Adapting to learner characteristics is essential when selecting exercises for learners in an intelligent tutoring system. This thesis investigates how humans adapt next exercise selection (in particular difficulty level) to learner personality (self-esteem), invested mental effort, and performance to inspire an adaptive exercise selection algorithm. First, we describe the investigations to produce validated materials for the main studies, namely the creation and validation of self-esteem personality stories, mental effort statements, and mathematical exercises with varying levels of difficulty. Next, through empirical studies, we investigate the impact on exercise selection of learner's selfesteem (low versus high self-esteem) and effort (minimal, little, moderate, much, and all possible effort). Three studies investigate this for learners who had different performances on a previous exercise: just passing, just failing, and performed well. Participants considered a fictional learner with a certain performance, self-esteem and effort, and selected the difficulty level of the next mathematical exercise. We found that self-esteem, mental effort, and performance all impacted the difficulty level of the exercises selected for learners. Using the results from the studies, we generated an algorithm that selects exercises with varying difficulty levels adapted to learner characteristics. Finally, through a survey with professional teachers, we evaluated our algorithm and found that the algorithm's adaptations were appropriate in general.

The study called for the identification of a group of underachievers at the eleventh and tenth grade levels.

Without academic intervention, such as tutoring, at-risk students may not pass their courses. This study examined differences between the final grades of at-risk students and tutoring methods, such as self-determined tutoring, academic advisor scheduled tutoring, group tutoring, one-to-one tutoring, peer tutoring, and professional tutoring. This study drew from cognitive learning theory and humanistic theory for its conceptual framework. A quantitative, ex post facto research design was used. Archived data supplied by the Registrar's Office and the Academic Enrichment Coordinator included records of 95 male and female students conditionally enrolled at Methodist University in the Academic Enrichment Program during the 2007 to 2009 academic years. The results of an independent samples t test determined there was a significant difference between final grades of students who had self-determined tutoring compared to those who had academic advisor determined tutoring. Results of a one-way analysis of variance determined there were significant differences in final grades of students who received group tutoring compared to one-to-one tutoring and peer tutoring compared to professional tutoring. The preliminary results raised questions of the importance of tutor status in a group or one-to-one setting. A post hoc analysis using a paired-samples t test revealed a statistically significant difference in final grades of students in group settings but not in one-to-one settings. The results of this study offer the potential for positive social change to those in higher education by advancing the understanding of how to support and provide intervention programs, such as tutoring for at-risk students, in order to reduce their risk of academic failure during college.

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.

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.

For urban secondary students, the benefits of attending after-school programs may not be solely academic—rather, their attendance and participation may yield more fundamental development needs. A supportive network of influential and positive mentors can improve urban secondary students learning experience outside of the classroom. Urban secondary students may have access to support and assistance from mentors by attending an after-school program. This qualitative ethnographic study explored the perceptions of tutors working in an after-school program in a large urban school district. This study attempted to understand of the tutors’ motivation for working with students, the support that they provided to the students, and the needs they thought the students have. The data was collected through individual interviews and observations of the tutors during the program. Data was analyzed for common themes to support the research questions. From the interview questions, a total of twelve themes were generated to answer the three research questions. According to the participants interviewed in this study, the interactions with the tutors in the program served as catalysts that promoted student academic success and social development. While the themes originating from the questioned varied, the underlying conclusion of the interview data from this research study is that students take more of an interest in themselves and their academic ability when someone else takes a genuine interest in them and their academic ability.

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.)--University of Texas at Austin, 2000. / Vita. Includes bibliographical references (leaves 219-229). Available also in a digital version from Dissertation Abstracts.

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

Thesis (Ph.D.)--Ohio State University, 2003. / Title from first page of PDF file. Document formatted into pages; contains xii, 207 p.; also includes graphics. Includes abstract and vita. Advisor: Ralph Gardner, College of Education. Includes bibliographical references (p. 157-172).