Course - Information Technology, Introduction - IT1001
Information Technology, Introduction
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About the course
Course content
The course provides an introduction to procedural programming, with Python as language, as well as experience in conducting a small programming project related to the teaching of STEM subjects in high school. Concepts covered: Variables and data types, representation of numbers and implications in calculations (e.g., rounding errors). Input and output. Control structures: sequence, branching, looping, recursion. Structuring and modularization of programs; functions and modules. Data structures: strings, lists, tuples, arrays, sets, and dictionaries. Files and exception handling. Basic numerical calculations, visualization and plotting.
Learning outcome
Knowledge:
- K1: Can explain basic principles for digital representation of information.
- K2: Can explain the purpose and semantics of key constructs for procedural programming in Python.
- K3: Can explain some basic algorithms and solution patterns for general purpose programming and simple calculations.
Skills.
- F1: Can solve problems by writing procedural programs, by completing code where some fragments are missing, and find and correct errors in code.
- F2: Can conduct a small programming project.
- F3: Can demonstrate and explain own code, and provide constructive feedback on code written by others.
General competencies:
- G1: Can reflect upon the opportunities and challenges for programming as a tool in the teaching of STEM subjects in high school.
Learning methods and activities
Compulsory activity:
The student must have participated in at least 80% of seminars, and at least 80% of individual meetings with their teaching assistant. The compulsory activity must be done to get a grade in the course. The department may under special circumstances accept applications for lower participation.
The seminars contain discussions with teacher, assistant, and peer students. The individual meetings with the teaching assistants are a dialogue about the student's progression and mastery in the course.
In addition to the compulsory activities, digital learning resources will be made available for the students for supplementary self-study.
Compulsory assignments
- Seminar
- Meetings with teaching assistant
Further on evaluation
Assessment in the course is done by means of a mastery ladder where students can choose their individual ambition level and progress plan. There are two main components in this mastery ladder:
(i) The test series: A series of automated tests. Counting tests must be performed under supervision.
(ii) The project: A programming project developed iteratively to gradually higher levels of ambition.
The tests have increasing ambition level, and each test must be passed before it will be possible to continue with the next test. A failed test can be attempted again in the next available time slot.
In the project, each student shall develop unique Python code with usage potential in STEM subjects in high school, related to the students' LUR discipline (Biology / Chemistry / Physics / Mathematics / Informatics). Together with the program, they shall also deliver a short report reflecting upon experiences from the project and the potential pedagogical use of the program. The project is developed iteratively, to be acknowledged to gradually higher levels of ambition.
Only one joint grade is achieved in the course. To pass the course, a passing level must have been reached both in the test series and project. If the level achieved in these two components differ, the grade will be determined by the lowest level.
In the event of voluntary repetition, fail (F) or valid absence, the entire portfolio must be retaken in a semester with teaching.
Specific conditions
Admission to a programme of study is required:
Natural Science with Teacher Education, years 8 - 13 (MLREAL)
Recommended previous knowledge
None.
Required previous knowledge
None.
Course materials
Digital learning resources. Will be provided at the beginning of, and during, the semester.
Credit reductions
| Course code | Reduction | From |
|---|---|---|
| TDT4109 | 7.5 sp | Autumn 2023 |
| TDT4110 | 7.5 sp | Autumn 2023 |
| TDT4111 | 7.5 sp | Autumn 2023 |
| TDT4127 | 5 sp | Autumn 2023 |
| INFT1010 | 7.5 sp | Autumn 2024 |
Subject areas
- Computer Science