Grading of ITIs New Data Driven Grading Methodology

Skill Info



  1. Methodology for Grading of ITIs: 

    New Data Driven Grading Methodology(DDGM)




    Introduction

    The Ministry of Skill Development and Entrepreneurship (MSDE) launched the grading system in 2017 for assessing the performance and quality of training being provided by Industrial Training Institutes (ITIs). The phase-II grading was launched in 2019, where external agencies verified the data to assign tentative grades to ITIs. The grading system is essential for ensuring the quality of training imparted to students in ITIs. In this blog, we will discuss the methodology for grading ITIs and its implementation.


    Objective of Grading

    The objective of grading is to assess the quality of training provided by ITIs. It helps in identifying the strengths and weaknesses of the ITIs, enabling them to improve their performance. The grading system encourages healthy competition among the ITIs, which ultimately leads to providing better quality training to the students.


    Table of Contents:

    • Objective of the Grading
    • Background of Previous Grading System
    • Need for New Grading Methodology
    • New Methodology for Grading of ITIs
    • Detailed Grading Framework for Grading Year 2023

    Objective of the Grading:


    The Industrial Training Institutes (ITIs) grading is a method to assess the performance and 

    quality of training being provided by these institutes.


    Background of Previous Grading System:


    The Ministry of Skill Development and Entrepreneurship (MSDE) launched the first grading system (Phase-1) in January 2017, followed by Phase-II grading in 2019. The grading methodology involved field visits and data validation by an external agency for grading ITIs. The final grade was published on the DGT portal, and a total of 13480 ITIs in the country were graded.


    Need for New Grading Methodology:


    As per the order MSDE-35(4)/MIS ITT grading, phase-2/2018-NPIU dated November 29, 2019, the current grading are valid through the academic year 2022-2023. Hence, a new grading system is needed, and the MSDE decided to develop a new methodology for grading ITIs using the parameters/information available on the NCVTMIS portal.


    New Methodology for Grading of ITIs:


    To assign new grading value to ITIs, the grading committee proposed a new Data Driven Grading Methodology (DDGM) for grading all existing ITIs using the parameters/information available on the DGT MIS portal. The following parameters are identified for grading ITIs on a scale of 0 to 10:


    The following parameters are identified for grading ITIs on a scale of 0 to 10:

    • Admission % (Average of the maximum admission of 2 years out of last 3 years)
    • Female Participation (Average of the maximum admission of 2 years out of last 3 years)
    • Trade Diversity (New emerging Trades /Non-Engineering Trades)
    • Pass% (Average of the maximum % of 2 years out of last 3 years Against the trainees Hall Tickets generated)
    • CBT examination participation (% Hall Tickets generated against Admitted trainees; Average of the maximum of 2 years out of last 3 years)
    • Average marks % of all the trainees appeared in CBT exam
    • DST enrolled trainees against total admitted trainees
    • SC/ST/PwD enrolled trainees against total admitted trainees


    Detailed Grading Framework for Grading Year 2023



            

    Sl. No.

    Parameters

    Weight age

    Parameter Scale

    0

    1

    2

    3

    4

    5

    1

    Admission       %   (Average        of the

    35

    <=20%

    >20-

    >30-

    50-60

    60-

    > 70%

     

    maximum of 2 years out of last 3 years) 2018-19, 2019-20, 2022-23)

     

     

    30%

    50%

    %

    70%

     

    2

    Female Participation (Average of

    5

    0

    0-5%

    5-10%

    10-15%

    15-

    >20%

     

    the maximum of 2 years out of last

     

     

     

     

     

    20%

     

     

    3 years) 2018-19, 2019-20, 2022­23)

     

     

     

     

     

     

     

    3

    Trade         Diversity     (New        Age

    5

    -

    Any 1

    -

    Any 2

    -

    All 3

     

    Course/Non-Engineering

     

     

    type of

     

    type of

     

    type of

     

    Trade/Engineering Trade)

     

     

    course

     

    courses

     

    courses

    4

    Pass% (Average of the maximum %

    35

    <40

    >=40-

    >=50-

    >60-70

    >70-

    >80%

     

    of 2 years out of last 3 years Against the trainees HT generated) 2017-18, 2018-19, 2019-20

     

     

    50%

    60%

    %

    80%

     

    5

    CBT examination participation (%

    5

    0-20%

    >=20-

    >=40-

    >=60-

    >=70-

    >80%

     

    HT                     generated      against     Admitted

    trainees Average of the maximum of

     

     

    40%

    60%

    70%

    80%

     

     

    2 years out of last 3 years)

     

     

     

     

     

     

     

    6

    Average marks % of last year

    5

    0-40%

    >40-

    >50-60

    >60-70

    >70-90

    >90%

     

    trainees

     

     

    50%

     

     

     

     

    7

    DST enrolled trainees against total

    5

    0

    >0-5%

    >=5-

    >=10-

    >=15-

    >=20%

     

    admitted trainees

     

     

     

    10%

    15%

    20%

     

    8

    SC/ST/PwD      enrolled    trainees

    5

    >0-5%

    >=5-

    >=10-

    >=20-

    >=30-

    >=40%

     

    against total admitted trainees

     

     

    10%

    20

    30%

    40%

     








    Conclusion 


    In conclusion, the new Data Driven Grading Methodology (DDGM) proposed for grading ITIs using parameters/information available on the DGT MIS portal is expected to provide a more accurate and data-driven assessment of the performance and quality of training being provided by ITIs. The methodology is expected to improve the overall quality of training being provided by ITIs in India.


    FAQ:

    • Q: What is the objective of ITI grading?
      A: The objective of ITI grading is to assess the performance and quality of training being provided by the Industrial Training institutes (ITIs).
    • Q: What is the background of the previous grading system?
      A: The Ministry of Skill Development and Entrepreneurship (MSDE) launched the first grading system in January 2017, followed by phase II grading in 2019. The methodology adopted for grading involved field visits and data validation by an external agency.
    • Q: Why is there a need for a new grading methodology?
      A: The validity of the current grading system will last through the academic year 2022-2023, so a new grading system is needed. As per the discussion held with Secretary MSDE, DG DGT it was decided to develop a new methodology for grading all existing ITIs using the parameters/information available on the NCVTMIS portal.
    • Q: What is the new methodology for grading ITIs?
      A: The new methodology for grading ITIs is the Data Driven Grading Methodology (DDGM), which uses the parameters/information available on the DGT MIS portal to grade ITIs on a scale of 0 to 10.
    • Q: What are the parameters used in the new grading methodology?
      A: The parameters used in the new grading methodology are admission %, female participation, trade diversity, pass%, CBT examination participation, average marks % of all the trainees appeared in CBT exam, DST enrolled trainees against total admitted trainees, and SC/ST/PwD enrolled trainees against total admitted trainees.




    Disclaimer:

    Disclaimer: The information provided in this blog is for general knowledge purposes only. The content is not intended to be a substitute for professional advice or guidance. Always seek the advice of a qualified expert in the relevant field with any questions you may have. The views and opinions expressed in this blog are those of the author and do not necessarily reflect the official policy or position of any agency or organization mentioned.





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