Dan Ryan » Computational Thinking

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Course Description

This course will examine the basic ideas of computational thinking. In particular it will focus on principled thought processes, approaches and principles that guide computational analyses, from problem formulation all the way to effective and efficient problem solving. It will contain an introduction to algorithm building and their complexity, basic data structures used in computational solutions as well as the use of necessary tools to tackle large-scale problems in a variety of domains. The course will also discuss the application of computational thinking in different areas such as the humanities, social sciences and the arts, potentially looking into the impact it may have on them. Finally, it will serve as a necessary preamble for students who will follow a more technical career, especially in the area of Information Systems and Applied Data Science.

Program Learning Outcomes

Program-level outcomes for the Master of Information (MI) program at the University of Toronto include the following:

Students understand and are conversant with fundamental concepts, theories, practices, and the diverse horizons of information disciplines, and can respond to changing information practices and needs of society. (INFO)
Students develop knowledge and values appropriate to their future exercise of economic, cultural, and/or social leadership, and thereby provide leadership in defining the social responsibility of information professionals to provide information services for all, regardless of age, educational level, or social, cultural, or ethnic background. (VALUES)
Students develop the ability to contribute through research and publication, to the continuous expansion and critical assessment of the body of knowledge underlying the information and archives sciences. (CONTRIBUTE)
Students develop an understanding of the development of theory concerning information, where it is found, and how it is used. (THEORY)
Students develop an understanding of the application of new technological developments to the preservation and communication of information, and in the identification of the impact of such developments on society. (SOCIETY)
Students continue in life-long intellectual growth beyond graduation. (LIFE)

Course Objectives

The purpose of this course is to convey, in a manner that is accessible to students coming from a wide variety of intellectual backgrounds and useful to students destined for a wide variety of further avenues of study, a set of intellectual reflexes and styles of thought and a repertoire of practical skills drawn from, and deployed in, computational science. The course is NOT intended as "computer science 101" or "a first course in programming" or "introduction to data processing."

Course Learning Outcomes

This course introduces students to a style of thinking that yields problem solutions that can be programmed, are predictably reliable, involve careful and exhaustive consideration of problem and solution spaces, and can be implemented at high speed and high volume. Although this usually means solutions that are carried out by machines, the application of this style of thinking is more generally applicable.

The goal, then, will be to inculcate an "algorithmic" style of thinking: the deliberate decomposition of large and complex problems into a set of nested subproblems, the construction of solutions in terms of sequence, repetition, and contingency, the recognition and exploitation of pattern, and the inclination to defer detail, automate, and modularize.

Upon successful completion of this course you will have enhanced your capacity to

have enhanced general purpose critical thinking skills (THINK)
think slowly about things that move fast and/or have many parts (SLOW)
break large and complex problems into cognitively/computationally/organizationally manageable subproblems (DECOMPOSITION)
recognize, describe, and exploit patterns (PATTERN)
defer detail and move between levels of abstraction (ABSTRACTION)
build complex, robust, and legible systems from cognitively manageable and reusable parts (MODULARITY)
think about data and information structurally (DATA)
understand the complexity of computational solutions (COMPLEXITY)
formulate problems and solutions using computational thinking in different fields of endeavor (APPLY)
deploy a set of mental categories, intellectual reflexes, conceptual tools, and practical skills necessary for a participatory role contemporary information technologies (TECH)

The relationship of these course outcomes to the program outcomes is summarized in the table below.

	INFO	VALUES	CONTRIBUTE	THEORY	SOCIETY	LIFE
THINK
SLOW
DECOMPOSITION
PATTERN
ABSTRACTION
MODULARITY
DATA
COMPLEXITY
APPLY
TECH

Instructional Agenda

Each week, students will engage with text and other media introducing a topic and work one or more preparatory problems based on this material PRIOR to each class session. Approximately one third of each class session will be devoted to lecture/review of this material in a "flipped class" format (that is, students are assumed to have already heard "lecture" and attempted problems). The middle third will be an interactive workshop or simulation, and the final hour will be review and motivation of the next week's topic.

About one half of each week's 6-8 hours of "homework" will be an opportunity to demonstrate competence on the topic of the previous week and about half will be preparation for the topic of the coming week. The former will be submitted as graded assignments.

Assignments, Activities and Course Learning Outcomes

Each course assignment and activity will be an opportunity to practice or demonstrate mastery of one or more of the learning outcomes described above. The tables below summarize the relationship between assignments, activities, and learning outcomes.

	ASSIGNMENT
Outcome	01	02	03	04	05	06	07	08	09	10
THINK	A01	A02	A03	A04	A05	A06	A07	A08	A09	A10
SLOW	A01	A02	A03	A04	A05	A06	A07	A08	A09	A10
DECOMPOSITION	A01	A02	A03	A04	A05	A06	A07	A08	A09	A10
PATTERN	A01	A02	A03	A04	A05	A06	A07	A08	A09	A10
ABSTRACTION	A01	A02	A03	A04	A05	A06	A07	A08	A09	A10
MODULARITY	A01	A02	A03	A04	A05	A06	A07	A08	A09	A10
DATA	A01	A02	A03	A04	A05	A06	A07	A08	A09	A10
COMPLEXITY	A01	A02	A03	A04	A05	A06	A07	A08	A09	A10
APPLY	A01	A02	A03	A04	A05	A06	A07	A08	A09	A10
TECH	A01	A02	A03	A04	A05	A06	A07	A08	A09	A10

Outcome	Where does it show up in assignments?
THINK	Critical thinking, understood as a careful, systematic, robust, analytical mental reflex is practiced throughout the course. Examples include …
SLOW	- - - -
DECOMPOSITION	- - - -
PATTERN	- - - -
ABSTRACTION	- - - -
MODULARITY	- - - -
DATA	- - - -
COMPLEXITY	- - - -
APPLY	- - - -
TECH	- - - -

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Grading

Please consult the iSchool’s Grade Interpretation Guidelines, the University Assessment and Grading Practices Policy and Guidelines on the Use of INC, SDF, & WDR. . Note that several graded assignments will be handed back before the final date to drop without penalty.

These documents will form the basis for grading in the course.

The grading breakdown for assignments and exams for this course will be:

Included page "ct:inf1339-grading-breakdown-2018" does not exist (create it now)

Writing Support

As stated in the iSchool’s Grade Interpretation Guidelines, “work that is not well written and grammatically correct will not generally be considered eligible for a grade in the A range, regardless of its quality in other respects.” With this in mind, please make use of the writing support provided to graduate students by the SGS Graduate Centre for Academic Communication. The services are designed to target the needs of both native and non-native speakers and all programs are free. Please consult for more information. the current workshop schedule.

Academic integrity

Please consult the University’s site on Academic Integrity. The iSchool has a zero-tolerance policy on plagiarism as defined in section B.I.1.(d) of the University’s Code of Behaviour on Academic Matters. You should acquaint yourself with the Code.

Also review the material in Cite it Right and if you require further clarification, consult the site How Not to Plagiarize.

Cite it Right covers relevant parts of the U of T Code of Behaviour on Academic Matters (1995). It is expected that all iSchool students take the Cite it Right workshop and the online quiz. Completion of the online Cite it Right quiz should be made prior to the second week of classes. To review and complete the workshop, visit the orientation portion of the iSkills site.

Accommodations

Students with diverse learning styles and needs are welcome in this course. If you have a disability or a health consideration that may require accommodations, please feel free to approach Student Services and/or the Accessibility Services Office as soon as possible. The Accessibility Services staff are available by appointment to assess needs, provide referrals and arrange appropriate accommodations. The sooner you let us know your needs, the quicker we can assist you in achieving your learning goals in this course.

Academic Dates

Consult the iSchool's online calendar for various course-relevant dates (e.g., October 29 Final date to drop fall session full-year (Y) or fall session (F) courses without academic penalty).

Statement of Acknowledgement of Traditional Land

I (we) would like to acknowledge this land on which the University of Toronto operates. For thousands of years it has been the traditional land of the Huron-Wendat, the Seneca, and most recently, the Mississaugas of the Credit River. Today this meeting place is still the home to many Indigenous people from across Turtle Island and we are grateful to have the opportunity to work on this land.¹

iSchool Workshops:

The iSchool workshops are a series short skill sessions that are available exclusively to the iSchool community. iSchool professors, Inforum librarians, current students, alumni, and a collective of professionals and academics from each program and concentration, work together to create these unique rosters. Together with the MMSt and MI curricula, these academic, professional, and technical iSkills workshops provide a robust information and heritage graduate educational experience.

Workshop topics of particular relevance to this course will be noted by the instructor.

In an effort to ensure your success at the iSchool, key information and skills that all iSchool students must possess, regardless of program or concentration, are covered in these online orientation workshops. You should avail yourself of these sooner rather than later.

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Computational Thinking Fall 2018

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CALL get-the-slide-deck-small2(ct, ct_think_slow,no)

Week 2

CALL get-the-slide-deck-small2(ct, ct_flow_dec_mod,no)

EDIT SLIDES

Week 3

CALL get-the-slide-deck-small2(ct, ct_countingNprobability,no)

EDIT SLIDES

Week 4

CALL get-the-slide-deck-small2(ct, ct_infojigs,no)

EDIT SLIDES

CALL get-the-slide-deck-small2(ct, ct_api_edl,no)

Week 6

CALL get-the-slide-deck-small2(ct, ct_solvingwithiteration,no)

EDIT SLIDES

Week 7

CALL get-the-slide-deck-small2(ct, ct_pat_rec,no)

EDIT SLIDES

Week 8

CALL get-the-slide-deck-small2(ct, ct_comp_vis,no)

EDIT SLIDES

Week 9

CALL get-the-slide-deck-small2(ct, ct_auto_cont,no)

EDIT SLIDES

Week 10

CALL get-the-slide-deck-small2(ct, ct_block,no)

EDIT SLIDES

Week 11

CALL get-the-slide-deck-small2(ct, ct_robots_ai,no)

EDIT SLIDES

Week 12

CALL get-the-slide-deck-small2(ct, ct_wrapup,no)

EDIT SLIDES

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NOTES

TO DO

Abstraction

Layers | 6. How to throw a dinner party | 5. Abstraction - Making a Map | 3. Reverse Mad-Libs |

Algorithms

Bureaucracy as Machine and Automation | Layers | 1. Assessing a Sorting Algorithm |

Pattern Recognition

Decomposition

Layers |

Foreword

Basic Course Concepts

The goal of this course is to equip the student with certain styles and habits of thought as a set of skills AND to provide a sense of how much one knows and how much one would need to know of what in order to proceed further in various areas related to computational work.

Reprise abstraction | decomposition | pattern recognition | algorithm multiple times throughout the course at different scales (sometimes concentrating an entire class on one of these, sometimes all four illustrated or practiced in a single example or activity). Perhaps only formally present them at the end of the course.
I hear and I forget; I see and I remember; I do and I understand.
Ever class session follows same ritual of review, motivate, introduce, practice, project
There will be an explicit inventory of skills and concepts
At every stage examples and applications from many fields
Course BEGINS with FINAL EXAM and BACKGROUND INVENTORY

Relation to programming. Relation to computer science. Relation to computer literacy.

Course begins with final exam and intake questionnaire.

And a poster of diagrams.

Finish with exam and one page posters.

NOT computer literacy and not computer science.

Denning’s Great Principles of Computing break down into seven categories: computation, communication, coordination, recollection, automation, evaluation, and design. (Report of a Workshop on The Scope and Nature of Computational Thinking
http://www.nap.edu/catalog/12840.html pg. 29)

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danryan.us

Course Description

Program Learning Outcomes

Course Objectives

Course Learning Outcomes

Instructional Agenda

Assignments, Activities and Course Learning Outcomes

Grading

Writing Support

Academic integrity

Accommodations

Academic Dates

Statement of Acknowledgement of Traditional Land

iSchool Workshops:

Computational Thinking Fall 2018

Rest of the Wiki

Week 2

Week 3

Week 4

Week 6

Week 7

Week 8

Week 9

Week 10

Week 11

Week 12

NEW

NOTES

TO DO

Abstraction

Algorithms

Pattern Recognition

Decomposition

Foreword

Basic Course Concepts

Subpages