TRAM500 Introduction to Computational Thinking for Translators

By the end of the module students will be able to:  

• demonstrate a thorough understanding of the basic and intermediate concepts from computer science and programming 
• Develop computational thinking and problem-solving skills that can be applied to everyday tasks 
• Demonstrate ability to analyse and implement computational solutions for problems from the field of translation 
• Demonstrate intermediate knowledge of Python 
• Demonstrate ability to communicate solutions in writing using the required conventions of the field of computer science 

• Key notions of computer science and programming, how to analyse problems and design appropriate solutions  
• Basic python notions (data structures, syntax, functions, etc)  
• Key notions about Large Language Models and prompting techniques for interacting with them  
• Automatic processing of multilingual texts  
• Automatic extraction of statistics from corpora  
• Regular expressions  

The learning and teaching strategy is designed to provide students with problem-solving skills and a good understanding of computer science and programming with emphasis on how they can be used to tackle problems from translation. By the end of the module, students will feel confident of their ability to write small programs that allow them to accomplish useful goals related to translation technology. 

Learning and teaching includes:  

• Seminars and workshops interspersed with opportunities for group and whole class discussions 
• Captured content addressing module content 
• Guided learning – such as signposted hands-on exercises and guidelines relevant to advanced practice in the field 
• Problem-based practical exercises  
• Discussion and group work (in-class) 
• Practice-based learning – application of knowledge acquired throughout the module in realistic or academically simulated contexts 

Portfolio of Solutions to the Exercise and Reflective Comments on the Solutions (60%) 

Students will be given practical homework every two weeks and will be asked to prepare a portfolio with their answers to the homework. In some cases, students will be asked to write "small essays" (200 - 250 words) explaining how they used some tools, whilst in other cases they will need to provide documented code. The portfolios can be seen as a diary of the practical activities covered in this module. The solutions are expected to indicate any problems that the students encountered and how they solved them. In order to pass, the students will have to submit all the homework. For the homework given in the first eight weeks, the solutions will be discussed in class and the students will have the chance to update their portfolios with reflective analysis of their initial solutions. All the pieces of homework given during the semester will have to be included in the final portfolio and the marking will focus on both how the solution was achieved and on the reflective analysis. The portfolios will be due at the end of the semester. 

Open Book Practical Task to Take Place in Class (40%) 

Students will have to solve a number of practical unseen exercises by having access to all lecture notes. 

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