updated portfolio again ...

portfolio.md

@@ -6,44 +6,48 @@ nav_order: 04
 # Social Coding Portfolio
 
 ### Project Description
-For the final project in this course, you will create and maintain a social coding portfolio on GitHub that will serve as both a public submission portal for your coursework and a professional showcase of your progress in programming basics, data science, and digital humanities. This portfolio will house your responses to five programming activities, each accompanied by a reflective account of your learning process, and will culminate in a final semester reflection.
+For the final project in this course, you will create and maintain a social coding portfolio on GitHub that will serve as both a public submission portal for your coursework and a professional showcase of your progress in programming basics, data science, and digital humanities. This portfolio will showcase your technical and reflective responses to four programming activities, culminating in a final semester notebook and reflection on the process. 
 
-### ** Programming Activities**
+### Programming Activities
 
-- **Jupyter Notebook:** For each of the five programming activities, you will create a complete, well-documented notebook (`.ipynb`) that demonstrates your approach to the assigned problem. Your notebook should include code, visualizations, and explanatory markdown cells that clearly communicate your process and results.
-- **Reflective Account:** Alongside each notebook, you will write a one-page reflection in markdown (`.md`) that details your learning process, the challenges you encountered, and the insights you gained during the activity. These reflections will be committed to your social coding portfolio and later featured on the course website as part of a gallery of student reflections. 
+**Jupyter Notebook Responses (4 total):** For each of the four programming activities, you will create a complete, well-documented notebook (`.ipynb`) that demonstrates your approach to the assigned problem. Your notebook should include code, visualizations, and explanatory markdown cells that clearly communicate your process and results.
 
-### **Final Reflection**
+**Reflective Log (4 total):** Alongside each notebook, you will write a one-page reflection in markdown (`.md`) that details your learning process, the challenges you encountered, and the insights you gained during the activity. These reflections will be committed to your social coding portfolio and later featured on the course website as part of a gallery of student reflections. 
 
-- **Purpose:** Your final reflection will be an analytical narrative that draws connections between the topics, methods, and datasets we’ve explored throughout the semester. It should reflect on how the knowledge and skills you’ve developed in data science apply to broader contexts, including your personal life, future studies, or professional ambitions.
-- **Guidelines**
-  - **Length:** Approximately 2 double-spaced pages.
-  - **Formatting:** Use Times New Roman, 12-point font, or Arial/Helvetica, 11-point font. Adhere to MLA citation format for any sources referenced in your reflection.
-  - **Content:** Your reflection should go beyond a mere recount of your activities. It should integrate your experiences with analytical insights and demonstrate how your work in this course intersects with broader academic and personal contexts. You may include examples from your lived experiences, current events, or relevant media to enrich your reflection.
-- **Submission Format:** Save your reflection as a markdown file (`.md`) and commit it to your social coding portfolio in the `Final-Reflection` folder.
-- **Public Sharing:** Ensure that your portfolio remains accessible to the course community by keeping your GitHub repository public. You may use a pseudonym or nickname as your GitHub username to protect your privacy while participating in the public sharing of your work. 
+### Final Reflection
 
-### Project Overview 
+Your final reflection will be an analytical narrative that draws connections between the topics, methods, and datasets we’ve explored throughout the semester. It should reflect on how the knowledge and skills you’ve developed in data science apply to broader contexts, including your personal life, future studies, or professional ambitions. 
 
-- **Repository Structure**
-  - Use the GitHub repository you created at the start of the semester to serve as your class portfolio
-  - Name the repository following the convention: `[username]/CCNY-Coding-Portfolio`.
-  - Ensure that your repository is set to public access to allow for peer review and course-wide visibility. Remember, you may use a pseudonym or nickname if you wish to maintain anonymity.
-- **Initiate with a README.md file** 
-  - Briefly describe the purpose of the repository
-  - Provide a summary of the course portfolio contents
-  - Embed links to each activity folder as they are added
+Ensure that your portfolio remains accessible to the course community by keeping your GitHub repository public. You may use a pseudonym or nickname as your GitHub username to protect your privacy while participating in the public sharing of your work. If you would prefer to keep your portfolio private and only share with me, then please reach out to make that request. 
 
-- **Notebook and Reflection Folders**
-  * Organize your repository with two main folders: 1) `Notebooks` and 2) `Reflections`
-    * In the **Notebooks** folder, create a file for each activity, named activity-X.ipynb, where X is the activity number (e.g., activity-1.ipynb)
-    * In the **Reflections** folder, create a corresponding markdown file for each activity, named activity-X-reflection.md, to document your reflections and insights on that activity
-- **Final Reflection Folder:**
-  - Create a folder named `Final-Reflection`.
-  - This folder should include:
-    - `final-reflection.md`: A cumulative reflection on the broader arc of your learning experience in the course, considering how your understanding of data science, cultural analytics, and/or the digital humanities has grown since the onset of the term. 
+* **Submission Format:** Save your reflection as a markdown file (`.md`) and commit it to your social coding portfolio in the `Final-Reflection` folder.
 
-___
+* **Length:** Approximately 2 double-spaced pages
+
+* **Formatting:** Use Times New Roman, 12-point font, or Arial/Helvetica, 11-point font. Adhere to MLA citation format for any sources referenced in your reflection
+
+* **Content:** Your reflection should go beyond a mere recount of your activities. It should integrate your experiences with analytical insights and demonstrate how your work in this course intersects with broader academic and personal contexts. You may include examples from your lived experiences, current events, or relevant media to enrich your reflection. 
+
+### Portfolio Structure 
+
+To structure your course portfolio, use the GitHub repository you created at the semester’s outset. This repository will serve as a centralized showcase of your work, accessible to both your peers and the instructional team. For clarity and consistency, name your repository following this convention: [username]/CCNY-Coding-Portfolio. Ensure that the repository is set to public, enabling course-wide visibility and peer review opportunities. If you prefer to remain anonymous, feel free to use a pseudonym or nickname.
+
+Begin by creating a README.md file within your repository. In this file, briefly describe the purpose of the repository as a portfolio for your coursework. Include a summary of its contents, outlining the types of activities and projects housed within. As you add new activity folders, embed links to each within the README for easy navigation. This README will serve as a guide for anyone exploring your repository, giving them insight into your learning trajectory and achievements.
+
+**Notebook and Reflection Folders**
+
+Organize your repository with two main folders: `**Notebooks**` and `**Reflections**`
+
+1. In the `**Notebooks**` folder:
+   1. save the Jupyter notebook file from Colab to your Google drive,
+   2. follow the instructions and complete the programming tasks save the file,
+   3. download the competed notebook, then upload it to the `Notebooks` folder on GitHub
+
+2. In the `**Reflections**` folder: in a text editor, create a markdown file (.md) for each activity named `activity-X-reflection.md` to document your reflections and insights on that activity 
+
+**Final Reflection**
+
+For your cumulative reflection on the semester, upload a file named final_reflection.md directly to the parent directory of your repository. This reflection should encapsulate the broader arc of your learning experience, considering how your understanding of data science, cultural analytics, and/or the digital humanities has evolved over the term. This final reflection will provide a summative perspective on your academic growth and any significant insights gained throughout the course.
 
 ### Submission Guidelines
 
@@ -59,28 +63,23 @@ Your social coding portfolio will be assessed based on:
 - **Completeness:** Submission of all required components for each activity and the final reflection.
 - **Quality of Work:** The accuracy, effort, and thoroughness of your Jupyter notebook responses.
 - **Reflective Log:** Successful submission of a written reflection for each of your programming activities.
-- **Organization:** The clarity, structure, and navigability of your portfolio's file structure.
-- **Critical Analysis:** Especially in your final reflection, demonstrating engagement with the themes and lessons of the class, from critical theories of data feminism to applied methods of data science
-
-### Project Deadlines
-
-In addition to the required activities—**Activity 1** and **Activity 2**—choose two of the remaining three:
+- **Project Organization:** The clarity, structure, and navigability of your portfolio's file structure.
+- **Critical Thinking:** Especially in your final reflection, demonstrating engagement with the themes and lessons of the class, from critical theories of data feminism to applied methods of data science
 
-* Required: **Activity 1: Building Blocks** - Due: 10/08 (Tue)
-* Required: **Activity 2: Python Primer** - Due: 10/22 (Tue)
-* **Activity 3: Practicing Pandas** - Due: 11/12 (Mon) - 11/15 (Fri) [Floating Deadline]
-* **Activity 4: Writing Documentation** - Due: 11/21 (Thu)
-* **Activity 5: Data Visualization** - Due: 12/05 (Thu)
+### Benchmarks and Deadlines
 
-___
+Everyone must complete the first two activities on Python basics:
 
-* **Social Coding Portfolio**: Due: 12/19 (Thursday)
+* **Required**: Activity 1: Building Blocks - Due: 10/08 (Tue)
+* **Required**: Activity 2: Python Primer - Due: 10/22 (Tue)
 
-  \- [ ] Activity 1 AND Activity 2
+After completing Activity 1-2, choose two from the following three options:
 
-  \- [ ] Activity 3, Activity 4, OR Activity 5
+* Activity 3: Practicing Pandas - 11/14 (Thu)
+* Activity 4: Writing Documentation - 11/21 (Thu)
+* Activity 5: Data Visualization -: 12/05 (Thu)
 
-  \- [ ] Final Reflection
+**Social Coding Portfolio**: Due: 12/19 (Thursday)
 
 ### Optional Content
 Feel free to include additional content in your portfolio that showcases your learning journey, such as: