Example-based learning is a well-known instructional method for effective cognitive skill acquisition in complex domains. "(Contrasting) erroneous examples" are a promising extension that embed errors in instructional material, potentially fostering not only positive but negative knowledge. However, the mechanisms and conditions for…

In designing an intelligent tutoring system, a core area of the application of AI in education, tips from the system or virtual tutors are crucial in helping students solve difficult questions in disciplines like mathematics. Traditionally, the manual design of general tips by teachers is time-consuming and error-prone. Generative AI, like…

In learning from examples, students are often first provided with basic instructional explanations of new principles and concepts and second with examples thereof. In this sequence, it is important that learners self-explain by generating links between the basic instructional explanations' content and the examples. Therefore, it is well…

This study aimed to combine the use of electronic technology and dynamic testing to overcome the limitations of conventional static testing, and adapt more closely to children's individual needs. We investigated the effects of a newly developed computerized series completion test using a dynamic testing approach and its relation to school…

The general public consumes financial products such as loans that are administered in the realm of nominal and effective interest rates. It is debatable if most consumers really understand how these rates function. This article explores the conceptions that student teachers have about nominal and effective interest rates. The APOS theory…

Background: We tested the effects of an intervention on the learning of introductory thermodynamics principles. This intervention, OEM-Thermo, is designed to prompt the cognitive operations of meaningful learning: organization, elaboration, and monitoring. We also sought evidence to show that execution of these operations was associated with…

Purpose: The purpose of this paper is to develop a set of generic prompting principles and a framework of prompts that have the potential to foster learning and skill acquisition among adult novices when performing complex, ill-structured problems. Design/methodology/approach: Relevant research in the literatures surrounding problem structure,…

Learning to argue is prerequisite to solving complex problems in groups, especially when they are multidisciplinary and collaborate online. Environments for Computer-Supported Collaborative Learning (CSCL) can be designed to facilitate argumentative knowledge construction. This study investigates how argumentative knowledge construction in…

How does the type of learning material impact what is learned? The current research investigates the nature of students' learning of math concepts when using manipulatives (Uttal, Scudder, & DeLoache, 1997). We examined how the type of manipulative (concrete, abstract, none) and problem-solving prompt (metacognitive or problem-focused) affect…

In two experiments we explored how learning from traditional molar worked-out examples--focusing on problem categories and their associated overall solution procedures--as well as from more efficient modular worked-out examples--where intrinsic cognitive load is reduced by breaking down complex solutions into smaller meaningful solution…

THE OBJECTIVES OF THIS STUDY WERE (1) TO IDENTIFY AND COMPARE THREE KINDS OF TRANSFER EFFECTS--AN EFFECT ASSOCIATED WITH CUE REPETITION, A LEARNING-TO-LEARN EFFECT, AND A WARM-UP EFFECT, AND (2) TO EVALUATE THE USEFULNESS OF CUE-RESPONSE CORRELATIONS IN EXPLAINING TRANSFER EFFECTS. THE STUDY WAS BASED ON THE DEFINITION OF TRANSFER EFFECTS AS…