GECO-CN: Ghent Eye-tracking COrpus of sentence reading for Chinese-English bilinguals

The current work presents the very first eye-tracking corpus of natural reading by Chinese-English bilinguals, whose two languages entail different writing systems and orthographies. Participants read an entire novel in these two languages, presented in paragraphs on screen. Half of the participants first read half of the novel in their native language (Simplified Chinese) and then the rest of the novel in their second language (English), while the other half read in the reverse language order. This article presents some important basic descriptive statistics of reading times and compares the difference between reading in the two languages. However, this unique eye-tracking corpus also allows the exploration of theories of language processing and bilingualism. Importantly, it provides a solid and reliable ground for studying the difference between Eastern and Western languages, understanding the impact and consequences of having a completely different first language on bilingual processing. The materials are freely available for use by researchers interested in (bilingual) reading.

Expanding horizons of cross-linguistic research on reading: The Multilingual Eye-movement Corpus (MECO)

Scientific studies of language behavior need to grapple with a large diversity of languages in the world and, for reading, a further variability in writing systems. Yet, the ability to form meaningful theories of reading is contingent on the availability of cross-linguistic behavioral data. This paper offers new insights into aspects of reading behavior that are shared and those that vary systematically across languages through an investigation of eye-tracking data from 13 languages recorded during text reading. We begin with reporting a bibliometric analysis of eye-tracking studies showing that the current empirical base is insufficient for cross-linguistic comparisons. We respond to this empirical lacuna by presenting the Multilingual Eye-Movement Corpus (MECO), the product of an international multi-lab collaboration. We examine which behavioral indices differentiate between reading in written languages, and which measures are stable across languages. One of the findings is that readers of different languages vary considerably in their skipping rate (i.e., the likelihood of not fixating on a word even once) and that this variability is explained by cross-linguistic differences in word length distributions. In contrast, if readers do not skip a word, they tend to spend a similar average time viewing it. We outline the implications of these findings for theories of reading. We also describe prospective uses of the publicly available MECO data, and its further development plans.

Improving reading rate prediction with word length information: Evidence from Dutch

Previous research in English has suggested that reading rate predictions can be improved considerably by taking average word length into account. In this study, we investigated whether the same regularity holds for Dutch. The Dutch language is very similar to English, but words are on average half a letter longer: 5.1 letters per word (in non-fiction) instead of 4.6. We collected reading rates of 62 participants reading 12 texts with varying word lengths and examined which change in the English equation accounts for the Dutch findings. We observed that predictions were close to the best-fitting curve as soon as the average English word length was replaced by the average Dutch word length. The equation predicts that Dutch texts with an average word length of 5.1 letters will be read at a rate of 238 words per minute (wpm). Texts with an average word length of 4.5 letters will be read at 270 wpm, and texts with an average word length of 6.0 letters will be read at a rate of 202 wpm. The findings are in line with the assumption that the longer words in Dutch do not slow down silent reading relative to English and that the word length effect observed in each language is due to word processing effort and not to low-level visual factors.

Cross-lingual neighborhood effects in generalized lexical decision and natural reading

The present study assessed intra- and cross-lingual neighborhood effects, using both a generalized lexical decision task and an analysis of a large-scale bilingual eye-tracking corpus (Cop, Dirix, Drieghe, & Duyck, 2016). Using new neighborhood density and frequency measures, the general lexical decision task yielded an inhibitory cross-lingual neighborhood density effect on reading times of second language words, replicating van Heuven, Dijkstra, and Grainger (1998). Reaction times for native language words were not influenced by neighborhood density or frequency but error rates showed cross-lingual neighborhood effects depending on target word frequency. The large-scale eye movement corpus confirmed effects of cross-lingual neighborhood on natural reading, even though participants were reading a novel in a unilingual context. Especially second language reading and to a lesser extent native language reading were influenced by lexical candidates from the nontarget language, although these effects in natural reading were largely facilitatory. These results offer strong and direct support for bilingual word recognition models that assume language-independent lexical access. (PsycINFO Database Record

Beyond associations: Do implicit beliefs play a role in smoking addiction?

BACKGROUND AND OBJECTIVES

Influential dual-system models of addiction suggest that an automatic system that is associative and habitual promotes drug use, whereas a controlled system that is propositional and rational inhibits drug use. It is assumed that effects on the Implicit Association Test (IAT) reflect the automatic processes that guide drug seeking. However, results have been inconsistent, challenging: (1) the validity of addiction IATs; and (2) the assumption that the automatic system contains only simple associative information. We aimed to further test the validity of IATs that are used within this field of research using an experimental design. Second, we introduced a new procedure aimed at examining the automatic activation of complex propositional knowledge, the Relational Responding Task (RRT) and examine the validity of RRT effects in the context of smoking.

METHODS

In two experiments, smokers performed two different tasks: an approach/avoid IAT and a liking IAT in Experiment 1, and a smoking urges RRT and a valence IAT in Experiment 2. Smokers were tested once immediately after smoking and once after 10 hours of nicotine-deprivation.

RESULTS

None of the IAT scores were affected by the deprivation manipulation. RRT scores revealed a stronger implicit desire for smoking in the deprivation condition compared to the satiation condition.

CONCLUSIONS

IATs that are currently used to assess automatic processes in addiction have serious drawbacks. Furthermore, the automatic system may contain not only associations but complex drug-related beliefs as well. The RRT may be a useful and valid tool to examine these beliefs.