engleski

Prediction of reading comprehension ability in English as a second language

Developing reading comprehension skills is one of the key purposes of teaching and learning a foreign language. Reading is a complex process dependent on a number of factors such as learners’ language proficiency, prior experience and background knowledge, the way of processing information and personality. Since the use of modern technology has a growing impact on socialization and education nowadays, this research, besides addressing the issues of English as a second language (ESL) reading comprehension ability, Internet overuse and shyness, is concerned with achieving better understanding of the relationships among these variables. It aims to create a neural network model with good prediction capacity when the categories of measured Internet overuse and shyness, along with some other variables, are used as predictors. 225 class teacher students took part in this research. The results showed that the majority of these students have limited symptoms of problematic Internet use (61.78%) and moderate level of shyness (58.67%). Moreover, these two variables did not show statistically significant relationships (p<0.05) with ESL reading comprehension. Neural network model managed to predict a great degree (72.73%) of students’ ESL reading comprehension abilities and revealed the significance of these variables in its prediction.

ESL, reading comprehension, neural network, predicting

Knjiga sažetaka "42nd Annual ATEE Conference 2017 Book of Abstracts" je dostupna samo u elektroničkom obliku.