Fundamentals of Computer Science I Course Descriptor

Course Overview

This course is an introduction to computing and programming. Its primary goal is to introduce students to the principles of systematic problem solving through programming and the basic rules of computation.

By the end of this course, students will have a sense of the differences between a programmer and a well-trained software engineer. Students will also have a sense of the complexities involved in developing solid software and be able to apply their knowledge to solve many non-computational problems in a systematic way (incl. analytic reading, synthesis, goal setting, planning, plan execution, and testing).

The course does not assume any prior programming experience. It is suitable for all students who wish to explore the ideas behind the discipline of computer science. The course does assume, however, some familiarity with arithmetic and algebra, and it demands curiosity, self-discipline, and the capacity to work well with others.

Learning Outcomes

On successful completion of the course, students will be able to:

Knowledge and Understanding

Subject Specific Skills

Transferable and Employability Skills

Teaching and Learning

This course has a dedicated Virtual Learning Environment (VLE) page with a syllabus and range of additional resources (e.g. readings, question prompts, tasks, assignment briefs, discussion boards) to orientate and engage students in their studies.
The scheduled teaching and learning activities for this course are:

• Lectures/labs. 40 scheduled hours – typically including induction, consolidation or revision, and assessment activity hours:
  • Version 1: All sessions in the same sized group, or
  • Version 2: most of the sessions in larger groups; some of the sessions in smaller groups

Faculty hold regular ‘office hours’, which are opportunities for students to drop in or sign up to explore ideas, raise questions, or seek targeted guidance or feedback, individually or in small groups.

Students are to attend and participate in all the scheduled teaching and learning activities for this course and to manage their directed learning and independent study.

Indicative total learning hours for this course: 150

Assessment

Both formative and summative assessment are used as part of this course, with purely formative opportunities typically embedded within interactive teaching sessions, office hours, and/or the VLE.

Summative Assessments

Further information about the assessments can be found in the Course Syllabus.

Feedback

Students will receive formative and summative feedback in a variety of ways, written (e.g. marked up on assignments, through email or the VLE) or oral (e.g. as part of interactive teaching sessions or in office hours).

Indicative Reading

Note: Comprehensive and current reading lists are produced annually in the Course Syllabus or other documentation provided to students; the indicative reading list provided below is for a general guide and part of the approval/modification process only.

Matthias Felleisen, Robert B. Findler, Matthew Flatt, and Shriram Krishnamurthi. 2014. How to Design Programs, Second Edition. MIT Press. Available at htdp.org.

Indicative Topics

Note: Comprehensive and current topics for courses are produced annually in the Course Syllabus or other documentation provided to students; the indicative topics provided below are used as a general guide and part of the approval/modification process only.

• Fixed-size data (numbers, characters, enumerations) and operations on them
• Arbitrary large data structures (e.g., lists, graphs, trees) and operations of them
• Designing functions with fixed-size and arbitrary large data
• Designing functions with abstractions
• Generative recursion
• Examples of real-world programs (e.g., batch or event-driven)