Using electronic portfolios (e-portfolios) to assist learning is an important component of future educational models. A portfolio is a purposeful collection of student work that exhibits the student's efforts, progress and achievements in one or more areas. An e-portfolio contains a variety of information about a person's learning outcomes, such as artifacts, assertions from others, self-reflective information and presentation for different purposes. E-portfolios become sources of evidence for claims about prior conceptual knowledge or skills. This thesis investigates using the information contained in e-portfolios to initialize the learner model for an intelligent tutoring system. We examine the information model from the e-portfolio standardized specification and present a method that may assist users in initializing learner models using e-portfolios as evidence for claims about prior conceptual knowledge or skills. We developed the EP-LM system for testing how accurately a learner model can be built and how beneficial this approach can be for reflective and personalized learning. Experimental results are presented aiming at testing whether accurate learner models can be created through this approach and whether learners can gain benefits in reflective and personalized learning. Monitoring this process can also help ITS developers and experts identify how an initial learner model can automatically arise from an e-portfolio. Additionally, a well-structured learner model, generated by an intelligent tutoring system also can be attached to an e-portfolio for further use by the owner and others.

Thesis (Ph. D.)--Carnegie Mellon University, 2001. / "March 2001." Includes bibliographical references.

No description available.

No description available.

No description available.

No description available.

No description available.

Programming is one of the core skills required by Computer Science undergraduates in tertiary institutions worldwide, whether for study itself, or to be used as a tool to explore other relevant areas. Unfortunately, programming can be incredibly difficult; this is for several reasons, including the youth, depth, and variety of the field, as well as the youth of the technology that frames it. It can be especially problematic for computing neophytes, with some students repeating programming courses not due to academic laziness, but due to an inability to grasp the core concepts. The research outlined by this thesis focuses on our proposed solution to this problem, a constraint-based intelligent tutoring system for teaching the Java programming language, named J-LATTE. J-LATTE (Java Language Acquisition Tile Tutoring Environment) is designed to solve this problem by providing a problem-solving environment for students to work through programming problems. This environment is unique in that it partitions interaction into a concept mode and a coding mode. Concept mode allows the student to form solutions using high-level Java concepts (in the form of tiles), and coding mode allows the student to enter Java code into these tiles to form a complete Java program. The student can, at any time, ask for feedback on a solution or partial solution that they have formed. A pilot study and two full evaluations were carried out to test the effectiveness of the system. The pilot study was run with an assignment given to a postgraduate Computer Science course, and because of the advanced knowledge level of the students, it was not designed to test teaching effectiveness, but instead was useful in determining usability issues and identifying any software errors. The full evaluations of the system were designed to give insight into the teaching effectiveness of J-LATTE, by comparing the results of using the system against a simulated classroom situation. Unfortunately, the participant base was small, for several reasons that are explained in the thesis. However, the results prove interesting otherwise and for the most part are positive towards the effectiveness of J-LATTE. The participants’ knowledge did improve while interacting with the system, and the subjective data collected shows that students like the interaction style and value the feedback obtained.

No description available.

This thesis illustrates and evaluates a generic adaptive tutoring environment based on the theory of cognitive skill acquisition. The theory concerns acquiring problem-solving abilities in intellectual tasks, and emphasises the learning benefits of providing multiple examples and encouraging students to recognize and study their common structure. The system teaches by presenting side-by-side examples and providing devices to highlight their structural components. The purpose of the design is to assist the process of generalisation and reduce mapping by surface features, allowing students to apply their newly gained knowledge to different sets of problems. The study describes the development of Structural Example-based Adaptive Tutoring System (SEATS), which uses a simple adaptive engine and emphasises the structures of side-by-side examples to encourage students to compare them. / Thesis (PhD)--University of South Australia, 2001