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)

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 (CSL) learners. In supporting CSL learners to build robust orthographic representations in Chinese, addressing the challenges of visual similarity of characters (e.g., 理 and 埋) 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: (1) (...) Stroke Sequence, aform-emphasisstrategy, (2) Key-images, aform+meaningstrategy utilizing visual code, (3) Pithy Formulas with Key-images, aform+meaningstrategy 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 (visually similar vs. dissimilar), and testing time. The dependent variables were learners’ proportions of accurate responses to reading and writing Chinese characters through a posttest (immediately performed after learning) and a delayed posttest (1 week after learning); 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 charactersviathe three strategies, respectively, differing between whether the characters were presented in similar pairs or dissimilar pairs. Data were analyzedviathree-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 (verbal and visual) over the Key-images (visual) 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 twoform+meaningstrategies over the strategy that focused primarily onform.Suggestions for future research and pedagogical implications on learning visually similar characters were offered. (shrink)

We analyze naturally occurring datasets from student use of educational technologies to explore a long-standing question of the scope of transfer of learning. We contrast a faculty theory of broad transfer with a component theory of more constrained transfer. To test these theories, we develop statistical models of them. These models use latent variables to represent mental functions that are changed while learning to cause a reduction in error rates for new tasks. Strong versions of these models provide a common (...) explanation for the variance in task difficulty and transfer. Weak versions decouple difficulty and transfer explanations by describing task difficulty with parameters for each unique task. We evaluate these models in terms of both their prediction accuracy on held-out data and their power in explaining task difficulty and learning transfer. In comparisons across eight datasets, we find that the component models provide both better predictions and better explanations than the faculty models. Weak model variations tend to improve generalization across students, but hurt generalization across items and make a sacrifice to explanatory power. More generally, the approach could be used to identify malleable components of cognitive functions, such as spatial reasoning or executive functions. (shrink)

How do teachers learn about what learners already know? How do learners aid teachers by providing them with information about their background knowledge and what they find confusing? We formalize this collaborative reasoning process using a hierarchical Bayesian model of pedagogy. We then evaluate this model in two online behavioral experiments (N = 312 adults). In Experiment 1, we show that teachers select examples that account for learners' background knowledge, and adjust their examples based on learners' feedback. In Experiment 2, (...) we show that learners strategically provide more feedback when teachers' examples deviate from their background knowledge. These findings provide a foundation for extending computational accounts of pedagogy to richer interactive settings. (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)