Uml-alf agent based adaptive learning framework : a case study on uml

Download
2010
Kocabaş, Efe Cem
As the amount of accessible and shareable knowledge increases, it is figured out that learning platforms offering the same context and learning path to all users can not meet the demands of learners. This issue brings out the necessity of designing and developing adaptive hypermedia systems. This study describes an agent-based adaptive learning framework whose goal is to implement effective tutoring system with the help of Artificial Intelligence (AI) techniques and cognitive didactic methods into Adaptive Educational Hypermedia Systems (AEHS) in the domain of Unified Modeling Language (UML). There are three main goals of this study. First goal is to explore how supportive agents affect student’s learning achievement in distance learning. Second goal is to examine the interaction between supportive agents and learners with the help of experiments in Human Computer Interaction laboratories and system analysis. The effects of the methodology that agents give misleading hints which are common mistakes of other learners are also investigated. Last goal is to deliver effective feedback to students both from IAs and tutors. In order to assess that UML-ALF has accomplished its objectives, we followed an experimental procedure. Experimental groups have taken the advantage of adaptive and intelligent techniques of the UML-ALF and control groups have used the traditional learning techniques. The results show that there is a positive correlation between variables practice score and number of agent suggestion which means, as the participants benefit from supportive agents, they get higher scores.

Suggestions

Usability Issues in Online Courses; User Tests of Web Course Tools
Gündoğan, Mihraç Banu (2006-09-13)
In online learning, the learner is responsible for his or her own learning process in a virtual environment. Before learning can take place, the design of the virtual environment is important since the user may face troubles in understanding the interface. Alongside with content development and media selection, usability issues also need to be considered and user tests provide beneficial feedback at the design and development stages.This study aims to draw attention to usability in online learning en...
Ontology learning and question answering (qa) systems
Başkurt, Meltem; Alpaslan, Ferda Nur; Department of Computer Engineering (2010)
Ontology Learning requires a deep specialization on Semantic Web, Knowledge Representation, Search Engines, Inductive Learning, Natural Language Processing, Information Storage, Extraction and Retrieval. Huge amount of domain specific, unstructured on-line data needs to be expressed in machine understandable and semantically searchable format. Currently users are often forced to search manually in the results returned by the keyword-based search services. They also want to use their native languages to expr...
Crossing: a framework to develop knowledge-based recommenders in cross domains
Azak, Mustafa; Birtürk, Ayşe Nur; Department of Computer Engineering (2010)
Over the last decade, excess amount of information is being provided on the web and information filtering systems such as recommender systems have become one of the most important technologies to overcome the „Information Overload‟ problem by providing personalized services to users. Several researches have been made to improve quality of recommendations and provide maximum user satisfaction within a single domain based on the domain specific knowledge. However, the current infrastructures of the recommende...
Missing link discovery in wikipedia: a comparative study
Sunercan, Ömer; Birtürk, Ayşe Nur; Department of Computer Engineering (2010)
The fast growing online encyclopedia concept presents original and innovative features by taking advantage of information technologies. The links connecting the articles is one of the most important instances of these features. In this thesis, we present our work on discovering missing links in Wikipedia articles. This task is important for both readers and authors of Wikipedia. Readers will benefit from the increased article quality with better navigation support. On the other hand, the system can be employ...
A hybrid movie recommender using dynamic fuzzy clustering
Gürcan, Fatih; Birtürk, Ayşe Nur; Department of Computer Engineering (2010)
Recommender systems are information retrieval tools helping users in their information seeking tasks and guiding them in a large space of possible options. Many hybrid recommender systems are proposed so far to overcome shortcomings born of pure content-based (PCB) and pure collaborative fi ltering (PCF) systems. Most studies on recommender systems aim to improve the accuracy and efficiency of predictions. In this thesis, we propose an online hybrid recommender strategy (CBCFdfc) based on content boosted co...
Citation Formats
E. C. Kocabaş, “Uml-alf agent based adaptive learning framework : a case study on uml,” M.S. - Master of Science, Middle East Technical University, 2010.