Adaptive learning for ESL based on computation

Abstract

In the conventional English as a Second Language (ESL) class-based learning environment, teachers use a fixed learning sequence and content for all students without considering the diverse needs of each individual. There is a great deal of diversity within and between classes. Hence, if students' learning outcomes are to be maximised, it is important to know how to provide learning content using students' preferences, learning characteristics and knowledge background as a basis. A five-step algorithm was proposed that was based on the four factors (gender, learning motivation, cognitive style and learning style) as the different learner characteristics. The percentage increase between the pretest and posttest scores was used to determine optimal adaptive learning sequences to accommodate a variety of individual differences. The algorithm included the following five steps-to obtain the learning performance, to distinguish the learning performance of the lowest and highest groups, to use the different learning sequences as a basis for categorisation, to test the four factors between the lowest and highest performance, and to reduce the number of handouts. Finally, an empirical study for validating the adaptive learning sequence was conducted. By analysing the students' characteristics and the optimal learning sequences, an attempt was made to develop an adaptive learning sequence system to facilitate students' learning and to maximise their learning outcome, thus addressing the problem of fixed learning sequences in conventional ESL instruction. IntroductionAdaptive learning is a system that was developed to accommodate a variety of individual differences. Recently, in order to improve students' interaction and learning

Mandatory use of technology in teaching: Who cares and so what?

“…However, within the environment of most school settings where traditional pedagogies prevail, it may not be easy for teachers to adopt comfortably the kind of risk‐taking behaviours described by Sacristán et al (2007). Hence, even though there is evidence to show that educational technology can change the way teachers teach to become more dynamic (Teo, 2010a; Wang & Liao, 2011), it is essential for teachers to see the usefulness of technology applications for learning purposes (Jung & Latchem, 2011) and to build up their confidence in such applications (Kessler & Plakans, 2008).…”

“…This is consistent with McWilliam's (2008) proposed concept of a “guide on the side,” but it seems that to be a “meddler in the middle,” there are further steps to be taken. In fact, the appropriate use of educational technology can change teaching into a more dynamic and adaptive form because it broadens the possibilities for learning processes (Nachmias, Mioduser & Forkosh‐Baruch, 2008) and maximises the potentials of students from diverse backgrounds and abilities (Wang & Liao, 2011). However, the first step to actualise a change of teacher's role and teaching style is to make teachers see how DT works in various settings (see Jung & Latchem, 2011).…”

A systematic literature review of personalized learning terms

“…For instance, adaptive learning has been interchangeably used by Yang, Hwang and Yang (2013) in their study that focused on the development of adaptive learning by considering students' preferences (Dwivedi and Bharadwaj, 2013) and characteristics, including learning styles (Çakıroğlu, 2014;Klašnja-Milićević, Vesin, Ivanović and Budimac, 2011) and cognitive styles (Lo, Chan and Yeh, 2012) which concluded to be effective. Wang and Liao (2011) defined adaptive learning as a developed system (Lu, Chang, Kinshuk, Huang and Chen, 2014) to accommodate a variety of individual differences (Scheiter et al, 2019;Wang & Liao, 2011) such as gender, learning motivation, cognitive type, and learning style to determine optimal adaptive learning experience that accommodates a variety of individual differences (Afini Normadhi et al, 2019) to remove barriers of time and location. Griff and Matter (2013) discussed that adaptive learning is also referred to as computer-based learning, adaptive educational hypermedia, and intelligent tutoring.…”

Effects Of Personalization in Teaching English On The Achievement Of University Students and Student Views Regarding The Implementation

“…At this point, Brusilovsky (2001: 90) accepts adaptive learning as a crucial alternative to the "one size fits all" approach. Adaptive learning is based on the consideration of individual differences and making the system suitable according to those differences (Wang & Liao, 2011). These learning systems are related to the preferences or interests of learners and an adaptive learning system is personalized by building the teaching process on one of these elements (Mamat & Yusof, 2013: 587).…”