Human-Computer Interaction Institute,
BibTeX
@MISC{Wylie_human-computerinteraction,
author = {Ruth Wylie and Kenneth Koedinger and Teruko Mitamura},
title = {Human-Computer Interaction Institute,},
year = {}
}
OpenURL
Abstract
Abstract. Self-explanation is an effective instructional strategy for improving problem solving in math and science domains. However, our previous studies, within the domain of second language grammar learning, show self-explanation to be no more effective than simple practice; perhaps the metalinguistic challenges involved in explaining using one’s non-native language are hampering the potential benefits. An alternative strategy is tutoring using analogical comparisons, which reduces language difficulties while continuing to encourage feature focusing and deep processing. In this paper, we investigate adult English language learners learning the English article system (e.g. the difference between “a dog ” and “the dog”). We present the results of a classroom-based study (N=99) that compares practice-only to two conditions that facilitate deep processing: self-explanation with practice and analogy with practice. Results show that students in all conditions benefit from the instruction. However, students in the practice-only condition complete the instruction in significantly less time leading to greater learning efficiency. Possible explanations regarding the differences between language and science learning are discussed.







