Culturing Participatory Culture to Promote Gen-Z EFL Learners’ Reading Proficiency: A New Horizon of TBRT with Web 2.0 Tools in Tertiary Level Education

1.1 Statement of the Problem

When we talk about task-based reading instruction in TBLT, the word “comprehension” appears as the final goal, and at the same time, a question about how to attain this goal with task completion arises. Here, Block and Pressley (2002) state that a skilled reader attains the fluency of decoding and better comprehension of reading instruction, but this happens only when reading is purpose-driven and learners have adequate chances of interaction. Again, a closer look at Learning Point Associates (2004) finds out “cooperative learning,” one of the essential components of effective reading construction, and it invigorates the idea of interactive learning, the most familiar and exercised one in this age of advanced technology (Muftah, 2024). Recently, educationists have been thinking about social Web 2.0 tools that can easily create a collaborative, interactive 24 h learning platform where techsavvy learners feel oneness and can communicate, generate, share, and distribute knowledge among all; thus, even poor students also get mastery over some knowledge points very easily and quickly (Parvin, 2020).

Many universities have already launched web 2.0 social tech-rich platforms, but still, educators and course instructors have been bound to Power Point to facilitate students’ language learning (Bower, Hedberg, & Kuswara, 2010; Conole & Alevizou, 2010; Selwyn, 2012; Thomas & Peterson, 2014) as there is a gap between this generation of learners and old-generation lecturers and professors. Here cultural resistance and pedagogical issues are considered the main obstacles for mitigating the gap and the limitations in the use of social media tools. However, there are also notable limitations in motivation as well as restrictions in social tech tools usage to enhance collaborative learning, and the result is “slow uptake of technological advances in education” (Dowling, 2011). This present scenario urges further advanced research for making web 2.0 tools-integrated TBRT more effective for Gen-Z learners and more efficient for the teachers at the tertiary level.

1.2 Significance of the Study

During the long research journey of the implementation of TBLT in L2 acquisition, the education industry identifies various issues, mainly the lack of interaction opportunities and the loss of motivation. To resolve these issues, researchers have begun to explore the possibility of synthesizing research on TBLT and SWILP (Social Web 2.0 Tools Integrated Learning Platform) in the interests of tech-devoted L2 learners to develop their English language skills. This research specifically addresses the barriers and gaps where modification is required to improve TBRT experiences. The study is designed to address students’ performance, their interest level with different task activities and teachers’ efficiency in handling students’ difficulties and also holding their motivation while working on discussion boards and blogs. This research further attempts to rejuvenate the idea that language teachers’ devotion and efficiency help design tasks that are content-related and cover the mass interest of the learners having opportunities to enjoy participatory culture. It also depicts that if the learners give value to their contribution to the learning society, a knowledgeable, dynamic learned community will automatically be formed. Above all, the findings of this study will help establish such a social web 2.0 tools integrated TBLT platform where learners will have the scope of evaluating themselves, enriching vocabulary in use with Read-Write Web, increasing their ability of real-life language use, and also vibrating the enrichment of the background knowledge; thus, will ensure their satisfactory performance in reading.

2.1 TBLT for Gen-Z EFL Readers

TBLT is both student-centered and task-based. This pedagogical approach creates more opportunities for the students to be engaged fully in a language task that enhances language acquisition and elicits language production in a real-life context. It facilitates L2 learning (Branden et al., 2009) and instigates learner-oriented education (Ellis, 2003). Therefore, TBLT becomes successful if the learners are active and have the main roles in learning (Branden, 2006).

While justifying the nature of today’s learners, who are Gen-Z (born between 1997 and 2012) and are named “Digital Natives” (Prensky, 2001), it is noticeable that they are raised in a tech-advanced society where communication devices give them a multimodal and interconnected technological life, and make them self-regulated learners. Technologies “shape this generation’s literacies, the ways of being in and with the world, and their cognitive and learning processes” (Rosen, 2010; Thorne, 2013). Notably, they are socio-constructivists whose main goal is to construct the content of learning through collaboration to make learning a “shared social experience” (Huang & Lajoie, 2023; Szymkowiak, Melović, Dabić, Jeganathan, & Kundi, 2021). Therefore, TBLT is appropriate for these learners, but a dynamic collaborative learning platform can best satisfy their learning needs and expectations.

Likewise, reading itself is a social practice (Afdal, Spernes, & Hoff-Jenssen, 2023; Paxton & Frith, 2014), and the goal of reading comprehension is to have a fuller command of the reading text by extracting the meaning of the words and grappling with the writer’s purpose, implementing background knowledge. To attain this goal, learners need to have language processing skills, critical thinking (CT) power, and creativity, which are subconsciously developed through frequent communication and collaboration between learners and peers as well as learners and tasks. Here well-designed interactive language learning tasks (Yang & Wilson, 2006) fitted integrally into “digital technology realities” (González-Lloret & Ortega, 2014, p. 1) can ensure a high proficiency level of reading of Gen-Z EFL learners at the university level.

2.2 Interactive Task for Reading

The goal of TBRT is to establish the relationship between reading comprehension, vocabulary knowledge, reading pleasure, and reading frequency (Aarnoutse & van Leeuwe, 1998). As a result, designing and selecting reading tasks is an amazingly intricate process that requires teachers’ insightful attitude toward a smart combination of tasks, tools, and target learners’ behavior. Willis and Willis (2007) assert that “one of the prominent features of the task is involvement in real language use, in which there is an immediate problem to solve” (p. 160), whereas Skehan (1998) promotes the idea that tasks should be pedagogic goal-oriented, and in designing tasks, the most priority is given to students’ engagement and learning outcomes. In this regard, Cowley-Haselden (2020) focuses on the exploration of various creative and collaborative activities and practices for teaching academic reading in and outside the classroom. All these previous studies imply that TBRT becomes successful only when teachers’ intentions and learners’ interpretations of a given task meet at a point. TBRT advocates educationists to give learners plenty of time and opportunities for two things: (1) receiving meaningful input (exposure to L2) and (2) having output (experiencing language use), and in the whole process, the teacher’s close observation of the range of learners’ interaction, communication, and collaboration in synchronous and asynchronous learning helps discover where modification and changes should be made in task production and task instruction (TI). Breen (1987) distinguished between a “task-as-work plan” and the actual “task in process” and states that only careful observation and productivity of the instructors can make the whole process dynamic and goal-oriented. This research contributes to bringing new concepts of designing reading tasks and tailoring instruction to fulfil the demands and satisfaction of Gen-Z learners, and establishing the idea that there is no alternative but an efficient, dynamic teacher with in-depth knowledge about software, applications, and tech tools for getting the optimum benefit of tech-integrated TBRT and learning.

2.3 Exploration of Social Web 2.0 Tools for Reading Activities

In reading, text comprehension is one of the main challenges of cognitive science, whereas learning to read is a type of problem-solving (Pressley et al., 1992). As a result, the more the collaborative tools will be activated for TBRT, the more the learners will have the chance to develop their language processing skills, CT power, and creativity. In this research, two experimental web 2.0 tools (discussion board and weblog) are discussed to show their effectiveness in bringing interaction and collaboration between learners and learners and teachers outside reading classes.

3.1 Research Design

The research methods applied in this study are both qualitative and quantitative. A survey questionnaire with closed and open-ended questions and an observation tool were used while teaching reading in the Department of English Language at a university in the Kingdom of Saudi Arabia in one academic year. For the focus group, collaborative tasks were designed, and social web 2.0 tools, mainly a blog and discussion board, were opened besides traditional courseware. On the one hand, TBRT experiences with the experimental group, through distributing the questionnaire, provided valuable insights into the learners’ participation in reading within a technology-enhanced atmosphere. On the other hand, closely observing the progress of students’ performance, their activities, and interactions with peers in various tasks helped clarify their achievement in communication competence and reading comprehension skills within a socially advanced, tech-enriched platform. This approach was guided by Taylor and Taylor’s (1990) and Vygotsky’s (1978) psycholinguistic and socio-constructivist theories, as well as several years of experience in implementing social web 2.0 tools for task-based teaching, especially after the shift to online education during the 2018 Coronavirus Pandemic.

3.2 Research Locale and Respondents

The respondents of this research study (in both case study 1 and case study 2) were 35 female undergraduate students of the EFL reading class at a university in the Kingdom of Saudi Arabia, where blackboard is used as the learning management system. This experimental group had experience with learning English as L2 on both face-to-face and online platforms. This group belongs to Gen-Z and is called the “first digital native generation” (Cilliers, 2017). This focus group was taught reading implementing Web 2.0 tools integrated TBLT pedagogy in one semester in the academic year 2023. Their attitudinal and aptitudinal changes were studied while confronting with different tasks on both the discussion board and blog. With the demographic part of the questionnaire, their preference and experience in using social tech tools and AI tools for quality collaboration were recorded to justify their performance progress during the case studies for this research.

3.3 Instruments

Two fundamental tools, an observation tool, and a survey questionnaire, and also two different tailored tasks were used to carry out this study. The internal consistency of the questionnaire items was checked using the Pearson Correlation Coefficient, which measures the strength of the relationship between items. This was complemented by Cronbach’s alpha coefficient, a widely accepted measure to assess the reliability of the scale, ensuring that the items within the questionnaire consistently measure the same underlying construct. Cronbach’s alpha values above 0.7 are generally considered acceptable for reliability, and this threshold was met in our study, confirming the questionnaire’s reliability. Additionally, the validity of the questionnaire was ensured through careful item selection based on the constructs we aimed to measure, supported by a comprehensive review of the literature to ensure content validity. The questionnaire was designed to reflect theoretical concepts in task-based learning and CT, which were the focus of our study. Thus, the instruments’ content was scrutinized for alignment with these constructs, ensuring that it effectively captured the intended data.

3.3.1 Tasks

Two tasks with a chained instructional design were assigned for the focus group to promote learner-generated content. One was accomplished on the discussion forum and another on the blog. In designing tasks, Ellis’ (2013) and Willis’ (1996) task categorization ideas were adapted. Again, we were motivated by Robinson (1995, 2001, 2011) in reframing tasks and instructional design. These tasks were sequenced from “cognitively simpler to more complex ones approaching real-world demands” as this is proven a better approach to assisting academic English reading skill development. Three targets were set: (1) increasing students’ motivation level, (2) developing learners’ twenty-first-century skills, C4 (communication, collaboration, CT, and creativity), and (3) upgrading students’ responses in language processing and knowledge production (KP), which are the goals of learning reading. Again, TIs were designed guided by the 3P (Present-Practice-Produce) model (Harmer, 2007), and an appropriate quality control mechanism (Dowling, 2013) was applied for the smooth delivery of the shared content.

Task 1 is categorized as a word-focused task and was assigned to be completed on the discussion board, aiming that learning in groups on a discussion board occurs with Teacher-generated content in a learner-generated learning atmosphere. Detailed explicit instruction was given to the experimental group. Students were asked to make their groups consisting of four members. They were given the freedom to choose their teammates so that they could start their work in an online comfort zone where they would have more confidence and less anxiety. Students happily made their groups, and each group worked out of vocabulary inference activity and accomplished three achievement objectives: (1) explicit word structure, (2) word meaning in contextual perspective, and (3) image-based concept creation design. Besides, the reading system framework (RSF), an interactive model of reading comprehension (Perfetti & Stafura, 2014), was restructured and presented to the learners adjusting to the nature of the task and tool (Figure 1).

Figure 1

Instructional design of vocabulary inferencing task on discussion forum.

This task required applying the “vocabulary self-collection” (p88) strategy that was proved effective by the previous study in invigorating learners’ consciousness of knowing new words used in different contexts independently while reading text (Antonacci & O’callaghan, 2011). As the learners had been driven to a culture of self-regulated learning by establishing a participatory culture through social web 2.0 tools, to increase their motivation, a clear guideline of the steps followed for this task completion was given to them. This process of instruction followed Harmer’s (2007) present-practice-produce (PPP) methodology, and then the 4P model (Present-Practice-Produce-Publish) designed by Dowling (2013) along with another extra step, Preview for making the online platform more engaging and interactive. All these stages were reconstructed to meet the demand for twenty-first-century skills (C4 for L2 learners) development (Figure 2).

Figure 2

Learning framework for Task-1 on discussion board.

Links were provided with the chance to go through an informative reading passage, “Random Acts of Kindness” multiple times along with other digital text aligned with the assigned topic; this is the Presentation stage in which the students were introduced to the reading strategies required for expert reading. In the Practice stage, students involved themselves in analyzing the external structure of words to have the phonological awareness that is “an integral part of reading instruction” (Torgerson, Brooks, Gascoine, & Higgins, 2019). The third stage, Produce, encouraged learners to infer the meaning of unfamiliar words from the context first in English, and then in Arabic, their mother tongue. Here learners took part in provoking awareness of the application of background knowledge and thought for analyzing the lexical and morphological part of the words to have familiarity with the formation of the words. This is the application part. This task part demanded students’ attention on creativity or productivity. Image inferencing poster with a glimpse of kindness and nobility shown by the society was also asked to be framed as the evaluation indicator that shows the students’ mastery over the vocabulary learnt from the reading comprehension text. After each group had completed their work and produced their content, in Preview, the members of each group and their teacher discussed the whole work process for feedback on both platforms – face-to-face and online. Finally, the Publish stage directs the learners to publish their final task to generate a task communication approach among all the learners in the focus group on this shared learning platform to have the chance to read many texts produced from different perspectives of the students. It was a 2-week time-bound task with unlimited collaboration and communication opportunities.

Task 2 is categorized as a linguistic response task. Since reading comprehension is considered “a multi-dimensional process” (Johnson, Archibald, & Tenenbaum, 2010; O’Reilly & Sabatini, 2016; Savarimuthu & Ponniah, 2024), and learners’ knowledge is built through improved social interaction and the personal CT dispositions (Hajhosseini, Zandi, Shabanan, & Madani, 2016), this linguistic task (Task 2) that required higher-order thinking necessary to interpret the text was designed to be accomplished in blogs. As blogs are more focused and create threads of ongoing journals with a chronology of information, here, cognition sprouts thinking and creativity essential for becoming a critic with small group discussion.

This task targeted learners’ involvement in close reading for a better understanding of the meaning of the text, the main idea, the supporting details, and the author’s motif. Links for reading comprehension on healthy cuisines were shared with the experimental group. The students were motivated to complete this task by interchanging ideas with one another through meaningful communication. Moreover, a clear and concise online reading practice framework (ORPF) adapted from RSF by Perfetti and Stafura (2014) was used to clarify the nature of this task to the learners to ensure their engagement and to improve confidence (Figure 3).

Figure 3

ORPF for linguistic response task.

These six steps started from word integration to the text to the assimilation of various information through creating, understanding, and combining propositions in a shared learning platform. This cycle demanded efficient analysis and evaluation of a reading text that developed learners’ CT and KP.

3.4 Data Collection

Mixed methods, both qualitative and quantitative, were designed for this study, and for the collection of data, two instruments were used. For Task 1 in case study 1, the observation tool was used to observe the students’ attitudes and aptitudes with the collaborative tasks and tool individually during the whole semester, and all participants’ responses were recorded. For Task 2 in case study 2, the questionnaire was distributed with clear instructions and explanations to all the participants after they had completed their group activities on blogs. Collecting comparable data was done with ease, and this method of data collection provided greater confidence in drawing a logical conclusion about how and why the integration of social Web 2.0 tools in TBRT can enhance L2 learners’ reading task performance to an expected level.

3.5 Data Analysis

Basic descriptive statistics for the qualitative data collected on learners’ involvement in task 1 on the discussion forum and regression analysis for the quantitative data collected through the survey questionnaire answered by the learners who worked on the blog seemed useful to explain the study of this research. Statistical calculation with Microsoft Excel is done to analyze the qualitative data composed of the respondents and is displayed in a bar chart. This idea highlights that descriptive analysis involves a series of steps: developing a conceptual framework, organizing data according to this framework, identifying key findings, and interpreting them (Altunışık, Coşkun, Bayraktaroğlu, & Yıldırım, 2010). Recent studies further support this view noting that descriptive analysis facilitates not only the systematic organization of data but also the creation of meaningful links between findings and theoretical concepts (Creswell & Creswell, 2018; Gray, 2021). These steps are essential for producing clear and insightful interpretations of research outcomes. On the other hand, the statistical software (SPSS) is used for the result analysis of the questionnaire used for task 2 on a blog. Here regression analysis seemed the best fit to show how the variables are dependent on each other and the degree of influence of the independent variable (Task Interaction) upon dependent variables (CT and knowledge construction). The internal consistency of the questionnaire items is checked with the Pearson Correlation Coefficient, and the reliability of the study tool is verified by Cronbach’s alpha to determine how groups of test items are closely connected. Finally, to give meaning to the analyzed data, the answers are interpreted in a logical meaning chain, and a diagram, percentage data, Likert’s scale, and tables are used to show the outcome and to analyze the collected responses. The steps taken for data analysis will open the door of future research for the successful implementation of web 2.0 tools integrated TBLT for developing the reading efficiency of L2 learners.

4.1 Case Study 1: Reading Supplemented with a Word-Focused Task on the Discussion Board

This section analyzes the experimental group’s progress in vocabulary learning which is considered the key to developing reading comprehension (Strasser et al., 2013) measuring by an observation tool. This checker evaluates students’ progress by justifying four factors: (1) Task interaction, (2) communication, (3) collaboration, and (4) language processing including four sub-domains in each. The analysis of the result depicts learners’ motivation level in task interaction, their experience of participatory culture, and also the attainment of learning outcomes (Figure 4).

Figure 4

EFL readers’ Task 1 achievement on the discussion board. Note: Qualitative data collected through an observation tool (in Appendix A) is integrated to show the range (in percentage) of students’ communication and collaboration to attain language processing skills with Task 1 on the discussion board.

The result depicts that notably 83% of the learners promptly responded to this vocabulary learning task on the discussion board after having clear and concise instruction (Figure 1) but without heeding objectives set in the learning framework (Figure 2). Therefore, in the initial stage, course instructor needed to pay more attention to mitigate interaction gap among the students. Then, with the course instructors’ careful vigilance 71% of the students were found to actively communicate with their peers, whereas, 60% kept themselves engaged in collaboration to make their tasks perfectly done after they had realized the necessity of reading peers’ tasks and following their comments and feedback for fusing different viewpoints into a single shared output. The learners ascertained that the most difficult level of the tasks was “language processing” as cognition is the matter here. As a result, only 67% successfully performed the final task activity on time to be posted for peers’ evaluation. It is noticeable that there is a sharp decline in the percentage between task genuity and final task processing, and the cause is slower progress in collaboration among peers and also in communication. The demographic statistic clarifies that this scenario happens because of learners having little experience of using this collaborative tool in group work and also bearing Gen Z’s trait of remaining individualistic (Mohr & Mohr, 2017). Therefore, it was a big challenge for them to show efficiency in collaborating, resolving conflict, and communicating ideas clearly. However, the task nature and the learning platform involved all the learners from the lower level to the upper in taking part in the activity as well as playing the role of the evaluator where peer evaluation sounds great. Overall, this research study indicates that making more prolonged motivation in tasks for developing reading comprehension skills is a combination of the teacher’s effort in designing tasks as per the suitability of the learning platform as well as learners’ confidence and desire to generate effective communication and collaboration.

4.2 Case Study 2: Linguistic Response Task on Blogs

This section analyzes the data collected through the responses of the experimental group to the survey questionnaire and helps assess how well students developed their CT and KP skills by managing interaction with task 2 on a blog, a collaborative learning platform. A regression analysis that is a powerful reliable statistical procedure to estimate the relationship between variables (task interaction on blog [TIB], CT, and KP) was done after assessing the reliability of the instruments with Cronbach’s alpha (reliability results: TIB = 0.857 and CT = 0.821, and KP = 0.747) The regression analysis results in a summary are shown in Table 3.

The result highlights if task interaction on the blog significantly impacts learners’ CT and KP, which are very important for the deep understanding of a reading text. To test the hypothesis, the dependent variables (CT and KP) were regressed on the predicted variable (TIB). TIB significantly predicted CT, F(1, 33) = 22.88, p < 0.001, which indicates that TIB has a considerable impact on CT (ꞵ = 0.640, p ≤ 0.001). This analysis demonstrates how and to what extent task interaction on the blog positively affects learners’ CT. Moreover, the R ² = 0.409 depicts that the model explains 40.9 of the variance in CT. It indicates that there are 41 units of positive and progressive change in learners’ CT based on one unit that increases task interaction while working on a blog. Once more, learners’ task interaction also significantly influences their KP (ꞵ = 0.366, t = 6.07, p < 0.031), indicating that the collaboration tools somehow ensure learners’ engagement in collaborative tasks and develop their creativity (Figure 5).

Figure 5

The regression weights and beta coefficients for TIB and its effects on CT and KP.

To ensure the robustness of the regression analysis, key statistical assumptions were tested, including normality of residuals, homoscedasticity, and independence of observations. The Shapiro–Wilk test (W = 0.98, p > 0.05) and histograms confirmed that residuals were approximately normally distributed, while Q–Q plots further supported this assumption. Homoscedasticity was examined using Levene’s test (F = 1.45, p > 0.05) and scatterplots of standardized residuals against predicted values, which indicated a consistent variance across the data. Additionally, the independence of observations was verified by ensuring that each response was recorded separately, with the Durbin-Watson statistic calculated at 1.98, indicating a value close to 2, which suggests that there is no significant autocorrelation in the residuals.

To check for multicollinearity, variance inflation factor values were calculated and found to be 1.000 for all predictors, indicating no multicollinearity issues. Tolerance values were also 1.000, confirming the absence of collinearity concerns. These statistical checks validate the reliability of the regression results and confirm that the relationship between TIB and the dependent variables – CT and KP – is statistically sound and interpretable (Figure 6).

Figure 6

Residual diagnostics: Histograms and Q–Q plots for regression models on CT and KP.

The histograms suggest that the residuals for both CT and KP follow a bell-shaped curve, indicating approximate normality. Q–Q plots reinforce this observation, as most points align with the diagonal reference line. The residual spread in both histograms appears fairly consistent, suggesting no major heteroscedasticity concerns, while the lack of strong patterns in the residual distribution supports the assumption of independence of observations. These findings confirm that the regression analysis meets the required statistical criteria, strengthening the reliability of the study’s conclusion.

Overall, the analysis of the study explores that blogs allure learners’ interaction with tasks and contents (both teacher and learner-generated) and provide them more exposure to the reading text, and these develop their motivation, nurture critical thinking, flourish creativity, and finally make them a critic. This finding is parallel to these established results that if the students were provided with collaborative work in social space, they exhibited “a developmental sequence of learning” (c.f. Cowley-Haselden, 2020; Nguyen & Henderson, 2020), as well as extended “confidence in academic reading” (c.f. Kimberley & Thursby, 2020).

5.1 Case Study 1: Vocabulary Inferencing on the Discussion Board

The first case study, which involved vocabulary learning on a discussion board, highlighted the significance of structured tasks in fostering engagement and promoting language development. As noted in the literature, vocabulary is a critical component of reading comprehension (Binder, Cote, Lee, Bessette, & Vu, 2017). This finding is consistent with earlier studies that underscore the need for explicit vocabulary instruction to enhance learners’ inferencing skills (Antonacci & O’callaghan, 2011). The application of the RSF model (Perfetti & Stafura, 2014), adapted for task-based online learning, helped students engage with word structures and contextual meanings through group discussions.

However, the study revealed an interaction gap in the early stages of the task. While 83% of the students promptly responded to the vocabulary task, only 71% actively communicated with peers, and 60% fully engaged in collaboration. This gap can be attributed to the learners’ limited experience with collaborative online platforms, as well as tendencies associated with Gen-Z, such as individualistic behavior (Mohr & Mohr, 2017). These findings suggest that successful task completion in digital environments requires not only clear instruction but also ongoing teacher guidance to foster group cohesion and effective communication (Pietarinen, Palonen, & Vauras, 2021; Yildiz Durak & Atman Uslu, 2023).

The study also demonstrated the importance of scaffolding and explicit instruction in task design. The use of Harmer’s (2007) PPP methodology, along with Dowling’s (2013) 4P model, provided a clear structure that helped students navigate the task. However, while the instructional design supported vocabulary learning, the decline in language processing outcomes (67%) points to the complexity of language cognition tasks. This aligns with findings that vocabulary learning, especially in a foreign language, requires substantial cognitive effort (Torgerson et al., 2019).

5.2 Case Study 2: Linguistic Response Task on Blogs

In the second case study, the linguistic response task on blogs aimed to foster CT and higher-order processing. The regression analysis revealed that TIBs significantly influenced CT (ꞵ = 0.640, p ≤ 0.001) and KP (ꞵ = 0.366, p ≤ 0.031). This supports previous research that emphasizes the role of collaborative tools in enhancing learners’ cognitive abilities and knowledge construction (Zajda, 2021).

Blogs, as a digital learning platform, allowed students to engage in more reflective, in-depth reading, helping them interpret texts and express their ideas through writing. The findings align with the view that reading comprehension is a multifaceted process requiring higher-order thinking skills (Schönpflug, 2023). By integrating CT tasks into collaborative online spaces, the study promoted learners’ academic confidence and creativity, as noted in prior research (Barber, 2020; Vijayakumar Bharathi & Pande, 2024).

Despite the positive outcomes, the study suggests that integrating collaborative tools requires careful planning and consideration of students’ digital literacy. While students’ CT and KP improved, it is likely that unfamiliarity with blog-based tasks created initial hurdles for some learners. This mirrors Ahmed Abdel-Al Ibrahim, Cuba Carbajal, Zuta, and Bayat (2023) findings, which highlight the need for providing adequate scaffolding to ensure students feel confident engaging with academic reading in collaborative spaces.