Edited by: Trude Heift and Mathias Schulze
Published by: Routledge
Series: Routledge Studies in Computer-Assisted Language Learning (nr 3)
Published: 2007
I had the pleasure of reading Trude Heift and Mathias Schulze’s interesting book ‘errors and intelligence in computer-assisted language learning. Parsers and technologies’, the first book to bring together a ‘comprehensive overveiw of the research involved [in Natural Language Processing] and that offers a solid introduction for students and researchers in CALL, Applied Linguistics and /or Computational Linguistics’ (p.4).
The authors start their book with a compelling argument for greater attention to the role of the technologies that feature in their book, such as Natrual Language Processing, Student Modeling, and Intelligent Language Tutoring Systems. They write: ‘Without intelligence, the system is merely another method of pesenting information, one not necessarily preferable to a static medium like print. Instead of multiple choice questions, relatively uninformative answer keys and gross mainstreaming of students characteristic of workbooks, NLP-based CALL is aiming at interactive computer systems possessing a high degree of artificial intelligence and capable fo processing natural language input ‘ (p.2). In doing so, they clearly link their interest in the subject with practitioners’ concerns. They also review studies that have shown that students prefer the feedback afforded by Natural Language Processing and some that have showed their superiority in affecting acquisition. (Trude Heift recently published a study with her colleague Annre Rimrott (2008), conducted along these lines which showed that tailored feedback from a spelling checker designed for language learners, can affect successful production.)
The book is divided into six parts: the first two parts discuss key concepts and different approaches of Natuaral Language Processing techniques in CALL and research into its effectiveness. Part three deals with error analysis and challenges in analysing human language, as well as some of the progress that has been made to-date. Part four discusses the role of feedback, part five discusses student modeling and the final part takes a broader view of both the history and future of the subject.
This is not an introductory text to computational linguistics and requires a degree of prior knowledge on the part of the reader. Concepts such as ‘parser’ are not explained at a basic level (although they are discussed at length). This book is not going to attract readers interested in learning more about CALL applications in language teaching, or even to learn about computational linguistics. Rather, it caters to a readership that is already interested in and has knowledge of computer applications in learning, teaching, and research. For these readers, the book offers a comprehensive, and well-written discusssion of the subject.
References
Kay, R. (2006). “Evaluating strategies used to incorporate technology into preservice education: a review of the literature.” Journal of research on technology in education 38(4): 383-408.
Stevens, V., R. Sussex R. and W. V. Tuman. A Bibliography of Computer-Aided Language Learning. New York: AMS Press, 1986.