Learning management system (LMS) is usually used in higher education system. It has become compulsory to help the end users (instructors, students, and administrators) in their daily use, and learning analytics presents an auspicious approach. This chapter aims to investigate the acceptance of analytics and use of an LMS at Jordanian universities. It also focuses on the factors influencing acceptance of analytics in LMS at Jordanian universities. Therefore, the chapter presents a new model for acceptance of analytics in learning management systems at Jordanian universities called Jordanian Learning Management System (JLMS). This chapter is based on the most recent and related literature explaining various scenarios where LMSs address learning issues in the digital environment in a way that was not possible in the previous confines of print logic.
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In the last few years, the use of information technology (IT) has received interest from people in every walk of life (Majdalawi, Almarabeh, & Mohammad, 2014). At the present, IT based tools are not only used for business and daily activities, but also for university education, where it is used to manage different academic activities (Denscombe, 2014). A learning analytics system (McDaniel, Fanfarelli, & Lindgren, 2017) is software that is used in administration, reporting and other training exercises (Al-Dmour, 2014). The research question is: “What are the factors for the acceptance of analytics in learning management system at Jordanian universities?” This paper aims to identify the factors that impact on the acceptance of analytics in learning management system at Jordanian universities. This paper also investigates the literature on LMSs in many different contexts of learning analytics and the research methodology for the study is also presented.
Learning analytics are widely used at universities for streamlining teaching and learning tasks, as they effectively manage learning tools and resources for user participants (students and teachers) (Kats, 2010). A phenomenal revolution has occurred in the university education over the past decade as a result of learning analytics, as they have been found to significantly benefit students’ understanding and academic progress (Alnsour, Muhsen, Dababnah, Eljinini, & Barhoum, 2011). LMS applications are multifunctional, enabling students to have ubiquitous access to systems, watch lectures, download course materials and upload assignments online (AlQudah, 2014).
The latter provides convenience to students as never before and is conducive to study. To have efficient functioning of learning analytics, it is necessary to enable well-established links between data that is indexed by search engines, and web bots that connect and bind information together (Babić, 2012). LMS empowers users and offers a greatly enhanced user experience overall (McIntosh & Torres, 2014; Phillipo & Krongard, 2012).
A learning analytics greatly simplify learning and deliverables, such as tests, assignments and other forms of assessment, with the use of multimedia applications that incorporate team learning through dynamic, real time, documented collaboration. Some examples include the use of chat, file transfer and assessment applications. A learning analytics create new platforms for the active learner and results in greatly expanding the learning curve. To fully understand the nature and implications of different LMSs, it is vital to explore exactly what the LMS context is (Ahmad, Chinade, Gambaki, Ibrahim, & Ala, 2012). This study is based on the most recent and related literature explaining various scenarios where learning analytics address learning issues in the digital environment in a way that was not possible in the previous confines of print logics.