Date of Award
Doctor of Philosophy
Arthur C. Graesser
Philip I. Pavlik
Jia Wei Zhang
Learners often cannot apply (transfer) the knowledge they learned from instructional settings into a new context. Therefore, their knowledge is likely “inert.” Research shows that learners must be actively involved in learning construction activities to enable knowledge transfer to occur. Self-explanation is one such constructive cognitive activity that involves explaining learning materials (expository texts, worked examples) to oneself with attempts to make sense of new information. It has been shown to support deep comprehension and knowledge transfer. However, self-explanations usually cannot be spontaneously generated by learners, but need to be elicited by prompts. The prompts can range from generic type (e.g., “Explain this!”) to content-specific type (e.g., filling in the blank of an incomplete sentence or selecting an explanation from multiple choices.) based on the amount of guidance they provide. This dissertation investigated the effectiveness of three types of self-explanation prompts (content-specific prompts, generic prompts, and generic prompts with a form of guidance) being applied to learners with different levels of aptitudes (prior knowledge and learning ability) when they learn probability. The self-explanation session was implemented in AutoTutor. The learners were prompted to self-explain correct and incorrect solutions to procedural probability questions. Four research questions were investigated in the study. First, are all three types of prompts effective in improving learning? Second, are the generic prompts with a form of guidance more effective than content-specific and generic prompts? Do they elicit more high-quality self-explanations in general? Third, are there interaction effects between learners’ aptitudes and different types of prompts? And lastly, do high-quality self-explanations facilitate far transfer ofknowledge? The results suggested that only generic prompts with or without guidance were effective in improving learning. Moreover, they were more effective but did not elicit more high-quality self-explanations than content-specific prompts. There were no interaction effects between learners’ aptitudes and different types of prompts, which means that learners’ aptitudes do not vary the effects of different types of prompts on learning. High-quality self-explanations predicted far transfer of learning, as was expected. The dissertation discusses the results, the limitations of the study, and future directions on self-explanation research.
Dissertation or thesis originally submitted to the local University of Memphis Electronic Theses & dissertation (ETD) Repository.
Shi, Genghu, "Prompting Self-explanations during the Learning of Probability: Content-Specific versus Generic versus Generic with a Form of Guidance" (2021). Electronic Theses and Dissertations. 2187.