No abstract

<span>A Web server log files contain an entire record of the user’s browsing history such as referrer, date and time access, path, operating system (OS), browser and IP address. User navigation pattern discovery involves learning of user’s browsing behaviour to gain the pattern from web server log file. This paper emphasizes on identifying user navigation pattern from web server log file data of iLearn portal. The study implements the framework for user navigation including phases of acquisition of weblog, log query parser, preprocessor, navigational pattern modelling, clustering, and classification. This study is conducted in the context of the actual data logs of the iLearn portal of Universiti Teknologi MARA (UiTM). This study revealed the navigational patterns of online learners which relatively related to their intake or group along the semester of 14 weeks. Besides, access patterns for students along the semester are different and can be classified into three (3) quarter, namely Q1, Q2 and Q3 based on the total of week per semester. Future work will focus on the development of prototype to improve the security of online learning especially during the assessment progress such as online quiz, test and examination.</span>

Online learning is become more popular among university due to its flexibility and adaptability. The student authentication as online learner is widely seen as a major concern for online assessment. In most cases, there is absent of face-to-face supervision during online assessment, this situation leads the student to use or find help from others in order to get high scores in their result. This paper address the issue related to online assessment. The main objective of this work was to propose the use of online learner verification framework. This proposed solution utilizes the keystroke analysis and activity-based authentication for the online learner authentication. A fuzzy neural network is used to train and validate the online learner's identity. The proposed framework can be implementing in any online learning environment for verifying online learner identity.