Unit 1
Unit 1: Online Library Tutorial. 12 hours
| Course Name | Academic Writing & Communication |
| Course Code | 25SDS505 |
| Program | M.Sc. in Social Data Science & Policy |
| Semester | 1 |
| Credits | 3 |
| Campus | Faridabad |
Unit 1: Online Library Tutorial. 12 hours
Unit 2: Critical reflection of introductory article, including all relevant references in academic style (Chicago Manual of Style for example) format. 12 hours
Unit 3: Outline of arguments for essay, including all relevant references in in academic style format. 12 hours
Unit 4: Final Essay. 12 hours
Unit 5: Final Presentation. 12 hours
Prerequisite: NA
This course focuses on two elements. In the Writing component, the course covers the various stages of composition of an academic piece, including close reading of sources, summary, citation and reference, identifying rhetorical aspects in a text or flaws in reasoning, developing an argument, finding and using textual evidence, organising ideas effectively, compiling and referencing bibliographic material, avoiding plagiarism, and finally, strategies for revision. In the Communication component, the course focuses on covers the many facets of delivering effective presentations, such as organization and structure, modes of delivery, effective linking, choice of terminology, and interaction with an audience.
Course Objectives:
Course Outcomes:
CO1: Students will be able to apply and compare knowledge and understanding of at least two themes within Social Data Science.
CO2: Students will be able to write a nuanced and critical thesis statement or problem question, and can answer this question in the body of their essay, using a logical structure and clear argumentation.
CO3: Students will learn careful reading techniques, learn to analyse and summarize the main argument of a text in a critical and nuanced manner, and gain an understanding the current literature on social data science.
CO4: Students will get an understanding of the research area in social science that can leverage data sciences.
CO5: Students will have an understanding of the process pipeline from data collation to modelling and forecasting through the careful reading of literature on social data science.
Skills:
Program outcome PO – Course Outcomes CO Mapping
|
PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
|
|
CO1 |
X |
– |
– |
– |
– |
– |
– |
– |
|
CO2 |
– |
– |
X |
– |
X- |
– |
– |
– |
|
CO3 |
– |
X |
– |
– |
– |
– |
– |
– |
|
CO4 |
– |
– |
– |
– |
– |
– |
– |
– |
|
CO5 |
X |
– |
– |
– |
– |
– |
– |
– |
Program Specific Outcomes PSO – Course Objectives – Mapping
|
PSO1 |
PSO2 |
PSO3 |
PSO4 |
PSO5 |
|
|
CO1 |
X |
– |
– |
– |
– |
|
CO2 |
– |
X- |
– |
– |
– |
|
CO3 |
– |
– |
X- |
– |
– |
|
CO4 |
– |
– |
– |
– |
X- |
|
CO5 |
– |
– |
– |
– |
– |
|
Assessment |
Internal |
External |
|
Final Presentation (Unit 5) |
20%each |
|
|
Units |
15% each Unit 1-3 |
|
|
End Semester (Final Essay,Unit 4) |
30% |
|
|
Attendance |
5% |
*CA – Can be Quizzes, Assignment, Projects, and Reports, and Seminar
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