A Heuristic Method for Learning Path Sequencing for Intelligent Tutoring System (ITS) in E-learning

Abstract

Course sequencing is one of the vital aspects in an Intelligent Tutoring System (ITS) for e-learning to generate the dynamic and individual learning path for each learner. Many researchers used different methods like Genetic Algorithm, Artificial Neural Network, and TF-IDF (Term Frequency- Inverse Document Frequency) in E-leaning systems to find the adaptive course sequencing by obtaining the relation between the courseware. In this paper, heuristic semantic values are assigned to the keywords in the courseware based on the importance of the keyword. These values are used to find the relationship between courseware based on the different semantic values in them. The dynamic learning path sequencing is then generated. A comparison is made in two other important methods of course sequencing using TF-IDF and Vector Space Model (VSM) respectively, the method produces more or less same sequencing path in comparison to the two other methods. This method has been implemented using Eclipse IDE for java programming, MySQL as database, and Tomcat as web server.

Multi-Agent Paradigm for Semantic Web Service in E-learning System

“…We assumed m as the semantic value of the keyword in particular book. We have used this approach to compute the semantic values to find the learning path sequencing in previous work (Al-Radaei & Mishra, 2011).…”

“…The result of these rules is based on the semantic keywords of the background concept and concept leaned. The next courseware is assign to the learner as we have compute in our previous work (Al-Radaei & Mishra, 2011)…”

Learner's Performance Evaluation based on Knowledge Extracting and Ontology

“…The highest values for this keyword is in courseware cw5 because the learning materials in cw5 are contain of class and object topic. We have used the calculation of keywords semantic values to generate dynamic learning path sequencing for learner according to his course selection [16].…”

Optimal Strategy for the Smartphone Industry in Taiwan

“…ANP is an extension regarding the analytic hierarchy process (AHP); Saaty (1999) proposed an assessment scheme based on the holistic significance via integrating linkages and feedback into a decision-making system. The AHP denotes a framework with an independent hierarchical relationship (Rigi & Khoshalhan, 2011); and it also has been used to assign a weight to each course using its attitudes, knowledge level, motivation, and learning style (Al-Radaei & Mishra, 2011). Technically, the published ANP applications has mainly dealt with strategies and logistics in the supply-chain management (Sarkis, 2003), project selection (Meade & Presley, 2002;Cheng & Li, 2005), location selection (Eddie, Cheng, & Ling, 2005), strategic alliance partner (Büyüközkan, Feyzioğlu, & Nebol, 2008), project selection (Amiri, 2010), and so on.…”