Scaffolding design to increase reading comprehension for learners of English through online strategy training

Abstract

This study explored the effects of reading strategy training delivered online through an experimental scaffolding tool in comparison to similar training delivered by a teacher, and a control condition. The instructional design of the tool followed scaffolding design guidelines, reciprocal teaching model, and principles of multimedia design. The training provided metacognitive reading strategy instruction to improve reading comprehension through multiple strategies using multiple texts. The participants were 87 college students studying English as a Foreign Language (EFL) at an English medium university in Turkey. At pretest, the control group had scored significantly higher in reading comprehension based on a standardized measure. Both of the experimental groups significantly improved their reading comprehension and metacognitive strategy awareness, while the control group’s reading and engagement scores decreased. The in-class experimental group also improved on the engagement scale. No significant difference was found between the experimental groups or compared to the control group in reading comprehension. The findings have implications regarding institutional policies for teaching reading in EFL and online reading strategy design at the tertiary level.

Keywords

Online reading strategy training scaffolding design reading comprehension in english as a foreign language metacognitive strategy awareness engagement in reading in english as a foreign language

Introduction

Being able to read and communicate in more than one language has become an essential skill in a globalized world, where human migration and digital innovations are both on the increase (Marconi et al., 2020). English is the most commonly taught language in the world, and it is used as a medium of instruction in education in countries where it is not spoken as a first language (Ammon, 2015; Macaro et al., 2018). Mastering reading in English seems essential not only for academic work, but also for succeeding in an increasingly digitized world, since it is also the “digital” lingua franca.

While English has been used as a medium of instruction at all levels of education around the world, its use at the tertiary level is rapidly increasing for a variety of reasons (Fenton-Smith et al., 2017; Macaro et al., 2018). For example, 22.5% of all the undergraduate programs in Turkey’s 203 universities are offered in English (CoHE, 2021), and in many others 30% of the courses are delivered in English, as part of an internationalization effort to meet the challenges of global economy (Kerestecioğlu and Bayyurt, 2018). Therefore, universities have established English language preparatory schools to increase their students’ proficiency level in English upon entry to the university. These schools are under pressure to prepare students with limited English skills for academic reading/writing in a single school year. Consequently, they sometimes make rushed decisions regarding learners’ proficiency levels based on their own proficiency tests.

Since reading is a complex skill essential for academic success, students should be prepared for the demands of academic reading (Grabe and Stoller, 2020). Therefore, teaching reading in English as a Foreign Language (EFL) is important for the preparatory programs in higher education in Turkey (CoHE, 2021). When learners are explicitly trained in reading strategies and how to use them, comprehension and vocabulary scores increase, along with awareness of reading strategies in EFL (e.g. Fogarty et al., 2017; Huang et al., 2009; McNamara, 2017; Soto et al., 2019). Inference making, a vital skill in comprehension (Kendeou et al., 2016) can also be improved with explicit training (McMaster and Espin, 2015). However, EFL teachers may refrain from providing additional strategy instruction in favor of following the textbook, mainly because of large class sizes and lack of time and readily available materials aligned with curricula (Haznedar, 2010; Sadeghi and Izadpanah, 2018). Such shortcomings can be addressed using digital online training, given its time and space independence, opportunity for self-pace, and cost effectiveness (Martin and Betrus, 2019). Thus, digital technologies may provide alternative venues for the delivery of additional reading instruction, such as strategy training (e.g. Ali and Razali, 2019; Dalton et al., 2011; Proctor et al., 2007).

Two lines of research can be identified in reading strategies in digital/online environments: one focusing on how reading strategies are employed in multimedia environments (e.g. Park et al., 2014) by readers at different proficiency levels (e.g. Chen, 2015; Cheng, 2016; Huang, 2014), and the other, on the effects of reading strategy training on reading comprehension (e.g Anderson, 2003; Huang et al., 2009; Shang, 2018). In the latter, the multimedia environments designed for strategy training to increase comprehension tended to focus on a single strategy, such as vocabulary (e.g. Proctor et al., 2007), or inference (e.g. McNamara et al., 2006). The digital environments designed in these studies included some scaffolding features to prompt learners, such as a pedagogical agent giving directions, or feedback.

Since proficient readers make use of a range of strategies, providing training in multiple strategies rather than a single one can help readers develop awareness of ways of improving their comprehension. In addition, abiding by principles of multimedia design (Mayer, 2014), and scaffolding software (Quintana et al., 2004) might provide further benefits.

In this study, an experimental online tool, Meta-S, was designed based on the cognitive theory of multimedia learning (Mayer, 2014), and scaffolding guidelines for learning software (Quintana et al., 2004) to provide training on metacognitive reading strategies (Mokhtari and Reichard, 2002) to college students enrolled in an EFL preparatory school at a university in Istanbul, Turkey. The training addressed the essential components of reading comprehension, such as vocabulary knowledge (e.g. Cromley and Azevedo, 2007; Koda, 2005), prior knowledge (e.g. Meyer et al., 2010; Kispal, 2008), and inference (e.g. Barth et al., 2015; Kispal, 2008). The results were compared to those from the same strategy training delivered by the teacher in the classroom, and a control group. To our knowledge, comprehensive metacognitive reading strategy training and engagement to increase comprehension using an experimental online scaffolding tool were rarely studied in the higher education EFL context. The following are the research questions addressed in the study:

(a) Is there a significant difference in the EFL students’ reading comprehension scores after a reading strategy training delivered online, or face-to-face, compared to a control group?

(b) Are there significant differences in metacognitive awareness of reading strategies and engagement for the reading lesson at the end of the implementation?

(c) Does modality (online vs classroom delivery) make a difference in reading comprehension, engagement, or metacognitive awareness of reading strategies?

Theoretical background

Reading strategy training for comprehension

Reading comprehension is a multidimensional skill that requires the integration of several components and processes. Models of reading focusing on the identification of component skills studied linguistic and cognitive components such as language comprehension (e.g. Kim, 2017) vocabulary knowledge (Koda, 2005), prior knowledge (Kispal, 2008), and comprehension monitoring (Oakhil and Cain, 2012). Those focusing on the process of reading were concerned primarily with the construction of mental representations during reading (Kendeou et al., 2016). These two lines of research have a common ground; both emphasize vocabulary, background knowledge, and inference making either as components that predict reading ability or as separate or compound contributors in the reading process. In this sense, a successful reader would be one who can use strategies such as employing knowledge of background and vocabulary, and making inferences to critically read and understand text.

As strategies are conscious actions, learners are actively involved in selecting and using them to improve reading and language learning. Some strategies are observable, such as taking notes; others are unobservable mental processes such as reflecting on one’s background knowledge or guessing the intention of the writer. Some strategies are never used in isolation, but rather considered part of the same process (Anderson, 2003). These metacognitive or self-regulative reading strategies “oversee, regulate, or direct the language learning task, and involve thinking about the learning process” (Vandergrift, 2002: 559), thus enabling learners to coordinate their own reading processes (Baker and Beall, 2009; Mokhtari and Sheorey, 2002). Similarly, Anderson (2003) hypothesized that metacognitive strategies play a more significant role in reading comprehension compared to others, since understanding how to regulate one’s learning would expedite language acquisition.

While the effective use of reading strategies seems necessary for successful reading both in one’s native language and a second/foreign language (Cesur and Fer, 2011; Erçetin, 2010; Nassaji, 2011), reading comprehension in the latter can be more challenging, due to unfamiliarity with the sociocultural context, vocabulary, or background information (Grabe, 2009). Not surprisingly, explicit teaching of metacognitive strategies was found helpful for EFL learners’ reading comprehension (e.g. Tavakoli and Koosha, 2016).

In strategy training, self-regulative tasks such as summarizing (self-review), questioning, clarifying, and predicting are widely used for monitoring and fostering comprehension. These are generally based on Palinscar and Brown (1984)’s reciprocal teaching model that integrates multiple strategy training in teaching reading. Mokhtari and Reichard (2002) categorized metacognitive reading strategies into global, problem solving, and support strategies. Global strategies encompass general text related strategies such as having a purpose to read, and predicting what the text is about, while problem solving strategies comprise rereading, guessing unknown vocabulary, etc., and support strategies include note taking.

Although its efficiency has not been unequivocal (Rees-Miller, 1993), most researchers agreed that strategy-based instruction had positive impact on reading comprehension, and suggested that effective strategy instruction should be metacognitive (Carrell, 1998; Connor et al., 2019; Taki, 2016). Research has also shown that struggling L1 readers and L2 learners with lower proficiency levels benefit more from instruction in certain types of strategies, such as inference or support strategies, compared to skilled readers (Fogarty et al., 2017; Huang, et al., 2009; Soto et al., 2019). Therefore, metacognitive strategy training can promote novice learners’ metacognitive awareness in reading (McNamara, 2017). In addition, knowing when, where, and how to use these strategies can compensate for difficulties in other aspects of reading comprehension such as vocabulary and background knowledge (Zhang, 2017).

Strategy training in digital/online environments

Strategy intervention studies in digital environments tended to focus on a specific component of reading, such as prior knowledge, and a single strategy, usually, vocabulary-based inference (e.g. Kamil et al., 2000; Connor et al., 2019; Dalton et al., 2011; Proctor et al., 2007; Ranalli, 2013). This can be expected, due to the complex nature of reading, where components and strategies are usually intertwined.

Some of the earlier studies focusing on vocabulary acquisition compared learning vocabulary through classroom instruction to learning via multimedia presentation of vocabulary, and found significant increases in the latter condition (e.g. Tsou et al., 2002; Silverman and Hines, 2009). More recently, Ranalli (2013) compared online vs face-to-face training in L2 in a college-level writing course, where online SBI yielded significant gains in strategic pattern knowledge, and the learners found the instruction effective and relevant. Studies focusing on prior knowledge aimed to compensate the readers’ lack of knowledge of text structure as well as the topic of reading (e.g. Erçetin, 2010; Sullivan and Puntambekar, 2019).

Few of the tool-based studies focused on the effects of comprehensive strategy training to support reading comprehension. Huang et al. (2009) examined EFL learners’ online reading strategies at high and low proficiency levels in a web-based reading program to determine the effects of strategy use on comprehension. They found low proficiency learners who made use of global strategies achieved higher recall scores, while the high proficiency group increased recall scores when they used support strategies with global strategies. Connor et al. (2019) who worked with elementary students from lower SES backgrounds found significant gains after consistent e-book reading in vocabulary knowledge and metacognitive strategy use.

The learning gains seem to increase when multiple strategies are addressed in intervention studies. McNamara et al. (2006) examined the effects of strategy training on adolescent readers’ comprehension through a web-based strategy trainer that provided modeling and practice of comprehension monitoring, paraphrasing, prediction, elaboration, and self-explanation strategies. The findings showed that the success of reading instruction was related to teaching reading strategies, which also increased the number of relevant elaborations, along with self-explanation training. Likewise, the increase in text comprehension varied based on strategy knowledge—the students with low strategy knowledge performed better on the text-based questions, while the students with high strategy knowledge generated more inferences and better answered the bridging inference questions.

Chang and Lin (2019), who worked with university level EFL learners, found a significant increase in the reading test scores after a 10-weeks web-based training on four different strategies. Multiple strategy training using digital tools such as mind-mapping applications, electronic sticky notes, and weblogs showed promising results also for EFL learners with learning difficulties (Jozwik and Douglas, 2017). In a comprehensive review of different technologies in foreign language learning, Golonka et al. (2014) reported that intelligent tutors can be helpful for improving reading comprehension instruction, with increased possibilities for interaction and effectiveness of feedback. For example, Serrano et al. (2017) developed an intelligent tutoring system to teach sixth graders monitoring and self-regulation strategies in task-oriented reading, via dialogues between two animated agents followed by a practice session. The intervention was found beneficial primarily for poor readers’ monitoring skills, who outperformed the control group receiving the same instruction in the classroom.

While the content and design of strategy instruction is crucial in any intervention, training will not be effective if learner engagement cannot be maintained. A major challenge in online learning environment is keeping students engaged, in addition to managing class interaction and complex learning tasks (Chen et al., 2010; Henrie et al., 2015; Muir et al., 2019; Wang et al., 2018). Therefore, a second focus in this study was to determine the engagement level of students in reading strategy training.

Scaffolding in digital/online environments

Appropriate scaffolding of learning is an essential aspect of instructional design also in digitized environments. Scaffolding here refers to software affordances, and not the teacher or a more knowledgeable person that supports the learner. The effectiveness of digital/online learning environments can be increased by offering multiple support systems for learning, even when the content or tasks become difficult to handle.

In earlier research, Sharma and Hannafin (2007) suggested cognitive and interface design elements for technology-mediated scaffolding, and recommended making cognitive processes more explicit, by presenting different sources, emphasizing target structures, and providing metacognition to enable learners to work iteratively. The scaffolding design framework by Quintana et al. (2004) offered guidelines to support the processes of inquiry, such as sense-making, process management, and articulation and reflection. Although the guidelines were originally developed for science inquiry software, some are also valid for designing online reading strategy training in L2. Providing conceptual and visual organizers, and multiple representations will also help EFL learning. The reading strategies of activating prior knowledge, making the strategies explicit, planning, and monitoring coincide with the design features recommended by Quintana et al. (2004).

An important scaffold, expert guidance, is mostly provided by teachers in a conventional classroom setting. In scaffolding software, this role is replaced with pedagogical agents (PAs) or coaching avatars, which can deliver feedback messages, verbal guidance, and modeling, and thus provide an individualized reading experience (e.g. Meyer et al., 2011; Tan et al., 2020). The use of PAs has been found to increase recall and transfer of information (Moreno et al., 2010), students’ perception of the learning experience (Lin et al., 2020), and informative text recall when PAs use politeness strategies (Wang et al., 2008).

Personalized PAs employ personal pronouns to evoke the feeling of being in an informal conversation with the learner, which has been found to increase motivation for the learning material in prior research (Kartal, 2010; Moreno and Mayer, 2004). When PAs provided elaborative, detailed, and user-friendly feedback, learners paid more attention to form and problems in their writing (Ferris, 2003), and their engagement increased (Lin et al., 2020). The Meta-S tool designed in this study made use of scaffolding, and a personalized PA.

Methodology

This study has a pretest-posttest quasi-experimental design, with two experimental and one control group. Intact groups were assigned to treatment and control groups, because it was not feasible to assign individuals randomly (Gay et al., 2011). Although nonequivalent groups have internal validity threat regarding selection (McMillan, 2016), the groups had been formed based on a proficiency exam held by the university, with similar age and gender distribution, and assigned to the same teacher for the reading lesson.

Participants

The participants were 87 college students enrolled in the English preparatory school of a private university in Istanbul, where the first author worked as an English language teacher. There were 28–30 students in each class, with an age range of 18–24. The native language of all the participants was Turkish. According to the placement of the university, their language proficiency level was assumed to be newly achieved B1, however, the groups showed some variance, since the institutional exam allowed a large range within the same group (20 points over 100). This level seemed appropriate for conducting the study since the findings in the literature showed that students with lower levels of proficiency were more likely in need of strategy training (e.g. McNamara 2017). The data from three students were excluded from analysis, because two of them did not complete the tasks, and one was an extreme outlier. Therefore, the final number of participants was 84, with 28 students in each group.

Materials

Reading texts

Three narrative texts were selected from the reading textbook used at the English preparatory school to make sure that the intervention is fully integrated with the curriculum, and aligned with learning goals. An important criterion for text selection was the inclusion of the most common text structures, such as cause and effect, problem solution, compare-contrast, and description. The same texts were used both in the experimental scaffolding tool, Meta-S, and in the training provided by the teacher in the classroom. The control group also worked on the same texts, but with no special mention of reading strategies, other than that found in the textbook.

Reading strategies covered

The strategies covered in the two experimental groups were based on the literature reviewed above. For classification, Mokhtari and Reichard (2002)’s grouping was preferred: global, problem solving, and support strategies. Greater emphasis was given to the global strategies due to their benefits for increasing reading comprehension, especially for low proficiency learners.

Five global strategies were included: (1) having a purpose, (2) predicting what the text is about, (3) activating background knowledge on text structure, (4) noticing text features, (5) making local and global inferences. In addition, two problem solving strategies were addressed: (1) guessing words from the context with signal words, word classes, and words in the vicinity, and (2) rereading. One support strategy, note-taking, was also included (see the Figure 1 and Figure 2 for a sample screenshot).

Figure 1.

Screen shot—Scanning.

Figure 2.

Screen shot—Text structures.

Meta-S

Developed specifically for this study, Meta-S scaffolded EFL learners’ acquisition of metacognitive reading strategies by providing opportunities to implement the strategies covered. While many other tools focused on a few strategy types and/or one specific aspect of reading comprehension, Meta-S provided a holistic approach to strategy instruction and reading comprehension by addressing multiple strategies in multiple texts.

The instructional design of Meta-S was based on scaffolding design guidelines for inquiry software (Quintana et al., 2004) to digitize the reading strategy training suggested by Palinscar and Brown (1984)’s reciprocal teaching model. The interface design is aligned with basic visual design guidelines and Mayer (2014)’s principles of multimedia design. In Table 1, the reading comprehension strategies covered in Meta-S are matched with each design feature and the type of scaffold provided.

Table 1.

Strategies trained for and scaffolding provided in Meta-S.

Classification (Mokhtari and Reichard, 2002)	Reading comprehension strategy (Palinscar and Brown, 1984)	Recommended by	Type of scaffold (Quintana et al., 2004)	Software feature providing scaffolding
Global strategies	Having a purpose	Pressley and afflerbach (1995)	Embed expert guidance	PA’s explanation and modelling
		Mokhtari and Reichard (2002)	Provide reminders and guidance to facilitate productive planning	Log for note-taking to type purpose
		Anderson (2014)	Provide reminders and guidance to facilitate productive monitoring	Reflection scale with a link back to purpose for self-monitoring
	Predicting what the text is about	Pressley and afflerbach (1995), Grabe and Stoller (2020)	Describe complex tasks by using ordered and unordered task decompositions	Text partially faded showing title, pictures, first and last sentences of paragraphsand count-down feature to ensure skimming for predicting
	Predicting what the text is about	Pressley and afflerbach (1995), Grabe and Stoller (2020)	Provide reminders and guidance to facilitate productive monitoring	Log for noting one’s prediction; reflection scale with a link back to prediction to self-assess one’s prediction
	Activating background knowledge on text structure	Pyle et al. (2017), Duke et al. (2021), Hebert et al. (2016), Yapp et al. (2021)	Provide visual conceptual organizers to give access to functionality	Graphic organizer mapping the major and minor ideas to help with text structure; questions to fill out organizer with feedback
			Enable learners to inspect multiple views of the same object or data	Links for further information about text structures; descriptive and comparison tables; practice questions; related videos
			Give learners “malleable” representations that allow them to directly manipulate representation	Drag and drop; charts to construct sentences for main idea; similarities and differences; informative feedback
	Noticing text features	Mokthari and Sheorey (2002), Fisher, frey and lapp (2008)	Restrict a complex task by setting useful boundaries for learners	Hot spots for text features in short pieces; multiple choice or matching for purpose of text; feedback
	Making local and global inferences	McMaster and Espin (2015), Hall (2016), Elleman (2017)	Restrict a complex task by setting useful boundaries for learners	Pieces of text presented for local inferencing, followed by multiple choice questions and adaptive feedback
			Use descriptions of complex concepts that build on learners’ intuitive ideas	Drag and drop for technical terminology inferred from text, followed by feedback
			Enable learners to inspect multiple views of the same object or data	Link to animation about making inferences where characters’ actions say more than words
Problem solving strategies	Guessing word meanings from the context via signal words, word classes and words in vicinity	Pressley and afflerbach (1995), Mokhtari and Reichard (2002), Anderson (2014)	Describe complex tasks by using ordered and unordered task decompositions	Prompts for each strategy to guess words through ordered instruction by PA; multiple-choice questions focusing on one aspect at a time with informative feedback
			Provide reminders and guidance to facilitate productive monitoring	Log for note-taking to record word meanings guessed, to monitor and practice newly learned vocabulary during tool use
	Re-reading	Pressley and afflerbach (1995) Magnusson et al. (2018)	Facilitate navigation among tool and activities	Option to access the whole text under study with one click at all times
Support strategies	Note taking	Mokthari and Sheorey (2002) Pressley and afflerbach (1995)	Facilitate the organization of work products	Option to access note pad with one click at all times; automatically saving of all notes
Tool-specific other strategies	Reflection	Quintana et al. (2004)	Facilitate ongoing articulation and reflection during the investigation	Checklists showing learners what has been covered
	Reflection	Quintana et al. (2004)		Self-evaluation scales after global, problem solving and support strategies, and in the end to rank performance, with options to go back for revision or move forward
	Navigation	Quintana et al. (2004)	Facilitate navigation among tools and activities	Back and next buttons; menu for each activity; pinned buttons for whole text, note-pad, and further information on the top navigation bar

Meta-S delivered instruction in four sections. Training started with an explanation of the strategy under study supported by visuals and screen elements and the image of a PA, with audio and video links, followed by a demonstration of how to apply the strategy in context. Learners were then provided with practice activities, such as text entry, multiple-choice, hot-spot, chart-filling, and drag and drop, all supported by PA’s immediate feedback. Finally, learners were invited to reflect on the material covered, and evaluate their own learning on 5-point Likert scales.

Meta-S was developed in Articulate Storyline 360. The users accessed it online, and user logs were kept by an online tracking add-on (see sample screen shots in the Figure 1 and Figure 2 below).

Procedures and implementation.

The study lasted for 5 weeks, and each weekly session was 90min long. The in-class experimental group was provided explicit reading strategy training in the classroom setting, while the online experimental group used Meta-S in the computer lab. The control group received regular instruction using the same texts, but with no explicit instruction on metacognitive reading strategies other than that provided in the textbook. All the groups were taught by the same teacher-researcher.

Ethical approval was obtained, and the participants’ informed consent was secured at the beginning of the study. The intervention was carried out during regular class hours. The learners were allowed to go at their own pace, and take notes if they wished. While the control group and in-class experimental group took paper and pencil notes, the online experimental group was able to take notes on a notepad provided in Meta-S. The teacher provided assistance when needed.

Instruments

A standardized reading comprehension test and two inventories were used to assess the effects of the training. In addition, the online tool group completed a user feedback questionnaire at posttest. All participants filled out a demographic questionnaire at the beginning of the study,

Reading comprehension was measured by the reading section of the Cambridge Preliminary English Test (PET), an international standardized placement exam (B1 Preliminary, 2016). The PET was preferred as an objective measure with appropriate validation as an internationally recognized standard test. It consists of 35 questions, including multiple-choice, true-false, and matching, with a focus on inference and vocabulary questions. Each question is worth one point. Testing the results against an objective measure was important for the study, given the school’s need to bring all learners in a proficiency group to the same level. The reliability of the PET Reading test was reported 0.88 by the developers (Cambridge Assessment English, n.d.). The reliability coefficient for this sample was 0.68.

The Turkish version of the Metacognitive Awareness of Reading Strategies Inventory (Mokthari and Sheorey, 2002) was employed to assess the participants’ perceived metacognitive awareness and strategy use before and after the intervention. The inventory was adapted and validated in Turkish by Öztürk (2012). The survey consists of 30 questions based on a 5-points Likert scale. The maximum score is 150. The Classroom Engagement Inventory (CEI) was employed as a measure of engagement, originally developed by Wang et al. (2014), and adapted for use in Turkish by Sever (2014). The inventory consists of 23 items assessing students’ level of engagement and disengagement during class, based on a five point-likert scale, with a maximum score of 115. The reliability coefficients for the Turkish versions of MARSI and CEI for this sample were 0.87 and 0.83, respectively.

Finally, user feedback was collected from the participants in the Meta-S group, via five open-ended questions, about the interface, features of the tool that are liked most, and the strategies that helped students the most and in what ways. The answers were tallied and grouped for each question. Common themes were detected and the total number of answers in each theme was summed. This was meant for user feedback on the Meta-S interface, and therefore a detailed qualitative analysis was not conducted.

Findings

In this section, the pretest scores of the three groups are compared first, to select an appropriate statistical test. Then the analyses of the pre and posttest results are reported, followed by a summary of the findings from the user feedback questionnaire about Meta-S.

Analysis of the pre and posttest scores

The data met the normality and homogeneity of differences assumptions, and one-way ANOVA on the pretest scores showed that the groups were not equal at the beginning of the study. The control group’s pretest scores for PET were significantly higher than both of the experimental groups (p = 0.001). There was no statistically significant difference between the two experimental groups. In addition, the online tool group showed a significant difference compared to the control group on the pretest MARSI (p = 0.024), and CEI scales (p = 0.017). There was also a significant difference between the tool group and the in-class group based on the pretest CEI scores (see Table 2 for descriptive statistics). There were no significant differences between the in-class and control groups regarding these two scales.

Table 2.

Descriptive statistics for pre-and post-test scores.

Groups	Control		In-class		Online tool
Pre-test	M	SD.	M	SD.	M	SD.
PET	20.85	3.69	15.46	2.92	13.57	4.12
MARSI	99.64	15.40	106.57	14.97	110.42	12.07
CEI	82.50	8.47	80.50	11.24	87.35	8.26
Post-test	M	SD.	M	SD.	M	SD.
PET	19.46	3.51	17.07	2.29	17.64	2.89
MARSI	101.03	13.70	113.25	15.14	118.85	12.75
CEI	78.14	8.71	85.17	10.49	87.57	9.93

Note: PET= Preliminary English Test. MARSI= Metacognitive Awareness of Reading Strategies Inventory (Turkish version). CEI= Classroom Engagement Inventory. N = 28 for all groups.

Therefore ANCOVA was run on the posttest scores to control for the pretest scores, after checking to see whether the data met the assumption of homogeneity of regression slopes. The ANCOVA results showed that the experimental groups did not significantly differ from the control group in terms of performance on the PET at the end of the study, despite the significant difference at the beginning.

The ANCOVA conducted on the posttest scores from the two scales showed that there was a significant difference among the groups both for MARSI (F (2, 80) = 7.82, p = 0.001, partial η2 = 0.164) and CEI (F (2, 80) = 7.82, p < 0.000, partial η2 = 0.222) after the pretest scores were factored in the analysis as a covariate. Pairwise comparisons showed that the MARSI mean scores for both the online tool group (M = 118.85, SD = 12.75) and the in-class training group (M = 113.25, SD = 15.14) were significantly higher than the control condition (M = 101.03, SD = 13.70) at the p = 0.017 and p = 0.001 levels respectfully. The CEI mean scores for both the online tool group (M = 118.85, SD = 12.75) and the in-class training group (M = 113.25, SD = 15.14) were also significantly higher than the control condition (M = 101.03, SD = 13.70) at the p = 0.007 and p < 0.000 levels respectfully. There were no significant differences between the online tool and in-class groups for either the MARSI or CEI posttest scores.

Paired samples t-tests showed that both the online tool group (p < 0.000), and the in-class group (p = 0.029) significantly improved their reading comprehension scores, while the control group scored significantly lower in PET at the p = 0.043 level. The in-class group significantly improved their scores from pre-to posttest on both MARSI (p < 0.000) and CEI (p = 0.003) scales, while the online tool group showed significant improvement only on the MARSI scale (p < 0.000), and no significant difference on CEI. The control group, on the other hand, showed a significant decrease on CEI (p = 0.001), while an insignificant slight decrease on MARSI.

Meta-S feedback

The results from the feedback questionnaire are based on the responses from the 27 out of 28 participants in the online tool experimental group who used the Meta-S. The feedback showed that the participants’ experience with the tool was mostly positive. Table 3 below displays the questions in the questionnaire, common themes identified, the frequency of each theme, and sample answers for each.

Table 3.

User feedback about Meta-S.

Feedback question	Common themes	No of responses	Sample response
Q1: What do you think about the strategy training you have received?	Helpful content	9	I think this study and strategies greatly helped us improve our reading skills
	Future use possible	5	When I read articles in my department, I will use these strategies
Q2: Which strategies helped you the most?	Guessing unknown words	10	I now try to guess the meaning of a word instead of looking it up in a dictionary
	Text structure	5	Finding the text structure helped me understand the text better
	Predicting	5	Predicting what the text is about was helpful for me
Q3: How did these strategies help you?	Focused attention	6	I realized that I improved a lot. I used to start reading directly, now I know what to pay attention due to these strategies
Q4: Which features of the tool did you like the most?	Skimming and scanning	4	I liked the skimming and scanning activity which shows what to do step by step with the audio and the blocks
Q5: What were the difficulties in the tool or in the instruction?*	--	3	I need more concrete materials such as books while learning, so getting used to the tool was difficult for me
			I had difficulty in finding the main idea of the text
			One minute was too short for me to skim and scan the text. I also had difficulty with comprehension questions in notepad

Note: *Only three students answered the last question about user interface issues and content related difficulties. Therefore, no common theme is reported.

The most frequent answer to the question about the students’ general assessment of the training delivered by Meta-S was that they found it helpful and transferrable to future reading tasks. When the students listed the most helpful strategies covered in Meta-S, guessing unknown words from context was the most popular. Text structure and predicting what the text is about were other strategies they found most useful. When asked about the ways in which the strategies helped them, the most frequent comment was that they learned what to pay attention to during reading. In response to the question about the most liked features of the tool, the step-by-step skimming and scanning activity was pointed out most frequently. The last question about the interface and the difficulties regarding training was answered by only three students. The answers they gave were about lack of experience with computers, limited time, and answering questions in the notepad feature of the tool.

Discussion

In this section, the findings will be explained within the context of the study, and then implications for institutional and general policy will be discussed. Finally, recommendations will be provided for the design of digital learning environments for strategy training in reading comprehension in EFL.

The results of the statistical analysis showed that the experimental groups fell short of outscoring the control group in the reading comprehension test. This might be because the control had already scored significantly higher at the beginning of the study, despite the placement of all three groups within the same proficiency level (B1) by the preparatory school. Such a finding can indicate that the reading strategy training provided in both of the experimental groups helped increase the learners’ reading comprehension to a level where there was no significant difference compared to the control group.

That the two experimental groups did not differ significantly in reading comprehension indicates that a computer-based modality can be as effective as in-class training, when instructional design strictly follows guidelines in the literature. This is consistent with findings from other studies where design is closely based on research (e.g. Dalton et al., 2011; McNamara et al., 2006). That these findings were obtained through an internationally validated instrument can also be noteworthy, as most of the technology-mediated studies of reading in EFL were generally based on custom made non-standard measures (Hsieh and Huang, 2019; Lin and Lin, 2019). Within groups comparisons for both of the experimental groups were also positive, since the students in both groups improved their reading comprehension, pointing to the effectiveness of scaffolding in reading strategy training, regardless of modality.

In respect to metacognitive reading strategy awareness, both of the experimental groups increased their scores significantly compared to the control, and pairwise. This is encouraging given the context of the study, and also more generally, because of a need to advance English skills shortly upon entry to the university, due to the increasing preference for English as the medium of instruction in higher education in Turkey (Kerestecioğlu and Bayyurt, 2018), and around the world (Macaro, 2018). This can be considered a contribution of the study, given the unequivocal findings in the literature (Wang, 2016; Wilkins, 2014), and few studies on metacognitive awareness and strategy training in computer-based online environments (Altıok et al., 2019).

As for engagement, highest improvement was observed in the in-class experimental group, both within groups and compared to the control, indicating a successful implementation of the strategy training in the face-to-face classroom. While the students in the online tool group also outscored the control in engagement, they showed no significant difference within groups, probably because they already had the highest engagement levels at the beginning of the study. This finding can be interpreted as an indication that the design of Meta-S helped keep the extraneous cognitive load to a minimum (Mayer, 2014), so that the students who used it maintained their engagement, despite the challenges associated with online learning environments (e.g. Chen et al., 2010; Henrie et al., 2015; Muir et al., 2019; Wang et al., 2018).

The unexpected decrease in the control group’s reading comprehension and engagement scores, on the other hand, has important implications for how the reading lessons are structured, delivered, and assessed at the institutional and policy levels. The reading course at the university where the study was conducted had a streamlined structure, with warm-up questions presented before a text on a specific topic, followed by comprehension and vocabulary questions, and only occasionally included activities for strategy training. Although this kind of skill-based lessons and textbooks can engage students at the beginning, the repetitive pattern may cause a loss of interest as the semester pursues. Given the importance of engagement for learning (Järvelä and Renninger, 2014), it may not be surprising that the reading comprehension and engagement scores moved in the same direction. A lack of challenge can be another reason for the falling scores in the control group. When students feel bored, isolated, or insecure, their focus will shift to emotional well-being, and therefore they might “deliberately withhold effort from the learning task or seem to work playfully with less vigilance” (Boekaerts and Corno, 2005: 204). Since the students in the control were already ahead of their peers at the beginning as detected in the pretest, the reading lessons streamlined for the same level might have fallen short of providing them sufficient challenge, and hence decrease their engagement.

This particular finding also has implications for how reading is assessed at the institutional and policy levels. Contrary to the university’s placement test, the control group was not at the same level as the experimental groups before the implementation. Using a validated standard measure may provide more appropriate placement in different tracks. The results also indicate that reading instruction that is not supported by reading strategy training may not prove effective when tested against a standardized measure. This might be because standardized international tests, such as the PET, require not only text-based surface level reasoning, but also inference making. Starting from B1, higher level reading comprehension strategies such as inference making should be included in instruction and assessment, because the purpose of the English language preparatory schools is to prepare students to critically read and comprehend academic texts. The constraints imposed by the need to cover a dense syllabus in limited time can be overcome by reading strategy training provided online by a carefully designed scaffolding tool, such as Meta-S.

The feedback from the participants who used Meta-S demonstrated that they found the tool beneficial not only for the reading lesson but also for the academic skills they needed in other courses. The design of the activities such as text structure, graphic organizers, extra information, and vocabulary activities were favored by the learners. Among these, background knowledge of text structure and vocabulary were found to be the most helpful strategies, as has been reported elsewhere (Kispal, 2008; Koda, 2005; Rapp and Braasch, 2014; Zhang, 2017).

A major contribution of the study lies in its scaffolding design and multiple strategies covered in multiple texts in the training. Most studies in the literature focused on one or two types of reading strategy, with no particular focus on scaffolding design. However, a more comprehensive strategy training with appropriate scaffolding, as in this study, seems to be more beneficial for adult leaners who are expected to learn EFL rapidly so that they can pursue their academic programs in college. In addition, it seems necessary to explore the possibility that strategy training for EFL learners might be more beneficial than for L1 or ESL learners, who have been the target of many studies earlier (e.g. Dalton et al., 2011; Fogarty et al., 2017; McNamara et al., 2006).

As Oliver (2013) argued, technologies cannot be assumed given or neutral but must be appraised, selected, and designed, which is only possible when design decisions are made carefully, supported by research. Based on the findings of this study, the following design guidelines can be recommended for online reading strategy training for EFL learners, to help turn a naturally receptive skill into an active one:

(a) Segmenting the content, signaling the beginning and the ending of each instructional section (Mayer, 2014), and integrating previous learning with the new information.

(b) Providing notepads and graphic organizers that present learning objectives to supply a reading purpose; checklists and surveys to keep track of one’s own learning process.

(c) Pedagogical agent offering detailed, informative feedback for every activity, usually not possible in a conventional classroom setting due to the number of students and limited time.

(d) Concurrent narrative text and audio, and hyperlinks for supporting information.

(e) Components that enable learner interaction to increase engagement

Despite the fact that this study was conducted earlier, the design guidelines recommended seem to have relevance for teaching and learning remotely in emergency contexts such as the COVID-19 pandemic of 2020–2022. The online learning experience in this study was far from the isolation of the students and teachers due to lockdowns, however, the guidelines offered above, particularly regarding the presence of a pedagogical agent, and inclusion of features enabling interaction are relevant for the design of online learning environments employed also in the context of unexpected circumstances where social-presence is lacking.

Limitations

The findings of this study must be approached with some caution since it was conducted with a specific learner profile—college students learning English at a university in Turkey. Although the reading strategies covered were probably one of the most comprehensive compared to other studies in the literature, the number and type of texts used were limited, and the time allocated for the training was limited, given the curricular and temporal constraints imposed by the school setting. For a complete set of design guidelines in digital/online metacognitive strategy training for EFL learners, further research is needed with varied learner profiles at different levels of schooling with a larger number of participants and for a longer duration, where multiple text types are employed.

Conducting research in one’s own classroom poses limitations, such as researcher bias. On the other hand, it can help ensure fidelity of implementation, and minimize confounding factors resulting from teaching style. In addition, scrutinizing one’s own practice has many advantages for teacher/researchers, as evidenced in the action research tradition.

Another limitation of the study was the insufficiency of the physical facility where the participants in the online tool group received training. The computer lab was initially not accessible to the preparatory school students, and had many infrastructural problems, which cost time loss at the beginning of the study. Another limiting aspect can be that some students may have low interest or less comfort in technology-mediated learning. Despite the fact that the interface was quite intuitive and similar to other software applications, one participant mentioned her discomfort using computers for learning in her response to the feedback questionnaire. Regardless of the friendliness of the interface, an introductory session could be conducted to familiarize all users with the interface, which could not be carried out in this study due to time constraints.

Each technology-mediated learning design effort will have to take into account the specific learner needs and the features of the context. Since this was more of an exploratory study, it will not have the statistical rigor of randomized studies the findings of which can be generalized. However, the purpose here was to provide a model for a robust learning design that works, which can be adapted by other educators, researchers, teachers, and which policy makers can build upon. Further research is needed to examine fully the relationship between engagement and learning in technology-mediated learning environments.

Footnotes

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Günizi Kartal

Author Biographies

Gamze Ucak completed her MA degree in Educational Technology at Bogazici University. She is currently a PhD student in Learning Sciences at the same university. She is employed as an English instructor and IT and planning unit specialist in the English Preparatory Program at Istanbul Medipol University. Istanbul, Turkey. Her research interests include the design of digitally scaffolded learning envrionments for learners of English a a Foreign/Additional Language. Email: gamze.ucak@boun.edu.tr

Dr. Gunizi Kartal is the head of the Department of Computer Education and Educational Technology at Bogazici University in Istanbul. She is also the director of the Center for Educational Technology Research and Implementation. She earned her doctorate at Teachers College, Columbia University, in Language, Literacy, and Technology. She worked at IBM's T.J. Watson Research Center in New York, as part of a research project on speech recognition technology for reading practice. Her current research interests comprise design of digital technologies for reading, and computational thinking, and preservice teacher education in information and communication technologies and computer science.

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