No description available.

Motivation is important for learners. As the provision of education moves increasingly towards online delivery, keeping motivation high is a key challenge. The lack of personalized approaches traditionally delivered by human tutors increases drop out rates. This thesis investigates how a conversational agent, taking the role of a virtual tutor, could deliver personalised feedback on performance to learners. It also investigates the most effective emotional support to incorporate in this feedback in order to maintain learner motivation. How learners respond to feedback depends on many factors. We focus on learner personality as our adaptation criterion, in particular Generalized Self Efficacy (GSE) and the Five Factor model (FFM). First, based on the literature, the thesis establishes how the core concepts of motivation, affective state, feedback and personality relate to one another, and discusses other research into learner motivation and feedback. Our main methodology is the User-as-Wizard method where we model how people adapt to personality in the real world when giving feedback to learners. An algorithm is then developed to encapsulate these adaptations, and is then evaluated. To achieve this, we required a way to express different learner personalities in a controlled way. Personality can be described by many models, but one of the most popular and reliably validated is the Five-Factor Model. In this model, the personality of an individual is described by a score for each of the five dimensions or 'traits'. There are numerous self-report questionnaires for these traits, indicated by a measure of agreement with certain adjectives on a scale. To express the traits at polarized levels, we produced and validated ten stories, two for each of the traits, expressing only that trait at high and low level. These stories were based on the adjectives used in the IPIP-NEO questionnaire. We also created two polarized stories for Generalized Self Efficacy. Subsequently, we investigated how people use different slants (or bias) in performance feedback, depending on learner personality. We designed two experiments, in which participants took the role of a teacher. Participants were shown the learner's personality (through the personality story) and a set of test scores on a range of topics. We provided different ways of describing the learner's performance which could result in positive, neutral or negative slants (e.g. “you are slightly below my expectations” on a score of 10% is positive, and “you are substantially below my expectations” is neutral). The type of slant was established by a focus group of experts prior to the experiments. We found some evidence that slanting was used for very low test scores for students with low GSE, and positive slanting for conscientious students who had only just failed a test. Next, we investigated supplementing slant with emotional support. A set of emotional support statements was generated and categorized. A series of five experiments was run where participants gave feedback to students with differing personality traits (using the FFM stories) and test scores. Participants could provide the same performance feedback (with associated slant) from the previous experiments, and could choose to supplement this with the validated emotional support statements. The type of emotional support given did indeed vary between different personalities (e.g. neurotic individuals with poor grades received more emotional reflection), and an algorithm was created to describe these adaptations. Finally, we ran a qualitative study with teachers and students to investigate the algorithm's effectiveness. During the course of the thesis we also developed a methodology for generating, validating and investigating the use of Emotional Support for other domains. This has already been applied in research to persuade older adults to participate in social interactions and to support Community First Responders and carers when experiencing various stressors.

A multiple baseline design across activities and people was used to assess the effectiveness of a feedback package on the facial orientation of a young girl with autism. During baseline, observations indicated low rates of facial orientation and high rates of gaze avoidance during conversation (restricted operant) and play (free operant) conditions. After treatment, facial orientation rates increased and gaze avoidance rates decreased to levels similar to typically-developing peers and maintained at one month follow up. These results suggest that the feedback package was effective in producing durable facial orientation across different environments and people. Possible interpretations, strengths, and limitations are discussed.

Peiguan Wu. / Thesis (Ph.D.)--Chinese University of Hong Kong, 1998. / Includes bibliographical references (p. 73-89). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Mode of access: World Wide Web.

Two studies were undertaken in order to investigate the effect of different forms of error feedback and error framing in learning a complex novel task. The experimental task in both studies was a computer-based simulation of a group management situation. After each of the 12 trials, all participants received feedback about their performance on that trial. Participants receiving signal error feedback were also advised as to where they had made errors. Participants receiving diagnostic feedback were told how they could have achieved optimum performance on the previous trial. Learning, performance, strategy, exploration and depth of processing were measured during the task. Self-report measures of self-efficacy, self-set goals, satisfaction and intrinsic motivation were taken after the first six trials and again after all 12 trials were completed. In study 1, detailed diagnostic feedback was associated with better performance than feedback which simply signaled where an error had been made, or feedback that did not identify errors. Diagnostic feedback facilitated the development and use of effective problem-solving strategies and discouraged trial-and-error exploration of the problem space. In this research, exploration was found to be negatively associated with learning and performance. Learners??? self-efficacy moderated the effects of error feedback: learners with high self-efficacy showed high levels of performance regardless of the level of information that the feedback provided but for those with low self-efficacy, detailed diagnostic feedback was essential for the learning process. In the second study, positive error framing (error management) was investigated as a possible means of making signal error feedback more valuable in learning. However while positive error framing was associated with more exploration as expected, it also produced poorer strategies and worse performance than negative error framing (error avoidance instructions). Participants who used good learning strategies instead of exploration performed well despite impoverished feedback. Self-efficacy moderated the impact of error framing: positive error framing helped those with low self-efficacy, but for those with higher self-efficacy it was of more value to encourage error avoidance than error tolerance. The findings show important interactions between error framing, error feedback and learner characteristics.

Thesis (M. Ed.)--University of Hong Kong, 2006. / Title proper from title frame. Also available in printed format.

Thesis (Ph. D.)--University of Texas at Austin, 2006. / Vita. Includes bibliographical references.

Thesis (Ph. D.)--University of Missouri-Columbia, 2003. / Typescript. Vita. Includes bibliographical references (leaves 105-113). Also available on the Internet.

Thesis (Ph. D.)--University of Missouri-Columbia, 2003. / Typescript. Vita. Includes bibliographical references (leaves 105-113). Also available on the Internet.

Thesis (Ph.D.)--Ohio University, November, 2009. / Title from PDF t.p. Includes bibliographical references.