Higher Education Information Management Sudhanshu Bhushan 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 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 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 nonrecurring) 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 student’s enrolment, course details and foreign students studying in Colleges. • 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/Institutions 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. 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. Process of Collection of Data • MHRD - the ES forms are distributed to all State/UT’s Directorate of Education. • State/UT’s 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. 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. 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. 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. 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. 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. 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. 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. • 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. 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. • • • • • • 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 university’s 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 policymakers 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. 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) Thank you 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