時間星期四, 10:30 - 12:15
地點李兆基樓302室 (LSK 302)
課程講師 馬思途 (firstname.lastname@example.org)
助教 MONTERO Claudia Isabelle Violeta (email@example.com)
The use of digital methods to either ask historical questions or display historical data is growly rapidly. This course introduces students to the exciting world of digital history, including digital mapping, visualization, digital curation, and some basic programming. These are skills that students will be able to apply to a range of historical problems, and will also be useful in a variety of future careers.
*If class is in person, please bring your laptop/electronic device to every class*
Reading: Watch introductory video and read the various parts of “Concepts in Digital Humanities: https://libguides.lib.cuhk.edu.hk/Intro-DH
Sections 1.1, 1.2,. 1.3, 2.1, 2.2, 3.1, 4.1, 4.3 of Beginning Excel https://openoregon.pressbooks.pub/beginningexcel/front-matter/introduction/
Reading: Do Tableau tutorials: https://public.tableau.com/app/resources/learn
Students might also want to browse https://youtu.be/-KfpkyTrrtc
MEET IN DIGITAL SCHOLARSHIP LAB
Learn all major voyant tools: https://voyant-tools.org/docs/#!/guide/tools
WordPress.org (not .com)
Reading https://wordpress.org/support/ “Basic usage & Customizing”
Reading: explore the following resources: Google MyMaps https://www.google.com/maps/d/, Timeline https://knightlab.northwestern.edu/ . Do QGIS Lessons 2.1-2.2 https://docs.qgis.org/3.10/en/docs/training_manual/index.html
Reading: QGIS Lessons 2.3-2.4 https://docs.qgis.org/3.10/en/docs/training_manual/index.html ;
Reading: Openshot tutorial: http://www.openshot.org/static/files/user-guide/introduction.html
Teaching Evaluation at start of class.
10% Attendance and Participation in Lecture
Students are expected to attend and contribute to lectures. Students are also expected to do the set reading ahead of class and do any set homework exercises. Although students will become expert in only one or two digital methods, they must learn the rudiments of all the methods covered.
N.B. Students will also be expected to attend at least three meetings of the digital humanities seminar (advertised on the Faculty of Arts website), as well as office hours on at least one occasion.
10% Weekly Response Paper
10x 200-word response papers for weeks 2-12. These should answer the question: “How is this week’s tool(s) useful for creating or disseminating historical insights?” Please answer with reference to the specific skills you have learned from doing the tutorials. Post on Blackboard forum. Due by Thursday 9am each week (absolute deadline).
30% Discussion in tutorial (7.5% each tutorial)
In each of the tutorials, each of the subgroups will collectively present their ideas/progress (in the form of a PowerPoint with relevant data/visualizations/etc.) and seek feedback from other students. Each tutorial will be devoted to a different stage of project management: planning, build-up, implementation, closeout.
50% Final Group Project
Students will complete a coherent group project on one of four topics of their collective choice (Africa and China from antiquity to the present; rare books about China in the CUHK Library, history of Macau, pandemics in Asian history, western books in CUHK library [if in person]). Depending on numbers, students will be divided into small groups, each responsible for a different element, e.g. data/visualizations, maps, app, video, website (+overall coordination), programming component (if someone particularly wants to learn this), etc. Students should communicate regularly and I suggest you set up a Whatsapp group for this purpose. Each group will keep a project diary (also called learning log) of which methods they learned, how many times/how long they communicated, collaborated, how they organized their time/effort/etc. Grade will be based on both the collaboration/teamwork process (20% based on learning log) and the final product (30% based on the project).
Due date December 9, 5pm.
The Programming Historian (https://programminghistorian.org/en/)
|Grade A||Outstanding performance on all learning outcomes.|
|Grade A-||Generally outstanding performance on all (or almost all) learning outcomes.|
|Grade B||Substantial performance on all learning outcomes, OR high performance on some learning outcomes which compensates for less satisfactory performance on others, resulting in overall substantial performance.|
|Grade C||Satisfactory performance on the majority of learning outcomes, possibly with a few weaknesses.|
|Grade D||Barely satisfactory performance on a number of learning outcomes.|
|Grade F||Unsatisfactory performance on a number of learning outcomes, OR failure to meet specified assessment requirements.|