pass, and FD with FF as fail. The results on recoded values indicated that the p value was greater than the significance level [X ²(7) = 3.84, p > .05]; thus, I concluded that there were no significant differences between ERT and F2F scores for the controlled writing task. Descriptive results are presented in Fig. 4 .

Fig. 4.

Comparison of final grades in controlled academic writing.

Considering the free writing skills, the results on peer review scores of ERT (Mdn = 72.00) and F2F (Mdn = 65.00) did not indicate significant differences, U(n _ERT = 149, n _F2F = 136) = 10,112.50, z = −0.03, p > .05. The results for the writing scores of ERT (Mdn = 80.00) and F2F (Mdn = 71.00) also indicated no significant differences, U(n _ERT = 149, n _F2F = 136) = 9626.50, z = −0.74, p > .05.

Once again, I ran Chi Square test of independence to check whether the students’ grades differentiated significantly. As there were 8 cells (40.00%) with an expected count less than 5, I merged DC with DD, and FD with FF. The results on recoded values indicated that the p value was greater than the significance level [X ²(7) = 7.41, p > .05]; indicating no significant differences between ERT and F2F scores for the free writing task. Descriptive results are presented in Fig. 5 .

Fig. 5.

Comparison of final grades in free academic writing.

Considering the nature of writing classes and several factors involved in writing achievement, it would be naïve to expect the same results in different semesters with different groups of students. Yet, in reality, the aforementioned inferential statistics revealed no significant differences, providing evidence of similarity in the grades both in ERT or F2F. In addition, it is important to note the similarity regarding dropout students, as there were 8 (out of 115) in the F2F controlled writing class and 12 (out of 116) in ERT, whereas there were 37 (out of 136) in the F2F free writing class and 43 (out of 149) in ERT.

4.2. Perception towards ERT implementation

To answer RQ2, I used the students’ reflection papers submitted on a voluntary basis on three occasions during the 2019/20 spring semester, in addition to interviews.

In Reflection 1, students explained how they revised their papers with regard to teacher feedback and how this feedback affected them. In Reflection 2, this time they clarified how they provided the feedback. Finally, in Reflection 3 they expressed their experiences in peer and self–feedback besides ERT practices. Table 1 illustrates the themes from reflection papers.

Table 1.

Recurring themes from reflection papers.

Categories	Themes	f
Teacher feedback	Most useful	75
	Flow of ideas	62
	Motivational	61
	Academic writing	49
	Mechanics	46
	Sources	39
	Concluding remarks	20
Peer feedback	Giving feedback useful	62
	Increased awareness	55
	Mechanics	50
	Referencing	49
	Academic writing	35
	Giving feedback difficult	33
	Unclear feedback	31
	Useless feedback	27
	Punctuation	26
	Idea presentation	24
	Rubric useful	14
Self–feedback	Mechanics	61
	Flow of ideas	54
	Idea connection	48
	Rubric useful	35
ERT	Interaction problems	74
	Effective	55
	Recordings useful	42
	Prefer F2F	32
	Anxiety	21
	Technological issues	11
	Demotivation	8

Four categories were formed to group recurring themes from the reflection papers presenting students’ perceptions on teacher feedback, peer feedback, self–feedback, and ERT.

Students regarded teacher feedback as the most useful one and confirmed that it helped them develop several aspects of their papers including idea flow, academic writing rules, mechanics, source selection, concluding statements in addition to providing motivational support. The following interview excerpt confirms the effectiveness of teacher feedback.

Audio–recorded teacher feedback and teacher feedback sessions on Teams helped a lot and motived me to continue my work. [ERT1]

Peer feedback, especially giving it by means of the rubric despite its difficulty, was found useful. Students thought that exchanging peer feedback increased their awareness and indicated its contribution to mechanics, referencing, academic writing, punctuation, and idea presentation. However, students also complained about unclear and useless feedback they received. The following interview excerpts provide some more insights about peer feedback exchange.

I received some misleading feedback and checked them from reference sources to confirm. [ERT1]

I realized there were some good samples in my friends' papers, which inspired me to develop my own ideas. [ERT2]

Students reflected that self–feedback contributed them to improve mechanics, idea flow, and idea connection. Again, they acknowledged the implementation of rubric as a checklist. The following interview excerpts confirm the contribution of self–feedback.

The rubric was extremely useful for realizing my own weaknesses and mistakes. [ERT1]

The skills that I developed while providing peer feedback later helped me spot my previously overlooked mistakes while self–reviewing [ERT2].

The responses indicated that students found ERT instruction effective; however, they still preferred to have the course as F2F, due to ease of communication and interaction. Despite increased anxiety and technological issues, students highlighted the contribution of being able to watch the lecture recordings. For example, as a repeating student ERT2 attributed his success in ERT to lecture recordings as seen in the excerpt below. Yet, sustaining motivation in ERT was regarded as more challenging compared to F2F. This was the main barrier for ERT3 preventing him to complete his assignment in ERT. The following excerpts from the interview sessions provide evidence for these claims.

I find F2F instruction better because we can interact with the teacher more effectively. [ERT1]

It was difficult to take notes in F2F lectures. ERT made it easy with access to lecture recordings afterwards. [ERT2]

Although I found ERT lectures effective, I stopped working on my assignment to control my anxiety. [ERT3]

4.3. Suspicious cases in F2F and ERT

To answer RQ3, I checked the frequency for suspicious academic misconduct cases in the 2018/19 spring, 2019/20 fall and spring, and 2020/21 fall semesters. In Fig. 6, I discriminated the cases in controlled practice from the ones in free writing practice. I also separated accidental plagiarism incidents—weak citation practices and patchwriting—from deliberate ones, which were lengthy expressions directly copied from other sources without being accredited, as well as evidence of collusion. The number of incidents were similar to each other, regardless of being in F2F or ERT.

Fig. 6.

Comparison of Plagiarism Incidents: F2F vs ERT.

5. Discussion

I revisited the AMMW model and reported the outcomes of implementing the model on an ERT Writing Skills course for freshmen, both in controlled and free academic writing tasks. Considering my overall experience of ERT as a teacher, in general it went well as students’ outputs were similar to pre-Covid era, including academic integrity threats. RQ results confirm this claim.

With regard to RQ1, investigating students' achievements in both controlled and free ERT academic writing practices, I compared their peer feedback and writing assignment scores in ERT to the corresponding pre-Covid F2F scores and found no significant differences. RQ1 findings confirmed that students' peer review and writing performances, regardless of being controlled or free in the Writing Skills course, were similar either in F2F or ERT. This provided evidence of assessment practices in ERT meeting learning outcomes; otherwise, unsystematic and ill–assessment practices in online teaching would result in failure (Pu & Xu, 2021). Covid-19 increased both students’ workload and anxiety (Yang, Chen, & Chen, 2021), resulting in demotivation. The results of this study indicated motivational concerns with some students; however, the vast majority of them managed to complete their tasks, despite all the challenges.

RQ2 aimed to reveal how they managed process writing, including feedback exchange in ERT using the AMMW model. The themes from reflection papers indicated students’ preference for teacher feedback over peer feedback. Teacher feedback also seemed to meet the principles that were highlighted by Shvidko (2020) for encouraging students. Despite the inclusion of some useless feedback, peer feedback was also deemed to be useful. This contradicts the findings of Xu (2021), where the contribution of peer feedback was very limited during Covid-19. Although giving feedback was regarded as a challenging process in the present study, students highlighted its contribution as increasing their metacognitive awareness; thus, the students were successful in adapting themselves to Covid-19 norms, in line with the findings of Yang, Mak, and Yuan (2021). Despite the drawbacks of ERT due to lack of socialization and interaction (Gao & Zhang, 2020), for students and teachers, the results indicated that it was beneficial for students to have access to lecture recordings for future reference. Considering the limited interaction, as I was teaching a large group of students, the students did not turn on their cameras to avoid system lock up because of large data transmission. Thus, during the lectures, not only did students suffer from limited interaction but also, I did.

RQ2 results also indicated that some students had complaints regarding useless and unclear feedback that they had received. Although this might be due to a lack of skills either in writing or critiquing, the reason might be because other students may resist criticizing their friends' work while providing feedback (Liou & Peng, 2009), thereby preventing them from highlighting problematic aspects. They may also be prejudiced about their friends’ language proficiency (Ruecker, 2011), in addition to “race, native language, gender, and nationality” (Cote, 2014, p. 69). The relevant literature reports several samples of low–quality peer feedback due to either reluctance or language incapability, resulting in students misleading each other. Thus, asking weak learners to provide feedback for more proficient ones probably results in low–quality feedback.

However, reception of asynchronous online feedback from three peers ensures a balanced distribution of “asymmetrical” and “symmetrical” feedback. Considering Diab's (2010) claims of peers' inability to spot all contentious issues while exchanging feedback, the concept behind the distribution of asymmetrical and symmetrical feedback seems reasonable. In this way, the AMMW model promises to minimize the probable detrimental impact of misleading peer feedback, while securing homogeneous distribution of effective peer feedback.

The AMMW model supports exchanging peer feedback anonymously to enable more useful feedback by removing bias, as recommended (e.g., Cote, 2014; Hosack, 2003; Johnson, 2001; Liou & Peng, 2009; Lu & Bol, 2007; Robinson, 2002; Y. Zhao, 1998). Although both reviewers and student–authors are kept anonymous, the confidentiality of reviewer identity is more essential. It is no surprise for teachers to encounter student–reviewers who can predict the peer–authors’ identity, especially in small classes; however, this does not spoil the smooth running of the model as long as the reviewer identities are kept confidential. Unfortunately, anonymity may also encourage some reviewers to provide negative feedback (Lu & Bol, 2007). It is therefore essential to guide students to provide constructive feedback and be polite to each other while criticizing their work.

The AMMW model bridges the interaction between review skills and writing skills by encouraging teachers to assign peer feedback scores depending on feedback quality, besides assigning the writing assignment scores, in line with the principles of Assessment for Learning (AfL; Hattie & Timperley, 2007; Mak & Lee, 2014) and eclecticism in assessment (Bayaga & Wadesango, 2013). Relatively, the AMMW model also stimulates the use of the rubric not only as an assessment tool but also as a learning tool to exchange feedback, as suggested by Fyfe and Vella (2012). By doing so—as opposed to Cheng and Zhang's (2021) expectation of focused feedback to avoid cognitive overload—learners do not merely focus on grammatical accuracy while providing feedback (Storch, 2007); otherwise, exchanging peer feedback might be problematical since learners may pay more attention to form than idea presentation (Vinagre & Muñoz, 2015). Although Lee (2020) recommends not to score feedback, my experience tells me to do just the opposite in order to encourage students to do their best when providing feedback, and to appreciate their efforts. In conclusion, all this interaction seems to contribute to the development of Howard and Jamieson's (2021) “rhetorical intertextuality” as it encourages learners “to build the web of meanings” (p. 396) by going beyond “mechanical intertextuality,” simple instruction of referencing styles, and “ethical intertextuality,” commitment to the fundamental values of academic integrity.

Finally, RQ3 did reveal a similar number of misconduct cases in F2F and ERT, supporting Eaton (2018) who considers increased plagiarism in online teaching as a myth. The Writing Skills course, guided the principles of the AMMW model, adopted a proactive policy aiming to prevent any academic misconduct before it occurred, rather than stick to detective or reactive policies, mainly focusing on sanctions. The students had access to text–matching software similarity reports and I trained them to interpret these reports. The AMMW model was successful in preventing plagiarism in student assignments in a F2F setting and the findings of this study indicated that the model reached this goal in the ERT setting as well.

Results confirm there are still cases of plagiarism in both F2F and ERT settings, both accidental and deliberate. My 15 years of teaching writing experience has taught me that an expectation of “0” plagiarism in student assignments is just a utopia, especially with freshmen who have almost no background in academic writing. As an accidental form of plagiarism, Howard's (1992) patchwriting requires more pedagogical support (Pennycook, 1996), and indeed might be regarded as an indicator of developing good academic writing skills from the very first assignments.

RQ3 confirmed that plagiarism can be prevented to a great extent by following a proactive academic integrity policy in ERT. Students may change after being accused of plagiarism and develop proper academic writing skills (Pecorari, 2015). As a final remark, the prevention of plagiarism cannot be left to text–matching software. Such tools may help teachers detect plagiarism to some extent; however, they should be implemented in the curricula with a pedagogical purpose. Simply depending on ratios provided in similarity reports, such as the use of Turnitin similarity percentage as an indicator of plagiarism, must be avoided.

6. Conclusion and implications

To conclude, the AMMW model worked well in ERT by enabling scaffolding through asynchronous online feedback coming from the teacher, peer, and self; encouraging a balanced distribution of asymmetrical and symmetrical feedback with the integration of the rubric as a learning tool. There was no increase in academic misconduct in ERT instruction utilizing the AMMW model.

This study, as an anthology of EAP writing practice amid the Covid-19 outbreak, may help other teachers that resemble the cases presented here by providing evidence for the smooth running of the model in ERT, for teaching either controlled or free academic writing skills. However, this does not necessarily mean that F2F instruction should be replaced with a form of online learning. Qualitative results revealed the limitations of online teaching, especially regarding the importance of teacher–student(s) interaction. Although students managed to complete their tasks in ERT and enjoyed this experience to some extent, they would far more appreciate social interaction with their teachers and peers. In ERT, students need greater empathy from their teachers to boost their motivation; therefore, teachers should avoid harsh comments that would discourage students from completing their tasks.

Teacher feedback plays a critical role in the development of writing skills. It may not be possible or practical for teachers to deliver frequent individual feedback in large classes. Under such circumstances, conference feedback might be useful. In addition to instructing students how to give feedback, teachers also need to know how to address peer feedback, considering the possible contradictions from various peers. The development of such skills should be given importance, especially for freshmen. Self–review might be beneficial if implemented, especially proceeding the exchange of peer feedback.

It is worth considering the limitations of this exploratory action research as it is limited in scope since I mainly aimed to revisit the AMMW model in an ERT setting. It did not investigate the detailed aspects of improvements in student papers after the feedback sessions, since this was beyond the scope of this study. My results were reported from the ELT department, which may differ from other populations. In addition, as the students in this study enrolled in the Writing Skills course largely under lockdown, replications are needed to see how the AMMW model works in a flipped classroom, blended learning and remote teaching in the post-Covid era.

All in all, I did my best as a teacher to train my students during Covid-19, which turned out to be an achievable goal with the help of professional networks when necessary. Students’ achievement in writing by means of the implementation of the revised AMMW model in ERT highlights the sound theoretical background behind the model and its flexibility towards unprecedented challenges. While contributing to the institution of a culture of academic integrity, the framework of the model also provides ideas for standalone teaching and assessment practices to teachers to maximize learning both in F2F and online classes relating to exchanging various type of feedback even in large classes, using rubric as a learning tool, assessing writing, implementing text–matching software, preventing plagiarism, and developing academic writing skills from the very beginning until students become independent writers.

Author statement

I confirm that the manuscript has not been published previously and it is not under consideration for publication elsewhere. I have approved the contents of this paper and have agreed to the System's submission policies. I obtained “Ethical Approval” from the “Anonymous” University Ethical Committee and its publication is approved by the Dean's Office of the Faculty of Education. If accepted, it will not be published elsewhere in the same form, in English or in any other language, including electronically without the written consent of the copyright-holder. I understand that the publisher may use Crossref Similarity Check to retrieve a similarity report of my manuscript. I verify that throughout the research, I ensured ethical standards and procedures for data collection and publishing the results which were in line with the General Data Protection Regulation of the European Union. I confirm that I kept self-citations at a minimum by citing four of my earlier publications to avoid citation manipulation.

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Data availability

The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.

Declaration of competing interest

I state that I was involved in organization of conferences and summer schools which received funding from Turnitin and also received “Turnitin Global Innovation Awards” in 2015. I confirm that this research did not receive any external funding and the aforementioned facts did not influence the research in any phase.

Appendix A. Fundamentals of Academic Writing Rubric (FAWR)

Questions	Rating
Introduction
1. Relevance of the topic	0	1	2	3	4	5
2. Introduction of the topic and the problematic situation	0	1	2	3	4	5
3. Introduction of the thesis statement	0	1	2	3	4	5
Citation
4. Use of paraphrases	0	1	2	3	4	5
5. Use of quotations	0	1	2	3	4	5
6. Avoidance of expressions that need citation	0	1	2	3	4	5
Academic Writing
7. Level of formality	0	1	2	3	4	5
8. Effective use of passive voice	0	1	2	3	4	5
9. Complexity of sentences	0	1	2	3	4	5
10. Use of abbreviations	0	1	2	3	4	5
Idea Presentation
11. Structure of the essay	0	1	2	3	4	5
12. Main idea and thesis statement relevance	0	1	2	3	4	5
13. Conclusions and main idea relevance	0	1	2	3	4	5
14. Development of paragraphs	0	1	2	3	4	5
15. Effectiveness of concluding remarks	0	1	2	3	4	5
16. Flow of ideas including unity and coherence	0	1	2	3	4	5
Mechanics
17. Grammatical accuracy	0	1	2	3	4	5
18. Spelling accuracy	0	1	2	3	4	5
19. Punctuation accuracy	0	1	2	3	4	5
20. Avoidance of short forms/contractions	0	1	2	3	4	5

Appendix B. TAWR (Razı, 2015)

Evaluation criteria		Poor	Acceptable	Excellent
INTRODUCTION
1	Topic selection	0	1	2
2	Narrowing down the topic	0	1	2
3	Title of the paper	0	1	2
4	Headings and subheadings	0	1	2
5	Abstract	0	1	2
6	Key words	0	1	2
7	Introduction to the topic	0	1	2
8	Mentioning the aims in the introduction	0	1	2
CITATION
9	Citing when necessary	0	1	2
10	Introducing paraphrases and summaries (variations in the style)	0	1	2
11	Restructuring in paraphrases/summaries	0	1	2
12	Rewording in paraphrases/summaries	0	1	2
13	Introducing quotes (variations in the style)	0	1	2
14	Use of quotations	0	1	2
15	Citing quotes appropriately	0	1	2
16	Ratio of quotes	0	1	2
17	Sufficiency of the number of cited sources	0	1	2
18	Reliability of the cited sources	0	1	2
19	Appropriate use of secondary sources	0	1	2
20	Ratio of secondary source use (abundance reduces the reliability of the author)	0	1	2
21	Appropriate use of in-text citation rules	0	1	2
22	Writing reference entries	0	1	2
23	Order of reference entries	0	1	2
24	Exact match of citations with reference entries	0	1	2
ACADEMIC WRITING
25	Focusing on the issue (omitting personal pronouns)	0	1	2
26	Appropriate use of abbreviations	0	1	2
27	Avoiding contractions (e.g., don't)	0	1	2
28	Avoiding extremeness (e.g., use of must)	0	1	2
29	Avoiding slang, jargon and clichés	0	1	2
30	Use of words with precise meaning	0	1	2
31	Use of objective language	0	1	2
32	Balanced use of passive forms	0	1	2
IDEA PRESENTATION
33	Appropriate use of markers (e.g., firstly)	0	1	2
34	Appropriate use of linking devices (e.g., however)	0	1	2
35	Flow of ideas	0	1	2
36	Paragraph unity	0	1	2
37	Overall unity	0	1	2
38	Paragraph coherence	0	1	2
39	Overall coherence	0	1	2
40	Appropriate length of paragraphs	0	1	2
41	Complexity of the sentences	0	1	2
42	Relevance of conclusions with the discussion	0	1	2
43	Drawing effective conclusions	0	1	2
MECHANICS
44	Paper format	0	1	2
45	Grammar	0	1	2
46	Spelling	0	1	2
47	Punctuation	0	1	2
48	Vocabulary selection	0	1	2
49	Use of tables and figures	0	1	2
50	Length of the paper	0	1	2

Appendix C. “Writing Skills 1” Course Syllabus: Fall Semester (Controlled Writing)

Week/Date	Discussion Topics	Main Reading	Supplementary Reading	Assignments
Week 1	Introducing course content.	–	–	–
05-09.10.2020
Week 2	Introduction to academic writing.	Razı (2011) [Chapter 1]	APA (2020)	–
12-16.10.2020			Cumming (2006)
			Oshima (1997)
Week 3	Basic steps in process writing. 5th Int. Day of Action against contract cheating.	Razı (2015a, 2015b)	Bailey (2011)	–
19-23.10.2020			Reid (2000)
Week 4	Introduction to in-text citations.	Razı (2011) [Chapter 8]	APA (2020)	Assignment 1 (First draft)
26-30.10.2020
Week 5	Presenting in-text citations.	Razı (2011) [Chapter 9)	APA (2020)	Assignment 1 (Peer review)
02-06.11.2020			Hashimoto et al. (1982)
			Zemach & Rumisek (2003)
Week 6	Familiarization of academic integrity: Avoiding plagiarism and contract cheating.	Razı (2017b)	Bailey (2011)	Assignment 1 (Final version)
09-13.11.2020			Williams & Davis (2017, pp. 67–94)
Week 7	Feedback on assignment Interpreting text-matching software similarity reports.	Razı (2017c, 2018)	–	–
16-20.11.2020
Week 8	Details with in-text citations.	Razı (2011) [Chapter 11]	APA (2020)	Assignment 2 (First draft)
23-27.11.2020
Week 9	Practising in-text citations.	Razı (2011) [Chapter 10]	APA (2020)	Assignment 2 (Peer review)
30.11-04.12.2020
Week 10	Exchanging effective peer feedback.	Razı (2016a, 2016b, 2016c, 2017a)	–	Assignment 2 (Final version)
07-11.12.2020
Week 11	Feedback on assignment.	–	–	–
14-18.12.2020
Week 12	Connecting ideas: Unity and coherence.	Razı (2011) [Chapter 6]	Bailey (2011)	Assignment 3 (First draft)
21-25.12.2020
Week 13	Online writing tools (e.g., SAS writing reviser).	–	Peachey (2017, pp. 21–32)	Assignment 3 (Peer review)
28.12-01.01.2021
Week 14	Feedback on the draft assignment.	–	–	Assignment 3 (Final version)
04-08.01.2021
11-22.01.2021	Final Exam Week	–	–	–

Appendix D. Instructions for Controlled Writing Assignments

Assignment 1

Topic: Examine the procedure of teaching English as a foreign language to young learners by giving specific emphasis to the role of using children's L1 (mother tongue) in the classroom.

Instructions:

• •Read the three sources that are about ‘teaching English to young learners’ carefully.
• •Support your discussion by using the three sources listed below in accordance with APA style in-text citation rules.
• •You are not allowed to use any other sources. Cite only the sources that I provide, nothing else.
• •Copy the following reference list and paste it to the end of your paper.

Length: 700 words (excluding the reference list); up to ± 10% is acceptable.

Deadlines:

2 November 2020, 23:59 (Submission of the first draft).

9 November 2020, 23:59 (Peer review deadline).

16 November 2020, 23:59 (Submission of the final version).

References

House, S. (1997). An introduction to teaching English to children. Richmond.

Phillips, S. (2001). Young learners (8th impression). Oxford University Press.

Puchta, H., & Williams, M. (2011). Teaching young learners to think: ELT-activities for young learner aged 6 – 12. Helbling Languages.

Assignment 2

Topic: Explain how you can encourage your learners to read in English in the classroom and/or after school. Instructions.

• •Read the three sources that are about ‘teaching EFL reading’ carefully.

• •Support your discussion by using the three sources listed below in accordance with APA in-text citation rules.

• •You are not allowed to use any other sources. Cite only the sources that I provide, nothing else.

• •Copy the following reference list and paste it to the end of your paper.

Length: 700 words (excluding the reference list); up to ± 10% is acceptable.

Deadlines:

30 November 2020, 23:59 (Submission of the first draft).

7 December 2020, 23:59 (Peer review deadline).

14 December 2020, 23:59 (Submission of the final version).

References

House, S. (1997). An introduction to teaching English to children. Richmond.

Lowes, R., & Target, F. (1998). Helping your students to learn: A guide to developing student autonomy. Richmond.

Phillips, S. (2001). Young learners (8^th impression). Oxford University Press.

Assignment 3

TopicExplain the development of listening skills in EFL young learner classes.

Instructions

• •Read the four sources carefully.

• •Support your discussion by using the four sources listed below in accordance with APA (7th ed.) in-text citation rules.

• •You are not allowed to use any other sources. Cite only the sources that I provide, nothing else.

• •Copy the following reference list and paste it to the end of your paper.

• •You must use at least one secondary-source in your paper (no more than two).

Length: 700 words (excluding the reference list); up to ± 10% is acceptable.

Deadlines:

28 December 2020–23:59 (Submission of the first draft).

4 January 2021–23:59 (Peer review deadline).

11January 2021–23:59 (Submission of the final version).

References

Harmer, J. (2001). The practice of English language teaching. Longman.

House, S. (1997). An introduction to teaching English to children. Richmond.

Linse, C. T. (2005). Practical English language teaching: Young learners. McGraw-Hill.

Lowes, R., & Target, F. (1998). Helping your students to learn: A guide to developing student autonomy. Richmond.

Appendix E. “Academic Writing Skills 2” Course Syllabus: Spring Semester (Free Writing)

Week	Topic	Related reading	Assignment
Week 1	Meeting students:	–	–
17-21.02.2020	Introducing course content.
Week 2	Topic selection and finding relevant sources.	Related academic journals and reference books	–
24-28.02.2020
Week 3	Reviewing literature.	Razı, 2011 (Chapter 12)	–
02-06.03.2020	Credibility of sources and avoiding predatory publishers.
Week 4	Outlining.	–	Submission of outline
09-13.03.2020
Week 5	Parts of an academic paper.	Razı, 2011 (Chapter 13 & 14)	–
16-20.03.2020	Headings in APA style.
Week 6	Writing a list of references.	Razı, 2011 (Chapter 15)	Submission of references included outline
23-27.03.2020
Week 7	Writing a list of references.	Razı, 2011 (Chapter 15)	–
30.03-03.04.2020
Week 8	Practising writing references.	Razı, 2011 (Chapter 16)	–
06-10.04.2020
Week 9	Drafting ideas.	–	–
13-17.04.2020
Week 10	Lecturer feedback on first draft.	–	Submission of first draft
20-24.04.2020
Week 11	Presenting tables and figures.	Razı, 2011 (Chapter 17)	–
27.04-01.05.2020
Week 12 04-08.05.2020	TAWR.	Razı, 2015	Submission of second draft
Week 13	Practising scoring by means of TAWR.	Razı, 2015	Peer review
11-15.05.2020
Week 14	Lecturer feedback on second draft.	–	–
18-22.05.2020
Final Exam Week	Submission of the final version.	–	Submission of final version
01-12.06.2020

Appendix F. Instructions for Free Writing Assignments

Instructions

For this semester, you are expected to submit a review paper constituting approximately of 2000 words, excluding abstract and references, on a topic of your preference which is dealing with any issue related to English language teaching. Throughout the semester, you will be asked to submit several draft versions for which you will receive either tutor or peer feedback. The process of submitting assignments and exchanging peer feedback will be managed through Turnitin. Submission of the draft versions is mandatory as I consider this as an opportunity to question your work considering probable collusion and/or contract cheating involvement. You will receive lecturer feedback through Turnitin on three occasions throughout the semester on your earlier drafts that are subject to pass/fail scoring. If you cannot manage to receive two pass scores out of three, you will not be allowed to submit the final draft at the end of the semester and automatically fail the course. Please remember to benefit from text-matching software similarity report for any draft submission and avoid either accidental or intentional plagiarism. You are advised to write your paper by using Microsoft Word as I will give some tips throughout the semester that are available on MS Word. If you do not have access to MS Word, I would like to remind you that you may download it to your laptop/PC by using your university email account. You may visit our university Information Technologies Unit to receive help should you experience any issues in downloading MS Word.

At the first week of this semester, I ask you to find a relevant topic to write on that might be of your interest. At this step, I recommend you to check the last four issues of prominent journals in our field, including ELT Journal, Journal of Second Language Writing, System, and TESOL Quarterly to have an inspiration about a writing topic. At the second week, I will encourage you to talk about possible writing topics so that you can exchange ideas with your peers while receiving my immediate feedback about your ideas. After the class, I will ask you to brainstorm on your topic; therefore, you reveal what you already know about the topic that you would like to write on. At the third week, I will lecture on how to review the literature and find relevant sources. We will study the criteria that might help us identify the credibility of sources and avoid predatory publishers. Bearing this in mind, I will ask you to find some essential sources from the relevant literature and prepare your outline. Although there is no restriction against Google searching on your topic, ideally you will need to review the literature by using our university library services so that you will have access to sources behind paywall. By the fourth week, you will submit your outline and receive first lecturer feedback. In your outline, you need to write the title of your paper accompanied by subheadings. You need to indicate the thesis statement for the introduction section, main ideas for each paragraph in the discussion section, and possible concluding remarks for conclusion. I attach a sample outline including references to the end of these instructions for your information. For the fifth week, I will lecture on the parts of an academic paper so that you will know where to pay attention while reading the relevant sources. For the sixth week, you will merge your citations to your outline. This will be listing the sources that you plan to use while writing your paper. You should cite approximately 15 sources that you find reliable – no less than 12, no more than 18. It might be acceptable to have a few paragraphs in your paper in which you cite a very important single source and summarize it to your readers; however, mainly you are expected to cite several sources in each paragraph, enabling discussion of the main idea from various perspectives, rather than simply summarizing a single source. You will receive the second lecturer feedback on the revised version of your outline merged with the sources that you plan to use. For the seventh, eighth, and ninth weeks, I will lecture on writing list of references and we will practise this. You will submit your first draft on the tenth week and receive the third lecturer feedback on it. After you receive my feedback, you will need to submit a reflection paper as a response to my criticism. This reflection assignment is an opportunity for you to write about how you revised your paper by taking the tutor feedback into account. I would like you to explain what kind of revisions you made to develop your second draft. You do not need to explain every change that you made in your paper; however, it would be good if you could provide some examples from these changes. I will use your reflection paper in order to understand how you managed the writing process. At the eleventh week, I will lecture on how to present tabular information, visual materials, such as figures in your papers. At the twelfth week, I will lecture on TAWR which will be used to exchange both peer feedback and score your assignments by the lecturer. At the thirteenth week, I will introduce the guidelines to exchange effective feedback and model how to provide effective feedback by using TAWR with reference to several sample assignments from previous years. The peer review process aims to provide constructive feedback from your peers to you which can be used to improve your work. Your peers will be expecting to receive positive, clear, and concise feedback as well as constructive criticism from you. To do this, please make suggestions as to how your peer can improve clarity, succinctness, and the overall quality of paper. You do not need to edit the paper for English, but it is helpful if you highlight some grammatical issues in the paper to call your peer's attention on problematic aspects.

Within this perspective, you will submit your second draft at the thirteenth week and you will be assigned with three of your peer's papers to exchange peer feedback. Please note, you will need to submit second draft in two different versions with and without track of changes. The tracked version will allow me to see the improvements you made with your paper compared to the first draft and the non-tracked version will be used to exchange peer feedback. You will have finished exchanging peer feedback by the fourteenth week. During the final examination week, you will be asked to submit a reflection paper addressing the peer feedback you received. You should explain how you managed providing peer feedback process. There were 50 items in the rubric under 5 categories. You may explain, for example, which of these categories you found easier or more difficult to give feedback. I will use your reflection paper in order to interpret your process in giving peer feedback. You will need to list what you changed after receiving peer feedback and provide your response for the peer feedback that you do not take into consideration. You will be asked to upload digital versions of all sources use used to write your assignment as a precaution against plagiarism including contract cheating and collusion. Finally, you will submit the final version of your assignment, both with and without track of changes during the final examination week by specifically considering the peer feedback you received.

Deadlines

Please mark the following deadlines on your calendar.

Tutor feedback on outline: 9 March 2020.

Outline submission deadline: 15 March 2020.

Reference list submission deadline: 12 April 2020.

First draft submission deadline: 1 May 2020, 23:59.

Tutor feedback deadline: 8 May 2020, 23:59.

Second draft submission deadline: 15 May 2020, 23:59.

Reflection paper (changes in the second draft) submission deadline: 18 May 2020, 23:59.

Peer feedback exchange: 19–27 May 2020, 23:59.

Reflection paper (giving peer feedback) submission deadline: 29 May 2020, 23:59.

Final version submission deadline: 5 June 2020, 23:59.

Self-evaluation deadline: 7 June 2020, 23:59.

Reflection paper (changes in the final version) submission deadline: 7 June 2020, 23:59.

Google Drive upload sources: 7 June 2020, 23:59.