Vocabulary knowledge is regarded as a multidimensional construct consisting of a set of sub-constructs (Henriksen, 1999; Henriksen & Haastrup, 1998) including orthographic knowledge (how a word is spelled and written), phonological knowledge (how a word is pronounced), morphological knowledge (the components of a single word), semantic knowledge (meaning of a word, antonyms, synonyms), syntactic knowledge (the position of a word in a sentence, the collocation patterns of the word), and pragmatic knowledge (in which context a specific word should be used). Figure 1 ay reveals this multidimensionality of lexical knowledge and also the common order of their learning more vividly. The point which needs to be pointed out here is that this offered order is not fixed. In other words, different persons depending on different conditions might start with different sub-components of vocabulary knowledge. A learner might, for example, first learn the meaning of a new lexical item without paying any attention to how the word is spelled; while another one first learns the pragmatic aspect of word and then its morphological structure. This proposed order is, however, the most common and logical order for developing vocabulary knowledge which is also directly related to learners’ proficiency level in the sense that the higher the proficiency level of a learner is, the more aspects of lexical knowledge is learned.
The receptive/productive aspect of vocabulary knowledge is also part of the multidimensional nature of vocabulary knowledge. Based on some researchers (such as Abednia & Tajik, 2012), while receptive vocabulary knowledge is part of semantic processing vocabulary knowledge component as it involves learners’ knowledge to process and retrieve the meaning aspect of lexical items; productive knowledge is part of syntactic vocabulary knowledge component in that it entails learners’ knowledge to actively make use of their lexical knowledge in their output. Productive knowledge, however, is related not only to the syntactic knowledge (as Abednia & Tajik (2012) state), but also to the pragmatic knowledge in the sense that it also involves learners’ knowledge about the contextual information of words according to which they should know in what contexts which word is more appropriate to use.
As with the receptive/productive lexical knowledge differences, although there are still unknown angles, some findings have gained consensus. First, Waring (1997) contended that the higher the proficiency level of EFL learners, the higher the likelihood of knowing words receptively and productively. Warring further added that this finding is limited to high-frequency words and in order to be able to generalize it to all words, further studies should be conducted. Webb (2008) also studied the impact of explicit teaching on learners’ receptive and productive knowledge and finally concluded that explicit instruction helps learners know words both receptively and productively. The findings of these two studies, along with some others, imply that receptive and productive knowledge should not be considered to be independent. Instead, they are interrelated and had better be regarded as a continuum. Melka (1997) also argued for the existence of a continuum between receptive and productive knowledge. Melka clarified this continuum contending that it represents increasing degrees of knowledge or familiarity with a word. It means that the more a person knows about a word, the more he/she moves forward from receptive end of the continuum toward the productive end. Notwithstanding the fact that learners’ receptive knowledge is usually larger than their productive knowledge (Melka, 1997; Modrian & Wierma, 2004), learners can, or better to say, should try to extend their receptive knowledge into productive mode and make a balance between the two modes of lexical knowledge (via different ways such as instruction, practice, interaction with others) so that they would be able to use language more efficiently. This point endorses the previously-mentioned point that these two aspects of vocabulary knowledge overlap and are complementary not independent from each other.
To make such equilibrium, some strategies and ways have been offered among which explicit instruction appears to be a good way. Hayashi & Murphy (2009), for instance, stated that based on the findings of studies on receptive/productive knowledge, it seems that learners’ explicit learning of receptive/productive vocabulary knowledge has a positive role in developing their efficient receptive/productive knowledge, which, in turn, leads to their effective language use. Moreover, Webb (2008) also maintained that intentional teaching approach can cause learners to have a balanced development of receptive/productive vocabulary knowledge. Notwithstanding the importance of a balanced development of receptive/productive knowledge, it should also be pointed out that first of all, creating an equal balance between the two types of vocabulary knowledge is out of question mainly due to their different rate of acquisition and development. Nowadays, there is consensus on the point that receptive vocabulary typically grows faster than and before productive vocabulary (Melka, 1997, Ringbom, 1985); and second, the number, amount, and quality of receptive/productive vocabulary knowledge differ across different learners. One reason for such a difference is surely related to individual differences of meaning that different features of learners might directly or indirectly affect their learning both quantitatively and qualitatively. To the best of the author’s knowledge no study has ever dealt with the impact of individual differences, especially FI/D characteristics, on the receptive/productive knowledge of learners. Waring (1999) similarly mention this lack of adequate attention and asks for conducting studies in different contexts To fill such a gap, the present study tried to examine the same issue on a set of Iranian EFL learners.
Probably the best point to start discussing the issue of individual differences is the fact that there are several factors affecting individuals’ performance. People differ from each other in many terms such as motivation, gender, personality, etc. and each of them can considerably influence their behavior, achievement, and performance. In a similar vein, as far as second or foreign language learning is concerned, learners might be influenced differently by different factors while attempting to master a language (Dornyei, 2009; Griffiths 2008; Naiman et al., 1978; Skehan, 1998). These differences are generally referred to as individual differences. Knowing about these characteristics and how they affect learners’ performance in different strands of language might be advantageous for both students and teachers. In other words, when students know about their individual differences, they would be able to make use of strategies, approaches, and tools that best suit them. Furthermore, teachers’ knowledge about their students’ differences will also help them to provide their learners with the best and most efficient teaching techniques to maximize their teaching effectiveness. Moreover, as Eliason (1995) also rightly put, learners might empower their learning via increasing their awareness of their learning styles and working to develop them further as it can substantially increase their intellectual growth. In keeping with this, teachers can also determine the effective style patterns in their classes and then, devise plans and procedures that are in line with individual learning style preferences.
Individual differences, however, are very wide and are classified into different types. As an example, according to Skehan (1998), language learning process is likely to be affected by all or some of these four main areas: (1) learning styles (2) learning strategies (3) language aptitude and (4) motivation. Each of them, in turn, consists of a set of subcategories. Learning styles, for instance, comprises factors such as FD/I, thinking/feeling, ambiguity tolerance/intolerance, etc. Owning to the fact that considering all of them in a single study is neither practical nor logical, the present study focused on learning styles in general and FD/I in particular.
Learning style is generally defined as the link between personality and cognition (Keefe, 1979). Some researchers (Brown, 1994; Chastin, 1988; Wyss 2002), however, regard this link as the definition of cognitive style arguing that learning style is a sub-type of cognitive style which is restricted to pedagogical contexts. Whether to consider them separate or the same does not seem to make any salient difference in that both terms have the interplay of personality and cognition as their basic characteristic and their difference lies merely in the context domain. In this paper, for the sake of clarity, the term learning style is used. Witkin (1973) simply describes learning styles as the way individuals try to approach, process, and solve a situation, problem, or phenomenon. According to this definition, learning styles deal with the process and not product of activities. One point about this Witkin’s statement, however, is that learning styles not only affect the process directly, but also influence the final product of individuals’ performance. It means that regardless of the ultimate achievement, learning styles of determine how a specific person approaches a problem, issue, or situation and as a result, this differences in dealing with a situation might lead to differences in the final achievement.
The important point as to learning style is that it should be considered as an umbrella term consisting of a set of components. Wyss (2002), similarly, postulated that there are as many learning styles as there are individuals and the practical implications of learning styles are numerous especially for teaching-learning interactions (P. 1). Figure 2 can more vividly represent the general concept of learning style.
The terms FI and FD have generally been defined as two types of learning styles that illuminate the way people perceive and process information (e.g., Brown 1994; Ellis, 1985; Kang, 1999). To be more detailed, FD learners usually look at the whole of a specific task which contains many items. These learners have difficulty in focusing on a particular item when it is embedded within other items. In contrast, FI learners can easily focus on particular items and are not distracted by other items in the background or context (Gollnick & Chein, 1994). Additionally, FD individuals are globally-oriented meaning that they are more sensitive toward the environment. On the contrary, FI learners are more analytically-oriented in the sense that they are mostly indifferent to the surrounding and prefer to stay independent. Zhang (2004) refered to the source of cues used by individuals to define FI/D terms stating that FI persons make use of internal cues for organizing a conduct while FD ones actively use external cues for thinking, processing, and organizing a conduct.
Regarding the impact of these two types of learning style on individuals’ performance in academic contexts, some studies can be found in the literature. For example, it has been concluded in some studies that while FI learners are more likely to outperform FD ones in academic contexts where the focus is on form, analysis, and drills, FD learners usually outperform their FI counterparts in the contexts in which meaning, use, and interaction are emphasized (Ellis, 1994; Skehan, 1998; Yousefi, 2011) took a more or less moderate position maintaining that although both types can be regarded as efficient tools in educational contexts, and although FI learners have been found to be more successful in achieving most of intellectual tasks especially those which require elaborate analysis, process, and attention, it does not necessarily mean that FD learners cannot perform adequately on these tasks. Some points should be mentioned here. First, these findings are all relative and not absolute as not only they have been resulted from a limited number of participants so that they should be approached cautiously, but also, they are resulted in specific contexts with specific contextual factors including specific tasks. Second, terms FI and FD should not be considered absolute either. In other words, FI and FD are better to be taken along a continuum meaning that a single person, depending on a specific context, might be FD, FI, or even field intermediate Fig. 3). Mancy & Reid (2004) have categorized learning styles into three and not two sub-types of field-independence, field-dependence, and field intermediate (also sometimes referred to as field neutral). This taxonomy is highly related to the following figure implying that learners processing ability is flexible and it does not stand to reason saying that one learner is absolutely FI or another learner Y is completely FD. Rather, it is better to state that one learner is FI-oriented and another learner is FD-oriented. The term field neutrality or intermediate also implies the same point. It does not mean that a person is neither FI nor FD. Instead it indicates that in some situations a learner might become far from his/her dominant learning style and takes a more moderate style to cope with a specific context.
All taken together, as it was already stated, knowing about learners’ learning styles might be a great help to teachers as they can match their teaching methods with their learners’ learning styles so that teachers’ teaching effectiveness and learners’ learning would maximize. Furthermore, As Brown (1994) also maintained, by creating such a match, learners’ motivation, performance, and achievements would also increase. The point which, however, needs to be noticed is that although learning styles, especially FI/D types, have been extensively investigated as far as language learning is concerned, some gaps are noticeable in the related literature. One is the lack of even a single study (to the best of the author’s knowledge) dealing with the effect of FI/FD on receptive/productive knowledge. Besides, the same problem is even more considerable in EFL contexts where, due to the lack of language use in everyday communications, investigating vocabulary from different angles such as learning styles can effectively influence learners’ performance. To fill such lacuna in the literature, this paper tried to shed light on the impact of FI/D characteristics of a number of Iranian EFL learners on their receptive/productive lexical knowledge.