Publications

Abstract

Individual differences in using language are prevalent in our daily lives. Language skills are often assessed in vocational (predominantly written language) and diagnostic contexts. Not much is known, however, about individual differences in spoken language skills. The lack of research is in part due to the lack of suitable test instruments. We introduce the Individual Differences in Language Skills (IDLaS-NL) test battery, a set of 31 behavioural tests that can be used to capture variability in language and relevant general cognitive skills in adult speakers of Dutch. The battery was designed to measure word and sentence production and comprehension skills, linguistic knowledge, nonverbal processing speed, working memory, and nonverbal reasoning. The present article outlines the structure of the battery, describes the materials and procedure of each test, and evaluates the battery’s factor structure based on the results of a sample of 748 Dutch adults, aged between 18 and 30 years, most of them students. The analyses demonstrate that the battery has good construct validity and can be reliably administered both in the lab and via the internet. We therefore recommend the battery as a valuable new tool to assess individual differences in language knowledge and skills; this future work may include linking language skills to other aspects of human cognition and life outcomes.

Abstract

Experimental psychologists and psycholinguists increasingly turn to online research for data collection due to the ease of sampling many diverse participants in parallel. Online research has shown promising validity and consistency, but is it suitable for all paradigms? Specifically, is it reliable enough for individual differences research? The current paper reports performance on 15 tasks from a psycholinguistic individual differences battery, including timed and untimed assessments of linguistic abilities, as well as domain-general skills. From a demographically homogenous sample of young Dutch people, 149 participants participated in the lab study, and 515 participated online. Our results indicate that there is no reason to assume that participants tested online will underperform compared to lab-based testing, though they highlight the importance of motivation and the potential for external help (e.g., through looking up answers) online. Overall, we conclude that there is reason for optimism in the future of online research into individual differences.

Abstract

Many studies have demonstrated that listeners use information extracted from verbs to guide anticipatory eye movements to objects in the visual context that satisfy the selection restrictions of the verb. An important question is what underlies such verb-mediated anticipatory eye gaze. Based on empirical and theoretical suggestions, we investigated the influence of five potential predictors of this behavior: functional associations and general associations between verb and target object, as well as the listeners’ production fluency, receptive vocabulary knowledge, and non-verbal intelligence. In three eye-tracking experiments, participants looked at sets of four objects and listened to sentences where the final word was predictable or not predictable (e.g., “The man peels/draws an apple”). On predictable trials only the target object, but not the distractors, were functionally and associatively related to the verb. In Experiments 1 and 2, objects were presented before the verb was heard. In Experiment 3, participants were given a short preview of the display after the verb was heard. Functional associations and receptive vocabulary were found to be important predictors of verb-mediated anticipatory eye gaze independent of the amount of contextual visual input. General word associations did not and non-verbal intelligence was only a very weak predictor of anticipatory eye movements. Participants’ production fluency correlated positively with the likelihood of anticipatory eye movements when participants were given the long but not the short visual display preview. These findings fit best with a pluralistic approach to predictive language processing in which multiple mechanisms, mediating factors, and situational context dynamically interact.