Artificial Intelligence Methods in E-Learning

Artificial Intelligence Methods in E-Learning

Meltem Eryılmaz, Afaf Muftah Adabashi, Ali Yazıcı
DOI: 10.4018/978-1-5225-8476-6.ch015
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Gathering and extracting knowledge from the large amount of data available today is becoming more and more important in our information society, and similarly, learning is an essential important part of our everyday lives. The new requirements of the competing world and the development of more advanced technologies have also changed traditional educational systems, which now employ better and more effective teaching and learning methods. In this regard, the integration of artificial intelligence (AI) technologies in the field of education offers both great challenges and opportunities in building e-learning systems. E-learning systems allow learners to access the educational materials ubiquitously from anywhere at any time. Therefore, these systems have to become adaptive to the needs and preferences of each individual learner. This chapter presents a review of the important concepts and background for research to include introduction and examination of e-learning systems and intelligent tutoring systems (ITSs), available today.
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E-Learning has been seen by many as a major shift from the teacher-centered model in the traditional learning system to a learner-centered one, where students learn actively and can decide what, how, where, and when to do it (Brown, 2003). Furthermore, Rosenberg (2001) defines the term e-learning as, “the use of Internet technologies to deliver a broad array of solutions that enhance knowledge and performance.” Longmire (2001) states that “e-Learning covers a wide set of applications and processes such as computer-based learning systems, Web-based learning systems, virtual classrooms, and digital collaborative learning GroupWare packages.” E-Learning content is for the most part conveyed by means of Internet, satellite communication, TV, DVD and CD-ROM.

Both computers and software have evolved with the development of Internet, so that online learning has become widespread worldwide. Such learning also removes the distance barriers to education, thereby helping students and other learners access web-based material anytime from anywhere in the world by being connected to Internet. Figure 1 shows the advantages of E-learning systems.

Figure 1.

Advantages of e-learning systems


Through the evolution of Internet and the growth of Web technology, distancelearning environments have been created to support learning processes such as Massive Open Online Courses (MOOCs), which first emerged from the Open Educational Resources (OER) in 2008. MOOCs allow learners around the world to access courses offered by different educational institutions via Internet (Sinclair, Boyatt, Rocks, & Joy, 2015). There are many commercial and non-profit providers of MOOCs such as Coursera1 and FutureLearn2.

Key Terms in this Chapter

Faculty Development: Also known as faculty professional development which refers to the activities that help faculty members in improving their knowledge skills, teaching effectiveness, and in improving the vitality of educational institutions.

Intelligence Tutoring Systems: A computer program that contains some intelligence and aims to provide customized course material or feedback to learners based on their characteristics.

Artificial Intelligence: The certain behaviors and characteristics of computers and machines that make them mimic mental abilities and behave like human being.

Adaptive Learning: Is a computer-based or web-based learning system that creates a unique learning environment meeting the needs and preferences of each individual student.

Student Characteristics: Different aspects of learner essential to be considered when developing intelligent educational systems, which can be static such as age, email, etc., or dynamic like knowledge level, learning styles, preferences, etc.

Learner-Centered Learning: The method that focuses on shifting the teaching process from teacher to student and aims to engage student in a hard work independently or collaboratively

Machine Learning: One of the branches of artificial intelligence developing algorithms and technologies that makes the computer able to learn from experiences.

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