Design an Adaptive E-learning Application Architecture based on IEEE LTSA reference model

Abstract

IntroductionThe rapid development of information technology makes the data communication and information delivery technology most effective. Moreover, this development has considerable advantages in every field of life, especially in education sector. Qomaruddin [1] proposed that using e-learning has many advantages over conventional learning, such as: quick feedback to students, saving of time in marking, consistently in marking and improve monitoring in students. While there are numerous e-learning solutions available today, the differentiating factors are the innovative instructional design and custom content development process [2]. Furthermore, to establish learning and development theories in web based learning, the system design should able to recognize the individual learning requirements [3]. The system has to recognize the individual requirements for ergonomic reasons, or adaptations to learning styles for an easier introduction into a topic.In the context of e-learning, the adaptation is about creating a learner experience that purposely adjusts to various conditions over a period of time with the intention of increasing success for the effectiveness of e-learning application. The adaptation concept in e-learning application has been on the e-learning research agenda for well over three decades in different research topics such as intelligent tutoring systems [4], adaptive hypermedia [5][6][7] and Multiagent systems [8] often based upon an instructional design model or guidelines and concept understanding. Linawati [9] explain that the students wer satisfied with adaptive hypermedia courseware, their academic achievement were rise significantly and the dropout rate were diminished.Meanwhile, several studies have focused on the pedagogical aspect of e-learning systems over the past few years, but they have provided insufficient guidelines for e-learning designers [10]. The development of e-learning standards is a complicated, time-consuming, and challenging process. Some projects have focused on determining the standard architecture and format for learning environments, such as IEEE learning technology systems architecture (LTSA), instructional management systems (IMS), and sharable content object reference model (SCORM) [11].Nowadays, the standardizations of e-learning application are abundant and cover all aspects of e-learning and distance education, from representation, packaging, and publishing of learning objects (LOs); to metadata that describe LOs. Furthermore, some standards

MCGDM with AHP based on Adaptive Interval Value Fuzzy

“…These steps are Modeling Stage, Modeling is the stage of identification of MCGDM problems by determining the number of variables to be used in the study (criteria, alternatives, appraisers, and respondents) as shown in Figure 4. The measurement indicators of e-learning in this study are determined based on Learning Technology System Architecture (LTSA) with adaptive design personalize and ISO 9126 [15][16]. The next step, weighting using the concept of Adaptive Interval Value Triangular Fuzzy Number (AIV-TFN) with different interval points as shown in Figure 2.…”

“…Some previous researchers about interval value Fuzzy are decision-making model based on Interval Value Triangular Fuzzy Number by using extension Fuzzy TOPSIS for selection [11], Fuzzy analytic hierarchy process with Fuzzy type-2 interval sets [12], hybrid [15,16]. The novelty research is to study the concept of group decision making with interval value Fuzzy to improve the point of the interval.…”

MCGDM with AHP based on Adaptive Interval Value Fuzzy

“…These steps are Modeling Stage, Modeling is the stage of identification of MCGDM problems by determining the number of variables to be used in the study (criteria, alternatives, appraisers, and respondents) as shown in Figure 4. The measurement indicators of e-learning in this study are determined based on Learning Technology System Architecture (LTSA) with adaptive design personalize and ISO 9126 [15][16]. Figure 2.…”

“…Some previous researchers about interval value Fuzzy are decision-making model based on Interval Value Triangular Fuzzy Number by using extension Fuzzy TOPSIS for selection [11], Fuzzy analytic hierarchy process with Fuzzy type-2 interval sets [12] [15,16]. The novelty research is to study the concept of group decision making with interval value Fuzzy to improve the point of the interval.…”

Step-Function Approach for E-Learning Personalization

“…These works differ in terms of factors and approaches that are considered for the e-learning personalization. [17] Accordingly, this paper focuses on the research question, "how to propose a stepfunction approach for an e-Learning personalization based on the knowledge-ability factor?". At the moment, there are no similarities researchers have been discussing the step-function approach.…”