使用MTurkR自动发布微批次HIT后无法在请求者账户查看的求助

Hey there! Let’s work through your MTurkR issue together— I’ve dealt with similar headaches when setting up automated micro-batches, so I think I can help you get this sorted.

First, let’s tackle why your HITs aren’t appearing in your dashboard even though the code says they’re successful:

1. Fix the sandbox_val Data Type (Critical!) #

Your code sets sandbox_val <- "FALSE" with quotes, which is a string instead of a boolean value. In R, any non-empty string evaluates to TRUE in logical checks. That means even if you intended to run in production, your code is actually targeting the Sandbox environment (or vice versa if you set it to "TRUE").

Fix this by changing it to a boolean without quotes:

sandbox_val <- FALSE # For production (live MTurk)
# OR
sandbox_val <- TRUE  # For Sandbox testing

Double-check you’re logged into the correct corresponding account when searching for HITs—Sandbox and production are completely separate systems, so HITs created in one won’t appear in the other.

2. Verify HIT Registration & Creation #

Add quick debug prints to confirm your HITs are actually being created properly:

• After RegisterHITType, add:

  print(newhittype)
  

  This will show you if a valid HITTypeId was generated. If it’s empty, your AWS credentials might be misconfigured (even without errors, double-check that your keys match the environment you’re targeting).
• Modify your createhit function to capture and print output:

  createhit <- function() {
    hit <- CreateHIT(
      hit.type = newhittype$HITTypeId,
      assignments = 2,
      expiration = seconds(days = 30),
      annotation = myannotation,
      verbose = TRUE,
      sandbox = sandbox_val,
      hitlayoutid = my_hitlayoutid
    )
    print(hit) # Print HIT details to confirm creation
    return(hit)
  }
  

  You can even manually search for the printed HITId in your MTurk dashboard to confirm it exists.

3. Account for Delayed Visibility #

Sometimes new HITs take 2-5 minutes to appear in the requestor dashboard, especially in production. Wait a few minutes, refresh the page, and check again before assuming something’s broken.

4. Confirm Layout IDs Are Environment-Specific #

Sandbox and production use separate layout IDs—make sure you’re using the Sandbox layout ID when sandbox_val = TRUE, and the production layout ID when sandbox_val = FALSE. Mixing them can cause HITs to be created but not display correctly.

To verify worker completion codes and approve/reject assignments manually before payment, here’s a straightforward workflow you can implement:

1. Retrieve Submitted Assignments #

Use GetAssignments to pull all pending or submitted assignments for your annotated HITs:

# Get all submitted assignments for your project
assignments <- GetAssignments(
  annotation = myannotation, 
  status = "Submitted", 
  sandbox = sandbox_val
)

2. Extract and Validate Completion Codes #

Worker answers are stored in XML format in the Answer column. Use this function to parse out the completion code:

library(xml2)

# Extract completion code from the XML answer string
extract_completion_code <- function(xml_string) {
  xml <- read_xml(xml_string)
  # Replace "completion_code" with the exact field name from your HIT layout
  code_node <- xml_find_first(xml, "//Answer/QuestionIdentifier[text()='completion_code']/../FreeText")
  xml_text(code_node)
}

# Add completion codes to your assignments dataframe
assignments$CompletionCode <- sapply(assignments$Answer, extract_completion_code)

# Filter valid vs invalid submissions (replace "YOUR_VALID_CODE" with your actual code)
valid_submissions <- assignments[assignments$CompletionCode == "YOUR_VALID_CODE", ]
invalid_submissions <- assignments[assignments$CompletionCode != "YOUR_VALID_CODE", ]

3. Approve/Reject Assignments #

Loop through the filtered submissions to approve valid work and reject invalid entries:

# Approve valid assignments
for (assign_id in valid_submissions$AssignmentId) {
  ApproveAssignment(
    assignment = assign_id, 
    feedback = "Great work—thank you for your participation!",
    sandbox = sandbox_val
  )
}

# Reject invalid assignments (optional, add clear feedback)
for (assign_id in invalid_submissions$AssignmentId) {
  RejectAssignment(
    assignment = assign_id, 
    feedback = "Sorry, your completion code didn't match our records. Please review the survey instructions and try again.",
    sandbox = sandbox_val
  )
}

4. Automate the Review Process #

You can add this review logic to your existing loop (right after createhit()) or set up a separate scheduled script to run every 10-15 minutes and check for new submissions. Just make sure to track which assignments you’ve already processed (e.g., log approved/rejected IDs in your log file) to avoid duplicate actions.

内容的提问来源于stack exchange，提问作者Kinga Reka Makovi