#!/usr/bin/env python
# coding: utf-8

# # Lesson Title
# Data Modeling in student groups of 3: Writing and Presenting a Computational Story
# 
# ## Lesson Description
# Working in groups of 3, students will receive a data dictionary and dataset from an archival agency that reflects the historical events depicted, and will engage in manipulation and visualization of the data to show patterns, identify or reconstruct decisions, and construct future uses of the records.
# 
# ### Lesson Name: 
# Writing a Computational Story. 
# 
# ### Author: 
# Sarah A. Buchanan 
# 
# ### Publication Date: 
# November 1, 2021
# 
# ### Resource URL: 
# https://cases.umd.edu/github/cases-umd/Japanese-American-WWII/blob/master/Cards-Solving-Cases/index.ipynb</p>
# 
# ## *Archival Topics* (2016 SAA GPAS)
# + A. Core Archival Knowledge > 1. Knowledge of Archival Material and Functions. > (c) Arrangement and Description.
# + A. Core Archival Knowledge > 1. Knowledge of Archival Material and Functions. > (e) Reference and Access.
# + A. Core Archival Knowledge > 2. Knowledge of the Profession. > (c) Ethics and Values.
# 
# ## ACA RDS (Role Delineation Statement) for Professional Archivists
# + K-8: how the core archival functions (selection, appraisal, and acquisition; arrangement and description; reference services and access; preservation and protection; and outreach, advocacy, and promotion) relate to each other and influence the administration of archival materials.
# + Domain 2: Arrangement and Description > Task 1: Analyze the existing arrangement and description of archival materials and make decisions about any further arrangement and description that may be necessary. Archivists know and apply knowledge about: **K-204**: The concept of hierarchical levels of arrangement.
# + Domain 7: Professional, Ethical, and Legal Responsibilities > Task 3: Knowledge about statutory or other legal authorities and professional standards and act appropriately with respect to archival materials. Archivists know and apply knowledge about: **K-705**: Ethical responsibilities of archivists to ensure archival materials and collections are preserved, collected and respectfully described with community input. (see https://www.certifiedarchivists.org/role-delineation, 2021)
# 
# ## Computational Thinking Topics
# + (DP3) Manipulating Data
# + (DP4) Analyzing Data
# + (DP5) Visualizing Data
# + (MS1) Using Computational Models to Understand a Concept
# + (MS2) Using Computational Models to Find and Test Solutions
# + (CPS3) Choosing Effective Computational Tools
# + (ST3) Thinking in Levels
# 
# ## Lesson Objectives
# Through this major lesson, students:
# + Develop skills to mediate among stakeholders (records creators, users, and IT staff) over the records lifecycle to ensure perpetual (tiered) access to analog and digital formats.
# + We work with “real data” prepared by archival agency staff according to the agency users’ needs. [Challenge Question:] But why are certain descriptive and access decisions made, can we reconstruct their creation? What content patterns are even contained in these records and how might we visualize or present them?
# 
# ## Pre/co-requisite knowledge
# By the time students co-present this work (~W9), in the course we have discussed the relevant topics of:
# + Evidential and informational value
# + Organizational culture and recordkeeping requirements
# + Data sharing and reuse practices in the disciplines
# + Contexts of records creation, curation, and use
# + Data visualization and storytelling
# 
# ## Resources
# This lesson requires:
# + Internet access to browse our and other modules published at the https://cases.umd.edu/ URL 
# + Data dictionary and dataset (linked at Canvas assignment page)
# + Individual and collaborative writing
# + Access to the following tools: OpenRefine
# + Access to GitHub and knowledge of developing and working with Jupyter Notebooks is optional and will enhance the experience.
# 
# ## Typical plan and expected variations
# This lesson is introduced in W1, when students form their group of three. The data dictionary and dataset are made available shortly thereafter to all groups, and members begin to work collaboratively. A Guest Lecture providing useful context may occur around W5. The group document and presentation are due one month later, comprising the major assessment of the course. Students can extend their Computational Story if they so choose for their final essay.
# 
# ## Outcomes/Assessment
# The grading rubric for the document comprises (a) ideas and content, (b) details and jargon, (c) expressive voice, (d) sentence fluency, organization, and grammar, and (e) SLO4 on assessing and responding to community needs and instructing users with informational resources.
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