ABSTRACT

This book explores the measurement of learning effectiveness and the optimization of knowledge retention by modeling the learning process and building the mathematical foundation of multi-space learning theory.

Multi-space learning is defined in this book as a micro-process of human learning that can take place in more than one space, with the goal of effective learning and knowledge retention. This book models the learning process as a temporal sequence of concept learning, drawing on established principles and empirical evidence. It also introduces the matroid to strengthen the mathematical foundation of multi-space learning theory and applies the theory to vocabulary and mathematics learning, respectively. The results show that, for vocabulary learning, the method can be used to estimate the effectiveness of a single learning strategy, to detect the mutual interference that might exist between learning strategies, and to predict the optimal combination of strategies. In mathematical learning, it was found that timing is crucial in both first learning and second learning in scheduling optimization to maximize the intersection effective interval.

The title will be of interest to researchers and students in a wide range of areas, including educational technology, learning sciences, mathematical applications, and mathematical psychology.

chapter Chapter 1|10 pages

Introduction on Multi-Space Learning

chapter Chapter 2|4 pages

Partition Spaces to Optimize Learning Effectiveness

chapter Chapter 3|15 pages

Matroid Theory

chapter Chapter 4|16 pages

Current Foundations of Learning Sciences

chapter Chapter 5|19 pages

Applications in Vocabulary Learning

chapter Chapter 6|27 pages

Applications in Math Learning

chapter Chapter 7|4 pages

Summary