Content Assessment in Intelligent Computer-aided Language Learning: Meaning Error Diagnosis for English as a Second Language
Year: 2008
Type: article
Abstract: Language practice that includes meaningful interaction is a critical component of many current language teaching theories.At the same time, existing research on intelligent computer-aided language learning (ICALL) systems has focused primarily on providing practice with grammatical forms.For most ICALL systems, content assessment of a learner response is limited to comparing it with a target response through string matching.But this severely restricts exercises that can be offered because expected responses must be tightly controlled.Yet the task-based activities that language instructors typically use in real language-learning settings require both form and content assessment in answer evaluation.Thus, there is a real need for ICALL systems that provide accurate content assessment beyond string matching.. . .
Author: Stacey M. Bailey
Institution: The Ohio State University
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: green
OpenAlex ID: W195850110