The impacts of visual input enhancement, semantic input enhancement, and inputflooding on L2 vocabulary among Iranian intermediate EFL learners

Abstract

In this study, 92 Iranian intermediate EFL learners (17 to 22 years) took part in 14 sessions in which they were taught L2 vocabulary through three input enhancements, i.e., visual input enhancement, semantic input enhancement, and input flooding. In fact, the selected participants were divided into three experimental groups and one control group. Using a before and after design, students were retested after 14 sessions. Indeed, at the end of the treatment, two posttests of comprehension and production of L2 vocabulary were administered. After data collection and running two One-way ANOVA tests, the results showed that all three experimental groups had better performances on their post-tests compared to their pre-tests. Furthermore, regarding the three input enhancement techniques used in this study, the findings indicated no significant difference among them so far as Iranian intermediate EFL learners’ comprehension and production of L2 vocabulary were concerned. We propose that, under supporting conditions, there can be clear benefits for EFL learners to spend time mastering L2 materials through input enhancement techniques.

Keywords:

• L2 vocabulary
• vocabulary comprehension
• vocabulary production
• visual input enhancement
• semantic input enhancement
• input flooding

PUBLIC INTEREST STATEMENT

Vocabulary is one of the most important competencies needed to teach and learn a foreign language. It is the basis for all other skills to be developed: reading comprehension, listening comprehension, speaking, writing, spelling and pronunciation. Vocabulary is the students ‘ main tool in their attempt to make successful use of English. When faced with a native English speaker, watching a film without subtitles or listening to a favorite English song, reading a text or writing a letter to a friend, students will always have to work with words. Considering the vital role, teachers are always searching suitable and successful techniques to teach vocabulary. In this study, the impact of three input enhancement techniques, i.e., visual input enhancement, semantic input enhancement, and input Flooding have been investigated. After analyzing the data, it was revealed that all three techniques had a significant impact on improving Iranian intermediate EFL learners.

1. Introduction

As a building block, vocabulary acquisition plays a fundamental role in any attempt to learn a second or foreign language, without which the learning process and use of a target language would be hindered immensely. In fact, one of the main reasons that special attention is paid to vocabulary learning is the experience that learners face with countless new and unknown terms while they are processing text (and speech), bringing about multiple difficulties, particularly in comprehension. As many researchers have ascertained (e.g., Shin & Nation, 2007; Stahl, 1990), a good repository of vocabulary knowledge can lead to an absolute understanding of a text. In English for Academic Purposes (EAP) and also English for Specific Purposes (ESP) research, vocabulary studies have played a long and significant role (Hyland & Tse, 2007). More specifically, academic vocabulary is defined as a core of high-frequency words that are found to be beneficial across academic disciplines (Shakibaei, Shahamat, & Namaziandost, 2019), (as opposed, for example, to discipline-specific terms such as medical, legal, mathematical, or chemical). In addition to the obvious role of vocabulary learning, development and use of it is of paramount importance Accordingly, the idea of input enhancement (IE) has gained special consideration from many researchers in the SLA area in anticipation of extending strategies for vocabulary teaching and learning. Sharwood Smith (1993) suggested input enhancement as a sub-category of form-focused instruction and concentrated the role of making characteristics of a language perceptually more conspicuous, representing the tension, agreement, and a number of other characteristics (e.g. accent, syllable stress, agreement, idioms).

Although there has also been a lot of research that gives unequivocal propositions and how many and which lexical items and chunks may be of primary significance for teaching students (e.g., Shin & Nation, 2007), there is less agreement about how instruction can effectively help this process. There is evidence that explicit grammatical and lexical instruction has a greater impact on learning than implicit teaching (Spada & Tomita, 2010) but as yet there are no deterministic responses to the kind of explicit teaching which leads to the most efficient learning of second languages. It may additionally be the case that the impacts of explicit teaching can be incremented through making the input learners receive as noteworthy as possible. The utilization of input enhancement (IE) as a way of augmenting noticing and learning has been one area of abiding surveillance in the research in particular upon the utilization of different sorts of textual enhancement (TE). TE usually entails enhancing a text while making bold, italicized or underlined the target objects.

The effect of TE has been studied in regard to a range of second languages alongside forms of explicit teaching (e.g., Zarei & Esfandiari, 2016) and an independent variable (e.g., Petchko, 2011) but findings have been amalgamated (Han, Park, & Combs, 2008). Aural enhancement (AE), whereby listening texts are controlled and modified to boost the prominence of target items (such as making the recording of those items louder or reiterating target items) has not been sufficiently researched, and what outcomes which are available are similarly indeterminate (e.g., Namaziandost, Neisi, Kheryadi, & Nasri, 2019; Reinders & Cho, 2011). However, TE studies have concentrated on grammatical structures rather than lexical components and AE and TE have been under-studied in amalgamation with explicit instruction. This research is an attempt to fill this void and provide some proof that TE can be a beneficial incorporation to vocabulary learning, as it can swiftly draw the attention of learners to the form and utilization of a word, something Nation (1999) proposes can be beneficial. As a technique, TE has the advantage of being potentially exceedingly adaptable and multifaceted. It could be applied for peripheral learning or intentional learning based on Coxhead’s Academic Word List (2000) or even utilized by learners themselves as an intentional learning strategy. The utilization of such strategies by learners has been characterized by Folse (2004) as a necessary feature of prosperous vocabulary learning.

2. Literature review

2.1. Input enhancement

The term ‘input enhancement” created by Sharwood Sharwood Smith (1991, 1993), who proposed that some types of enhancement may be beneficial to make input more prominent to students. Without such prominence, he believes, learners may not find features in the input they receive because a great deal of information is likely to be analyzed for meaning. Noticing, as explained by Schmidt (1994), Schmidt (2010) can be defined extensively as “conscious registration of attended particular instances of language” (Schmidt, 2010, p.725). It is this vigilant identification which is regarded as the first stage necessary to change input into the intake, and input improvement can be seen as one kind of’ consciousness raising’ (Sharwood Smith, 1981) exercise, which various scholars and instructors can utilize to aid students to identify the forms within input they understood. Sharwood Smith (1993) proposes numerous methods which might be utilized to develop input, containing text bolding for visual input and reproduction of targeted objects for audible input. These kinds of input enhancement would appear to be of specific relation in beginner training since in the initial stages of learning a new language, all information is absolutely paramount to the learner and hypotheses often have little idea as to which language parts are essential or more beneficial in the long term.

Different input improvement strategies can be referred to as typographic exploitation, input flooding, explicit instruction, marginal glosses, translation or interpretation (semantic development), corrective feedback, form-comparison and explicit training (Dastjerdi & Farshid, 2011; Lee & Lee, 2012; Namaziandost, Shatalebi, & Nasri, 2019). Three of the strategies alluded above, which are the subject of the current study, are further discussed below.

Visual Input Enhancement (VIE) is also known as’ textual or typographic enhancement’ or, in one instance, as Rashtchi and Gharanli’s’ visual input engineering’ (2010). VIE, as the name proposes, visually accentuates input. The opinion is to make definite components of input, which can otherwise be overlooked, visually considerable and eminent to learners. In other words, visual enhancement is incidentally used to enhance deterministic forms in the text or written input (Fahim & Vaezi, 2011; Namaziandost, Hashemifardnia, & Shafiee, 2019).

2.2. Input enhancement and vocabulary learning

As L2 vocabulary, studies on input improvement have been fixated on singular words. Kim (2006) investigated the arrangement of significance—lexical elaboration and printed upgrade—as two essential contemplations that impact the accidental obtaining of jargon by Korean students of English. The result was critical when the TEI was utilized together with lexical multifaceted nature, and it eventuated the understudies’ better acknowledgment of focused words or structures. IE procedures have been demonstrated to be similarly compelling as unequivocal guidance as demonstrated by Fahim and Vaezi (2011) among Iranian moderate EFL students. The outcomes of the examination demonstrated that both outwardly improved info and direct educating significantly affected the obtaining of action word thing lexical collocations. So also, the viability of visual info upgrade was contemplated by Kim (2008) whose review was intended to build the remarkable quality of obscure English words (with regards to perusing a book). The outcomes revealed that visual info upgrade helped the students’ notification the structures; be that as it may, the level of dubious learning of jargon did not create inside the understanding procedure. Further examinations have indicated that semantic information improvement has been unmistakably more powerful than visual info upgrade. For example, Rott (2007) found that a higher info recurrence was useful for students and that the semantic improvement utilizing shines supported the measure of profitable vocabulary learning. Williams (2005) believes that visual input enhancement may absorb the heed of learners to the written form of textual input and this strategy can be extensively utilized to navigate the attention of learners to the vocabulary. There is also other research that investigate the input enhancement hypothesis not only in the vocabulary field (Kim, 2008; Maftoon & Sharifi Haratmeh, 2012; Rassaei & Karbor, 2013; Zarei & Esfandiari, 2016) but also in other fields such as grammar, reading (e.g., Nahavandi & Mukundan, 2013). Therefore, the current study tries to find the check the impact of visual input enhancement, semantic input enhancement, and input flooding on vocabulary comprehension and production among EFL students.

Leow, Egi, Nuevo, and Tsai (2003), and Lee and Lee (2012) allude to various researches that utilized typographic distortion such as underlining, capitalizing, utilizing various kinds and sizes of fonts, color coding, bold-facing, italicizing, etc. in input to improve visual eminence.

One indirectly accomplished form of IE is input flooding, which is useful to those learners who enjoy exploration learning (Hamed Mahvelati & Mukundan, 2012; Ziafar & Namaziandost, 2019). ELT researchers repeatedly employ this type of input enhancement, which uses quantity as its essential function. Similar to visual input enhancement, the main theme underlying input flooding (IF) is that exposing learners to target objects enhances their prominence repeatedly (Abedi, Namaziandost, & Akbari, 2019) and the process of acquisition of will be simplified. (AsadiAmirabadi, Biria, & Sedaghat, 2014). Horst, Cobb, and Meara (1998) note that the use of iteration in a text or several texts provides learners an ability to process these repeated objects, and is also useful for implicit retention of vocabulary. Semantic Input Enhancement (SIE) involves providing the semantic characteristics of the target items to concentrate on those items and augment the attention and hence longer retention (Zarei & Esfandiari, 2016). Meaning’ is the primary aspect identified by scholars and linguists in different interpretations. For example, Barcroft notes that semantic elaboration is “the augmented assessment of an item as to its significance” (2004, p. 323). He also believes that this type of convolution leads to better retention and recognition of target forms, contrary to structural convolution.

2.3. Previous studies

The impact of input enhancement on the learning of specific forms has been checked by a number of researches. Previous studies have revealed that strategies for developing inputs can have a positive effect on the comprehension or production of a particular target type or structure by the learners. For example, Hamed Mahvelati and Mukundan (2012) compared the learning of lexical and grammatical collocations through an incidental input enhancement method (input flood) and an intentional one (consciousness-raising approach). The participants were divided into two experimental groups and a comparison group. The learners in one of the experimental groups received treatment for input flooding, while the other group members were provided with explicit instruction on collocation. The findings showed that while input flooding was successful, the learners in the group of consciousness-raising outperformed those in the group of input flooding, more significantly.

In a relatively similar research on conditional retention, AsadiAmirabadi et al. (2014) investigated the long-term impact of input enhancement and input flooding on the output of Iranian EFL learners. Seventy-five participants were divided into three experimental groups: input flooding, input enhancement, and a mixture of both. After 3 weeks, the posttest administered demonstrated that the group which received both IE and IF performed better than the other two.

Lee and Lee (2012) conducted one of the few studies which had considered three IE techniques. Their work on the immediate and delayed recall of English vocabulary is similar to the present study, investigating the effects of visual enhancement, semantic enhancement, and flooding of inputs. They argued that although these IE strategies did not affect delayed identification of meaning, they affected immediate meaning and type recognition to varying degrees in a positive way.

Resembling outcomes have been documented in a recent study by Birjandi, Alavi, and Najafi Karimi (2015), who studied the impact of three forms of feedback on English phrasal verbs acquisition. Thirty-five students at the intermediate level of English language skill obtained six different texts in unenhanced, typographically improved and lexically detailed forms; Based on the performance of the participants on the posttest, expanded text was more successful than the other two forms of input, and typographically enhanced type was more efficient than unenhanced form of input.

Ertürk (2013) explored the potential effects of pushed output, input processing and visual improvement on EFL/ESL learning and retention promotion. The findings demonstrated that visual improvement of inputs was not effective in drawing the attention of the learners to the intended target items.

Although a substantial number of studies has been carried out on the impacts of input enhancement techniques on different parts of language learning, few have concentrated on comparing these techniques or their impact on the comprehension and production of L2 vocabulary. Hence, the present study aims to investigate the effects of three input enhancement techniques on the learning of vocabulary by Iranian EFL learners. To fulfill, this study aimed to answer the following questions:

RQ 1. Does visual input enhancement, semantic input enhancement, and input flooding have any significant effect on Iranian EFL learners’ production of L2 vocabulary?

RQ 2. Does visual input enhancement, semantic input enhancement, and input flooding have any significant effect on Iranian EFL learners’ comprehensive knowledge of L2 vocabulary?

3. Method

3.1. Participants

The participants in this study were 92 male EFL learners whose ages ranged from 17 to 22. They were randomly chosen from a pool of a population of 175 learners who were enrolled in general English classes in a private language institute and were exposed to 4 h of classroom instruction each week. The participants had a prior exposure to EFL in primary and secondary schools, 2 to 4 years of which were formed in private language institutes. They were divided into four equal groups including three experimental groups, namely Group A (visual input enhancement (VIE)), Group B (semantic input enhancement (SIE)), and Group C (input flooding (IF)) and a control group (CG)) as Group D. Each group included 23 participants A form of consent for participation was administered with an indication of the general purposes to investigate English language learning and procedures of the study.

3.2. Instruments

3.2.1. Placement test

A sample of Oxford Placement Test from Solutions Book, 2nd Edition (Edwards, 2009), including 50-item vocabulary and grammar testing, was conducted to determine the population skill level. Participants were put on a CEFR-based intermediate level of language competency, B1-B2.

3.2.2. Pretest

The main instrument used in this study was a vocabulary test. It included 90-items which aimed to measure the respondents’ degree of familiarity with the target forms at the outset of the study. The pretest was actually a multiple-choice test in which the participants must select the appropriate option. Every object was an English sentence that omitted one or two vocabulary elements leaving only the first letter to rule out other potential vocabulary. The vocabulary parallels for L1 have also been given (Zarei & Esfandiari, 2016). Certain elements unknown to the students were chosen for inclusion in the posttest.

3.2.3. Treatment passages

Fourteen reading passages on a range of academic topics were selected randomly from among more than 50 academic passages retrieved from an online website that enhanced the academic words textually (www.uefap.com). The learners who were assigned to experimental groups, were exposed to passages whose academic words were bold-faced, italicized, and underlined within instructional sessions, whereas the control groups’ academic words within the passages were not enhanced through any IE techniques. The group of visual enhancements had the words enlarged, bolded and stressed. The semantic enhancement group received passages accompanied by the vocabulary equivalent L1, parenthesized immediately after the articles. The passages of the input flooding group were longer than the other groups since they contained more phrases with the target vocabulary in them (Zarei & Esfandiari, 2016). On the other hand, the control group received passages with no enhancement.

3.2.4. Posttest

The last instrument utilized in this study was a vocabulary comprehension and production test which was administered at the end of the treatment. The posttest included 2 parts: in one part, there were 40 multiple choice items which aimed to investigate participants’ comprehension of vocabulary. The second part consisted of 40 items which aimed to measure the participants’ productive knowledge of vocabulary. The test was in fill-in-the-blanks format, in which the participants were asked to give one of the elements of the vocabulary. The Persian equivalent of the vocabulary and the first letter of each blank were given to prevent the provision of other possible words which could be used in the context of the sentences (Zarei & Esfandiari, 2016). It is worth mentioning that the reliability of the pretest and post-test was calculated through Cronbach alpha formulas as it was 0.898 and 0.916, respectively. Moreover, both pre-test and post-test were validated by five English experienced teachers.

3.3. Procedure and data analysis

To do the current study, first the researcher attended the English institute mentioned above and administered the OQPT in order to manifest the participants’ homogeneity in terms of English language proficiency. Ninety-two participants out of 175 were selected for the target participants of the present study. Then, they were divided into four equal groups; three experimental groups namely, visual input enhancement (Group A or VIE Group), semantic input enhancement (Group B or SIE Group), and input flooding (Group C or IF Group) and one control group (Group D). Then, they were pretested through a 90 multiple-choice item test. The time allocated to answer the pretest was 70 min to respond to the test. The responses were examined and items that were previously known to the participants were omitted from the posttests. Next, the participants received the treatment. During the treatment, each group specific input enhancement techniques. That is, group A received visual input enhancement (using typographical tools such as font color and font size change, underlining or boldfacing), group B received semantic input enhancement (vocabularies were enhanced with the provision of Persian meaning), group C received input flooding (multiple iterations of target items in their passages), and group D received no input enhancement technique.

After the treatment period, which lasted for 12 weeks, a 40-item multiple-choice comprehension posttest and a 40-item fill-in-the-blanks production posttest were administered. The participants were had 70 min to answer the test. To answer the research questions, two one-way ANOVA tests were run on the obtained data.

4. Results

Before conducting any analyses on the pretests and post-tests, it was necessary to check the normality of the distributions. Thus, Kolmogorov–Smirnov test of normality was run on the data obtained from the above-mentioned tests. Since all the p values were larger than .05, it could be concluded that the distributions of scores had been normal. It was thus safe to proceed with a parametric test (i.e. one-way ANOVA in this case) and make further comparisons between the participating groups.

It was stated above that 92 intermediate learners were drawn from a larger pool of EFL learners as a result of their scores on the placement test, and were assigned to three experimental groups and one control group. To further ascertain the homogeneity of the two groups in terms of their vocabulary comprehension and production before the treatment, their pretest scores were compared via a one-way ANOVA. Since the p value was higher than .05 (.71 > .05), it was revealed that the four groups did not significantly differ on the pretest. Hence, it could be inferred that the learners in the four groups were at the same level of pretest.

As it was pointed out above, the first research question of the study was to investigate the effects of visual input enhancement, semantic input enhancement, and input flooding on Iranian EFL learners’ production of L2 vocabulary. To do so, a one-way ANOVA was used on the participants’ production posttest:

Based on the data presented in Table 1, in the production posttest, the highest mean belongs to the input Enhancement group (M = 13.23). The semantic input enhancement group has the second-highest mean (M = 13.10). Input flooding group has the third rank (M = 12.69), and the control group comes last (M = 10.21). To see whether the observed differences among the means were significant or not, the ANOVA was run.

As it can be seen in Table 2, there was a statistically significant difference in the posttest scores for VIE (M = 13.23, SD = .72), SIE (M = 13.10, SD = .85), IF (M = 12.62, SD = 1.06, and CG (M = 10.21, SD = .39) on the posttest of vocabulary production since the p value under the Sig. the column was found to be less than the specified level of significance (i.e. .000 < .05), meaning that the four groups significantly differed in terms of vocabulary production after the treatment. Pair-wise comparisons of the groups (in Table 3) reveals which two groups were significantly different on the posttest of vocabulary production.

Table 1. Descriptive statistics results comparing VIE, SIE, IF, and CG mean scores on the production of vocabulary

	N	Mean	Std. Deviation	Std. Error	95% Confidence Interval for Mean		Minimum	Maximum
					Lower Bound	Upper Bound
VIE	23	13.23	.72	.15	12.92	13.55	12.00	15.00
SIE	23	13.10	.85	.17	12.74	13.47	12.00	14.50
IF	23	12.69	1.06	.22	12.23	13.15	10.00	14.00
CG	23	10.21	.39	.08	10.04	10.38	10.00	11.00
Total	92	12.31	1.46	.15	12.01	12.61	10.00	15.00

Table 2. The results of the one-way ANOVA on vocabulary production

	Sum of Squares	df	Mean Square	F	Sig.
Between Groups	138.66	3	46.22	73.03	.000
Within Groups	55.69	88	.63
Total	194.35	92

Table 3. Results of the Scheffe post hoc test for comparing VIE, SIE, IF, and CG mean scores on the posttest of vocabulary production

(I) Groups	(J) Groups	Mean Difference (I-J)	Std. Error	Sig.
					VIE	SIE	.13	.23	.95
IF	.54	.23	.15
CG	3.02	.23	.00
SIE	VIE	−.13	.23	.95
	IF	.41	.23	.38
	CG	2.89	.23	.00
IF	VIE	−.54	.23	.15
	SIE	−.41	.23	.38
	CG	2.47	.23	.00
CG	VIE	−3.02	.23	.00
	SIE	−2.89	.23	.00
	IF	−2.47	.23	.00

Post-hoc comparisons using Scheffe test indicated that the mean score of the three experimental groups (M = 13.23, 13.10, and 12.62) was significantly different from the control group (M = 10.21). There was not, however, a significant difference between the three experimental groups. As a result, it could be inferred that using three modes of input enhancements led to a significant effect on EFL learners’ vocabulary production.

The second research question aimed to check the possible differences among the effects of visual input enhancement, semantic input enhancement, and input flooding on Iranian EFL learners’ comprehension of vocabulary. To this end, a one-way ANOVA test was run on the learners’ vocabulary comprehension posttest.

The mean scores of the VIE (M = 14.02), SIE (M = 13.78), IF (M = 13.39) and CG (M = 11.17) were different from one another on the posttest comprehension of vocabulary (Table 4). To figure out whether the differences among these mean scores were significant or not, one needs to check the p value under the Sig. column in the ANOVA table below (Table 5).

Table 4. Descriptive statistics results comparing VIE, SIE, IF, and CG mean scores on the posttest comprehension of vocabulary

	N	Mean	Std. Deviation	Std. Error	95% Confidence Interval for Mean		Minimum	Maximum
					Lower Bound	Upper Bound
VIE	23	14.02	1.26	.26	13.47	14.56	12.00	15.50
SIE	23	13.78	.83	.17	13.42	14.14	12.50	15.50
IF	23	13.39	1.46	.30	12.75	14.02	11.00	16.00
CG	23	11.17	.68	.14	10.87	11.46	10.00	12.50
Total	92	13.10	1.58	.16	12.77	13.43	10.00	16.00

Table 5. The results of the one-way ANOVA on vocabulary comprehension

	Sum of Squares	df	Mean Square	F	Sig.
Between Groups	117.53	3	39.17	31.79	.000
Within Groups	108.43	88	1.23
Total	225.96	91

As is displayed in Table 5., there was a statistically significant difference in the vocabulary comprehension posttest scores for VIE (M = 14.02, SD = 1.26), SIE (M = 13.78, SD = .83), IF (M = 13.39, SD = 1.46) and CG (M = 11.17, SD = .68) because the p-value under the Sig. column was smaller than the specified level of significance (i.e. .000 < .05), indicating that the four groups did significantly differ on the vocabulary comprehension posttest. Pair-wise comparisons of the groups (in Table 6) reveals which two groups were significantly different on the vocabulary comprehension posttest.

Table 6. Results of the Scheffe post hoc test for comparing VIE, SIE, IF, and CG mean scores on the posttest of comprehension posttest

(I) Groups	(J) Groups	Mean Difference (I-J)	Std. Error	Sig.
					VIE	SIE	.23	.32	.91
IF	.63	.32	.30
CG	2.84	.32	.00
SIE	VIE	−.23	.32	.91
	IF	.39	.32	.70
	CG	2.60	.32	.00
IF	VIE	−.63	.32	.30
	SIE	−.39	.32	.70
	CG	2.21	.32	.00
CG	VIE	−2.84	.32	.00
	SIE	−2.60	.32	.00
	IF	−2.21	.32	.00

Based on Table 6, it can be seen that the difference between VIE (M = 14.02) and SIE (M = 13.78) and VIE (M = 14.02) and IF (M = 13.39) was not statistically significant since the Sig. value corresponding to theses comparisons was higher than .05. Moreover, the difference between the three experimental groups and the control group was statistically significant. This means that using visual input enhancement, semantic input enhancement, and input flooding could lead to a significant effect on vocabulary comprehension.

5. Discussion and conclusion

As the results of the current study indicated, while the members of all three groups surpassed the control group (the group with unenhanced materials), these disparities were statistically significant, not only in the comprehension, but also in the production of L2 vocabulary. These results show that three types of instruction had a considerable benefit for the productive and comprehension knowledge of the target vocabulary. They also demonstrated that the gains were larger in general at the pre-post stage for the experimental groups revealing an obvious advantage for experimental teaching mixed with SIE, VIE, and IF.

This finding can support Schmidt (1994), who believed that drawing L2 learners’ heed to target language forms can help them notice the gap between the current interlanguage and the target language. According to Schmidt’s Noticing Hypothesis, “the necessary and sufficient condition for the conversion of input into the intake for second language learning to take place” (Schmidt, 1994, p. 17 is learners’ noticing to the features of L2 in the written or spoken input. Therefore, the enhancement of the input (Sharwood Smith, 1991, 1993), as was the technique employed in the present study, could draw L2 learners’ attention to the intended L2 input. This outcome is consistent with several studies (e.g., Hamed Mahvelati & Mukundan, 2012; Rassaei, 2015) which have reported that input enhancement could boost learners’ performance in different language abilities. However, there are studies which contradict the finding of the present study (Bayonas, 2017; LaBrozzi, 2016). Also, this study is in contradiction with VanPatten (1990) who found that it is difficult for second language learners especially at the beginning levels to pay attention to both form and meaning at the same time.

Additionally, this study supports the assumption that explicit lexical elaboration, fosters the learning of unfamiliar words in written texts. It can be argued that elaboration provides the necessary input that L2 learners need for learning a second/foreign language. It also offers the natural discourse models provided by native speakers to the EFL/ESL learners. Performance of the participants suggests that textual enhancement and elaboration facilitate L2comprehension at the sentential level, and elaborating target lexical items can facilitate their learning. Such findings are in line with general trends observed in earlier text amendment, L2 comprehension, and vocabulary acquisition studies (Crossley, Louwerse, McCarthy, & McNamara, 2007). The present study also finds support from the scholars who assert that simplified input contributes to a higher level of comprehension than unmodified input (e.g., Gass, 2003; Long, 2015). Gass (2003) argues that modified language makes the language input comprehensible although she refers to Chaudron (1983) and Yano, Long, and Ross (1994) who have not found that modified input is easier to understand than the unmodified one.

In addition, the findings of this study indicate a number of studies that concentrated on the impacts on various variables of either one or more of these input enhancement techniques. For instance, Fahim and Vaezi (2011), Jabbarpoor and Abdollahzade (2013), Nahavandi and Mukundan (2013) and Sahebkheir and Davatgari Asl (2014) all made a conclusion that different forms of visual enhancement of the input (bolding, emphasizing, highlighting, enlarging, etc.) will enhance the performance of the participants in learning grammatical points.

In light of the discoveries of Goudarzi and Raouf Moini (2012) and Birjandi et al. (2015), Semantic (or lexical) input enhancement and visual input enhancement have both a positive influence on the performance of learners. And, semantic enhancement is progressively effective. Negari and Rouhi (2012), and Rahbar and Mousavi (2014) are other researchers who have found that semantic elaboration is efficient. Furthermore, the outcomes of this study are consistent with those of Ertürk (2013) concerning the impact of pushed output, input processing, and visual information enhancement on learning and retention of participants. Visual input improvement proved ineffective in getting the target items to the attention of the learners.

In addition, AsadiAmirabadi et al. (2014) succeeded in using both input enhancement and input flooding techniques, resulting that a combination of these techniques is more effective than either of them alone. Some findings important for this research are those of Lee and Lee (2012), who based on all three methods used in this analysis. Although there were no variations in delayed vocabulary recall among the strategies, immediate posttests indicated positive impacts. The semantic input enhancement group did better in terms of context recognition, while input flooding and visual input enhancement groups enhanced at form diagnosis.

The outcomes of this study can be explained and justified by considering some factors. One such factor could be the circumstances under which the study was being performed, such as the study’s short duration. It took each participant about 2 months to receive the medication and complete the subsequent studies. In the long run various outcomes could be acceded. The timing of the study may also have influenced the findings, especially for younger people, as the experiment time occurred simultaneously with their tests at school or university.

Furthermore, several of the researched alluded above have been performed in areas where English was the second language. As Iranian learners are EFL students, the context and educational culture of Iran could have affected the study, and the only exposure they get to the target language is in the classroom. The results might also be attributed to sample characteristics. The participants in this research were all at the intermediate level. Faghih and Sharafi (2006), and Jafarpour and Koosha (2006) have revealed that there is a positive correlation between the level of proficiency and vocabulary acquisition.

In addition, the research sample size was limited and included only male learners. This study was conducted with 92 male EFL learners for practical reasons; 92 learners can hardly be representative of the entire population of EFL learners in Iran, especially since the participants in this study came from only one type of environment, private English institutes. Another significant and decisive aspect could be Iranian learners ‘ propensity to abide by conventional methods. The learners may have concluded that the delivery of information in each session was not adequate and turned to their own chosen way of learning the language, and this could have distorted the result of the strategies.

None of the strategies in this study turned out to be significantly superior to others in influencing the efficiency of the participants in terms of vocabulary, as shown by the research conclusions. In other words, under identical situations, neither enhancing the input (visually or semantically) nor that the sensitivity of the learners to the input will influence their learning of the target items in a different way. It can, therefore, be inferred that while developing materials for ESL or EFL classes, authors of materials do not need to be overly concerned with the delivery form of the materials (at least when it comes to vocabulary learning) and rely on other requirements that dominate.

In turn, teachers may easily choose the methodology they find most appropriate and more useful for their class, as other considerations such as class time control, lack of an exact alternative for the products, different skill levels, etc. that restrict the choice of instructor. Input flooding, for instance, in the class can be time-consuming, or semantic enhancement (L1 gloss) may not function for every lexical object. Based on the findings of this research, it may be inferred that teachers must resist the temptation to focus on one or more of the above strategies being applied in their classroom presentations. Practicality or manageability problems may be given priority. It can also be argued that since there are no significant differences in the degree to which the factors under review in this analysis influence vocabulary comprehension and development, a mixture of these strategies can yield better consequences. Given that students are multi-dimensional and that every student is an extraordinary creature with a novel arrangement of learning inclinations, a mix of introduction procedures will in all likelihood be more powerful than any single method utilized alone. This is basically on the grounds that diverse introduction methods can provide food for a more extensive scope of learning inclinations.

In addition, given that all the input reinforcement methods in this analysis are written and implicit, the conclusion to be drawn is that students may need more specific ways of learning vocabulary, and similar to what Farrokh (2012) and Hamed Mahvelati and Mukundan (2012) have concluded, it may be appropriate to specifically teach these subjects in language classes. This implies utilizing just certain strategies in showing vocabularies and trusting that students will locate an enchantment method for learning them might be leaving an excessive amount to risk. Regardless, for such an end to be founded on a more grounded establishment, the correlation must be made between the impacts of unequivocal and certain introduction systems on the learning of vocabularies, something not tended to right now reasonability reasons.

The present research can be useful to educators and materials designers. Given that the impacts of visual input enhancement, semantic input enhancement and input flooding do not contrast a lot, instructors or materials designers can pick the ones which are increasingly pragmatic and simpler to utilize. Accordingly, they can maintain a strategic distance from pointlessly changing the first messages. Besides, when a specific strategy is chosen, there is no compelling reason to move from one to the next. What’s more, it appears to be smarter to continue reliably to see the outcomes in the long-term.

Correction

This article has been republished with minor changes. These changes do not impact the academic content of the article.

Additional information

Funding

The authors received no direct funding for this research.

Notes on contributors

Ehsan Namaziandost

Ehsan Namaziandost was born in Shiraz Province of Iran in 1985. He holds an MA degree in TEFL from Islamic Azad University of Ahvaz. Now, he is a Ph.D. candidate in TEFL at Islamic Azad University of Shahr-e Kord. His main interests of research are second language acquisition, EFL teaching, teaching and testing, teaching language skills, language learning and technology, and communication and language learning strategies. His research papers and articles have been published by different international journals.