Naslov
Prediction of reading comprehension ability in English as a second language

Autori
Đurđević Babić, Ivana ; Benčina, Ksenija

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
42nd ATEE Annual Conference 2017 Changing Perspectives and Approaches in Contemporary Teaching / Sablić, Marija ; Škugor, Alma ; Đurđević Babić, Ivana - Brisel : Association for Teacher Education in Europe, 2018, 152-161

Skup
42nd Annual ATEE Conference Changing perspectives and approaches in contemporary teaching

Mjesto i datum
Dubrovnik, Hrvatska, 23.10.2017. - 25.10.2017

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
EFL, reading comprehension, neural network, predicting

Sažetak
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 foreign language (EFL) 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 indicate 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 EFL reading comprehension. Neural network model managed to predict a great degree (72.73%) of students’ EFL reading comprehension abilities and revealed the significance of these variables in its prediction.

Izvorni jezik
Engleski

Znanstvena područja
Informacijske i komunikacijske znanosti, Filologija

POVEZANOST RADA