Feedback Harness: ax7k - Data Explorer

Purpose

This feedback harness is a reviewer artifact that bundles all context needed for AI and human reviewers to evaluate student work. It contains:

• Student profile and persona information
• Project specification and rubric
• Student's submitted code as an artifact
• Commit history and development process
• Agent instructions for generating personalized feedback

Note: This harness is typically created via a custom GitHub Classroom integration (not provided in this example repository). The integration automatically bundles student submissions, commit history, and links to relevant curriculum materials.

Student-Facing Feedback

The feedback generated in this harness is extracted and delivered to the student as a separate file:

Student-facing feedback: ax7k-project-1.feedback.md

The student-facing file contains only the feedback content without internal context (rubric scores, commit history, agent instructions, etc.).

Student Profile

See: Student ax7k Persona

Quick summary:

• Prior experience: None (first-time programmer)
• Strengths: Detail-oriented, persistent, asks good questions
• Growth areas: Math anxiety, needs concrete examples
• Major: Biology (pre-med) — interested in data analysis for research

Project Specification

See: Project 1: Data Explorer

Requirements summary:

• Calculate average temperature
• Find highest/lowest and which days
• Count hot (>75) and cool (<70) days
• Classify each day
• Print formatted report

Rubric

See: Project 1 Rubric

Commit History

Recent commits from student's repository:

• a3f7c21: "finished project" (2025-10-03)
• 8b2e4f9: "added summary section" (2025-10-02)
• c91d5a3: "working on loop" (2025-10-01)
• 5e6f8a2: "started project 1" (2025-09-29)

Code Snapshot

weather_report.py

# Project 1: Data Explorer
# Name: [ax7k]
# Date: October 3, 2025

# Weather data
temperatures = [72, 68, 75, 80, 77, 71, 69]
days = ["Monday", "Tuesday", "Wednesday", "Thursday", "Friday", "Saturday", "Sunday"]

# Variables for tracking
total = 0
highest = temperatures[0]
lowest = temperatures[0]
highest_day = days[0]
lowest_day = days[0]
hot_count = 0
cool_count = 0

print("=== Weekly Weather Report ===")
print()
print("Daily Breakdown:")

# Loop through each day
for i in range(len(days)):
    day = days[i]
    temp = temperatures[i]

    # Add to total for average
    total = total + temp

    # Check for highest
    if temp > highest:
        highest = temp
        highest_day = day

    # Check for lowest
    if temp < lowest:
        lowest = temp
        lowest_day = day

    # Classify the day
    if temp > 75:
        category = "Hot"
        hot_count = hot_count + 1
    elif temp >= 70:
        category = "Mild"
    else:
        category = "Cool"
        cool_count = cool_count + 1

    print(day + ": " + str(temp) + "°F (" + category + ")")

# Calculate average
avg = total / len(temperatures)

print()
print("Summary:")
print("- Average temperature:", round(avg, 1), "°F")
print("- Highest:", highest, "°F on", highest_day)
print("- Lowest:", lowest, "°F on", lowest_day)
print("- Hot days (>75°F):", hot_count)
print("- Cool days (<70°F):", cool_count)

Agent Instructions

When generating feedback for this student:

1. Be encouraging: This is a first-time programmer who has made good progress
2. Connect to their interests: Biology/research applications when relevant
3. Be specific: Reference line numbers and exact code
4. Prioritize: Focus on 2-3 key improvements, not every issue
5. Acknowledge progress: Note the evolution from commits

Key Issues to Address

1. Boundary condition: 75°F is classified as "Mild" but rubric says >75 is Hot, so 75 should be Mild. This is actually correct! But verify the boundary logic matches the spec.

2. Variable naming: avg and total are okay, but temp in a weather context is good. Consider if i could be more descriptive.

3. Comments: Has header but inline comments are minimal. Suggest adding comments for key logic sections.

4. String formatting: Using + for concatenation works but f-strings would be cleaner (if covered in class).

Generated Feedback

Note: The feedback below is extracted and delivered to the student as curriculum/students/ax7k-project-1.feedback.md. The student-facing version omits internal context (rubric scores, commit history, agent instructions) and focuses solely on actionable feedback.

Summary

Great work on Project 1! Your program correctly analyzes the weather data and produces a clear, readable report. You've demonstrated solid understanding of loops, conditionals, and accumulator patterns. The code is well-organized and your logic for finding highs/lows is exactly right. Score: 85/100

What Works Well

• Correct logic for tracking highest/lowest: Your approach of initializing with the first value and updating as you find larger/smaller values is the standard pattern—well done!
• Clean loop structure: The single loop that handles all the calculations is efficient
• Good output formatting: Your report is easy to read and includes all required information
• Steady progress: Your commit history shows good incremental development—this is how real programmers work!

Key Improvements

1. Add More Inline Comments

Location: Throughout, but especially lines 23-45

Your header comment is good, but adding a few more comments would help readers (and future you!) understand the code faster.

Current code:

for i in range(len(days)):
    day = days[i]
    temp = temperatures[i]

Suggestion:

# Process each day's data
for i in range(len(days)):
    day = days[i]
    temp = temperatures[i]

Why: In research settings, you'll often revisit code months later. Comments are your future self's best friend.

2. Consider More Descriptive Loop Variable

Location: Line 23

Current code:

for i in range(len(days)):

Suggestion:

for day_index in range(len(days)):

Why: While i is a common convention, day_index makes it immediately clear what the variable represents. This matters more as programs get larger.

3. String Formatting Enhancement (Optional)

Location: Line 47

Current code:

print(day + ": " + str(temp) + "°F (" + category + ")")

Alternative approach (if you've seen f-strings):

print(f"{day}: {temp}°F ({category})")

Why: F-strings are more readable and you don't need to manually convert numbers to strings. This is a style improvement, not a correctness issue.

Next Steps

1. Add 2-3 inline comments explaining your key logic sections (the highest/lowest tracking and classification)
2. Keep building on this foundation—your loop skills will be essential for Project 2
3. Consider: How might you modify this to analyze a longer dataset? (Hint: your code would work without changes!)

Connection to Your Goals

This kind of data analysis is exactly what you'd do in computational biology—processing lists of measurements and finding patterns. Nice work building these foundational skills!