IDP Final Project Rubric - Intermediate Data Programming

Discovery Document¶

Below is the grading rubric for the Discovery Document, structured with three performance levels: “Exceeds Expectations,” “Meets Expectations,” and “Does Not Meet Expectations.” Each main requirement is assigned a maximum point value, totaling 100 points.

Requirement	Exceeds Expectations	Meets Expectations	Does Not Meet Expectations	Points
Title and Author(s)	Title clearly reflects specific research questions; author(s) properly credited.	Title reflects general research topic; author(s) credited.	Title is missing or does not reflect research topic; author(s) not credited.	5
Research Questions	Provides a numbered list of at least 3 well-defined, answerable research questions with 1–3 sentence descriptions.	Provides a numbered list of 3 research questions with brief descriptions; questions are somewhat clear.	Provides fewer than 3 research questions; questions are vague or lack descriptions.	15
Motivation	Clearly articulates the significance of the research questions in 1–2 well-developed paragraphs; explains relevance and potential impact.	Provides a general explanation of the significance of the research questions; relevance is somewhat clear.	Motivation is unclear or missing; does not explain the significance of the research questions.	10
Dataset Description For webscraping challenge; document the site for scraping URLs and expected format of future scraped data.	Thoroughly describes dataset(s) including exact URLs; dataset is real, contains over 500 lines, and is appropriate for research; explains data source, collection methods, and potential limitations. Deep understanding and documentation of data columns, formats, accuracy and caveats	Describes dataset(s) with URLs; dataset meets basic requirements; provides some information on data source and collection methods.	Inadequate description of dataset(s); missing URLs; dataset is inappropriate or insufficient for research; lacks information on data source and collection methods.	30
Challenge Goals	Selects at least 2 appropriate challenge goals; provides strong justification for their relevance and suitability to the project.	Selects 2 challenge goals; provides some justification for their selection.	Fails to select appropriate challenge goals; justification is weak or missing.	10
Overall	Documentation is well-organized, free of grammatical errors, and formatted professionally; tables and figures (if any) are clear and enhance understanding. All sections are complete with sufficient details (such as: Task List, Challenges working with the data...)	Document is organized and mostly free of grammatical errors; formatting is adequate; tables and figures (if any) are understandable. Some details lacking	Document is poorly organized, contains grammatical errors, and lacks professional formatting; tables and figures (if any) are unclear or absent.	30
Total Points				100

Data Organization¶

Requirement	Exceeds Expectations	Meets Expectations	Does Not Meet Expectations
Data Preparation and Code Submission (40 points)	- Data is meticulously pre-processed, well-organized, and thoroughly documented. - Comprehensive, well-annotated code provided for data collection and organization.	- Data is adequately pre-processed and organized. - Code for data collection and organization is complete but may lack detailed annotations.	- Data is poorly organized or not pre-processed. - Code is missing, incomplete, or contains significant errors.
Plot Sketches and Visualization Planning (40 points)	- All research questions are addressed through diverse, creative, and feasible plot sketches. - Sketches are detailed, with clear titles, labeled axes, appropriate use of color, legends, annotations, and statistical indicators. - Effectively highlights challenge goals, such as machine learning predictions or interactive controls.	- Most research questions are addressed with a variety of plot types. - Sketches include titles and labeled axes but may lack some details like color or annotations. - Some challenge goals are incorporated into the sketches.	- Few or none of the research questions are addressed. - Sketches are incomplete or missing essential elements like titles and labeled axes. - Challenge goals are not considered or addressed.
Overall Documentation and Clarity (20 points)	- All sketches and documentation is clear, well-organized, and easy to interpret. - Documentation is professional, adheres to all guidelines, and effectively communicates the intended message. - All documentation is submitted per the requirements.	- Sketches and documentation is generally clear with minor areas of confusion. - Documentation mostly adheres to technical writing standards and communicates the intended message.	- Sketches and documentation is difficult to interpret due to poor organization or lack of clarity. - Presentation does not adhere to guidelines and fails to communicate the intended message.
Total Points:			100

Final Delivery (250 pts)¶

Your final delivery will be due according to the schedule posted and will be comprised of the following elements for grading.

Presentation (100 pts) link¶

Part 1: Peer Evaluation Rubric¶

To be completed by classmates via the Google Quiz. These focus on the presentation “experience.”

Category	Excellent	Good	Adequate	Needs Work
Speaking & Engagement	Clear, confident, and polished delivery. Engages the audience effectively throughout.	Mostly clear delivery; occasional hesitations. Some effort to engage the audience.	Somewhat unclear or monotone delivery. Limited connection with the audience.	Unclear, overly quiet, or distracting delivery; little effort to engage.
Clarity & Structure	Strong, logical flow. Clearly communicates purpose, methodology, and outcomes.	Mostly clear with logical structure; transitions between topics are mostly smooth.	Somewhat hard to follow; lacks organization or clarity in specific sections.	Difficult to follow; unclear organization or missing key ideas.
Visual Accessibility & Pacing	Audience is given ample time to process each slide. Explanations are synchronized with visuals; data is visible to everyone.	Pacing is generally good. Most slides are explained well and visible; transitions feel slightly rushed.	Inconsistent pacing. Audience may struggle to see specific data points or keep up with the spoken explanation.	Slides are flashed too quickly or not explained; data is too small to see or obscured.
Data Viz Standards & Techniques	Exceptional adherence to unit guidelines. Uses correct chart types, avoids “chart junk,” and highlights key insights.	Good application of unit techniques. Visuals follow guidelines with only minor aesthetic or technical deviations.	Inconsistent use of principles. Charts may be misleading, cluttered, or fail to use techniques covered in class.	Fails to apply unit guidelines. Charts are difficult to interpret or use inappropriate/prohibited techniques.

Part 2: Instructor Evaluation Rubric¶

This will be completed by your teacher. These focus on technical rigor and group dynamics.

Category	Excellent	Good	Adequate	Needs Work
Analytical Rigor & Claim Accuracy	All claims fully substantiated by data. No “leaps of faith”; conclusions address necessary disclosures and segments.	Most claims are supported. Minor instances where conclusions slightly outpace evidence, but reporting is sound.	Several claims lack data; makes logical leaps or omits critical segments that should have been disclosed.	Significant “leaps of faith” without data. Fails to provide evidence or ignores major missing segments.
Team Collaboration & Transitions	All members contribute meaningfully. Transitions are seamless, demonstrating rehearsal and co-operation.	All members contribute clearly. Transitions are logical, though one or two may feel slightly unpolished.	Visible imbalance in contribution; transitions are awkward or members seem disconnected.	One or more members are significantly under-participating or absent; no cohesive team flow.

Report (100 pts) link¶

Category	Excellent	Good	Adequate	Needs Work
Technical Depth & Analytical Rigor	Purpose and technical features are justified with high-quality logic. Claims are fully substantiated by data with no “leaps of faith.” Findings connect seamlessly to research goals and future implications.	Purpose and logic are clear. Most claims are supported by evidence. Summarizes outcomes well and relates them to the project purpose with minor gaps in depth or detail.	Superficial overview; features are listed but not contextualized. Relies on unsubstantiated claims or omits critical context. Conclusion is brief or fails to explain the “so what.”	Unclear purpose or minimal technical explanation. Significant “leaps of faith” without data. Missing a conclusion or fails to relate findings to goals.
Methodology & Technical Execution	Sophisticated technical approach. The approach taken is clearly documented and justified. Technical hurdles are handled with elegant solutions.	Sound technical approach. Tools and methods are used correctly and described clearly, though some minor implementation details or justifications may be missing.	Basic implementation. Methods are described but lack detail on “why” specific tools/logic were chosen. Implementation is functional but unoptimized or simplistic.	Methodology is missing, fundamentally flawed, or a “black box.” No explanation of how the results were technically produced or how tools were applied.
Professionalism & Data Viz	Polished formatting and error-free writing. Data visualizations strictly adhere to unit guidelines (no chart junk) and enhance the narrative.	Well-formatted with few errors. Visuals are effective and follow most class guidelines, with minor aesthetic deviations.	Inconsistent formatting or grammar. Data visualizations may be cluttered, difficult to interpret, or ignore class techniques.	Disorganized or hard to read. Visuals are missing, misleading, or use prohibited techniques.
Challenge Goals	Successfully implements two or more listed challenge goals beyond core requirements. Documented with full technical transparency.	Challenge goals (two or more) do not meet the technical depth and effort expected for a semester-long research project.	One challenge goal met.	No evidence of challenge goals attempted.

Code/GitHub (50 pts)¶

Category	Excellent	Good	Adequate	Needs Work
Documentation & Administrative Setup	Main README provides a professional overview, folder map, and “How to Run” guide. All sub-folders have READMEs. The Research Report is correctly placed in the `final_doc` folder. Data schemas/columns are fully defined.	Main README and folder layout are clear. Research Report is included but perhaps misplaced. Data columns are described, but sub-folder documentation is sparse.	README is present but missing key components (e.g., folder map). Documentation of data columns is incomplete.	README is minimal or missing. Research Report is missing from the submission. Folder structure is undocumented.
Code Quality & Portability	Code is readable and organized in a maintainable, coherent way. All AI-generated logic and plots are clearly attributed with sources cited in comments. Program runs seamlessly on Windows and Linux/Codespaces.	Code is mostly organized. AI attribution is present for major blocks but may lack specific citations for plot generation. Runs on both platforms with minor manual tweaks.	Code is disorganized. AI-generated code is included but poorly documented or missing proper attribution. Platform-locked (e.g., only works on Windows).	Disorganized and impossible to follow. No attribution for AI use. Code fails to run on one or both required platforms.
Reproducibility & Plot Generation	All plots can be regenerated via a single script or clear, reproducible steps. Instructions for data processing are robust and error-free.	Most plots can be regenerated with minor manual intervention. Instructions for plot generation are mostly clear.	Unable to regenerate multiple plots. Code for data processing is missing or requires significant troubleshooting.	Plot generation code is missing, non-functional, or no instructions are provided.

Ongoing¶

Professionalism¶

This section will be ongoing through the entire project lifecycle and count towards the final grade (Professionalism category)

Category	Excellent	Good	Adequate	Needs Work
Professionalism	No instances of being off task. Asks for hints occasionally, independently researches, demonstrates problem-solving abilities.	1 or 2 reminders needed to be on task. Needs help with difficult issues but demonstrates ability to debug and grow independently.	3+ reminders to get back on task. Consistently unable to resolve (minor) issues without assistance.	Frequently off task. Cannot make progress without assistance.