Course Syllabus

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Sensemaking & Organizing

CogSci 150, 3 units, Spring 2022
Tuesday & Thursday 11:10am-12:30pm

Wheeler 106

TEACHING TEAM

Professor Robert J. Glushko
glushko@berkeley.edu

Aurum Kathuria
aurumkathuria@berkeley.edu

When something "makes sense” or "is organized” we are discovering or imposing order in the arrangement of concepts, events, or resources of some kind.    Sensemaking and organizing are fundamental human activities that raise many multi- or trans-disciplinary questions about perception, language, knowledge, decision making, and interaction with things and with other people.

We can analyze sensemaking and organizing from four interrelated perspectives. The most fundamental one is provided by language and culture, which shapes the perspectives one takes as an individual, in institutional contexts governed by business or legal processes, or in data-intensive or scientific contexts.

COURSE FORMAT and GRADING

The course is primarily lecture-based, but to enable more discussion, breakout sessions, and peer learning a mandatory 1-hour online session will take place on Friday (time TBD)

The expected workload should average 10 hours a week; 4 for the course meetings and 6 for preparation and deliverables.   The load will be lighter at the beginning of the semester and heavier toward the end when students are researching and writing their case study, the most important work product for the course.

  • 8 assignments (25%)
  • 2 timed exams, administered by bCourses (35%; 15% for #1, 20% for #2)
  • Case study (25%)
    • Purpose: To reinforce the generality of the organizing system framework.  After reading ten or more short case studies in the first few weeks of the course, students write one of their own as their course capstone. The best student cases end up in future syllabi
  • Class preparation and participation (15%)

SCHEDULE AND READINGS

The primary text is The Discipline of Organizing, (4th edition, 2016). This text has been extensively revised since it was first published and it can be found in multiple versions, and in both print and digital formats. We will be reading parts of the  "Core Concepts" and "Abridged" editions; the "Professional" edition can be consulted for more depth. 

Readings from this text are indicated with “TDO” and a chapter or section number, a * after a number (like 4.1*) means the identified section and all of its subsections

Many readings are short case studies, some from the textbook and some written by students taking this or similar courses. Their diversity demonstrates the breadth of the organizing system concept.

Part 1: Introduction to Sensemaking and Organizing

[1 - Jan 18] [1.1 - Jan 19] Course introduction; the concept of the "Organizing System”

An Organizing System is an intentionally arranged collection of resources and the interactions they support. This definition doesn't specifically mention books, people, datasets, shoes, animals, or any other type of resource. This definition also doesn't mention any specific ways in which resources are used.  Finally, this definition allows for any arrangement or structure that is needed to enable the interaction.

This abstraction allows the Organizing System concept to transcend the traditional view that information organization is a human activity and information retrieval is a machine activity, or that information organization is a topic for library and information science and information retrieval is one for computer science. Instead, we readily see that computers now assist people in organizing and that people contribute much of the information used when computers analyze and organize resources.

Because the Organizing System perspective can be applied to any kind of resource, it enables a more nuanced discussion of how the economic, social, and cognitive costs and benefits of organizing are allocated among different stakeholders and over time.

Case Studies:

[2 - Jan 20] Design Decisions for Organizing Systems

This lecture introduces six broad design questions or dimensions whose intertwined answers define an Organizing System: What, why, how,  when, by whom or what, and where. This framework for describing and comparing Organizing Systems overcomes the biases and conservatism built into familiar categories like libraries and museums while enabling us to describe them as design patterns. We can then use these patterns to support inter-disciplinary work that cuts across categories and applies knowledge about familiar domains to unfamiliar ones.

Case Studies:

[3 - Jan 25] Models for Organizing Systems; More Case Studies

Many academic fields – management, operations research, informatics, etc. – provide models or representations for describing organizing systems. In this lecture, we'll show how these different depictions distinguish and highlight different aspects of the organizing system. They can be thought of as different perspectives or points of view whose effectiveness depends on the nature of the resources and organizing principles in the organizing system.

[4 - Jan 27] The Activities of Sensemaking and Organizing

A perspective that brings together how we organize as individuals or as members of groups with how libraries, museums, governments, research institutions, and businesses create Organizing Systems requires that we generalize the organizing concepts and methods from these different domains. This lecture surveys a wide variety of Organizing Systems and describes four activities or functions shared by all of them: selecting resources, organizing resources, designing resource-based interactions, and maintaining the interactions and resources over time.

[5 - Feb 1] Resources

The design of an Organizing System is strongly shaped by what is being organized, the first of the six design decisions introduced in the second lecture. To enable a broad perspective on this fundamental issue we use resource to refer to anything being organized, an abstraction that we can apply to physical things, people, digital things, information about either of them, or web-based services or objects.

Two separate aspects cut across the "thingness" distinctions:
 - Granularity – do we think of the resource as unitary, or as consisting of parts?
 - Abstraction – “thing” or “type of thing” – are we thinking of the resource as a single instance or as a member of a bigger category?

Case Studies:

[6 - Feb 3] Names and Identifiers

A NAME is a label for some thing or some category that is used to distinguish one from another. If a name is used to refer to some specific thing and is unique in some context it is an IDENTIFIER. Choosing good names and identifiers is essential, difficult, and often contentious.

Case Study:

[7 - Feb 8] Resource Description

Categories can be defined in many different ways according to many different types of principles and processes.  The principles by which resources are organized and the interactions that can be supported for them largely depend on the nature and explicitness of the resource descriptions.

[8 - Feb 10] Describing Non-text Resources and Media; Resource Properties Framework

We will apply the concepts of resource abstraction, granularity, and description to art, artifacts, and music. 

Two important dimensions for understanding and contrasting resource properties used in descriptions and organizing principles are: property essence—whether the properties are intrinsically or extrinsically associated with the resource, and; property persistence—whether the properties are static or dynamic. Taken together these two dimensions yield four categories of properties.

Case Studies

 Part 2: Sensemaking and Organizing in Language and Culture

[9 - Feb 15] Introduction to Categorization; Cultural Categories; Astronomical Sensemaking and Other "Natural" Categories

Categories are sets or groups of resources or abstract entities that are treated the same.  Categories are involved whenever we perceive, communicate, analyze, predict, classify – or otherwise attempt to make sense of our experiences.

The universality of temporal concepts for "day," "month," "year," and "season" reflects their basis in natural astronomical events that have been systematically observed and recorded for well over ten thousand years.  Likewise, all cultures impose patterns on stars, often associated with myths. Studying how these constellation-embodied myths evolve and disperse over time using techniques of evolutionary biologists creates "the tree of myths." 

[10- Feb 17] Universal Cognition? Folk Biology; Linguistic Relativity;  Bi-lingualism & Bi-culturalism

All human languages and cultures divide the physical and experiential “worlds” into categories; there are substantial similarities but interesting differences. 

  [11 - Feb 22] Document Engineering and Modeling

We will discuss techniques of Document Engineering for systematically identifying the content, structure, and presentation components in documents and datasets to enable the design of robust models for information-intensive domains. We will contrast methods and formats for information models that differ in their semantic precision, maintainability, and ease of use. 

[12 - Feb 24] Describing Relationships and Structures, Part 1

An important aspect of organizing a collection of resources is describing the relationships between them. This lecture introduces the specialized vocabulary used to describe semantic relationships between resources and between the concepts and words used in resource descriptions.

 [13 - March 1] Describing Relationships and Structures, Part 2; Social network analysis

The structural perspective analyzes the patterns of association, arrangement, proximity, or connection between resources (and often ignores the reasons for them).

We can apply graph theory to understanding relationships from a structural perspective

[14 - March 3] Social thinking;  Dis-/Mis-/Mal- information

How do the groups we explicitly or implicitly belong to influence how and what we think? When does social thinking create better decisions and outcomes? When does social thinking create worse decisions and outcomes?

Social thinking is a critical factor in the problem of "fake news" -- which we will unpack into more precise categories so we can better understand its causes, mechanisms, and remedies.

 Part 3: Sensemaking and Organizing As Individuals

[15 - March 8] "Automatic organizing" using perceptual processes, Gestalt principles, statistical learning

Physical resources are often organized according to intrinsic physical properties like size, color, or shape because the human visual system quickly and automatically pays a lot of attention to them. Likewise, because people have limited attentional capacity, we ignore a lot of the ongoing complexity of visual (and auditory) stimulation, making us perceive our sensory world as simpler than it really is.  Infants have a remarkable ability to extract patterns in auditory and visual inputs so that they can learn their native language and cope with the complexity of their physical environments.

[16 - March 10] Categories made by Individuals; Personal Possession Management; Personal Information Management

Individual categories are created to satisfy ad hoc requirements that emerge from an individual’s unique experiences, preferences, and resource collections.  How people manage their personal possessions is a trendy topic and a lucrative consulting business, but some people have psychological disorders that prevent them from doing it well.  How people organize their personal information has been extensively studied by researchers and designers. The Memex, proposed by Vannevar Bush almost 80 years ago, embodied many novel ideas about personal information management and is often viewed as the inspiration for personal computers and the web.

[17 - March 15] Causality and Explanation

People have a cognitive bias to see order and purpose in the world. The vast majority of our decisions are influenced—at least in part—by our beliefs about the causal structure of the world.  It is essential for survival to understand and predict the properties and behaviors of physical objects and substances (Physics), plants and animals (Biology), and other people (Psychology).

But what makes some sequences of events causal, so we make inferences about similar events, and other sequences non-causal? Causes are not deducible, and are not always explicitly visible in sensory input

[18 - March 17] EXAM

 Part 4: Sensemaking and Organizing in Defined/Institutional Contexts

[19 - March 29] Category Structure; Institutional Categories

"Category structure refers to the principles by which a category is defined. Categories can be defined by enumerating their members, on the basis of one or more shared properties, or by less rigid principles like similarity. Institutional categories are explicitly constructed semantic models of a domain to enable more control, robustness, and interoperability than is possible with just the cultural category system.  They are essential in abstract, information-intensive domains where semantic precision is essential for processes and transactions (especially automated ones). They are usually developed via rigorous and formal processes (e.g., in standards organizations or legislative bodies) and require ongoing governance and maintenance

[20 - March 31] Classification; Standardization

The terms categorization and classification are often used interchangeably but they are not the same. Classification is applied categorization—the assignment of resources to a system of categories, called classes, using a pre­determined set of principles.  Because classification and standardization are closely related, the lecture also analyzes standards and standards-making as they apply to Organizing Systems.

[21 - April 5] Measurement, Controlled Vocabularies, Interoperability

Sensemaking and organizing in institutional or business contexts depend on systematic and robust descriptions of resources, events, processes, and people.  Systems of measurement have evolved from ad hoc techniques for comparison, many of which were based on body parts or common work artifacts. Controlled vocabularies and standard description schemas are essential in the operation of information-intensive and data-driven businesses.

[22 - April 7] Organizing and Interaction Design

Classifications arrange resources into categories. So every classification increases the capability and efficiency of interactions with resources that are “co-located” or “within-category” and makes “between-category” interactions less efficient. Choices about descriptions and organizing principles involve tradeoffs that determine which interactions are efficient, possible, difficult, or impossible.

Distributed cognition and external representations help people understand and interact effectively when faced with challenging cognitive and physical tasks.

[23 - April 12] Case Study Proposals

Brief presentations by students of their proposed case study.

Six more case studies assigned to further develop the analysis and design skills needed to write a case study.

 Part 5: Sensemaking and Organizing with Data

[24- April 14] Organizing with Interaction Traces

Interactions with physical resources sometimes leave traces or other evidence. Many of these traces are unintentional, like fingerprints, a coffee cup stain on a newspaper, or the erosion on a shortcut path across a lawn. However, when Organizing Systems contain digital resources or physical resources that have sensing, recording, or communication capabilities, interaction traces can be made predictable, persistent, and consistent. Each record of a user choice in accessing, browsing, buying, highlighting, linking, and other interactions then becomes an “interaction resource” that can be analyzed to reorganize the resource collection or otherwise influence subsequent interactions with the primary resources

[25 - April 19] Behavioral Economics

Choices about descriptions and organizing principles involve tradeoffs that determine which interactions are efficient, possible, difficult, or impossible.Organizing systems control the behavior of their users. The emerging field of applied behavioral economics explains how subtle differences in resource arrangement, the number and framing of choices, and default values can have substantial effects on the decisions people make.

[26 - April 21] Computational Description 

Categories are typically created computationally when a collection of resources or resource descriptions is too large for people to think about effectively.  The simplest computational categories are the implicit ones created by descriptive statistics that identify typical or frequent and atypical or infrequent items

[ 27 - April 26] Computational Classification; Computation {and,or, vs.} Cognition

Some classification tasks are hard because the categories are “close together” and the resource properties or features involved are not easy to understand and use.  Other classification tasks are conceptually simpler, but can't be done by people at the needed scale or speed.

In “data science,” a classifier is a system whose input is a vector of discrete or continuous feature (or attribute) values and whose output is the name of the class. This vector might be the description of a document, an image, a person, a molecule, just about anything

[28 - April 28] EXAM

[ 29 – May 3] Case Study Presentations

[ 30 – May 5] Case Study Presentations

Course Summary:

Date Details Due