Learning from examples is a very effective means of initial cognitive skill acquisition. There is an enormous body of research on the specifics of this learning method. This article presents an instructionally oriented theory of example-based learning that integrates theoretical assumptions and findings from three research areas: learning from worked examples, observational learning, and analogical reasoning. This theory has descriptive and prescriptive elements. The descriptive subtheory deals with (a) the relevance and effectiveness of examples, (b) phases of skill acquisition, and (...) (c) learning processes. The prescriptive subtheory proposes instructional principles that make full exploitation of the potential of example-based learning possible. (shrink)

Human and automated tutors attempt to choose pedagogical activities that will maximize student learning, informed by their estimates of the student's current knowledge. There has been substantial research on tracking and modeling student learning, but significantly less attention on how to plan teaching actions and how the assumed student model impacts the resulting plans. We frame the problem of optimally selecting teaching actions using a decision-theoretic approach and show how to formulate teaching as a partially observable Markov decision process planning (...) problem. This framework makes it possible to explore how different assumptions about student learning and behavior should affect the selection of teaching actions. We consider how to apply this framework to concept learning problems, and we present approximate methods for finding optimal teaching actions, given the large state and action spaces that arise in teaching. Through simulations and behavioral experiments, we explore the consequences of choosing teacher actions under different assumed student models. In two concept-learning tasks, we show that this technique can accelerate learning relative to baseline performance. (shrink)

This study investigates the effects of visual mnemonics and the methods of presenting learning materials on learning visually similar characters for Chinese-as-second-language learners. In supporting CSL learners to build robust orthographic representations in Chinese, addressing the challenges of visual similarity of characters is an important issue. Based on prior research on perceptual learning, we tested three strategies that differ in the extent to which they promote interrelated attention to the form and meaning of characters: Stroke Sequence, a form-emphasis strategy, Key-images, (...) a form + meaning strategy utilizing visual code, Pithy Formulas with Key-images, a form + meaning strategy combining visual and verbal codes. A pretest–posttest equivalent-group design was adopted. The independent variables were the learning strategy, the method of presenting character pairs, and testing time. The dependent variables were learners’ proportions of accurate responses to reading and writing Chinese characters through a posttest and a delayed posttest ; a learner experience survey was also administered to investigate learners’ opinions on each strategy. Sixty-six non-beginning learners of Chinese participated; they were randomly assigned to one of the two groups in which participants learned ten characters via the three strategies, respectively, differing between whether the characters were presented in similar pairs or dissimilar pairs. Data were analyzed via three-way ANCOVAs. The Pithy Formulas with Key-images and the Key-images generally yielded higher writing accuracy than Stroke Sequence immediately after learning. Notably, the advantage of the Pithy Formulas with Key-images over the Key-images on writing was specific to the participants that learned with visually similar pairs rather than those that learned with dissimilar pairs. All strategies were effective for reading, yet learners’ experience ratings favored the two form + meaning strategies over the strategy that focused primarily on form. Suggestions for future research and pedagogical implications on learning visually similar characters were offered. (shrink)

Evidence-Centered Design (ECD) is a framework for the design and development of assessments that ensures consideration and collection of validity evidence from the onset of the test design. Blending learning and assessment requires integrating aspects of learning at the same level of rigor as aspects of testing. In this paper we describe an expansion to the ECD framework (termed e-ECD) such that it includes the specifications of the relevant aspects of learning at each of the three core models in the (...) ECD, as well as making room for specifying the relationship between learning and assessment within the system. The framework proposed here does not assume a specific learning theory or particular learning goals, rather it allows for their inclusion within an assessment framework, such that they can be articulated by researchers or assessment developers that wish to focus on learning. (shrink)