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B2696 - LANGUAGE, TECHNOLOGY, RESEARCH I: COMPUTATIONAL THINKING

Academic Year 2023/2024

                
                        Docente:
                        Luis Alberto Barron Cedeno
                    
                        Credits:
                        6
                    
                        SSD:
                        INF/01
                    
                        Language:
                        English
                    
                        Teaching Mode:
                        Traditional lectures
                        
                            Campus:
                            Forli
                        
                            Corso:
                            First cycle degree programme (L) in
                            Languages and Technologies for Intercultural Communication (cod. 5979)

                            Teaching resources on Virtuale
                        
                                    Course Timetable
                                
from Feb 12, 2024 to Apr 24, 2024

Learning outcomes

The student knows the basic features (terms, concepts and methods) of computational thinking. S/he is able to: understand and use different types of data and data structures; design and implement scripts and use core libraries for the processing of numerical and textual data; apply the acquired knowledge to solve problems with computing tools.

Course contents

The course teaches how to use some of the computational tools that can help a professional in language and intercultural communication to solve problems. It pays particular attention to large-scale problems and to the implementation of solutions that go beyond using standard software.

Introduction to computational thinking
Decomposition
Pattern recognition
Abstraction
Algorithmic thinking
Introduction to programming
Jupyter notebooks
Basic operations
Dealing with text
Methods
Classes

This lesson represents the minimum necessary introduction to follow lessons on natural language processing and machine translation fine tuning (e.g., within the Translation and Technology MA curriculum).

Readings/Bibliography

Hey, T. and G. Pápay (2014). The Computing Universe: A Journey through a Revolution.Cambridge University Press
Jeannet M Wing. Computational thinking. Commun. ACL 49(3) [1], 33-35 (2006)

More TBA

Teaching methods

A combination of lectures and interactive seminars. The students will play an active role in the lesson by proposing and implementing solutions.

Assessment methods

50% final project

50% final program

30 - 30L Excellent. The student has acquired all targeted concepts, and has conducted a methodologically sound project that s/he clearly presented in the report and the oral presentation.
27 - 29 Above average. The student has a very good command of the targeted concepts, with some minor errors or inconsistencies in project implementation and/or presentation.
24 - 26 Generally sound. The student has a generally good command of the targeted concepts, but with larger gaps or inconsistencies in project implementation and/or presentation.
21 - 23 Adequate. The student has just an adequate command of the targeted concepts and displays significant shortcomings in project implementation and/or presentation.
18 - 20 Minimum. The student has only grasped the basic targeted concepts and was only partially successful in implementing a project.
< 18 Fail. The student does not reach a minimum threshold of knowledge and was unsuccessful in implementing a project.

Teaching tools

The course materials (slides, code) will be made available on moodle. The students will also use Jupyter notebooks to code in Python.

Office hours

See the website of Luis Alberto Barron Cedeno