A course in machine-assisted translation at final-year undergraduate level is the subject of the paper. The course includes a workshop session during which students compile a list of post-editing guidelines to make a text suitable for use in a clearly defined situation, and the paper describes this workshop and considers its place in the course and its future development. Issues of teaching MT to language learners are discussed.

This paper describes how a 45-hour Computers in Translation course is actually taught to 3rd-year translation students at the University of Alacant; the course described started in year 1995–1996 and has undergone substantial redesign until its present form. It is hoped that this description may be of use to instructors who are forced to teach a similar subject in such as small slot of time and need some design guidelines.

This paper describes some resources for introducing concepts of statistical machine translation. Students using these resources are not required to have any particular background in computational linguistics or mathematics.

This paper describes a graduate-level machine translation (MT) course taught at the Language Technologies Institute at Carnegie Mellon University. Most of the students in the course have a background in computer science. We discuss what we teach (the course syllabus), and how we teach it (lectures, homeworks, and projects). The course has evolved steadily over the past several years to incorporate refinements in the set of course topics, how they are taught, and how students “learn by doing”. The course syllabus has also evolved in response to changes in the field of MT and the role that MT plays in various social contexts.

This paper describes the approach used for introducing CAT tools and MT systems into a course offered in translation curricula at the Université de Montréal (Canada). It focuses on the automation of the translation process and presents various strategies that have been developed to help students progressively acquire the knowledge necessary to understand and undertake the tasks involved in the automation of translation. We begin with very basic principles and techniques, and move towards complex processes of advanced CAT and revision tools, including ultimately MT systems. As we will see, teaching concepts related to MT serves both as a wrap-up for the subjects dealt with during the semester and a way to highlight the tasks involved in the transfer phase of translation.

This paper describes a number of “toy” MT systems written in Prolog, designed as programming exercises and illustrations of various approaches to MT. The systems include a dumb word-for-word system, DCG-based “transfer” system, an interlingua-based system with an LFG-like interface structure, a first-generation-like Russian-English system, an interactive system, and an implementation based on early example-based MT.

Implementation of machine translation “toy” systems is a good practical exercise especially for computer science students. Our aim in a series of courses on MT in 2002 was to make students familiar both with typical problems of Machine Translation in particular and natural language processing in general, as well as with software implementation. In order to simulate a software implementation proc- ess as realistic as possible, we introduced more than 20 evaluation criteria to be filled by the students when they evaluated their own products. The criteria go far beyond such “toy” systems, but they should demonstrate the students, what a real software evaluation means, and which are the particularities of Machine Translation Evaluation.

Empirical methods in Natural Language Processing (NLP) and Machine Translation (MT) have become mainstream in the research field. Accordingly, it is important that the tools and techniques in these paradigms be taught to potential future researchers and developers in University courses. While many dedicated courses on Statistical NLP can be found, there are few, if any courses on Empirical Approaches to MT. This paper presents the development and assessment of one such course as taught to final year undergraduates taking a degree in NLP.