Project Details


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Project Details

RM0.00 Fixed Price
83 days


Industrial Training Assessment System

Speech Recognition, Signal Processing, Artificial Intelligence


Industrial Training Assessment System (ITAS) was designed to be a user friendly, generic, web-based system to ease access to assessment records for students undergoing industrial training in a more organised and efficient way. The assessment criteria provided will have radio buttons for the supervisors to tick the relevant sections and this makes rewarding of marks more standardised and also reduces human error in calculating the marks. The assessment rubrics are digitally stored and can be used to analyse and produce students’ result online. ITAS also includes a bulletin where students can read important news posted by their respective supervisors through a bulletin board.

The application meets the demand for making the task of assessment processing for students undergoing industrial training easier and efficient not only for UTHM but also for those considering designing a similar online system in managing industrial training assessment.

The questions generated are dynamic which means the university industrial training coordinator can edit the questions without need to change at the coding phase.

User-friendly System

ITAS is easy to use by all relevant parties even by those with minimal computer knowledge. The use of icons make good targets; sized large enough to be easily touched in a finger-operated user interface.

Ability to Calculate Automatically the Marks

ITAS uses radio buttons to allow both university and industrial supervisors to mark relevant score and the final marks are calculated automatically as a mean to reduce human error.

Ability to Analyse the Data Stored

ITAS allows university industrial training coordinator to view the number of users, the progress of assessment made by university and industrial supervisors, number of students and industrial supervisors answer the surveys, etc.

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Pintors (Location Identifier created to identify location of scholarly research project online)

Mohd Hanifa, R. (2018). Industrial Training Assessment System. Bangi, Selangor, Malaysia: MTUN Research Repository. QOI: 60.43650.2018-MTUNConnect.N095705
QOI (Quick Object Identifier created to identify a piece of scholarly research project online)
Visit QOI International Consortium.

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