A Meta-Synthesis of Technology-Supported Peer Feedback in ESL/EFL Writing Classes Research: A Replication of Chen’s Study

Abstract

Research on the efficiency of technology-supported peer feedback activities in the ESL/EFL writing classroom has led to contradictory results. Some studies claim that it improves learners’ motivation and attitudes toward writing while others mention technical difficulties or a lack of training as drawbacks affecting learners’ experiences and thus learning. This ongoing debate calls for a meta-synthesis of studies published between 2011 and 2022. Replicating Chen’s study, the authors identified 20 primary studies and analyzed them under the lens of Glaser and Strauss’s grounded theory constant comparison method. The findings revealed that students’ preferences, capabilities, and attitudes regarding the features of the technology used in classes; the contextual factors, suitable online platforms, and training on the provision of proper feedback; and the use of the selected technologies can determine the extent to which implementing technology-supported peer feedback activities would be successful.

1. Introduction

Peer feedback or peer assessment is becoming increasingly common in higher education (Van den Berg et al. 2006). According to Dochy et al. (1999), peer feedback is an educational arrangement in which the quality of the student’s work is assessed by their fellow students. As described by Hansen and Liu (2005), learners provide feedback in the capacities of an editor, tutor, or teacher by taking on their roles and employing similar strategies and techniques (p. 31). Specifically, based on past relevant research, the process of teaching writing has shifted from being product-oriented to being more process-oriented (Hedgecock 2005). A process-oriented approach to writing encompasses different phases, such as prewriting, writing, editing, revising, feedback, and rewriting activities (Ferris and Hedgcock 2013). By adapting this approach, educators use a variety of techniques to teach English writing as a second language (ESL) and a foreign language (EFL). Peer feedback, one of these techniques, was introduced from L1 to L2 in the 1980s and has been extensively used in EFL/ESL classes since the 1990s (Zamel 1982; Chen 2016).

In recent years, different lenses of evidence-based theoretical frameworks such as Vygotsky’s sociocultural theory (SCT), the zone of proximal development (ZPD), and collaborative learning approaches have been used to analyze and understand peer feedback practices in ESL/EFL writing classrooms. Vygotsky’s sociocultural theory emphasizes social interaction and collaborative dialogue. According to the sociocultural perspective, people rely on different tools to develop connections and a sense of belonging to society. Furthermore, language is considered the most potent instrument of communication created by human culture, which fosters problem-solving and higher-order thinking through meaningful interactions (Lantolf 2000). Collaboration and peer interactions through different feedback patterns (corrective and negotiated) promote learning with the revision of written text and enable language learners to assist their peers’ L2 development (Tajabadi et al. 2020). Vygotsky’s ZPD theory focuses on the language learners’ achievements and signifies what learners can achieve with or without a teacher or peer support. Chew et al. (2016) suggested that effective assistance enhances learners’ learning experiences if they are aided by peers rather than working independently. Additionally, it enables teachers or skilled peers to observe the learners’ engagement with the feedback (how learners receive and respond to it) by analyzing their revised written work (Storch 2018). The evidence-based framework focuses on improving learners’ feedback literacy. This model views peer feedback as a writing process that offers opportunities for planning, translating, and reviewing academic writing (Yu and Liu 2021). In other words, traditional teacher feedback is insufficient; peer feedback in a technology-supported learning environment assists learners in developing their writing proficiency (Kostopoulou and O’Dwyer 2021). The collaborative learning theory is based on the idea of social interaction (Vygotsky and Cole 1978), in which language learners work collaboratively to complete a task in a face-to-face or virtual platform. This theoretical framework enables peers to exchange dialogic feedback during multiple phases (planning, discussion, and translation) of construction (Er et al. 2021). At each stage, learners work together as a team while providing and receiving feedback. It is an effective way to build a meaningful interactive space where knowledge is exchanged during peer-to-peer collaboration.

During the 1970s, most types of feedback in L1 composition classes consisted of the production of multiple drafts through which the teachers made suggestions for revisions (Ravand and Rasekh 2011). Due to the popularity of interactionist theories, peer feedback practices became more common as they considered not only mechanical accuracy, control of language, and development of meaning, but also the specific audience that might read the learners’ writing (Ravand and Rasekh 2011). Teachers began integrating conventional feedback with technology-supported feedback as technology gained popularity and became more accessible. Teachers started using blogs (Kelly and Safford 2009), both synchronous and asynchronous computer-mediated peer feedback such as email or online discussion boards (Chen 2016), audio-visual feedback (Kim 2018), or even software with automated-writing feedback features such as Write to Learn (Hyland and Hyland 2019). It has been demonstrated that students also tend to perceive the use of technology-supported feedback as beneficial and comforting as well as able to strengthen relationships and promote active learning regardless of whether the feedback is provided using social media or via screencast (Ko 2019; Thompson and Lee 2012; Warnock 2008; Anson et al. 2016). However, other studies have found that traditional face-to-face peer feedback tends to be more helpful and of higher quality compared to online feedback because of the pressure of immediacy and the clues given by peers’ body language and facial expressions (Ahmed and Abdu 2021; Liu and Sadler 2003; Ho 2015). In addition, according to these findings, the extra steps needed when using digital tools can be seen as cumbersome and discriminating against students who lack access outside of the class (Cunningham 2019).

The present study intends to replicate Chen’s (2016) synthesis of 20 qualitative inquiries in 20 qualitative or mixed-research design primary studies. Chen’s (2016) study covered studies published between 1990 and 2010. The aim of this study is to investigate technology-supported peer feedback studies in ESL/EFL writing classrooms published between the years 2011 and 2022. Adopting a similar approach to Chen’s (2016) method, the authors of this study relied on the constant comparative method of the grounded theory (GT) to analyze the discussion sections of the selected 20 studies (Glaser and Strauss 1967). Based on the newly collected evidence and given the use of GT as a research methodology, the authors developed a new grounded theory as opposed to testing or verifying any preconceived hypothesis (Glaser 1998).

Therefore, the research questions shaping this article are the following:

(1)

What are the characteristics of technology-supported peer-feedback activities found in the primary studies from 2011 to 2022?

(2)

What are the technologies used in computer-mediated peer interactions, and what are their advantages and disadvantages? In what ways do these activities affect students’ perceptions and attitudes?

(3)

What are the main themes emerging from the GT analysis, and what is the metatheory for the synthesis?

2. Literature Review

The use of computer technology has been significant in L2 writing instructions during two major eras. Firstly, in the cognitive era of the 1980s, word processing was acknowledged as a tool for making revisions (Pennington 1993; Warschauer 2010). Secondly, in the socio-cognitive era of the 1990s, computer-mediated communication was considered a practical tool for the social construction of meaning (Kitade 2000; Warschauer 2010). After 2000, new technology tools such as blogs (Xu and Yu 2018; Lin 2015), Google Docs (Pham 2020), Turnitin (Li and Li 2017), Moodle (Belén Díez-Bedmar and Pérez-Paredes 2012), Office Word (Ho 2012), Wiki tools (Woo et al. 2013), and Edmodo (Kayacan and Razı 2017) emerged to enable the teaching and learning of L2 writing. The central question in the studies regarding the effects of computer-mediated peer feedback is whether using these technologies is better than the traditional ways of providing peer feedback (Chen 2016). Before explaining further grounded meta-synthesis on technology-supported peer feedback, an outline of the recent findings in this field is presented below.

Empirical studies on online peer feedback have shown the effectiveness of technology-supported peer feedback on students’ writing quality and its ability to provide better local and global revisions (Huisman et al. 2019; Noroozi and Hatami 2018; Chen 2016; Novakovich 2016; Pham 2020). Additionally, peer feedback can assist students in acquiring domain-specific knowledge (Noroozi et al. 2016). Ciftci and Kocoglu (2012) found that online peer feedback is an efficient way to reflect on students’ writing, and teachers can benefit from the feedback and design activities that enable students to read, respond to, and revise their peers’ essays.

Studies on the relationship between online feedback and its influence on revisions among EFL writers indicate that online peer feedback has the greatest impact on students’ revision quality (Liou and Peng 2009; Tuzi 2004). This is because online peer feedback is perceived as more welcoming and encouraging, and less intimidating (Ma019). However, some studies show contradictory findings. For instance, while Chen’s (2016) qualitative synthesis indicated that online peer feedback may not always lead to positive outcomes, other studies suggest that the effectiveness of online peer feedback is dependent on factors such as the students’ linguistic limitations (Schultz 2000; Tolosa et al. 2013) and peers’ confidence and strategies (DiGiovanni and Nagaswami 2001). On the other hand, Pham (2021) found no statistical differences in the effects of lecturer and peer online comments on student revisions. Similarly, Vaezi and Abbaspour (2015) found no statistically significant difference between the effects of face-to-face and computer-mediated peer-written corrective feedback in terms of writing achievement. Lastly, some studies indicated that technology-supported peer feedback may have detrimental effects on students and their writing performance. The negative impacts of technology-assisted peer feedback on learners, their attitudes, and perceptions have primarily centered on the absence of in-person interaction and insufficient language proficiency to give feedback on peers’ writing (Ho 2012, 2015; Lin 2015; Kitchakarn 2013; Li and Li 2017). Other challenges encountered include technical difficulties, anxiety, discourteous remarks, reduced engagement in online discussions (compared to teacher-led discussions), the absence of nonverbal cues (such as tone of voice, gestures, and facial expressions), and concerns about losing face.

In 2016, Chen conducted a meta-analysis of 95 articles related to computer-mediated peer review in ESL/EFL that were published between 1990 and 2010. The study’s results were organized into four categories: computer-mediated peer feedback characteristics, which encompassed factors such as interaction, language use, discourse patterns, students’ roles, and teachers’ roles, the advantages and disadvantages of computer-mediated peer feedback, including technical, affective, and practical issues, a comparison of synchronous and asynchronous computer-mediated peer feedback and their functions, and, lastly, implications for future technology-supported peer feedback research, including pedagogy, grouping, and training. Chen’s study suggests that the year 2000 marked a significant shift towards incorporating technology-supported peer feedback activities into ESL/EFL writing instruction. Incorporating technology into peer feedback activities provided students with increased access to written discourse, which indirectly enhanced their skills and strategies for written communication. Furthermore, the issues that are often present in traditional face-to-face peer writing groups, such as off-topic discussions, individual domination, and unequal participation, were less significant in computer-mediated interactions.

Chen (2016) predicted that with the emergence of technologies such as Facebook, Twitter, and Wikis, peer interactions will gradually shift from face-to-face to computer-mediated platforms after 2010. The level of students’ computer literacy will partially replace their oral proficiency and affect their involvement in peer interactions in computer-mediated writing classrooms. As a result, text revision and the quality and quantity of peer interactions generated from technology-supported peer feedback may differ from those generated from face-to-face peer feedback. Therefore, more scientific research is necessary to compare traditional peer feedback with technology-based peer feedback or to compare different types of technology-supported peer feedback to determine their effectiveness. Replicating Chen’s (2016) study, this study tries to conduct comparative reviews of the studies published from 2011 to 2022 on the characteristics of computer-mediated peer feedback activities in ESL/EFL writing courses.

3. Methodology

3.1. The Data Collection Stage

This meta-synthesis consists of primary research studies selected by the authors after the conduction of an exhaustive search of the literature through diverse academic sources from the year 2011 to 2022. The aforementioned search included review articles, references in studies, computerized bibliographic databases, relevant peer-reviewed journals, and the World Wide Web.

3.2. Literature Searching Steps

Since the current study aims to replicate Chen (2016), the search process adopted by the authors started with the adoption of the relevant keywords and subject words.

Step 1: The following relevant keywords and subject words were used for the literature search:

(1)

Peer feedback/peer response/peer review/peer editing/peer interaction;

(2)

Peer feedback (and the interchangeable items in item (1) + ESL/EFL writing);

(3)

Peer cooperation + ESL/EFL writing;

(4)

Peer feedback (and the interchangeable terms in item (1) + training in ESL/EFL writing);

(5)

Online (computer-mediated, technology-enhanced, synchronous, and asynchronous) + peer feedback (the interchangeable terms in item (1) + ESL/EFL writing).

Step 2: Computerized bibliographic database search.

Based on the authors’ access to resources and the current state of the databases originally mentioned in Chen’s study, the following databases were used for the literature search in order to identify eligible studies:

(1)

Educational Resource Information Center (ERIC);

(2)

Social Science Citation Index (SSCI);

(3)

Arts & Humanities Citation Index (AHCI);

(4)

Academic Search Premier (EBSCO HOST);

(5)

Cambridge Core;

(6)

Project Muse;

(7)

JSTOR;

(8)

Directory of Open Access Journals.

After launching several searches, utilizing the relevant keywords and subject words mentioned in Step 1, the authors obtained a cumulative result of 314 articles from the eight aforementioned databases.

Step 3: Major ESL/EFL refereed journals search.

The third step consisted of identifying articles published in the 30 following academic journals, considered major sources based on their significance in the ESL and Technology in Education fields: the Journal of Educational Technology & Society, the JALT CALL Journal, the Asia-Pacific Education Researcher, the Journal of Educational Technology & Society, Computers and Composition, an International Journal for Teachers of Writing, Computer Assisted Language Learning, CALICO Journal, the Journal of Educational Computing Research, the Journal of Information Technology Education: Research, Journal of Educational Technology and Society, Computers & Composition, the Turkish Online Journal of Distance Education, Educational Technology Research & Development, IJCALLT, the Indonesian Journal of English Language Teaching & Applied Linguistics, the International Journal Of Emerging Technologies In Learning, English Language Teaching, the Australasian Journal of Educational Technology, Language Learning & Technology, the ReCALL Journal, System, TESOL Quarterly, Applied Linguistics, ELT Journal, Language Teaching Research, Studies in Second Language Acquisition, TESOL Canada Journal, Language Teaching, IRAL Journal, and Language Teaching and Learning.

Step 4: World Wide Web Search.

The final step of the search for eligible published studies consisted of browsing the World Wide Web, notably the Google academic search engine (https://scholar.google.com/ accessed on 1 November 2022) which compiles academic studies, in order to identify additional journals, such as the TESL-EJ, and studies that were potentially not uncovered during Step 3.

3.3. The Data Evaluation Stage

Out of the 314 cumulative results from the searches in each aforementioned database, the authors conducted an initial screening in order to identify studies that met the following criteria:

(1)

The studies had to be published or completed between 2011 and 2022 and had to take place in ESL/EFL writing classrooms.

(2)

The instructors of the studies had to employ at least one type of technology (computer-mediated) mode of peer-feedback activities in the writing class.

The authors retained 33 articles which then had to pass a second screening process consisting of Chen’s inclusion criteria 3 and 4.

(3)

The studies had to use a qualitative or a mixed research design including qualitative analysis.

(4)

Similar to Chen’s study, the qualitative data found in each article had to meet five criteria, adopted from the Qualitative Research Guidelines of Journals of Language Learning and Technology and TESOL Quarterly:

(a)

The articles contained thorough descriptions of the research contexts and participants.

(b)

The procedures of data collection and data analysis had to be fully described.

(c)

The articles’ findings, limitations, and implications were described.

(d)

A description of a clear and salient organization of patterns should be included in the data analysis.

(e)

The findings had to be interpreted holistically, and the writers had to trace the meaning of patterns throughout all of the contexts in which they were entrenched.

The evaluation conducted by the three researchers according to the inclusion criteria led to the retention of 20 studies which formed the body of research for this grounded meta-synthesis.

Of the 20 studies, 6 studies employed a qualitative research design, and 14 employed a mixed-method research design (

Table 1. The types of research design in the selected studies.

Type of Research Design	Studies
Qualitative research design	(Ciftci and Kocoglu 2012) (Nguyen 2012) (Lin et al. 2013) (Saeed et al. 2018) (Xu and Yu 2018) (Saglamel and Çetinkaya 2022)
Mixed-method research design	(Yang and Wu 2011) (Belén Díez-Bedmar and Pérez-Paredes 2012) (Chen 2012) (Ho 2012) (Kitchakarn 2013) (Woo et al. 2013) (Lin 2015) (Hussin et al. 2015) (Ho 2015) (Kayacan and Razı 2017) (Li and Li 2017) (Abdullah et al. 2018) (Colpitts and Past 2019) (Pham 2020)

).

3.4. Coding the Literature

Procedures of Coding for the Two Main Coders. In the coding procedure, the constant comparative method of qualitative analysis by Glaser and Strauss (1967) was employed. To enhance the credibility and trustworthiness of the findings of the study, the coding was performed by two of the four researchers, both TESOL specialists and experts in teaching different English skills in ESL and EFL classes. All four authors are skilled qualitative researchers and have been previously involved in coding and analyzing qualitative data. In the first stage of the coding procedure, two of the researchers randomly selected 5 studies among the 20 studies retrieved from the databases and journals and began the data analysis procedure separately. This stage consisted of coding, memo writing, and sorting the categories. Then, the two researchers met face-to-face and discussed the coding procedures that were conducted separately and independently. During the discussions, they compared each individual code, the memos written while coding the data, clustered categories, their various dimensions, and the characteristics of the selected 5 studies. After three face-to-face discussions that each lasted at least 90 min, the two researchers agreed on and established a model of coding and analysis to analyze the rest of the 15 studies. The coding procedure for the rest of the studies was performed independently by the two researchers and lasted one month. After finishing the coding, analyzing, and sorting of the categories separately, the two researchers met again and compared their findings (which included codes, memos, subcategories, and core categories). In case any discrepancies were found between the two analyses, the two researchers discussed the rationale for the specific code or category and decided to keep only one. In order to add to the reliability of the findings, the other two researchers went over all 20 studies and reviewed the core categories and subcategories. In case of any ambiguity, the four researchers met and discussed the issue and, if needed, revised the codes or categories.

Coding Procedures of Grounded Theory. According to Glaser and Strauss (1967), the constant comparative method of analysis consists of four main stages: (1) data collection, (2) coding, (3) comparing, and (4) theory building. The analyst starts with data collection which involves collecting data from various sources. In this study, the data were collected from 20 articles about CMC peer feedback in ESL/EFL writing classes. The second stage is coding, substantive and theoretically, each incident into the categories to which it potentially belongs. In the third stage of the analysis, the analyst compares the coded data to identify the broader categories. Finally in the last stage, based on the patterns and relationships identified in the previous stage, the researcher builds a theory to explain the data and make sense of the findings. This theory may be revised as the analysis continues. Figure 1 illustrates the four stages of the grounded theory.

Coding, Interpreting, and Building Theory Stages. The substantive coding process refers to the process of categorizing and organizing data into themes or concepts that relate to the central phenomenon studied. This study started by identifying the commonalities in the ‘slices of data’ (Glaser and Strauss 1967) through the open coding process in the finding and discussion sections of the 20 articles. These commonalities are called the ‘categories’ and have their own specific properties (see Figure 2). During theoretical coding, which refers to the process of developing a theory based on the data that has been collected and analyzed, the authors interpreted the properties of emerging categories, identified the ‘relations’ among them, and found the building blocks of the final theory of this meta-synthesis. The process of open, substantive, and theoretical coding was repeated by incidents or ‘slices of data’ in the theoretical sampling step until we reached the theoretical saturation (Glaser and Strauss 1967). The last step before formulating the theory was densifying the concepts from the substantive and theoretical coding in the last steps. The result is a coherent substantive theory that is applicable to this area of inquiry (Fernandez et al. 2002). Figure 2 illustrates the steps and processes in building the grounded theory.

4. Coding Results

In total, the two coders created 297 initial codes, which led to 13 subcategories and 3 core categories as shown in

Table 2. The core categories and subcategories.

Core Categories	Subcategories	Studies Endorsing the Subcategory
Core Category A	Subcategories of Core Category A
Characteristics of technology-supported peer-feedback activities	1. Categories of CMC (20) *	Yang and Wu (2011); Colpitts and Past (2019); Xu and Yu (2018); Lin et al. (2013); Chen (2012); Pham (2020); Kayacan and Razı (2017); Ciftci and Kocoglu (2012); Saeed et al. (2018); Lin (2015); Li and Li (2017); Kitchakarn (2013); Woo et al. (2013); Nguyen (2012); Saglamel and Çetinkaya (2022); Abdullah et al. (2018); Hussin et al. (2015); Ho (2015); Ho (2012); Belén Díez-Bedmar and Pérez-Paredes (2012)
	2. Local and global feedback and revisions (10) *	Yang and Wu (2011); Colpitts and Past (2019); Pham (2020); Kayacan and Razı (2017); Saeed et al. (2018); Li and Li (2017); Woo et al. (2013); Saglamel and Çetinkaya (2022); Ho (2015); Belén Díez-Bedmar and Pérez-Paredes (2012)
	3. The dichotomy of peer and teacher feedback (5) *	Kayacan and Razı (2017); Lin (2015); Woo et al. (2013); Abdullah et al. (2018); Hussin et al. (2015)
	4. Revision-oriented and non-revision-oriented feedback (6) *	Saeed et al. (2018); Li and Li (2017); Woo et al. (2013); Nguyen (2012); Ho (2015); Belén Díez-Bedmar and Pérez-Paredes (2012)
	5. The importance of collaboration (4) *	Saeed et al. (2018); Saglamel and Çetinkaya (2022); Abdullah et al. (2018); Hussin et al. (2015)
	6. The dichotomy of online and face-to-face peer feedback (4) *	Pham (2020); Ciftci and Kocoglu (2012); Saeed et al. (2018); Ho (2015)
Core Category B	Subcategories of Core Category B
Perceptions and effects of technology-supported peer-feedback activities.	The influence of the (online) audience (3) *	Kayacan and Razı (2017); Ciftci and Kocoglu (2012); Saeed et al. (2018)
Perceptions and effects of technology-supported peer-feedback activities. Core Categories	1. The effects of blended learning feedback approaches (including sequential/combined face-to-face and online) (3) *	Yang and Wu (2011); Colpitts and Past (2019); Pham (2020)
	2. The advantages and disadvantages of technology-supported peer-feedback activities (18) *	Yang and Wu (2011); Colpitts and Past (2019); Xu and Yu (2018); Lin et al. (2013); Chen (2012); Pham (2020); Ciftci and Kocoglu (2012); Saeed et al. (2018); Lin (2015); Li and Li (2017); Kitchakarn (2013); Woo et al. (2013); Saglamel and Çetinkaya (2022); Abdullah et al. (2018); Hussin et al. (2015); Ho (2015); Ho (2012); Belén Díez-Bedmar and Pérez-Paredes (2012)
	3. The effects of CMC on students’ perception/attitudes (17) *	Yang and Wu (2011); Colpitts and Past (2019); Lin et al. (2013); Chen (2012); Pham (2020); Kayacan and Razı (2017); Saeed et al. (2018); Lin (2015); Li and Li (2017); Kitchakarn (2013); Woo et al. (2013); Nguyen (2012); Saglamel and Çetinkaya (2022); Abdullah et al. (2018); Hussin et al. (2015); Ho (2015); Ho (2012)
Core Category C	Subcategories of Core Category C
Pedagogical implications of technology-supported peer feedback activities	The importance of training (7) *	Colpitts and Past (2019); Xu and Yu (2018); Lin et al. (2013); Chen (2012); Saeed et al. (2018); Lin (2015); Li and Li (2017); Kitchakarn (2013); Woo et al. (2013); Nguyen (2012); Saglamel and Çetinkaya (2022)
Pedagogical implications of technology-supported peer feedback activities	1. The importance of contextual factors and taking dynamic and recursive perspectives (11) *	Colpitts and Past (2019); Xu and Yu (2018); Lin et al. (2013); Chen (2012); Pham (2020); Kayacan and Razı (2017); Ciftci and Kocoglu (2012); Saeed et al. (2018); Nguyen (2012); Saglamel and Çetinkaya (2022); Abdullah et al. (2018)
	2. The pedagogical implications of technology-supported peer-feedback activities (20) *	Yang and Wu (2011); Colpitts and Past (2019); Xu and Yu (2018); Lin et al. (2013); Chen (2012); Pham (2020); Kayacan and Razı (2017); Ciftci and Kocoglu (2012); Saeed et al. (2018); Lin (2015); Li and Li (2017); Kitchakarn (2013); Woo et al. (2013); Nguyen (2012); Saglamel and Çetinkaya (2022); Abdullah et al. (2018); Hussin et al. (2015); Ho (2015); Ho (2012); Belén Díez-Bedmar and Pérez-Paredes (2012)

Note: * the number of studies endorsing this concept embedded in the subcategory.

. The three core categories included: (1) characteristics of technology-supported peer-feedback activities, (2) perceptions and effects of technology-supported peer-feedback activities, and (3) pedagogical implications of technology-supported peer-feedback activities. In the first core category, the authors identified six subcategories, which were: the categories of CMC, local and global feedback and revisions, the dichotomy of peer and teacher feedback, revision-oriented and non-revision-oriented feedback, the importance of collaboration, and the dichotomy of online and face-to-face peer feedback. In the second core category, the subcategories of the influence of the (online) audience, effects of blended learning feedback approaches (including sequential/combined face-to-face and online), the advantages and disadvantages of technology-supported peer-feedback activities, and the effects of CMC on students’ perception/attitudes were discussed. Finally, in the third core category, the importance of training, contextual factors and taking dynamic and recursive perspectives, and the pedagogical implications of technology-supported peer-feedback activities were the subcategories that the coders discussed.

Of the 20 primary studies, the predominant subcategories included: (1) the categories of CMC (endorsed by 20 studies), (2) the pedagogical implications of technology-supported peer-feedback activities (endorsed by 20 studies), (3) the advantages and disadvantages of technology-supported peer-feedback activities (endorsed by 18 studies), and (4) the effects of CMC on students’ perception/attitude (endorsed by 17 studies). The following subcategories included: (5) the importance of contextual factors and taking dynamic and recursive perspectives (endorsed by 11 studies), (6) local and global feedback and revisions (endorsed by 10 studies), (7) the importance of training (endorsed by 7 studies), and (8) the dichotomy of online and face-to-face peer feedback (endorsed by 7 studies). These were followed by the less-predominant subcategories: (9) revision-oriented and non-revision-oriented feedback (endorsed by 6 studies), (10) the dichotomy of peer and teacher feedback (endorsed by 5 studies), (11) the importance of collaboration (endorsed by 4 studies), (12) the influence of the (online) audience (endorsed by 3 studies), and (13) the effects of blended learning feedback approaches (including sequential/combined face-to-face and online) (endorsed by 3 studies). The core categories, subcategories, and studies endorsing the categories are listed in Table 2.

5. Discussion of Research Questions

Research Question 1: What are the characteristics of technology-supported peer-feedback activities found in the primary studies from 2011 to 2022?

Among all the technologies used in these 20 studies, blogging platforms were used the most frequently compared to other CMC platforms. As we can see in Table 2, the researchers in 9 of the 20 studies used several blogging platforms in their technology-supported peer feedback activity studies. These blogging platforms include Qzone (Xu and Yu 2018), Blogger.com (Ciftci and Kocoglu 2012; Kitchakarn 2013), Lang8 (Lin 2015), Opera blog (Nguyen 2012), and other miscellaneous blogging platforms (Chen 2012; Abdullah et al. 2018; Hussin et al. 2015; Lin et al. 2013). The second most frequent platform used for technology-supported peer feedback activities in these 20 studies is Google Docs (Colpitts and Past 2019; Pham 2020; Saglamel and Çetinkaya 2022). The third most frequent platforms used in the studies are Online Meetings (Ho 2012, 2015), an interface simulating a split-screen protocol specifically designed for synchronous online peer review, and Facebook (Hussin et al. 2015; Saeed et al. 2018), a social networking website that can be used to exchange feedback for text revisions and written reflections. Other platforms used for the technology-supported peer feedback activities in these 20 studies are Diff Engine (Yang and Wu 2011), Office Word (Ho 2012), Moodle (Belén Díez-Bedmar and Pérez-Paredes 2012), a Wiki tool named PBworks (Woo et al. 2013), Turnitin (Li and Li 2017), and Edmodo (Kayacan and Razı 2017). For further information on how these technologies were used in the primary studies, refer to Table 2.

The characteristics of the technology-supported peer-feedback activities found in the 20 studies analyzed in this meta-synthesis can be summarized into four different aspects.

The first aspect covers the distinction between global (i.e., organization, development, and style of a text) and local revisions (i.e., grammatical errors). For example, one study suggested that an increase in interactions led to more local and global revisions (Yang and Wu 2011). However, the majority of the intermediate EFL students involved in this study focused on local revisions, similar to the advanced learners in the study by Colpitts and Past (2019), the students involved in the study by Saeed et al. (2018), and the young intermediate to advanced learners involved in the study by Woo et al. (2013) who mainly focused on spelling, punctuation, and grammar. In blended learning environments, sequencing seems to influence the type of revisions learners provide. In the article written by Pham (2020), students were first exposed to written asynchronous computer-mediated communication and then to oral face-to-face interaction provided more local revisions. However, they provided more global revisions when oral face-to-face interaction came first. In terms of feedback, using Turnitin as a technology tool suggests that in all but one writing task, students provided more local feedback (Li and Li 2017).

Contrary to the other studies analyzed, the study conducted by Kayacan and Razı (2017) suggested that high school students’ self-review and peer feedback led to both local and global revisions (i.e., organization, content, grammar, vocabulary, and format). The study conducted by Ho (2015), which involved college students, suggested that more revisions in the global area were conducted rather than in the local area. Not only could the interaction mode (i.e., face-to-face or computer-mediated) influence the type of revisions, but the nature of the writing assignments (i.e., problem-solution and cause-effect essays) might also play a role in the nature and type of comments learners give (Ho 2015). Finally, the study by Belén Díez-Bedmar and Pérez-Paredes (2012) observed a predominance of morphosyntactic and lexical language-related episodes among college students. Saglamel and Çetinkaya (2022) emphasized how experimenting with local or global revisions translated to learners’ deep involvement in the writing process.

The second aspect is the effect of the existing dichotomy of peer and teacher feedback. There is an impact on students’ perception of and response to feedback based on who the author of the feedback is. In the study conducted by Kayacan and Razı (2017), high school participants in their role of feedback providers noticed the similarity of their role with that of their teacher. For some students coming from a teacher-centered culture, this new position leads to overall uncertainty, discomfort when receiving peer feedback, and worry in terms of providing peer feedback (Lin 2015). In faceless environments, instructors’ immediate feedback is considered essential (Abdullah et al. 2018).

The third aspect is revision-oriented and non-revision-oriented feedback. In a study conducted by Saeed et al. (2018), college students used Facebook groups to provide both revision-oriented and non-revision-oriented feedback. This interactive online environment enabled learners to engage in comments promoting socialization and group cohesion. This phenomenon was also observed in the study of Woo et al. (2013) following participants’ familiarization with the technology used. In two out of three classes, a majority of revision-oriented comments, both at the content and meaning level and the surface level, were observed. Similarly, in the study by Li and Li (2017), most comments were revision-oriented. When analyzing four assignments, Ho (2015) noticed that 60 to 76% of comments were revision-oriented comments. In this study, and in both face-to-face and computer-mediated modes, there was an overall adoption rate of global revision-oriented comments of at least 70%, except for the fourth paper (59%). However, Nguyen (2012) identified 49% of comments as revision-oriented, but the authors noted that 90% of the revision-oriented comments posted by the students were accepted either completely or partially, whereas comments related to the ideas expressed in the essays were not taken into account.

The fourth aspect is the importance of collaboration, which seems to occur when learners create a rapport leading to the formation of a writing community and texts being constructed and co-constructed (Saglamel and Çetinkaya 2022). This rapport can be pre-existing (i.e., students choose their teammates) but they often praise others’ work and give feedback in a friendly and accessible manner, show positive attitudes toward group work interactions, and promote socialization and group cohesion through their comments (Abdullah et al. 2018; Saeed et al. 2018). This group work interaction was identified as an essential phase of collaborative writing and a key part of the social-constructivist notion (Hussin et al. 2015).

Research Question 2: What are the advantages and disadvantages of the technology-supported peer-feedback activities demonstrated in the primary studies, and what are the effects of these technology-supported peer-feedback activities on students’ perceptions and learning?

To answer this second research question, the authors defined three subcategories identifying the advantages and disadvantages of technology-supported peer-feedback activities and students’ perception of these activities: the influence of an online audience and the effects of blended learning feedback approaches and technology-supported feedback activities, as well as students’ perception of them. The findings from the primary study used to answer this second research question are further detailed in

Table 3. Platforms used in the technology-supported peer-feedback research.

Study No.	Author (Year)	Name of Platforms	Function of the Platforms
1	(Yang and Wu 2011)	Diff Engine	Diff Engine highlights newly added words and crosses out newly deleted words in the system to show revisions.
2	Colpitts and Past (2019)	Google Docs	Google Docs allows easy access to writing critiques, editing, and sharing peer feedback.
3	Xu and Yu (2018)	Qzone	A popular blog platform in China used to post student blogs.
4	Lin et al. (2013)	BALL	Used for blog-assisted language learning.
5	Chen (2012)	Blogging platform	A blog-based platform for peer-reviewing (no specific names).
6	Pham (2020)	Google Docs	Google Docs allows easy access to writing critiques, editing, and sharing peer feedback.
7	Kayacan and Razı (2017)	Edmodo	Edmodo is an educational technology platform for K-12 schools and teachers. Edmodo enables teachers to share content and distribute quizzes and assignments
8	Ciftci and Kocoglu (2012)	Blogger (http://www.blogger.com accessed on 28 December 2022)	Blogger is an American online content management system founded in 1999 that enables multi-user blogs with time-stamped entries.
9	Saeed et al. (2018)	Facebook Groups	A social networking website that can be used to exchange feedback for text revisions and written reflections.
10	Lin (2015)	Lang8	A free language blogging website, Lang8 allows users to create their own blogs.
11	Li and Li (2017)	Turnitin	Turnitin offers features such as PeerMark that give students the ability to browse, analyze, score, and assess the papers that their classmates have turned in.
12	Kitchakarn (2013)	Blogger.com (website)	Blogger, an online website, serves as a platform for peer feedback exercises. Blogger is an American online content management system founded in 1999 that enables multi-user blogs with time-stamped entries.
13	Woo et al. (2013)	Wiki tool (PBworks)	A wiki application called PBworks enables students to engage together in writing courses, co-create their writing on PBworks pages made specifically for each group, and exchange helpful criticism and comments on the platform.
14	Nguyen (2012)	Blog (www.opera.com accessed on 28 December 2022)	Users of a class blog (www.opera.com accessed on 28 December 2022) have access to a free blog service site where they can submit details on grammatical constructions, writing conventions, and reading texts.
15	Saglamel and Çetinkaya (2022)	Google Docs	Peer reviews can be written, edited, and shared using Google Docs.
16	Abdullah et al. (2018)	CMC (online Blog forum)	An online platform (CMC blog) that allows peer feedback exercises.
17	Hussin et al. (2015)	Blog and Facebook	CMC applications (blog and Facebook) improve writing ability through peer involvement and interaction.
18	Ho (2015)	Online Meeting	The CMPR involves OnlineMeeting, an interface simulating a split-screen protocol specifically designed for synchronous online peer review.
19	Ho (2012)	Online Meeting and Word	Word allows students to directly type comments on the computer, track changes, and highlight important features. The OnlineMeeting system automatically generates web links allowing users access to online chat rooms.
20	Belén Díez-Bedmar and Pérez-Paredes (2012)	Moodle	Moodle is a Course Management System (CMS) or learning platform designed to provide educators, administrators, and learners with a single robust, secure, and integrated system to create personalized learning environments.

.

Among the 20 primary studies, the research conducted by Chen (2012); Ciftci and Kocoglu (2012); Nguyen (2012); Lin et al. (2013); Kitchakarn (2013); Lin (2015); Hussin et al. (2015); Kayacan and Razı (2017); Li and Li (2017); Abdullah et al. (2018); Xu and Yu (2018); Colpitts and Past (2019); Pham (2020); and Saglamel and Çetinkaya (2022) all mentioned students’ positive perception of providing feedback in a digital environment, sometimes even preferring it to face-to-face mode (Saeed et al. 2018), and agreed that it helped them improve their writing skills, especially in grammar and vocabulary development, organization, coherence, and punctuation (Abdullah et al. 2018) as well as reduce their writing anxiety (Hussin et al. 2015; Abdullah et al. 2018). Blogging was considered new, interesting (Colpitts and Past 2019; Nguyen 2012), fun, user-friendly, time-independent, and a tool offering useful features (i.e., using photos or other materials) (Lin 2015), all of which contributed to enriching the learners’ essays (Ciftci and Kocoglu 2012). Learners believed that it positively contributed to their writing skill improvements (Xu and Yu 2018; Lin 2015), enhanced their schema (Hussin et al. 2015), and led to increased motivation (Lin 2015; Hussin et al. 2015) and self-confidence in their writing (Hussin et al. 2015). Providing peer feedback on others’ blog samples also helped learners reflect on their own work (Xu and Yu 2018). Technology-supported peer feedback was also described as a convenient and refreshing alternative to traditional ESL writing classes (Lin et al. 2013). Some learners felt comfortable using an online peer review process and perceived it as a positive experience (Chen 2012). After becoming familiar with the technology tool used (i.e., Wiki PBwork), students started posting playful comments, creating group cohesion (Woo et al. 2013). Being exposed to others’ work was considered beneficial since they were able to learn from each other’s mistakes (Kayacan and Razı 2017; Kitchakarn 2013). Some of the features perceived as beneficial by students were related to the possibility of anonymity in the review process, though a potential lack thereof seems to worry some learners. However, the different ways of providing feedback in a suitable manner, spell checks, and other tools were believed to reduce the cognitive load and enable the students to focus on the content (Nguyen 2012; Li and Li 2017; Woo et al. 2013). While the features offered by technology tools might explain the types of feedback used by learners, Ho (2015) suggests that overall, students preferred typing their comments rather than handwriting them as the track changes or highlighting features were deemed more helpful.

The ability to reflect and provide delayed feedback or revision in asynchronous tools was also perceived as a valuable feature (Li and Li 2017). The study conducted by Saeed et al. (2018) suggested that the delayed time between reading peer feedback and responding to it facilitated learners’ reflection on global and local issues. Asynchronous computer-mediated communication was also perceived as less face-threatening by learners involved in the study by Pham (2020).

This positive perception was confirmed by the findings of some of the studies selected. In the study by Ciftci and Kocoglu (2012), participants in the blog group had significantly higher scores in their second drafts, which suggests that the use of blogs as an instructional tool made a difference and enabled them to improve their writing skills. Participants in the study by Kitchakarn (2013) improved their writing abilities after using blogs for learning. In the study by Woo et al. (2013) on university students engaged in technology-enhanced group work, it was observed that the students tended to generate comments at the content meaning level more frequently than surface-level comments, as compared to face-to-face discussions. Additionally, Nguyen (2012) found that the use of asynchronous computer-mediated communication led to more revisions than traditional face-to-face interaction, implying that the feedback provided in online settings was more effective for facilitating learning. The study by Lin (2015) showed that participants experienced enhanced motivation, self-efficacy, and significant improvements after attending the blog-supported writing instruction.

Some studies identified several drawbacks of technology-supported peer-feedback activities such as students’ lack of time to engage in such activities, lack of training (Xu and Yu 2018), and lack of motivation to go beyond teachers’ requirements (Lin et al. 2013; Lin 2015). In blogging environments, some learners’ motivation could be affected by the overwhelming task of reading and writing blogs in a foreign language (Lin 2015) or providing good peer feedback (Kitchakarn 2013) or by the increased anxiety stemming from having their writings made public and open to peer criticism (Kitchakarn 2013; Lin et al. 2013). Students’ perception of the technology tools used for academic purposes can also affect their perception of the effectiveness of said tool (Ciftci and Kocoglu 2012). In addition, technical difficulties and potential glitches, such as problems with connection, play a role in learners’ perception of TSPR (Ciftci and Kocoglu 2012; Li and Li 2017). When using Turnitin some learners also mentioned the inability of communicating with the writer face-to-face, something that they considered as facilitating the peer review process. Another drawback was that while some participants positively perceived the chat feature of OnlineMeeting and the possibility of having online conversations, others mentioned the inefficiency of online chat as opposed to face-to-face talk (Ho 2012, 2015), the latter making expressing learners’ thoughts and negotiating meanings easier.

The sequential approach used by the teachers in blended learning also influenced the effects of TSPR. As Pham (2020) demonstrated, when students are first exposed to a face-to-face environment, followed by an online environment, they tend to provide more local revisions. When they are first exposed to an online environment, followed by a face-to-face environment, more revisions were performed at the global level.

Finally, when considering motivation, technology-supported peer-feedback activities can lead to more online interaction, which seems to lead to more local and global text revisions (Yang and Wu 2011).

Research Question 3: What are the main themes emerging from the GT analysis and what is the metatheory for the synthesis?

The main themes elicited from the research are concerned with the effects of incorporating technology into peer-feedback activities and the importance of factors affecting the successful implementation of computer-mediated peer feedback in writing courses. The following main themes emerged:

• The way students’ learning, perceptions, and attitudes are affected by technology-supported feedback activities should be considered.
• The benefits and drawbacks of using computer-mediated feedback (compared to face-to-face feedback) should be considered when applying them in the classes.
• The instructors should provide proper training for the students (both in terms of giving helpful feedback and utilizing the online platforms).
• Considering contextual factors in peer feedback activities plays an important role in successfully integrating technology in giving feedback.

Based on the four mentioned emerged themes, the meta-theory of this study can be structured as follows:

Understanding the students’ preferences, capabilities, and attitudes regarding using technology features in learning, as well as considering the contextual factors, the advantages and disadvantages of each online platform, and the instructors’ ability in providing training on giving proper feedback and using technology determine the extent to which implementing technology-supported peer feedback activities would be successful.

The successful implementation of technology and computer-mediated peer feedback in ESL and EFL classes depends on several factors including providing the students with proper and enough training on how to use the online platforms effectively and efficiently and ensuring that the giving and receiving of feedback is achieved in a constructive and helpful manner. Contextual factors, such as students’ linguistic competence and computer literacy, culture and power dynamics, technical difficulties, and students’ perceptions and attitudes towards using technology in giving and receiving peer feedback, are among the most important factors determining the effectiveness of utilizing technology and computer-supported peer feedback.

6. Implications

The implications for future research drawn from the 20 primary studies can be discussed in the following aspects: (1) the characteristics and effects of technology-supported peer feedback activities on the students’ perceptions of the activities, (2) the importance of providing efficient training, and (3) the pedagogical implications.

The reported effects of technology-supported peer feedback on learners fall into two main groups: positive and negative impacts. In terms of positive effects, the majority of the studies reported positive effects from using technology-supported peer feedback on learners. Most of the participants in the 20 primary studies describe their experiences as positive and inspiring (Yang and Wu 2011; Belén Díez-Bedmar and Pérez-Paredes 2012; Chen 2012; Ciftci and Kocoglu 2012; Ho 2012; Nguyen 2012; Kitchakarn 2013; Ho 2015; Hussin et al. 2015; Lin 2015; Li and Li 2017; Kayacan and Razı 2017; Xu and Yu 2018; Pham 2020; Saglamel and Çetinkaya 2022;), reliable, practical, fast, and useful (Ciftci and Kocoglu 2012; Nguyen 2012; Ho 2015; Kayacan and Razı 2017; Colpitts and Past 2019). Technological developments increased motivation and self-efficacy for writing content and made writing classrooms more creative, autonomous, and collaborative (Kitchakarn 2013; Lin 2015). Furthermore, they helped students improve their writing abilities both in the local and global aspects of writing (Belén Díez-Bedmar and Pérez-Paredes 2012; Ciftci and Kocoglu 2012; Chen 2012; Lin 2015; Nguyen 2012; Ho 2015; Hussin et al. 2015; Kayacan and Razı 2017; Xu and Yu 2018; Saglamel and Çetinkaya 2022; Saglamel and Çetinkaya 2022). One of the factors that tended to hinder writing skill improvements is second language writing anxiety (SLWA, Fattahi Marnani and Cuocci 2022). It was shown that one of the effects of technology-supported peer feedback on the students was lowering the stress and anxiety level in their writing through using computer-mediated peer feedback since it offers a friendlier and less threatening environment, especially in anonymous platforms (Belén Díez-Bedmar and Pérez-Paredes 2012; Hussin et al. 2015; Ho 2015; Lin 2015; Li and Li 2017). All in all, the participants revealed that they had an increased awareness regarding opportunities to use the Internet for academic purposes and developed critical thinking and their ability to take responsibility for their learning process (Chen 2012; Kayacan and Razı 2017; Li and Li 2017, Xu and Yu 2018). Some expressed great willingness to undergo more of these types of experiences in the future since it showed them their strengths and weaknesses and gave them a real challenge to deal with their language learning process (Lin 2015; Saglamel and Çetinkaya 2022).

Nonetheless, certain drawbacks were mentioned in several studies. The negative effects of technology-supported peer feedback on learners’ and students’ perceptions and attitudes were mostly concerned with the lack of face-to-face communication and inadequate language skills to provide feedback on others’ writings (Ho 2012, 2015; Lin 2015; Kitchakarn 2013; Li and Li 2017). Experiencing technical glitches, anxiety, impolite comments, limited attention to online discussions (compared to teacher-led discussions), lack of paralinguistic features (such as intonation, gestures, and facial expressions), fear of losing face—a common trigger of anxiety among English learners (Cuocci and Arndt 2020; Pappamihiel 2002), and lack of confidence and interest in giving feedback or participating in online discussions beyond the minimal requirements are also mentioned as the factors negatively affecting the students (Chen 2012; Nguyen 2012; Kitchakarn 2013; Lin et al. 2013; Ho 2015; Li and Li 2017). In two studies, some students felt the exchange of face-to-face comments was more efficient than synchronous online chats because they could easily express thoughts and negotiate meaning face-to-face. It was indicated that face-to-face peer feedback led to more peer-triggered revisions (Ho 2012, 2015).

These advantages and disadvantages perceived by students seem to reflect the ongoing debate researchers have regarding the effect of technology on learners (Cuocci and Fattahi Marnani 2022). However, it has been mentioned that students’ attitudes toward a given activity and their learning experience may change in the long run (Colpitts and Past 2019).

Regarding the implications concerning the effects of technology-supported peer feedback activities, it can be suggested that when selecting the most suitable online platform to implement in the writing classes, instructors need to consider several technological aspects of the platforms and their students’ capabilities and preferences; instructors need to provide them with the most suitable platforms based on the students’ preferences, contextual factors, and technical considerations. In terms of combining face-to-face and computer-mediated feedback, it is suggested that having face-to-face peer feedback first and then engaging in computer-mediated feedback increases the efficiency of the feedback activities (Pham 2020).

The second implication involves the necessity of giving effective and efficient training. The findings suggest that by giving sufficient training and purposeful explanation in terms of both giving helpful and appropriate feedback and utilizing the online platforms, students are able to give the most useful, relevant, and efficient feedback to their peers (Lin et al. 2013; Xu and Yu 2018; Colpitts and Past 2019; Saeed et al. 2018; Xu and Yu 2018).

The third group of implications includes the pedagogical implications. Though more research needs to be completed to identify the reason why some students provided more local/global comments/revisions, it seems that the participants in the 20 primary studies relied more on local revisions, especially intermediate/advanced (adult/young) learners. When providing peer feedback, students tend to adopt the role of a teacher, which can lead to potential issues when they are culturally more used to teacher-centered approaches. It can also lead to some students not considering their peers qualified enough (Kayacan and Razı 2017).

Moreover, while revision-oriented feedback was the noticeable majority throughout the studies analyzed, which tended to be acknowledged by students, some findings from the 20 primary studies revealed the important role of the existence of non-revision-oriented comments as well as the promotion of group cohesion via comments to promote socialization (Woo et al. 2013). Added to an environment promoting collaboration, such as the creation of groups based on pre-existing rapport, the provision of praises and the use of friendly and accessible feedback are all elements that were essential to co-construct texts of improved quality. Therefore, educators should keep in mind that not all peer feedback needs to be revision-oriented. Familiarity with the technology used in class and a positive perception of said technology might lead to the production of a non-academic type of work (i.e., non-revision-oriented feedback), which may positively influence learners’ skills.

Finally, the trend of peer feedback activities through blogging was noticeable. Blogging seems to be perceived as a fun tool educators can use to improve their learners’ writing skills. Google Docs and Turnitin are also among the most efficient platforms recently implemented in writing classes (Colpitts and Past 2019; Pham 2020; Saglamel and Çetinkaya 2022).

7. Conclusions

The combination of technology-supported peer feedback activities and other contextual factors such as socialization opportunities can lead to increased interaction and thus feedback; both influential factors in learning (Cuocci 2022). Although the types of feedback seem to vary based on factors such as synchronicity, the type of assignments, and students’ cultural background, an increase in feedback will likely lead to writing improvement. Educators must keep in mind the effects of some key functionalities offered by technology such as anonymity, spell check, convenience, clarity of typed comments (i.e., Google Docs), and access to online resources to assist learners in reducing their cognitive load, resulting in the potential improvement in writing skills as well as potential opportunities to create group cohesion. The optimal conditions prior to the integration of technology in the classroom are: (1) student training in the efficient use of the technology, (2) student training in the provision of proper feedback—specifically for beginners as they tend to mainly provide surface comments, and (3) the selection of a technology tool, which will likely lead to a manageable workload for the teachers.

As this meta-synthesis was replicated, an observation must be made regarding the evolution of emerging themes pertaining to this study and the study conducted by Chen (2016). Based on their work on 20 primary studies published between 1990 and 2010, Chen’s findings revealed a positive effect on students’ interaction when peer feedback activities were supported by technology due to the flexibility offered by technology interactions, the less controlling role teachers had in such environment, and the influential role of the dichotomy between synchronous and asynchronous activities. Some findings in this current study support Chen’s findings, such as students’ ability to reflect on their responses and the existence of features facilitating students’ feedback provision. Other findings revealed novel trends related to the evolution of technology tools that educators now have access to. The focus seemed to be less on the difference between synchronous and asynchronous activities and more on the importance of training, students’ perceptions, contextual factors influencing students’ learning experience, and the potential benefits offered by specific tools promoting CMC such as blogs. Future research should focus on identifying the necessary features and other covariates that potentially impact the likelihood of students producing local or global feedback and revision so that educators can be aware of the tools they need to choose based on the type of feedback and revision their students could most benefit from (Xu and Yu 2018).