E-learning op Maat: Automatische geïndividualiseerde materiaalselectie in het tweede-taalonderwijs

The present study explored the effect of reading texts in an electronic learning environment for 46 adult second language learners of Dutch with different proficiency levels. The reading materials were selected dynamically, based on the "fit" between the vocabulary proficiency of individual students and the relative difficulty of the texts. Text difficulty was determined on the basis of the relative proportion of words unknown to the learner (lemma coverage). The texts were analyzed, selected and presented online, accompanied by a personalized electronic dictionary with words that were assumed to be unknown to the reader. The vocabulary learned implicitly while reading was measured in a pretest - treatment - posttest design. The learners read three texts, with lemma coverages of 92%, 90% and 85%, respectively. The relation between dictionary use and word retention was also examined.The study revealed an average word-learning improvement of 32,5%, with no differences between texts with a 92%, 90% or 85% lemma coverage. With respect to dictionary use, the learners looked up an average of 8.0 words. Two-thirds of these words were known to them; they looked up only one-third of the unknown words. We found there was a relation between dictionary use and the retention of unknown words. We concluded that the method we propose for an automated adaptive selection of reading texts and individualized dictionaries ensures that learners of different proficiency levels receive linguistic input that is best suited to their abilities.