Elsevier

Computers & Education

Volume 127, December 2018, Pages 113-129
Computers & Education

Cognitive resources allocation in computer-mediated dictionary assisted learning: From word meaning to inferential comprehension

https://doi.org/10.1016/j.compedu.2018.08.013Get rights and content

Highlights

  • A new ‘checking-meaning’ function of computer-mediated dictionaries is proposed.

  • Checking-meaning function may influence readers' cognitive resource allocation.

  • Readers' vocabulary size may influence the use of a computer-mediated dictionary.

  • Research findings could be explained by the competition-cooperation relationship.

Abstract

Computer-mediated dictionaries have been important and widely used aids in the comprehension of, and learning from online texts. However, despite the convenience of computer-mediated dictionaries in retrieving word meaning, its use may reduce the time that readers spend reading each word and negatively affect word retention. In addition, readers' vocabulary size is a key factor influencing the lookup process, and its effectiveness. Therefore, in this study, we propose a new ‘checking-meaning’ function to optimize word retention and to explain readers' cognitive resources allocation in computer-mediated dictionary assisted learning. We conducted a 2 (checking meaning function: with vs. without) × 2 (vocabulary size: large vs. small) between-subjects design to explore the effectiveness of vocabulary acquisition and reading comprehension performance in computer-mediated dictionary-assisted reading. In line with the hypotheses, results revealed that the computer-mediated dictionary with checking-meaning function enhanced small vocabulary size learners' vocabulary acquisition, but negatively influenced large vocabulary size learners' reading comprehension performance. Based on these results, we propose the competition-cooperation relationship to explain readers' cognitive resources allocation in computer-mediated dictionary assisted learning.

Introduction

With the rapid development of the internet and the advent of globalization, the availability of authentic materials on the Internet has expanded exponentially. Consequently, computer-mediated dictionaries have become an important reading aid for online reading, replacing traditional paper-based dictionaries (Abraham, 2008; Hulstijn, Hollander, & Greidanus, 1996; Kramsch & Anderson, 1999; Laufer & Hill, 2000; Liu & Lin, 2011). Although computer-mediated dictionaries are widely used, only a few papers focus on their effects on readers' comprehension of foreign digital text (Chun & Payne, 2004; Knight, 1994; Liu & Lin, 2011; Liu, Fan, & Paas, 2014).

When readers encounter an unknown or unfamiliar word while reading a text in unfamiliar languages, the use of a dictionary is an important method to find the meanings of the word and understand the text (Knight, 1994; Wang, 2012). Using dictionaries helps users comprehend the meanings of unfamiliar words, and by extension, the contextual meanings of the text (e.g., Dang, Chen, Dang, Li, & Nurkhamid, 2013; Huang & Eslami, 2013; Huang, Chern, & Lin, 2009; Knight, 1994; Prichard, 2008). However, a number of studies indicated that the benefits of using dictionaries for vocabulary acquisition are limited (Bensoussan, Sim, & Weiss, 1984; Koyama & Takeuchi, 2007; Tono, 2011). For example, Tono (2011) indicated that using dictionaries cannot guarantee that users will select the appropriate word meaning to fit the context. An empirical analysis revealed that when users were asked to think aloud (ensuring that they concentrated on the dictionary lookup process), over 30% of them chose the wrong meaning (Tono, 2011). Lew, Grzelak, and Leszkowicz (2013) indicated that such results stemmed from the users' eagerness to complete the lookup process as soon as possible. When the users felt that they found the meaning to fit the context of the particular text, they stopped searching for a possible more appropriate meaning (Dang et al., 2013; Kulkarni, Heilman, Eskenazi, & Callan, 2008; Lew et al., 2013).

The abovementioned situation is even more evident in the use of computer-mediated dictionaries. Computer-mediated dictionaries can be used to quickly and conveniently look up word meanings (Liu & Lin, 2011; Shen, 2013), which enhances users' willingness to use computer-mediated dictionaries (Liu & Lin, 2011; Liu et al., 2014; Prichard, 2008). Click-on dictionaries are a convenient form of computer-mediated dictionaries, because they allow readers to simply double-click on any given word in the digital text to bring up a definition adjacent to or above the chosen word. Without a doubt, in comparison with paper-based dictionaries, the click-on form of computer-mediated dictionaries provides learners with a more convenient way to search for words, and exhibit an extremely high application willingness (Aust, Kelley, & Roby, 1993; Liu & Lin, 2011; Liu et al., 2014). However, previous studies indicated that despite the convenience of computer-mediated dictionaries in retrieving word meaning, they may reduce the time users spend reading each word (Liu & Lin, 2011), thereby negatively affecting word retention (De Ridder, 2002; Kobayashi, 2006; Nesi, 2000). In addition, excessively looking up words prolongs reading time, causing computer-mediated dictionaries to lose their supporting effects (Prichard, 2008). Moreover, the convenience of computer-mediated dictionaries reduces cognitive resource allocation requirements and causes users to look up more words with less effort, resulting in poor lookup efficiency (Liu & Lin, 2011; Liu et al., 2014; Prichard, 2008). For example, Liu et al. (2014) employed an eye tracker to collect the eye movements of computer-mediated dictionary users. Analyses revealed that the students using the more convenient computer-mediated dictionaries (i.e., click-on dictionary) were less likely to recognize a word and read word meanings than those using the less convenient computer-mediated dictionaries (i.e., key-in dictionary). These characteristics of computer-mediated dictionaries have a negative effect on users' ability to remember words they previously looked up (Liu et al., 2014; Prichard, 2008) and increase users' likeliness to choose the wrong meaning.

Hulstijn (2001) indicated that during the application of computer-mediated dictionaries to look up word meaning that match the context of texts, users are more likely to remember word information when they put increased effort into intra-word, inter-word, and/or word-context associations (e.g., morphological, orthographic, semantic, and pragmatic features). Laufer and Hill (2000) reported that the effort invested in computer-mediated dictionary lookup affects word retention. Specifically, the more attention users invest, the deeper their impression and the better their memory of the word they look up. Therefore, we developed a ‘checking-meaning’ function for click-on dictionaries to improve the lookup efficiency of click-on dictionaries. This function prompts users to focus on word meaning validation when looking up a word in the dictionary. When users click on an unfamiliar word within the digital text with computer-mediated dictionary, the checking-meaning function prompts them to select the meaning that best fits the context they are reading from a list of definitions presented in the dictionary query window. This function is expected to stimulate users to invest increased effort into comparing the unknown word with various definitions in the dictionary and considering the appropriateness of the meanings within the context, thereby helping them to memorize the word meaning. We anticipate that the proposed function can help users invest more cognitive resources in validating the appropriateness of word meanings in specific contexts during the application of computer-mediated dictionaries, thereby enhancing vocabulary acquisition during computer-mediated dictionary-assisted reading.

Is the checking-meaning function proposed in this study suitable for all users? To answer this question, three dimensions are discussed, namely, (1) the dictionary-assisted reading comprehension process, (2) users' cognitive resource allocation during dictionary-assisted reading, and (3) users' characteristics (large or small vocabulary size). In addition, we discuss the competition-cooperation relationship between low-level and high-level dictionary-assisted reading processes under finite cognitive resources.

Abraham (2008) illustrated that the comprehension processes of reading foreign digital texts includes low-level and high-level reading processes. Low-level reading processes refer to word recognition (e.g., decoding). High-level reading processes refer to text comprehension, such as applying vocabulary knowledge, syntactic knowledge, and background knowledge to understand or infer specific sentences, contexts, cross-paragraph meanings, article topics, and deduce author intentions (e.g., literal comprehension and inferential comprehension) (Chun, 2006; Gagné, 1985; Koda, 2005; Perfetti, 1999). A number of previous studies mentioned that computer-mediated dictionaries provide users with the pronunciation and meaning of word when they read foreign texts, thereby helping them understand the meaning of the text (Dang et al., 2013; Huang & Eslami, 2013; Knight, 1994; Prichard, 2008). The purpose of the checking-meaning function is to increase users' allocation of cognitive resources each time they look up a word and reinforce the word meaning retention. Therefore, in theory, the application of the checking-meaning function facilitates low-level vocabulary acquisition and high-level reading comprehension. However, user characteristics and their cognitive resource allocation must be considered in order to validate the effectiveness of the proposed checking-meaning function.

Baddeley and Hitch (1974) asserted that people have a limited working memory. Therefore, the allocation of cognitive resources when processing multiple tasks influences the performance of each task. In a botany-related action learning intervention, Gao, Liu, and Paas (2016) found that students' plant recognition performance was improved when they placed greater effort on plant recognition, but this hindered their performance on subsequent tasks, such as learning leaf characteristics. Because reading texts in unfamiliar languages entails low-level reading processes and high-level reading processes (Abraham, 2008; Chun, 2006), the allocation of increased cognitive resources to low-level processes during computer-mediated dictionary-assisted reading (e.g., the objective of the checking-meaning function) reduces the cognitive resources available for high-level reading comprehension. Accordingly, in this study we propose a competition-cooperation relationship between the allocation of cognitive resources to low-level reading processes (i.e. word recognition, word meaning selection) and high-level reading processes (i.e. inferential comprehension) during computer-mediated dictionary-assisted reading. In terms of cooperation, word meanings are instrumental in comprehension on logical as well as theoretical grounds (Perfetti, Landi, & Oakhill, 2005). When a reader encounters a text, his or her ability to access the meaning of the word, as it applies in the context of this text, is critical (Perfetti et al., 2005). When low-level skills (word recognition) are weak and effortful, comprehension will likely be impeded because words are misidentified (Perfetti, Marron, & Foltz, 1996; Perfetti et al., 2005; Torgesen, 2000). Therefore, improving word recognition (low-level reading processes) facilitates comprehension (high-level reading processes) (Perfetti, 1999; Perfetti et al., 1996; Torgesen, 2000). In terms of competition, working memory theories indicate that users have limited cognitive resources (Baddeley & Hitch, 1974) and that investing more effort into low-level reading processes reduces the cognitive resources available for high-level reading processes.

An important question that follows from the abovementioned argument is, what type of user is in higher demand of the checking-meaning function?

Vocabulary is one of the best predictors of word reading and reading comprehension in second language learning (Li & Kirby, 2012). Previous studies reported that user’ vocabulary size is related to look-up behavior in dictionary use (e.g., Hulstijn, 1993; Lai & Chen, 2015; Prichard, 2008). For example, Hulstijn (1993) pointed out that learners with greater vocabularies would look up fewer words than learners with smaller vocabularies. According to the competition-cooperation relationship, in this instance, the checking-meaning function prompts users to increase effort in low-level reading processes (i.e., selecting the dictionary definition that best matches the context), reducing the user's cognitive resources for high-level reading processes. Nevertheless, it is vital for readers with smaller vocabulary size to allocate more cognitive resources to low-level reading processes to facilitate reading comprehension. Therefore, the checking-meaning function should theoretically prompt the dictionary users to invest more cognitive resources in low-level reading processes, thereby improving their low-level vocabulary acquisition and, by extension, enhancing their high-level reading comprehension performance.

By comparison, readers with larger vocabulary size are less likely to look up words when reading foreign texts than those with smaller vocabulary size (Hulstijn, 1993; Prichard, 2008). When they encounter an unfamiliar word, they are more capable of guessing the meaning of the word while reading (Teng & He, 2015). Therefore, readers with larger vocabulary size allocate more cognitive resources into text comprehension (high-level reading processes) than checking the meaning of the word (low-level reading processes). The purpose of the checking-meaning function is to force readers to increase effort in validating the meaning of unfamiliar words of the text, thereby improving their vocabulary acquisition. However, improving vocabulary acquisition is not the most important issue for readers with a larger vocabulary size reading foreign texts. Thus, the design of the checking-meaning function may cause readers to displace cognitive resources. That is, the checking-meaning function may cause readers with a larger vocabulary size to allocate more cognitive resources originally for text comprehension to check the word meaning back and forth in the computer-mediated dictionary. For readers with a large vocabulary size, not only may the checking-meaning function be unbeneficial to low-level reading process during computer-mediated dictionary-assisted reading, it could even negatively impact high-level reading comprehension.

Taking into account that the convenience of computer-mediated dictionaries may hinder users' vocabulary acquisition during computer-mediated dictionary-assisted reading, this study has the following major research purposes: (1) proposing a checking-meaning function to increases students' allocation of cognitive resources in dictionary use; (2) investigating the effects of the vocabulary size of the target users of the checking-meaning function on the low-level vocabulary acquisition and high-level reading comprehension during computer-mediated dictionary-assisted reading.

Based on the research purposes, this study hypothesizes that the checking-meaning function facilitates students in focusing on looking up word meanings using computer-mediated dictionaries and strengthens their retention of word meanings. Students that have a profound memory of a specific word are less likely to repeatedly lookup and check the meaning of the same word by computer-mediated dictionaries. Therefore, we hypothesized that when an unfamiliar word is encountered again during reading, students with a small vocabulary size that use computer-mediated dictionaries with the checking-meaning function would look up the word less often than those who use computer-mediated dictionaries without the checking-meaning function (Hypothesis 1). Similarly, we hypothesized that when an unfamiliar word is encountered during reading, students with a large vocabulary size that use computer-mediated dictionaries with the checking-meaning function would look up the word less often than those who use computer-mediated dictionaries without the checking-meaning function (Hypothesis 2).

Research has shown that the use of computer-mediated dictionaries facilitates users' low-level processes when reading digital texts in unfamiliar language (Huang & Eslami, 2013; Knight, 1994). Likewise, the amount of attention users put into looking up the meaning of words in computer-mediated dictionaries affects their word retention, where memory performance increases concurrently with the cognitive resources invested (Laufer & Hill, 2000). The purpose of the checking-meaning function is to force students to invest more attentional resources in computer-mediated dictionary results and repeatedly compare the suitability of the computer-mediated dictionary definitions and the text context, thereby reinforcing their word meaning retention and their low-level vocabulary acquisition. Therefore, we argue that computer-mediated dictionaries with the checking-meaning function can facilitate users with a small vocabulary size to invest more cognitive resources into low-level reading processes, subsequently improving their vocabulary acquisition (low-level) and reading comprehension performance (high-level). On that account, we hypothesized that the vocabulary acquisition of students with a small vocabulary size that use computer-mediated dictionaries with the checking-meaning function would be higher than those who use computer-mediated dictionaries without the checking-meaning function (Hypothesis 3), and the reading comprehension performance (e.g., literal comprehension and inferential comprehension) of students with a small vocabulary size who use computer-mediated dictionaries with the checking-meaning function would be higher than those who use computer-mediated dictionaries without the checking-meaning function (Hypothesis 4). Although, according to the preceding discussion on the competition-cooperation relationship of cognitive resources, the checking-meaning function design may cause the displacement of cognitive resources in students with a large vocabulary size. That is, students with a large vocabulary size may displace cognitive resources originally for high-level text comprehension to low-level computer-mediated dictionary lookup when using computer-mediated dictionaries with the checking-meaning function. Hence, we hypothesized that the reading comprehension performance of students with a large vocabulary size using computer-mediated dictionaries with the checking-meaning function would be lower than those using computer-mediated dictionaries without the checking-meaning function (Hypothesis 5).

Section snippets

Participants

Participants were 88 non-English-majoring freshman students from a Taiwanese university, who were aged between 18 and 19 years (65 females and 23 males) with different majors (liberal arts, business, education, technology and engineering, art, music, and sports and recreation, etc.). Based on the division of the participants mentioned in previous studies (Hasegawa, 2013; Tanabe, 2016), before the experimental treatment, the participants underwent a vocabulary size test (50 items, which

Results

In order to decide about the normality of each group, we included Skewness and Kurtosis measures and ran the Shapiro-Wilk test. Based on the results of the Shapiro-Wilk tests in Table 3, Table 4, three of the fourteen outcomes were not significant, indicating they were normally distributed. The groups were then compared on the variables for all outcomes, using the nonparametric Mann–Whitney U Test for those variables not normally distributed, and the parametric Independent Samples t-Test for

The checking-meaning function effectively promoted the participants to place increased effort into computer-mediated dictionary lookup

This study indicates that the checking-meaning function facilitated participants in allocating increased cognitive resources to computer-mediated dictionary lookup. This was supported by two results, indicating that the checking-meaning function (1) effectively assisted the participants in selecting the correct meaning and (2) effectively enhanced participants' retention of word meaning.

The checking-meaning function effectively assisted the participants in selecting correct word meanings

Previous studies proposed different methods to elucidate participants' word meaning selection process using

Contributions

This study proposed and validated the presence of a competition-cooperation relationship in dictionary-assisted reading. Computer-mediated dictionary-assisted learning processes comprise word meaning lookup and reading comprehension. Due to limited cognitive resources, the two types of processes form a competition-cooperation relationship, which is affected by participants' vocabulary size. Participants with a small vocabulary size are required to place more effort into computer-mediated

Acknowledgements

The authors would like to thank Melissa Hui-Mei Fan, Peng-Yu Chen and Tzu-Ting Huang for assistance in this study. We also thank the Oxford University Press for granting permission to use Oxford dictionary content, and the permission to use the vocabulary size test developed by Dr. Nation and Dr. Beglar. Additionally, we are thankful for the kind assistance and helpful comments of the editor of Computers & Education and the anonymous reviewers of this paper.

Furthermore, we would like to thank

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