Open FlexiList and run your bookmarkOpen SCMobile and sign in normally with MIMS/MFA. Once FlexiList is open, click the GNOME Namelist bookmark you just made. It downloads the full Name, Class, Index and Teaching Group list.Open SCMobile FlexiList
3
Load the namelist into GNOMEChoose the downloaded GNOME Namelist YYYY.csv. It is read locally in this browser.
No namelist loaded
Already have a FlexiList Excel workbook?
GNOME can also read an existing FlexiList .xlsx locally. Teaching Groups are available only if those columns exist in that workbook.
Choose the expected cohort
After the school namelist loads, select one or more form classes and/or Teaching Groups. Overlaps are de-duplicated.
No expected cohort selected
Local processing
Roster files stay in this browser. The GNOME Namelist bookmark runs only inside your authenticated SCMobile tab and uses read-only same-origin FlexiList GETs.
LOCAL
STEP 3
Scan and Load
Scan the response sheets on the Canon feeder, classify every generated PDF with Microsoft Purview, then load all PDF chunks together.
No batch loaded
SCAN ON THE CANON
Scan the OMR response stack
With the scan-bed down, place your stack of OMR responses into the feeder.
Log into the Canon printer.
Click on Main > Scan and Send > Send to Myself >
THEN CLASSIFY THE PDF FILES
Apply OFFICIAL (CLOSED) - NON-SENSITIVE
Select all scanner PDFs in Windows Explorer → Show more options → Apply sensitivity label with Microsoft Purview → OFFICIAL (CLOSED) → NON-SENSITIVE.
1 · Show more options2 · Apply label3 · NON-SENSITIVE
Load all PDF chunks
Select multiple PDFs in one action. If the Canon created another chunk, use Add more PDFs before processing.
Batch files
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No files selected
Click to load one or more scanner PDFs.
Local processingPDFs, student responses, roster files and generated outputs are processed in this browser and are not uploaded to GNOME or Cloudflare.
Resume a previous GNOME session
No session loaded
Reading PDFs0%
Preparing batch...
STEP 4
Review & override
Confirm what GNOME read from each script. The teacher is authoritative; any overwrite immediately becomes the value used downstream.
No batch loaded
Class / Index
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Cohort: No expected cohort selected
TEACHER-AUTHORITATIVE REVIEW
Select a Class / Index entry to inspect.
Scanned identityClass + Index source evidence
Rendering...
Confirm Class / Index
Machine read-
Roster name-
Handwritten name
Confirm shaded responses
Each group of five keeps the annotated scan crop directly beside the matching teacher overwrite. Q1, Q6 and Q11 within each 15-question column begin at the same vertical position as their teacher controls.
STEP 5
Setup answer key
Set the question count, then enter or paste the answers and marks. The 45-question capacity is shown as three compact 15-question panels.
Not confirmed
Answer key grid
Paste directly from Excel if useful. Questions beyond the declared count are dimmed and ignored.
Tip: paste one or three columns starting at any active question.
Q#
Ans
Marks
Q#
Ans
Marks
Q#
Ans
Marks
STEP 6
Mark, inspect & download
Run the marking pass, inspect the preliminary cohort and item-level results, then download the complete results pack.
Not marked
Marking scripts
Any material change to cohort, identity, responses, answer key or marks makes the run dirty; simply re-mark.
Ready0%
Waiting to mark
Download results pack
Includes Scripts PDF, Annotated PDF, Result Slips, Analysis.xlsx, Answer Key.xlsx and Session JSON in one ZIP.
Ready0%
Waiting for a completed marking run
PRELIMINARY ANALYSIS
What the marking run is showing
Check these results before downloading the final workbook.
A quick-and-dirty guide to reading the Functional Index (Fi) and Discriminatory Index (Di) in the analysis workbook.
Functional Index (Fi)
This is simply the proportion of students who gave the correct response.
In this example, about half the student made a mistake for Q3. Most of the students gave the correct answer for Q2, so Q2 is considered to be 'easy' for this group of students.
A well-balanced test should have a good mix of easy, moderate and hard questions.
Discriminatory Index (Di)
This is a measure of how well the question can distinguish strong vs weak students.
Di is calculated by
(proportion of high overall scorers getting this question correct) - (proportion of low overall scorers getting this question correct)
For e.g., if ALL the high-scorers got Q1 correct, and ALL the low-scorers got the question wrong, then DI for Q1 = 1 - 0 = 1.
A problematic extreme case can be when ALL the high-scorers got Q2 wrong, and ALL the low-scorers got the question correct, then DI for Q2 = 0 - 1 = negative 1.
Real-world Example
The setters for this test should study if items Q6, Q7, Q9, Q12, Q14 are problematic.
This is meant as a quick-and-dirty guide. If you wish to go more in-depth, you should consider SEAB Certificate in Assessment (CEA) courses.