Process & Analyze · TPlus Exam Manual

5.1 Overview

In this chapter, all raw data files must be imported first before any processing begins. You will need to import Student Raw Data, Lecturer Raw Data, and Non Academic Raw Data into the system.

Once all raw data has been imported, you can proceed to process them in the following order:

Process Student Raw Data — must be processed first as it generates sections, courses, and student records.
Process Lecturer Raw Data — converts lecturers into invigilators and assigns them to the Academic group.
Process Non Academic Raw Data — converts non-academic staff into invigilators and assigns them to the Non Academic group.

After processing each raw data, analyze the results to verify accuracy before moving on. Make sure to correct any errors at this stage as they are much harder to fix once you proceed to the next phase.

5.2 Import Raw Data

Before processing any data, you must first import all raw data files into the system. Import the following raw data in any order:

Student Raw Data
Lecturer Raw Data
Non Academic Raw Data
Similar Courses (optional)

Note: If you are using TPlus eCampus and have already imported your database in Chapter 3: Data Preparation, the raw data files still need to be imported separately here. The eCampus import only covers rooms and courses data, not raw data.

5.2.1 Import Student Raw Data

Student raw data is course-student data which tells the system how many students are enrolled in each course. The system uses this to calculate room requirements and distribute students across venues during generation.

The file must be in CSV or Excel format with the following column structure: Student ID, Course Code, Course Name, and Student Name. Below is a sample of the expected file format:

Sample Student Raw Data Excel file format showing Student ID, Course Code, Course Name, and Student Name columns — **Figure 5.2.1.1:** Student Raw Data File Format

Note: Each row represents one student enrolled in one course. If a student is enrolled in multiple courses, the student will appear in multiple rows with different course codes.

Step 1 — Open the Raw Data tab.

Step 2 — Select Student Raw Data.

**Figure 5.2.1.3:** Student Raw Data selected

Step 3 — Click Import from File.

Import from File button — **Figure 5.2.1.4:** Click Import from File

Step 4 — A file browser will open. Browse to the student raw data file.

Browse for student raw data file — **Figure 5.2.1.5:** Browse for the student raw data file

Step 5 — Select the file and click Open.

Select file and click Open — **Figure 5.2.1.6:** Select the file and click Open

Step 6 — An import confirmation message will appear. Click OK.

Step 7 — The student raw data list is now displayed.

Student raw data list after import — **Figure 5.2.1.8:** Student raw data list displayed after import

Toolbar Icons in Student Raw Data Window

Inside the Student Raw Data window, the toolbar provides quick access to common functions.

Figure 5.2.1.9: Toolbar icons in the Student Raw Data window

5.2.2 Import Lecturer Raw Data

Lecturer raw data contains the list of lecturers who will be converted into invigilators for the exam schedule. The file must be in CSV or Excel format. Below is a sample of the expected file format:

Sample Lecturer Raw Data Excel file format — **Figure 5.2.2.1:** Lecturer Raw Data File Format

Step 1 — Open the Raw Data tab.

Step 2 — Select Lecturer Raw Data.

Step 3 — Click the Import from File icon.

Figure 5.2.2.4: Import from File icon

Step 4 — Browse and select the lecturer file.

Browse lecturer file — **Figure 5.2.2.5:** Browse and select the lecturer file

Step 5 — Select the lecturer list file and click Open.

**Figure 5.2.2.6:** Open lecturer list file

Step 6 — An import confirmation will appear. Click Ok to proceed.

Import confirmation for lecturer data — **Figure 5.2.2.7:** Import confirmation

Step 7 — The lecturer raw data will be displayed. Verify the records are loaded correctly.

**Figure 5.2.2.8:** Lecturer Raw Data loaded

Toolbar Icons in Lecturer Raw Data Window

Inside the Lecturer Raw Data window, the toolbar provides quick access to common functions.

Figure 5.2.2.9: Toolbar icons in the Lecturer Raw Data window

5.2.3 Import Non Academic Raw Data

Non Academic raw data contains the list of non-academic staff who will be converted into invigilators for the exam schedule. The file must be in CSV or Excel format. Below is a sample of the expected file format:

Sample Non Academic Raw Data Excel file format — **Figure 5.2.3.1:** Non Academic Raw Data File Format

Step 1 — Open the Raw Data tab.

Step 2 — Select Non Academic Raw Data.

Step 3 — Click the Import from File icon.

Figure 5.2.3.4: Import from File icon

Step 4 — Browse and select the Non Academic file.

Browse Non Academic file — **Figure 5.2.3.5:** Browse and select the Non Academic file

Step 5 — Select the Non Academic list file and click Open.

**Figure 5.2.3.6:** Open Non Academic list file

Step 6 — An import confirmation will appear. Click Ok to proceed.

Import confirmation for Non Academic data — **Figure 5.2.3.7:** Import confirmation

Step 7 — The Non Academic raw data will be displayed. Verify the records are loaded correctly.

**Figure 5.2.3.8:** Non Academic Raw Data loaded

Toolbar Icons in Non Academic Raw Data Window

Inside the Non Academic Raw Data window, the toolbar provides quick access to common functions.

Figure 5.2.3.9: Toolbar icons in the Non Academic Raw Data window

5.2.4 Similar Courses (Optional)

Similar Courses data is only required when there are courses that share the same exam and need to be scheduled in the same time slot. This may occur when courses have different course codes but the same course name, or different course names but share the same exam content.

By importing Similar Courses data, the system will group these courses together and ensure they are assigned to the same exam slot during schedule generation. This prevents scheduling conflicts for students who are enrolled in courses that share the same exam.

Step 1 — Open the Raw Data tab.

Step 2 — Select Similar Courses.

Step 3 — Click the Import from File icon.

Step 4 — A file browser will open. Browse to the similar courses file.

Browse for similar courses file — **Figure 5.2.4.4:** Browse for the similar courses file

Step 5 — Select the file and click Open.

Step 6 — An import confirmation message will appear. Click OK.

Step 7 — The similar courses data list is now displayed.

Similar courses data list after import — **Figure 5.2.4.7:** Similar courses data list displayed after import

Note: This import is optional and only needed when your institution has similar courses data. If there are no similar courses, you may skip this step.

Note: Ensure all required raw data files have been imported before proceeding to process them.

5.3 Processing Raw Data

After importing all raw data, the next step is to process each raw data type. The processing must be done stage by stage in the following order:

Stage 1: Process Student Raw Data (Course-Student)
Stage 2: Process Lecturer Raw Data
Stage 3: Process Non Academic Raw Data

Each stage must be completed before moving on to the next. The system relies on the processed data from the previous stage to correctly generate the schedule.

Note: Always start with Stage 1 (Student Raw Data) first, as the student enrolment data forms the foundation for room allocation, section generation, and the overall timetable structure. Lecturer and Non Academic data are processed after to assign invigilators and staff accordingly.

5.4 Process & Analyze Student Raw Data (Course-Student)

After all raw data has been imported, begin processing with Student Raw Data first. Processing activates the data so the system can generate sections, courses, and student records.

Step 1 — Navigate back to Student Raw Data under the Raw Data tab. Click Check All icon Check All icon to check all student raw data, then click Process Student Raw Data icon Process icon .

**Figure 5.4.1:** Check All and Process Student Raw Data

**Figure 5.4.2:** Process Student Raw Data

1. Sections and Constraint

Delete Section and Constraint options — **Figure 5.4.3:** Sections and Constraint options

Option	Description
Option 1: Delete All	Tick option 1 to delete all. This will delete all previous processed data and replace new ones. Choose this if you are first time user.
Option 2: Create new course (retain existing sections)	Tick option 2 to create new course but retain existing sections. Choose this if you are second time user.
Option 3: Update Student (create new course)	Tick option 3 to update student with create new course.
Option 4: Update Student (do not create new course)	Tick option 4 to update student without create new course.
Option 5: Update student remark only	Tick option 5 to update student remark only.

Important: You may only tick one option (Option 1–5) at a time.

If you choose Option 3 or Option 4, an additional Update Student Options panel will appear.

Tip: In the Update Student Options panel, you must pick one of the following:

Reassign Section — venue may change
Retain Section Original Time Slot — potential overflow

You can also tick Delete section with no student, Update exam duration, or both.

2. Grouping of Students

You may choose to group the students by sections and by similar courses.

If you don't tick at group students by section, Default Section Name column will appear. You may fill the default section name there.

**Figure 5.4.6:** Default Section Name Appear

If you tick on Group Students by similar course, you are able to choose between use same course name as similar courses OR use similar course group. You may also use combined course code as group name.

**Figure 5.4.7:** Group Students by similar courses

You can tick if you want to group students by campus. Note that if you tick here, a popup will appear saying it is recommended to put campus as room group.

You can tick if you want to Group courses by department and department field must exist.
You can tick if you want to Update Course Name in Student Raw Data.
You can tick if you want to Create sections into constraint group and you can put the name in blank section on the right side.

3. Additional Options

**Figure 5.4.9:** Part 3 Process Student Raw Data

Below is the recommended options to process Student Raw Data.

**Figure 5.4.10:** Recommended Options to tick

Click Ok to process Student Raw Data, and then go to Constraints Tree and Data Course List to see the result.

1. Constraints Tree

**Figure 5.4.11:** Constraints Tree Window

The Constraints Tree displays the hierarchical structure of all exam groups and their sections. You can sort the tree by Name or Size using the toolbar. When you select a group, the properties panel on the right shows the constraint settings for that group, such as Total Sections and Combined Capacity. These constraint properties can be configured later in the Apply Constraints chapter.

2. Data Course List

Analyze Student Raw Data

After checking the processed data, the next step is to analyze the results to ensure accuracy before applying constraints. Student raw data can be analyzed at:

Constraints Tree
Course List

Constraints Tree

Check if the sections have been placed into the right group folder, and verify that similar courses have been placed into the right combined group.

**Figure 5.4.14:** Constraint Tree Analyzation

Course List

Review the course list to ensure all course codes, names, sections, and durations are correct after processing.

5.5 Process & Analyze Lecturer Raw Data

After processing Student Raw Data, proceed to process Lecturer Raw Data. Lecturer records will be converted to invigilators and assigned to the appropriate group (e.g., Academic).

Step 1 — Navigate back to Lecturer Raw Data under the Raw Data tab. Click Check All icon Check All icon to check all lecturer raw data, then click Process Lecturer Raw Data icon Process icon .

**Figure 5.5.1:** Check All and Process Lecturer Raw Data

Step 2 — Before processing, a Lecturer Group (invigilator group) must be selected. Click the Update to Lecturer Group dropdown to check available groups. By default, only <root> is available.

Step 3 — Since no group exists yet, click Create New Group to create one.

**Figure 5.5.3:** Create New Invigilator Group

Step 4 — Enter the group name (for example: ACADEMIC), then click OK.

**Figure 5.5.4:** Entering New Group Name

Step 5 — After creating the group, click the dropdown button and select the newly created group (e.g., ACADEMIC).

**Figure 5.5.5:** Selecting Invigilator Group

The following tick options are available when processing:

Add Invigilator to Schedule — Adds the lecturer as an invigilator in the exam schedule.
Update Lecturer Information in Database — Updates the lecturer details stored in the database.
Update Invigilator Name — Updates the invigilator name if any changes have occurred.
Delete Existing Teaching Course — Removes previously assigned teaching courses before importing new data.

Step 6 — Click OK to start processing Lecturer Raw Data.

Analyze Lecturer Raw Data

After processing, analyze the results to ensure all lecturer records have been correctly converted to invigilators.

Invigilator List

Check if the invigilator name and group are correct. You may filter the invigilator based on the group you want. Also verify that each invigilator's campus is assigned correctly.

Invigilator Grouping

You can also verify lecturer data at Grouping > Invigilator Grouping. This view displays the invigilator groups (e.g. ACADEMIC, NON ACADEMIC) along with group details and available group actions.

Expand the ACADEMIC group to view all academic invigilators. When you select an invigilator, the right panel shows the Invigilator Details (schedule, workload, position), Courses/Sections assigned, and the Teaching List of that invigilator.

**Figure 5.5.7:** Academic Invigilator Grouping

5.6 Process & Analyze Non Academic Raw Data

After processing Lecturer Raw Data, proceed to process Non Academic Raw Data. Non Academic staff will be converted to invigilators and assigned to the Non Academic group.

Step 1 — Navigate back to Non Academic Raw Data under the Raw Data tab. Click Check All icon Check All icon to check all Non Academic raw data, then click Process Non Academic Raw Data icon Process icon .

**Figure 5.6.1:** Check All and Process Non Academic Raw Data

Step 2 — Before processing, a Non Academic invigilator group must be selected. Click the Update to Lecturer Group dropdown to check available groups. By default, only <root> is available.

**Figure 5.6.2:** Non Academic Group Dropdown

Step 3 — Since no group exists yet, click Create New Group to create one.

Create New Non Academic Invigilator Group — **Figure 5.6.3:** Create New Invigilator Group

Step 4 — Enter the group name (for example: NON ACADEMIC), then click OK.

Entering Non Academic Group Name — **Figure 5.6.4:** Entering New Group Name

Step 5 — After creating the group, click the dropdown button and select the newly created group (e.g., NON ACADEMIC).

Selecting Non Academic Invigilator Group — **Figure 5.6.5:** Selecting Invigilator Group

The following tick options are available when processing:

Add Invigilator to Schedule — Adds the Non Academic staff as an invigilator in the exam schedule.
Update Lecturer Information in Database — Updates the staff details stored in the database.
Update Invigilator Name — Updates the invigilator name if any changes have occurred.

Step 6 — Click OK to start processing Non Academic Raw Data.

Analyze Non Academic Raw Data

After processing, analyze the results to ensure all Non Academic staff have been correctly converted to invigilators.

Invigilator List

Check if the invigilator name and group are correct. You may filter the invigilator based on the group you want. Also verify that each invigilator's campus is assigned correctly.

Invigilator Grouping

You can also verify Non Academic data at Grouping > Invigilator Grouping. Expand the NON ACADEMIC group to view all non-academic invigilators. Non-academic staff will not have teaching courses, so the Teaching List will be empty.