This study examined the role of error-type and working memory (WM) in the effectiveness of direct-metalinguistic and indirect written corrective feedback (WCF) on self error-correction in first-language writing. Fifty-one French first-year psychology students volunteered to participate in the experiment. They carried out a first-language…

Learners of a second language often have limited access to the native culture of that language in an authentic way, resulting in them committing linguistic and intercultural mistakes. One of the main advantages of task-based learning is that it can expose students to real-world circumstances, which makes learning a language more meaningful and…

This study investigated the relative effectiveness of two instructional interventions (implicit and explicit feedback) as a function of implicit sequence-learning ability. Second language (L2) attainment was measured by means of a self-paced reading task, which shows online sensitivity to language errors. Implicit sequence-learning ability was…

Few published studies have systematically compared the efficacy of different prompt-fading methods in the training of complex response chains. The current study systematically compared a most-to-least physical prompt fading hierarchy with a most-to-least vocal prompt fading strategy in the training of four arbitrary Tinkertoy® construction tasks…

The present study tests whether presenting video modeling examples from the learner's (first-person) perspective promotes learning of an assembly task, compared to presenting video examples from a third-person perspective. Across 2 experiments conducted in different labs, university students viewed a video showing how to assemble an 8-component…

This study reports on the results of classroom research investigating the effects of using data-driven learning methods by students in revising their writing errors. The main purpose of the study is to examine to what extent is consulting a corpus effective in correcting lexical errors in their writing. It has been found in previous research that…

Ensemble approaches have been shown to enhance classification by combining the outputs from a set of voting classifiers. Diversity in error patterns among base classifiers promotes ensemble performance. Multi-task learning is an important characteristic for Neural Network classifiers. Introducing a secondary output unit that receives different…