Higher Education Information Management

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Higher Education Information Management

• Sudhanshu Bhushan

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Steps in Information Management

• (i) agency of collection
• (ii) data capture format and coverage of data
• (iii) process of collection
• (iv) compilation of data
• (v) tabulation of data
• (vi) analysis and presentation of information
• (vii) publication of information

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MHRD

• ES (1) C, Numerical Data of Institutions for
  Higher Education it covers enrolment on
  general, Professional and (other) higher
  education streams and also enrolment by type of
  institutions
• ES (II) C, Financial Data of Institutions for
  Higher Education data includes recurring and
  non-recurring income and expenditure procured by
  institution of higher education managed by
  Universities, Local Bodies, Central/State
  Governments and Private(Unaided) bodies.
• ES (III) C, Examination Results (Higher
  Education)- Data must include examination
  results of boys and girls appearing and passing
  out in General education, and Professional and
  other education, which includes both degrees and
  diplomas.
• ES (IV) C, Numerical Data of Institution for
  Higher Education- it covers number of
  institutions in the State, enrolment by the type
  of institution, number of teachers, type of
  management in running the institution for SC and
  ST

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University Grants Commission

• Format A (University Teaching Departments) deals
  with information about the University/institutions
  on students enrolment (general education,
  professional courses and other educational
  courses), details of courses offered, gender-wise
  students enrolment in general and professional
  courses designation wise details of teaching
  staff, information about non-teaching staff,
  number of students passed and appeared in
  examination and income and expenditure (recurring
  and non-recurring) incurred.
• Format B-AC (Affiliated Colleges) deals with
  courses offered by the Colleges, designation-wise
  and subject-wise teaching staff, subject-wise
  break up of students enrolment for both regular
  and self-financing courses, drop-out in students
  enrolment, course details and foreign students
  studying in Colleges.

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• Format- Library deals with library Statistics
  of the University Teaching Departments and
  University Colleges
• Format- Exam deals with examination results of
  Universities
• Format I/II Doctorate Degrees Awarded
• Format Directory of professors
• Format IS-Finance statistical information on
  financial parameters of the Institute of Higher
  Education
• Format IS- Foreign students No of foreign
  students on rolls in UTD/UC/CC and affiliated
  Colleges (AC)
• Format List of Colleges List of Colleges
  recognised by University, list of colleges
  disaffiliated by university and district-wise
  Colleges
• Format- Vacant Positions in Universities/Instituti
  ons

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Census

• The Census definition of higher education
  embraces all types of education public as well
  as private, distant, certificate, diploma and
  degree. College education includes graduate and
  above. Vocational education includes all
  technical and professional courses degree,
  diploma and certificate. The relevant tables
  pertaining to population attending educational
  institutions by type are published in C Series
  Social and Cultural Statistics.

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NSS

• NSS provide data on higher education, at times
  directly through dedicated reports on education
  (42nd and 52nd rounds) and also through rounds on
  employment and unemployment 38th (1983), 43rd
  (1987-88), 50th (1993-94), 55th (1999-2000)
  rounds that provide educational profile and
  enrolment in higher education. The 55th and 61st
  rounds provide information both on educational
  attainment and current attendance. All the rounds
  are not strictly comparable.

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Process of Collection of Data

• MHRD - the ES forms are distributed to all
  State/UTs Directorate of Education.
• State/UTs Directorate of Education collects
  information from recognised institutions of
  higher education through another format called CF
  -1 and CF -2
• In the case of UGC the collection of data from
  higher education institutions is made directly
  through specified formats made available to these
  institutions.

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Publication of Information

• MHRD publishes very selective information on
  enrolment. Gender wise and aggregate, SC ST
  enrolment for all states refers to Ph D, MA, M
  Sc., M Com., BA, B Sc., B Com., Technical,
  Medical, Teachers Training College and other.
• Information also pertains to number of teachers
  and PTR in higher education. Besides information
  on foreign students studying in India and Indian
  students studying in foreign countries are
  presented.
• All the information from data capture format is
  not presented. The intake in higher education,
  year-wise enrolment at graduation and post
  graduation is not given. As a result the
  transition of students and internal efficiency is
  not known.

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Publication of Information contd.

• UGC publishes annual report and provides state
  level information on stage wise enrolment in
  university departments/university colleges and
  affiliated colleges. It also provides faculty
  wise enrolment at the aggregate level only. It
  gives information on the distribution of teaching
  staff by designation in university
  departments/university colleges and affiliated
  colleges. Further the number of doctorates
  awarded is recorded in the annual report of UGC.

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Provisional Nature of SES Data

• It is so because in most of the cases the data
  that is supposed to reach the Statistical
  Division of the Department of Higher education,
  MHRD do not reach on time and in some cases it
  does not reach at all.

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Some Questions

• what is the source of collecting information
  contained in SES? Is the MHRD compelled to use
  other sources of information? What those sources
  of information are? In any case non compliance of
  data is a serious issue that impedes gravely the
  higher education policy, planning and management.

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Changing Definition and Methodology in
Calculating Ratios

• It is remarkable to note that The Open and
  Distance Learning was not included in total
  higher education till SES 2003-04. In SES 2004-05
  it was included in others and finally included in
  total higher education enrolment. The others as
  a category show 3 million enrolments out of 11.7
  million enrolments in 2004-05. It shows now an
  inflated GER of 9.7 in 2004-05. M.B.A enrolment
  is not included at all on ground of lack of
  availability of data. Thus curious reasons lead
  to changes in the concept of higher education.
  Besides, the methodology in calculating ratios in
  the SES has also not been clearly specified and
  educational indicators also keep changing
  according to the need.

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University Grants Commission

• Although UGC claims to receive 60 70 data
  directly from Universities and Colleges every
  year on the aforesaid formats, the other problems
  arising out of manual reporting, namely, delay in
  collection, vulnerability and inaccuracy of data
  hold good in the case of UGC as well. There are
  some defaulting Universities/ Institutions that
  is reluctant to share information in spite of the
  fact that it is mandatory for Universities to
  furnish information. Thus non compliance of
  information holds good in case of UGC, too. It
  was reported that obsolete facilities and
  shortage of technically skilled computer
  maintenance operator is the cause of delay. The
  problem, therefore, is that UGC even though
  collects lot of data, it finds very difficult to
  provide all tabulated information annually. It
  finally publishes very narrow set of information.

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Dilemmas of Unreliable Data on 11th Plan

• On the basis of SES the enrolment in higher
  education worked out to 91.4 lakhs (86 lakhs in
  General and 5.3 lakhs in Technical) in 2001. The
  corresponding figure for NSS and Census worked
  out to 115.3 lakhs (88.5 lakhs in general and
  27.1 lakhs in technical/vocational) and 160.9
  lakhs (144.3 lakhs in general and 16.6 lakhs in
  technical, degree, diploma and certificate) in
  2001. Such variation in the size of enrolment
  from the three sources poses problems in
  enrolment projection.

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• The important point to note is that inadequate
  and non comparable data base creates difficulty
  in planning. There were various other issues as
  well. The non availability of information on
  enrolment in terms of management posed another
  problem of estimating the plan for expansion.

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Features of an Efficient Data Management System

• Online Data Management and Information System
• Data Capture Format
• simple
• all the parameters to be included
• . Codes, wherever possible, should be provided so
  that maximum number of tables may be generated
  with the given command.
• As far as possible the institutions should be
  supplied the data capture format directly to fill
  the information. For example colleges should fill
  the DCF and the authentication of the data should
  be done by the university. After the data is
  authenticated and information is submitted to the
  central agency, the data should be secured and no
  alteration should be possible in the data.
• DCF should define the terms used in the format
  clearly.
• Training to Fill the DCF
• To manage the data efficiently, it is necessary
  that DCF be filled without any ambiguity.
• At the level of university the training should be
  provided to all the persons who are in charge of
  data in respective colleges or university
  departments.
• Periodic workshops should be conducted to redress
  any problems encountered in the management of
  data.

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The revamping of higher education management
system

• shift from manual to online data management
  through electronic data capture format.
• There shall be a nodal agency at the center which
  will be responsible to design the DCF and the
  format will be downloaded by the institution of
  higher education.
• Nodal agency shall be responsible for providing
  any support to the university with respect to the
  data capture format. Nodal agency will receive
  the authenticated DCF from the university
• and will be responsible for publication of report
  containing all the information - nation level,
  state level and university level reports will be
  generated.
• As the universities shall be the main data
  collection center, it is necessary that
  universitys statistical wing is fully
  computerized.
• The maladies of higher education information
  system can be best addressed if as nodal agency a
  National Information Centre for Higher Education
  can be created. It would not only help in
  integrating data from multiple sources but would
  also provide state policymakers and analysts
  timely and accurate data and information that are
  useful in making sound higher education policy
  decisions. The National Information Centre can be
  also useful to provide contextual information,
  for each measure there can be links for
  additional information. Such solution is already
  available in some developed countries like U.S.A.
  The Centre will be user-friendly but to avoid
  misuse of data and information its access should
  be restricted by membership. All institutions,
  state agencies of higher education and State and
  central level policy-makers should be eligible to
  become members. Such visions can be only made
  practicable when required funding is available to
  develop the infrastructure and maintain its
  sustainability and long-term operation.

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International Standard Classification of
Education (ISCED 1997)

• 4. Post Secondary Non Tertiary-6 months to two
  year duration
• 5.First stage of Tertiary Education
• 5A Theoretical, intended to provide qualification
  for entry into advanced research or profession
  with high skill requirement, year duration min.3
  years
• 5B more practical/technical/occupation specific,
  year duration min.2 years
• 6. Second stage of Tertiary Education (leading to
  advanced research qualification)

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• Thank
• you

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Output Indicators

• Access Participation- gender, social, muslim,
  PH levels of tertiary education, course and
  faculty wise, management, district, state and
  university wise
• Net Intake as proportion of Eligibles
• Net Intake as proportion of population of
  entrance age
• Entry Ratio as proportion of
• Gross Enrolment Ratio
• Gross Graduation Ratio
• Gender parity
• Pass percentage
• Drop out
• Transition rate
• Mobility of foreign students