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Componente 1 Modelo Alimentación (VA)
In line with other experimental works corresponding to the relationship between learning and DCT (see Sadowski 2005; Boers et al., 2007), Shen (2010) performed two experiments. In the first experiment, he analyzed the differences in learning Chinese concrete words in a situation where the subjects were provided only verbal coding instructions versus a situation where the subjects were given both verbal and imaginal coding instructions. In the second experiment, he examined the differences in learning Chinese abstract words in the same situations (verbal instructions versus verbal and imaginal instructions). In these two experiments, Shen sought to respond to this question: does the learning of Chinese abstract and concrete words differ in the verbal instruction situation in comparison with the imaginal plus verbal instructions situation? Namely, is there any difference in the activation of the verbal and non-verbal subsystems?
Design and Methodology
Both experiments had a 2 × 2 (instructional conditions × performance on vocabulary tests) design. Hence, two types of tests existed: the first test was taken immediately after the instructions were received and the second one was taken 24 hours after. Twenty concrete and twenty abstract words were chosen for the experiments. The selection of the words was performed from the integrated Chinese textbook. Concrete words are the ones which have direct access to sensory referents (e.g. 黄瓜 cucumber); on the other hand, abstract words are the words that do not have this direct access (e.g. 安全 safe). To be assured that there was a significant difference of abstractness between the abstract group and the concrete group, they mixed the words together and performed a word abstractness rating analysis. The t test demonstrated a noticeable statistical difference between concrete and abstract words102. The subjects were 45 students, of which five were not present either in the instruction part or in the test part of the concrete words part. In addition, ten were not present in the first or second day of the tests for the abstract words. Hence, the total number of the participants was 40 students for both tests of concrete words and 35 students in the case of abstract words.
Results and discussion
The results obtained from the two tests performed on concrete words are observable in tables 3.1 and 3.2103. In line with these results, it could be concluded that the subjects’ performance either on the first day or on the second day did not have any interaction with the type of instructions received (verbal or imaginal method used to encode stimulus). In agreement with these results, it can be deduced that the verbal encoding alone or verbal plus imaginal encoding do have the same results regarding the storage of concrete words in memory.
102 Mean rating for concrete words was 23.55 and for abstract words was 67.90, (t = 14.34, p < .000). 103 Shen (2010:494).
Table 3.1. Descriptive statistics of the testing results for concrete words
Table 3.2. ANOVA for recall of concrete words under two coding conditions: in-class test and delayed test.
Table 3.4. Analysis of variance for retention of abstract words under two coding conditions.
Table 3.5. Independent t-tests for retention of abstract words under two coding conditions
The results achieved in both experiments performed on abstract words are displayed in tables 3.3 and 3.4104. According to these results, and contrary to the previous results,
there was an interaction between the type of encoding method in the instructions for abstract words and the subjects’ performance on the abstract vocabulary testing. In addition, independent t-tests for recall of abstract words under two coding conditions (Table 3.5105) demonstrated that there was a significant difference for the recall of words’ meaning in the first day and for the recall of both words’ shape and meaning in the second day of abstract words testing.
The results reveal that there was no interaction between the type of applied encoding method for the given instructions and the subjects’ performance in both tests conducted on concrete words. This is contrary to the results in both tests on abstract Chinese words, which manifested interactions between type of employed encoding method and the subjects’ performance. In the case of abstract words, the indicated tables are in agreement with the DCT; however, this is not true for the concrete tests results. The reason for this discrepancy would be the sensory nature of the chosen concrete words and their pre-existing imaginal representations in the memory of the subjects. In DCT terms, in the tests conducted on concrete words, when the subjects were provided only
104 Shen (2010:495). 105 Shen (2010:495).
verbal instructions, they activated both imaginal and verbal representations. This is because in their long-term semantic memory they had stored the imaginal information correlating to those words. Namely, in order to accomplish an activation of the non- verbal subsystem and to activate imaginal representations, the subjects did not need pictorial instructions. Hence, the very close statistical results in both applied encoding methods would be due to this hypothetical aspect of DCT.
On the other hand, in keeping with the results achieved in the test conducted on abstract words, the question remains: why did the verbal plus non-verbal encoding instructions result in a superior recall rate of meaning and shape of abstract words and not in a superior recall rate of their sound? In accordance with Shen (2010: 496), Chinese lacks
sound-to-spelling correspondence. Chinese is also a tonal language in which four tones based on pitch levels are used. The written form of a word, however, indicates neither pronunciation nor tone. As a result, the employed imaginal encoding method in the
non-verbal instructions did not provide the subjects the necessary acoustic information that enabled them to have a better recall rate in comparison with the tests that included only the verbal instructions.
3.4. Words As social Tools or WAT theory
Borghi and Binkofsky (2014) proposed the WAT model for the representation of concrete and abstract words and concepts in the human cognitive system. In their model, abstract words and concepts are not different from concrete words from the embodiment point of view, although they do differ from concrete words in other viewpoints such as importance of linguistic contexts and associations for abstract words, acquisition modality, activation of neural networks in the human brain and meaning variability across languages. In the following section, WAT model and its theoretical aspects, together with some related experimental works, will be discussed.
3.4.1. The theoretical basis of WAT theory
Borghi and Binkofsky in their work (2014: 19-21) account for five principles as the basis of WAT theory. The first assumption is the centrality of embodiment for all the concepts. Namely, they state that not only concrete words and concepts but also abstract ones are grounded in our perception system, action system and emotional system. The second assumption is that the language and the linguistic contexts and associations are more important for the representation of abstract words and concepts than for the representation of concrete words and concepts. By this, Borghi and Binkofsky intend that abstract concepts and words activate linguistic areas in the human brain more than concrete words and concepts. This is rooted in two reasons: first, the members of an abstract category (and the experiences associated with them), like religion, differ drastically in comparison with the members in a concrete category, like cat, from the viewpoint of having sensorimotor features. Second, since they do not have any direct concrete referent, they need the linguistic associations and structures which connect them to our perception system, action system and emotional system. In other words, the language and linguistic structures play a mediator role between abstract words and our embodied experiences. By mediator role, Borghi and Binkofsky do not intend solely a linguistic label but also sometimes humans need some descriptions and explanations of a certain abstract concept (linguistically labeled) given by the members of their
linguistic cultural community. This enables us to assemble and put together sparse and
variable experiences, and consequently comprehend it better. The third assumption is
concerned with the modality of acquisition of abstract words. On the basis of the second part of assumption number two, Borghi and Binkofsky argue that the modality of the acquisition of abstract words and concepts relies more on the language and the linguistic associations than the modality of the acquisition of concrete ones. In the fourth assumption, in line with considerable neurolinguistic studies, they claim that while sensorimotor networks in the human brain are activated by both concrete and abstract words and concepts, the linguistic networks are activated more by abstract words and concepts (see Kiehl, Liddle, Smith, Mendrek, Forster & Hare, 1999; Jefferies, Patterson, Jones & Lambon Ralph, 2009). The last assumption is concerned with the linguistic diversity of abstract words and concepts and the fact that their representation depends more on the cultural and linguistic environment. In other words, abstract words may differ in different languages, cultures and/or in different linguistic cultural contexts between the members of the same linguistic community. In summary, WAT theory does not distinguish abstract words from concrete words according to the embodiment point of view. However, it does differentiate them from concrete words according to other viewpoints, such as importance of linguistic contexts and associations for the abstract words, acquisition modality, activation of neural networks in the human brain and meaning variability across languages.
In a more generic view, a highlighted role of language in the representation of the abstract words is the difference between these two linguistic conceptual categories. It is the role of language in abstract words and concepts representations that causes differences in their acquisition modality, brain representation and activation of neural networks and so on. The question is what is the origin of this language centrality for the abstract words and concepts and why does WAT assign this crucial role to language?