Design and development of an innovative individualized adaptive and intelligent e-learning system for teaching–learning of probability unit: Details of UZWEBMAT Özcan Özyurt a,⇑ , Hacer Özyurt b , Adnan Baki b a Department of Computer Technologies, Trabzon Vocational School, Karadeniz Technical University, Akçaabat, Trabzon, Turkey b Department of Science and Mathematics Education, Karadeniz Technical University, Trabzon, Turkey article info Keywords: Adaptive educational hypermedia Individualized e-learning Individual differences Learning style based e-learning system Mathematics education abstract In this study, an innovative adaptive and intelligent web based e-learning system, UZWEBMAT (Turkish abbreviation of Adaptive and INtelligent WEB based MAThematics teaching–learning system) was designed, developed and implemented. This e-learning system was intended for learning and teaching secondary school level permutation-combination-binomial expansion and probability subjects. Content which was prepared according to Turkish curriculum for secondary school mathematics course was transformed into learning objects in three different ways in accordance with VAK (Visual–Auditory– Kinesthetic) learning styles. Primary/secondary/tertiary learning styles of learners registering the system are determined and each learner receives the content appropriate for his/her dominant learning style. Also, they can be directed to contents of other styles according to their performances thanks to an expert system. Learning objects constituting the content were prepared according to constructivist approach. An active role for the learner was the purpose. Tips and intelligent solution supports within the learning objects were presented with expert system support to the learners. With this structure, UZWEBMAT bears the characteristics of intelligent tutoring system as well as an adaptive e-learning environment. All the movements of learners studying with UZWEBMAT are recorded and the necessary information is reported to both learners and teachers in a visualized way. Crown Copyright Ó 2012 Published by Elsevier Ltd. All rights reserved. 1. Introduction Today, learning environments vary and evolve in parallel with rapid development of informatics technology. In this sense, e-learning environments have become common in recent years. Traditional e-learning environments present pre-determinated content in the same sequence to all learners. Therefore, they be- came the focus of many criticisms due to their structure. These criticisms and new approaches led to the birth of a new concept which is Adaptive Intelligent Web Based Education Systems (AIW- BES). AIWBESs were developed as an alternative to traditional e-learning environments that are developed according to ‘‘one- size-fits-all’’ approach (Brusilovsky, 1996; Brusilovsky, 2001; Brusilovsky & Peylo, 2003). AIWBESs are systems where Adaptive Educational Hypermedia System (AEHS) and Intelligent Tutoring System (ITS) architectures are conceived together. Though AEHSs and ITSs are often used together, they do not mean the same concept literally (Brusilovsky & Peylo, 2003). AEHSs are environments where individual differences of learners are en- tirely taken into account offering different content and browsing support to each individual. As for ITSs, they are computer systems which are designed using artificial intelligence methods and which know what to teach, how to teach and whom to teach (Brusilovsky & Peylo, 2003; Murray, 1999). ITSs are considered as education sys- tems in which artificial intelligence methods are employed. They are also considered as systems offering intelligent problem solution supports and acting as intelligent solution analysts (Brusilovsky & Peylo, 2003; Keles ß, Ocak, Keles ß, & Gülcü, 2009; Muñoz-Merino, Molina, Muñoz-Organero, & Kloos, 2012). Design of AIWBESs is one of the important research topics for researchers’ education and computer sciences. Key concept in these systems is being known which characteristic of the learner will be computerized and how to use this information. Tendency of researchers regarding this topic is taking learning styles, which is considered as the preference of taking, using and saving the information, into account (Kainnen, 2009). According to research- ers, e-learning environments developed taking into account learn- ing styles are more efficient than traditional e-learning environments. Besides, according to many previous studies, e-learning environments employing a specific learning style are more efficient for learners with higher level of satisfaction and re- duced period of time for learning (Bajraktarevic & Fullick, 2003; Chua, Liaob, Chenc, Lind, & Chen, 2011; Manochehr, 2006; Mustafa 0957-4174/$ - see front matter Crown Copyright Ó 2012 Published by Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.eswa.2012.12.008 ⇑ Corresponding author. Tel.: +90 4622281052x7548. E-mail addresses: oozyurt@ktu.edu.tr (Ö. Özyurt), hacerozyurt@ktu.edu.tr (H. Özyurt), abaki@ktu.edu.tr (A. Baki). Expert Systems with Applications 40 (2013) 2914–2940 Contents lists available at SciVerse ScienceDirect Expert Systems with Applications journal homepage: www.elsevier.com/locate/eswa