(CSFs) of technical education - Inderscience Online

Int. J. Productivity and Quality Management, Vol. 11, No. 1, 2013

Development and validation of an instrument for measuring critical success factors (CSFs) of technical education – a TQM approach Anil R. Sahu* Department of Mechanical Engineering, B.D. College of Engineering, Sewagram-442001, India E-mail: [email protected] *Corresponding author

Rashmi R. Shrivastava G.H. Raisoni College of Engineering, Nagpur-440016, India E-mail: [email protected]

R.L. Shrivastava Department of Mechanical and Production Engineering, Yeshwantrao Chavan College of Engineering, Wanadongri, Nagpur-441 110, India E-mail: [email protected] Abstract: Like other systems, technical education system is also dynamic in nature. It faces many challenges in responding to societal, technological and economic changes in the local and global environment. The issue today is to ensure quality education delivery system for technical education. The literature shows that many educational institutes have initiated efforts for quality improvements. However, there is neither sufficient literature (regarding identification of critical factors responsible for excellence in technical education), nor appropriate measures (research instruments) to determine those factors. In this context it is necessary to identify key critical success factors (CSFs), which may be given special attention for ensuring desired excellence in technical education. Though different authors have proposed different ways to address the quality related issues in various domains, on the basis of critical review of literature, this study proposes use of a new research instrument for identification of critical success factors by using total quality management (TQM) as the base. The developed instrument was assessed for its reliability and validity using standard methods. The results indicated that the developed instrument was reliable and valid, which can be used to identify the critical success factors important for excellence in technical education. Keywords: technical education; excellence; total quality management; TQM; reliability; validity; critical success factors; CSFs; quality management.

Copyright © 2013 Inderscience Enterprises Ltd.

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30

A.R. Sahu et al. Reference to this paper should be made as follows: Sahu, A.R., Shrivastava, R.R. and Shrivastava, R.L. (2013) ‘Development and validation of an instrument for measuring critical success factors (CSFs) of technical education – a TQM approach’, Int. J. Productivity and Quality Management, Vol. 11, No. 1, pp.29–56. Biographical notes: Anil R. Sahu is currently working as an Associate Professor at Department of Mechanical Engineering, Bapurao Deshmukh College of Engineering, Sevagram, Wardha, India. He has more than 22 years of teaching experience to undergraduate and post graduate students of engineering and management. He has contributed more than 14 research papers in various conference of national and international level. Rashmi R. Shrivastava is currently working as an Associate Professor of Applied Chemistry at G.H. Raisoni College of Engineering, Nagpur, India. She has more than 20 years of teaching, training, consultancy, research and administrative experience. She has contributed more than 30 papers at national/international level at various journals, seminars and conferences. Her areas of interest are green chemistry, sustainable development, teachinglearning paedogogy, and re-manufacturing and quality/productivity improvement. She is keenly involved with activities leading to technical education excellence. R.L. Shrivastava is currently working as a Professor of Mechanical Engineering at Yeshwantrao Chavan College of Engineering, Nagpur, India. He has more than 25 years of teaching, training, consultancy, research and administrative experience. He is a Certified Master Black Belt in Six Sigma and a Qualified Lead Assessor for ISO 9000 QMS. He is also an Examiner for IMC Ramkrishna Bajaj National Quality Award (IMC RMNQA). He has guided several organisations on quality and productivity improvement. He has contributed more than 100 papers at national/international level at various journals, seminars and conferences. He has chaired sessions at international/national conferences and delivered invited talks. He is also reviewing research papers for some journals.

1

Introduction

Today, the rapid scientific and technological advancement has generated a communications revolution that is pervading every region of the world and creating a global information society. Indeed, the new information and communication technologies have dramatically affected the education delivery systems and changed the way people learn in many parts of the world, and India is no exception. Furthermore, there is a growing consciousness that the present pattern of technical education delivery system cannot be sustained for an indefinite period. A shift towards a developmental paradigm that holds sustainability as its central requirement is therefore imperative for the new millennium. Hence, in order to succeed in providing individuals with the right skills to keep the companies in different societies competitive, technical education institutes need to improve upon the level of excellence. This requires commitment from all the stakeholders, such as students, management and faculty (of technical education institutes), etc. Though there are many aspects that need to be given due importance for

Development and validation of an instrument

31

improving the technical education delivery system, the fundamental aspect of quality, i.e., integral to all the aspect warrants more attention. Quality management is a part of management aimed at achieving quality goals through planning, monitoring, assuring and improving quality. Involving all members of the organisation brings us closer to total quality control (total quality management, TQM). Efficient TQM system in organisation can facilitate quickly challenge in word market. The key points for the improvement of education are scientific and technological development, social changes and organisational changes. Education efficiency and success do not depend just on quantity but as well on quality. The quality indicator systems of education, as well as the criteria related to the quality indicators help technical institutes to identify the crucial areas of their activities – their own advantages, disadvantages and development opportunities. Although many approaches exist for quality management, arguably, TQM is the most comprehensive approach for quality management for all the sectors, with technical education being no exception. A large amount of literature has been written about how quality should be managed in an organisation for example, Mallesham (2005) advocated the quality of technical education will be better with highly qualified and motivated staff and equally motivated wards. While, Deshmukh, (2006) elaborated the usefulness of TQM, QFD and Six-Sigma concept for improving the quality of technical education. However, Mersha et al. (2009), in their study found out that TQM implementation was perceived to have a positive impact on several important dimensions of performance in the service agency. Similarly, Pandi (2009) and Singh and Khanduja (2010) described that by practicing TQM in an educational institution we not only fulfill customer requirements but also, thereby we can delight them. Wali and Boujelbene (2010) reported that, the TQM implementation has positive and significant impact on operating performance. Hong and Huang (2011), in their findings found out that TQM has not only a significant impact on product quality but also on product innovation. Recently, Ahuja (2011) emphasises upon adoption of concurrent quality drives for technical education system. On the basis of literature, the TQM approach has been identified as the most appropriate approach for dealing with quality management issues in technical education system. Hence, on the backdrop of above information, an attempt has been made to develop an instrument which will not only helpful in measuring critical success factors (CSFs) of technical education system but also its impact on excellence of technical education (especially for technical education institutes). These measures are then tested for reliability and validity using perceptual data collected from total sample of 241 stakeholders (principal, dean, professor, associate professor, lecturer, students, parents and manufacturing firm) of technical education system from all over India.

2

Literature review

In this section, a comprehensive set of critical factors of quality technical education are proposed. CSFs are those, which are essential for successful implementation of any

32

A.R. Sahu et al.

quality improvement initiative. Alternatively, it can be said that the CSFs are the select few (attributes) over arching requirements that must be present for an organisation to be able to attain its vision, and to be guided towards its vision (Wali et al., 2003). The identification of such factors will encourage, their consideration when organisations are developing an appropriate implementation plan. These CSFs are derived through a process that involved identification and synthesis of those critical requirements for excellence in technical education that have been prescribed by eminent quality practitioners and academics. The process included an exhaustive literature review, which is elaborated hereunder. The literature is abundant with studies that addressed identification of CSFs for the performance measurement in the manufacturing organisation, however, there have been only a few systematic attempts in the literature to identify and organise various CSFs for technical education system. Therefore, in this study the literature review focused only on those articles, books, or studies that will address quality management in technical education especially to engineering education. Past studies identified different CSFs, notable amongst them are top management leadership, process management, infrastructure, administration and employee training and involvement (Natrajan, 2000; Reddy et al., 2004; Sahney et al., 2004; Seetharaman et al., 2006) for successful implementation of TQM. While, infrastructure, transport and communication facilities and system approach (Joglekar et al., 1999; Kulkarni et al., 1999; Sirvanci, 2004), Satisfaction level of students (Dulawat, 2005; Pandi and Rao, 2007; Sakthivel et al., 2005), ISO certifications (Paul et al., 1998; Natrajan, 2000; Sakthivel et al., 2005; Singh and Feng, 2006; Pandi and Rao, 2007; Venkatraman, 2007). Table 1 summarises the recommendations of CSFs by some of the authors regarding the quality management roadmap implementation. The literatures also focus different methodology which has been developed by different researchers for quality improvement in technical education like, Ahuja et al. (2004) proposed the remedial action. While, Reddy et al. (2004) developed Analytic Hierarchy Process (AHP), Kulkarni (2005) Graph theory and matrix approach, (Chen et al., 2006) balanced scorecard, productivity measurement model (Singh and Bansal, 2007), Smith (2008) advocated the use of Malcolm Baldridge National Quality Award (MBNQA), (Pandi et al., 2009) Integrated Total Quality Management (ITQM), (Simon Wu et al., 2010) creative total quality management (CTQM) and a holistic quality management (HQM) model, and (Raj and Rajesh, 2011) proposed interpretive structural model (ISM). It is apparent from the literature that there is no consensus amongst researchers regarding the Critical successes factors (CSFs) and on methodology which will improve the efficiency (Quality) of technical education system. Therefore in this study, In addition to above reported CSFs in literature (Table 2) total 72 items were identified as possible attributes that have influence on the quality management in technical education domain further, these items/attributes were used as a basis for delineating the final research instrument (questionnaire) that can be used for identifying CSFs (critical input factors) for effective quality management in technical education.

X X X X X

Naik (2006)

Pandi and Rao (2007)

Sakthivel (2007)

Singh et al. (2007)

Prasad (2009)

Deshmukh (2006)

X

X

X

X

X

X

Chen et al. (2006)

X

X

X

X

Infrastructure and facility in technical institutes

Mallesham (2005)

Sahney et al. (2004)

Reddy et al. (2004)

Natrajan (2000)

Roles and responsibilities of senior management

X

X

X

X

X

X

Training development and placement

X

X

X

X

Academic aspects

X

X

Research and development and consultancy

X

X

X

X

X

X

X

Administration

X

X

X

Promoting institute’s initiatives

Table 1

Authors/critical factors

Development and validation of an instrument 33

List of CSFs as recommended by various authors for quality improvement in technical education

Good library (availability of books, periodicals, scientific journals), good ambience, well equipped laboratories, clean wash rooms, canteen, hostel accommodation, play ground, transportation, medical and internet facility, psychological counseling, computer centre, workshop Communication and technical writing skills, industrial training, trainings for knowledge beyond syllabus, quality management training (SS, TQM Lean QFD, etc.), information and interaction with potential employers, tracking placements of alumni, feedback from the employers Up to date syllabus, monitoring teaching aptitude and quality of faculty, competent teaching methodology, student – teacher ratio, qualification of non teaching staff Incentives for R&D, grants/funding for research projects, consultancy work

Infrastructure in technical institutes

Training development and placement

Academic aspects

Research and development and consultancy

Administration

Promoting institute’s initiatives

2

3

4

5

6

7

Institute’s initiatives publicity, instillation of awards for staff members

Planning and monitoring, facilitation of various demands of teachers and students, recruitment of competent staff, communication with stakeholders, inspection and maintenance of institute’s facilities, inspection of teaching/evaluating process, signing MOU’s with MNC’s and other institutes, organising lectures of experts, organising conference/seminars/workshops/training, etc., analysis regarding performance of students, teachers, etc., implementation of policies delineated by management and statutory bodies

Commitment, vision, resource allocation, stakeholder participation, performance-based promotion, proactive management, social accountability, ISO certification

Roles and responsibilities of senior management

Item

1

Critical factors

Table 2

Sr. no.

34 A.R. Sahu et al.

List of Items as CSFs that influence TQM implementation

Development and validation of an instrument Figure 1

Research instrument development process

Step 1

Literature review

Step 2

Identification of CSFs and performance measurement items of quality management related to technical education

Step 3

Initial selection of measurement items

Step 4

Pre-testing of instrument (pilot study)

Step 5

Finalization of the measurement items were done on the backdrop of Step 4.

Step 6

Data collection

Step 7

Check for internal consistency (i.e., for reliability)

Step 8

Check for item to scale

Step 9

Check for validity of scale

Step 10

Measurement instrument

35

No

No

No

Delete items that will improve internal consistency

Drop the items that correlated highly with more than one scale

36

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A.R. Sahu et al.

Construction of instrument

Though development of research instrument is neither simple nor straightforward, instrumentation techniques are available that help us to construct research instruments that constitutes acceptable levels of reliability and validity. The process of developing the research instrument in this study was based on generally accepted psychometric principles of instrument design, and was carried out according to the following steps as shown in Figure 1. Steps 1 and 2 of the process, the literature review and the identification of CSFs of quality management, have been discussed above. In Step 3, we finalised the initial selection of measurement items based on literature review, by personal experience and according to opinion of experts in education field. In Step 4, pre-testing of instrument have been done to test the degree of understanding of the meaning of the questions, difficulty in understanding the question by the respondents, to improve its content, format and sequence. Discussions were also done with experts of the technical education. And in Step 5, finalisation of the measurement items were done on the backdrop of Step 4. In Step 6, the research instrument has been send to 500 different stakeholders of technical education system like dean, principal, professors, students, parents, and industry representatives for collection of data and they were asked to respond to the questionnaire (Appendix) according to how they will perceived about various items that indicated CSFs of technical education on a five-point interval scale. In Steps 7 and 8, internal consistency analysis (i.e., reliability analysis) and detailed item analysis on collected data of 241 respondents were performed. In the final step, i.e., in Step 9 the validity of the instrument is tested (Content validity, criteria related validity, construct validity and convergent validity).

4

Sample size and response rate

In the present research, a sample size of 500 (consisting above mentioned stakeholders of technical education) was chosen for the final survey. Though data collection through questionnaire method has several advantages but it also have so many disadvantages like Low rate of return of the duly filled in questionnaires; bias due to no-response is often indeterminate; It can be used only when respondents are educated and cooperating; The control over questionnaire may be lost once it is sent; There is also the possibility of ambiguous replies or omission of replies altogether to certain questions; interpretation of omissions is difficult and last but not least this method is likely to be the slowest of all. To overcome all above difficulties following care has been taken to ensure good response. The questionnaire was mailed along with prepaid envelop in order to facilitate quick reply. Close friends and associates were identified in each area and the questionnaire was explained to them. They were entrusted with the responsibility to answer the queries of the respondents and also to do follow up. To start with, the rate of return of the complete questionnaire was very fast, but when the rate of flow slowed down, reminders were sent to them for an early reply. Telephone calls and e-mail were also made besides personal contacts with the organisation. The hectic efforts and the support of the friends and institutes generated a good response representing 48% response rate which was quite encouraging. Table 3 gives details about the profile of the respondents.

08.30 04.15 100

20 20 10 241

Parents

Industry

Other (w/s, non teaching, office staff)

34 23 144 201

Government

NIT

Unaided

Total

Category of the institute

Total

08.30

50

Students

100

71.64

11.44

16.92

20.75

16.60

20.75

50 40

12.45

Assistant professor

30

Professor

04.15

04.15

Percent %

Associate professor

10 10

Principal

Frequency

Dean /management

Position or title

72 114 201

More than 2,000 Total

15

-

201

1,001–15,000

501to 1,000

Less than 500

Total no. of students enrolled

Total

42

42

10–15 Less than 10

35

82

201

99

14

28

34

26

Frequency

15–20years

More than 20 years

Age of the institute

Total

Central

East

South

West

North

Location of institute

Respondent information

100

56.72

35.82

07.46

00

100

20.90

20.90

17.40

40.80

100

49.25

06.97

13.93

16.92

12.94

Percent %

Table 3

Respondent information


Profile of the respondents

38

5

A.R. Sahu et al.

Analysis of data

5.1 Reliability of empirical instrument The responses obtained to questionnaire were tabulated, fed into a computer and analysed for internal consistency analysis (i.e., for reliability). The data was analysed using SPSS package. The reliability analysis of a questionnaire determines its ability to yield consistent results. Reliability was operational zed as internal consistency, which is the degree of inter correlation among the item which comprise a scale (Flynn et al., 1994). Internal consistency can be established using a reliability coefficient such as Cronbach’s alpha. Alpha is the average of the correlation coefficient of each item with each other item (Nunally, 1978). The Cronbach’s alpha of questionnaire with 72 attributes/items was found to be 0.9596, implies that the questionnaire is reliable. Also the reliability of individual scales was tested found to be varied 0.7401 to 0.8892. Since the reliability coefficients of all the individual scales are above 0.7 considered adequate (Nunnally, 1967), all the developed scales indicated acceptable reliability (Table 4). Table 4 Factor no.

Extracted factors and reliability test Factors based on survey result

Cronbach’s α

KMO

Percentage variance explained by these factors (cumulative)

Fac-1

Infrastructure development (ID)

.8892

.862

Fac-2

Capacity building initiatives (CBI)

.8764

.869

Fac-3

Top management involvement (TM)

.7985

.845

Fac-4

Networking and collaboration (NC)

.8017

.686

Fac-5

Innovation efforts (IE)

.7973

.739

55.786

Fac-6

Continual improvement (CI)

.7924

.669

58.876

Fac-7

Quality culture creation (QCC)

.7401

.792

For total 72 items

0.95

.787

37.081 42.142 48.079 52.228

61.817

5.2 Factor analysis The collected data was analysed (using SPSS 18.0 software) by following factor analysis procedure as suggested by Nunnally (1967). Factor Analysis is a general name denoting a class of procedure primarily used for data reduction and summarisation. In research survey, there may be a large number of variables, most of them are correlated and which must be reduced to a manageable level and interpretable. The first step, prior to running the factor analysis, the Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy and the Bartlett’s test of sphericity were conducted. The KMO value was found to be 0.787 (Table 5) which is sufficiently large (>0.5), which indicated sample adequacy for factor analysis, and supporting the appropriateness of using factor analysis to explore the


39

underlying attributes. The Bartlett’s test of sphericity was highly significant (p < 0.000) significance value of Bartlett’s test is 0.000, rejecting the null hypothesis that the 72 important attributes are uncorrelated in the population. Table 5

Bartlett’s test

Bartlett’s test of sphericity

Approx. chi-square

14,272.441

df

2,556

Sig.

.000

5.3 Communalities The communalities of the data is reported greater than 0.6 for all the items of the scale. Communality referred to as the percentage of total variance explained by the common factors. Communalities represent the proportion of the variance in the original variables that is accounted for by the factor solution. The factor solution should explain at least half of each original variable’s variance, so the communality value for each variable should be 0.60 or higher. This term may be interpreted as a measure of ‘uniqueness’. A low communalities figure indicates that the variable is statistically independent and cannot be combined with other variables. In our instrument the communalities value is more the 0.70 (Table 6). Hence we can conclude that all the initial items selected which are responsible for TQM in technical education are dependent with each other and focusing on common issue. Table 6

Communalities

Attributes

Initial

Extraction

Well defined mission, vision and value system

1.000

.772

Management commitment

1.000

.689

well defined organisational structure and governance system

1.000

.745

Well defined long and short term goals

1.000

.687

Open and transparent system

1.000

.648

Well defined responsibility and authority matrix

1.000

.674

Deployment mechanism for policies

1.000

.749

Grievance redressal system

1.000

.667

Budgeting and Resource allocation

1.000

.744

Collaboration of institute/linkages/networking

1.000

.708

Fair and transparent appraisal systems

1.000

.783

Well defined rules, regulations and operating procedures

1.000

.751

Fair compensation package

1.000

.660

Congenial work environment

1.000

.805

Scholarships for meritorious students

1.000

.772

Scholarships for economically backward students

1.000

.817

Discipline promotion

1.000

.787

Social responsibility initiatives

1.000

.703

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A.R. Sahu et al.

Table 6

Communalities (continued)

Attributes

Initial

Extraction

Scholarships for economically backward students Discipline promotion Social responsibility initiatives Proactive management Good learning resource availability, accessibility Library automation, digital library Good ambiance for effective teaching learning process Adequate space provision Uninterrupted power supply Hygiene and maintenance in the institute Quality canteen provision Adequate and comfortable hostel accommodation on campus Residential campus Sports and recreation facilities Green/ecofriendly campus

1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000

.817 .787 .703 .645 .794 .774 .782 .704 .831 .804 .699 .691 .735 .766 .766 .751 .755 .766 .741 .801 .780 .706 .744 .788 .730 .755 .728 .800 .784 .783 .761 .638 .781 .711 .732 .726 .773 .771 .772 .819 .783

24 × 7 high speed internet access Bank and postal facility on the campus Medical facility (doctor/ambulance) Cooperative store facility Psychological counselling Active alumni association Input quality of students Stakeholder needs assessment Stakeholder feedback mechanism Installing corrective action mechanism for feedback Student performance monitoring system Training and placement network Entrepreneurship motivation Quality management training (Six Sigma, TQM, Lean, QFD, etc.) Patent information and promotion Regular conduct of co-curricular and extracurricular activities Institute industry interaction promotion Academic planning and monitoring Continuous evaluation and feed back system Teaching beyond syllabus Quality faculty Student faculty ratio Aptitude and availability of faculty Performance awards to students Performance awards to faculty Non-teaching staff skill

Development and validation of an instrument Table 6

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Communalities (continued)

Attributes

Initial

Extraction

Research and development Consultancy and testing focus Focus of corporate trainings Institution website (effective coverage and updating) Classroom teaching learning monitoring Institute brand image creation mechanism Extension activities focus Faculty participation Curriculum design and revision Faculty development programmes Soft skill trainings High end technical training Faculty exchange programme (national and international level) Student exchange programme (national and international level) PhD programme Age of institute Extraction method: principal component analysis

1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000

.772 .837 .792 .717 .845 .756 .821 .783 .755 .811 .764 .745 .842 .793 .808 .835

5.4 Total variance explained extracted factors Total 19 factors with eigenvalue above 1.0 were obtained after factor analysing the data using principle component and varimax rotation with Kaiser Normalisation. On the basis of criterion suggested by Cattell (1966) (scree plot) (Figure 2), seven factors (which accumulated 45 items) were selected to measure CSFs of technical education. These seven extracted factors have 61.817% of the total variance (Table 4). Figure 2

Scree plot of CSFs attributes (see online version for colours)

0.582 0.572 0.537 0.45

Adequate space provision


Quality canteen provision

Adequate and comfortable hostel accommodation on campus

0.424

Research and development

Faculty exchange programme (national and international level)

0.67

0.478

Soft skill trainings

0.672

0.492

Training and placement network

Well defined organisational structure and governance system

0.523

Performance awards to faculty

3


0.64 0.558

Stakeholder feedback mechanism

0.676

0.582

Cooperative store facility

0.736

0.644

Residential campus

Installing corrective action mechanism for feedback

0.673

Hygiene and maintenance in the institute

High end technical training

0.682

Bank and postal facility on the campus

0.798

0.706

Student performance monitoring system

0.726

Green/ecofriendly campus

2

0.448

4

5

0.438

6

7

Table 7

Sports and recreation facilities

1

42 A.R. Sahu et al.

Varimax factor rotated component matrix (CSFs item loading)

0.405

0.453

0.476


0.457

0.524


Good learning resource availability, accessibility

0.548


0.538

Faculty development programmes

0.738

0.576

Good ambiance for effective teaching learning process

7


0.658 0.534

0.699

0.509

Curriculum design and revision

Continuous evaluation and feed back system

0.514

6

Academic planning and monitoring

0.655

Institute brand image creation mechanism

0.47


Faculty participation

0.524

Non-teaching staff skill

0.798

0.74

5

Extension activities focus

0.743

0.557


Consultancy and testing focus

0.565

4

Focus of corporate trainings

0.604

Well defined long and short term goals

3

Budgeting and resource allocation

2 0.635

1

Table 7



Varimax factor rotated component matrix (CSFs item loading) (continued)

44

A.R. Sahu et al.

5.5 Factor loadings for TQM factors Items loaded under different factor were carried out using principal component method with varimax rotation, the items with factor loading 0.4 or greater were considered significant in this analysis (Table 7).

5.6 Interpretation of TQM factors and its naming To measure CSFs of technical education, following seven factors are considered. Factor 1, accounting for 27.081% of common variance, is named as ‘infrastructure development’ which accounts for all those items that form unique resources for a technical institutes. This include sports and recreation facilities, green/eco-friendly campus, bank and postal facility in the campus, hygiene and maintenance in the institute, residential campus, cooperative store facility, adequate space provision, scholarships for meritorious students, quality canteen provision, and adequate and comfortable hostel accommodation on campus such things generally not thought off very primary for the technical institutes but for total quality practice all the above mention supportive items are very important for performance/excellence of technical education These resources create asymmetry and differentiating advantages with respect to competitive institutes. The second factor, ‘capacity building initiatives’, accounts for 6.061% of common variance and includes such elements as student performance monitoring system, high end technical training, installing corrective action mechanism for feedback, stakeholder feedback mechanism, performance awards to faculty, training and placement network, training and placement network, soft skill trainings, research and development and faculty exchange programme at national or international level. By observing all the items of capacity building initiatives it is clearly implicit that merely class room teaching and finishing regular curriculum is not sufficient for technical institute to be withstand in this competitive environments but it is also required to providing knowledge beyond the syllabus and training students as per the need of stakeholders. The third factor, ‘top management involvement ‘, explaining 4.937% of the common variance, signify an important of role of top management and it includes management commitment, well defined long and short term goals, Open and transparent system, budgeting and resource allocation, and well defined organisational structure and governance system. The fourth factor, ‘Networking and collaboration’, accounting for 4.149% of the common variance has loading of such items as consultancy and testing, corporate trainings, collaboration of institute/linkages/networking and also on non-teaching staff skill. In present scenario for over all development of any students the exposes to real life training is very much essential and it is only possible when they get corporate training and able to solve their problems. The fifth factor, ‘innovation efforts’, accounting for 3.559% of the common variance has loading of such items as extension activities focus, faculty participation, institute brand image creation mechanism, and curriculum design and revision.


45

The sixth factor, ‘continual improvement’, accounting for 3.090% of the common variance has loading of such items as academic planning and monitoring, continuous evaluation and feed back system, good ambiance for effective teaching learning process, and faculty development programmes. The seventh factor, ‘quality culture creation’, accounting for 2.941% of the common variance has loading of such items as fair compensation package, fair and transparent appraisal systems, congenial work environment, grievance redressal system and good learning resource availability, accessibility.

5.7 Detailed item analysis Nunnaly (1988) developed a method to evaluate the assignment of items to scales. The method considers the correlation of each item with each scale. Specifically the item-score to scale score correlation are used to determine if an item belongs to the scale as assigned. If an item does not correlate highly with any of the scales, it is eliminated. Table 8 reports the correlation matrix for the seven scales. Item 1 has correlations of .755, .377, .355, .348, .298, .328, and .291 with the seven scales (corresponding to seven factors). Since scale 1 represents the average score obtained from items 29, 30, 32, 25, 28, 34, 23, 15, 26, and 27; the high correlation between scale 1 and item number 29 was expected. In addition, since item 29 showed relatively smaller correlations with the other scales it was concluded that it had been assigned appropriately to scale 1. As seen in Table 8, all items have high correlations with the scales to which they were assigned relative to all other scales. Hence it was concluded that all items in this instrument had been appropriately assigned to respective scales.

5.8 Validity of research instrument 5.8.1 Content validity Since, the contents of instrument (critical factors) were selected on the basis of extensive review of related literature regarding the implementation of TQM in technical education system, it may be concluded that the research instrument satisfied the content validity.

5.8.2 Criteria validity The criterion-related validity of the instrument developed for measurement of excellence in technical education was evaluated by examining the correlation coefficients between the seven CSFs. The positive and significant correlation coefficients obtained for all the variables (Table 9) indicated that the measures have a high degree of criterion-related validity when taken together (Saravanan and Rao, 2008).






Well defined organisational structure and governance system

42

67

57

69

6

3



27



26

55


15

39


23

Installing corrective action mechanisms for feedback


34

40

Residential campus

28


Hygiene and maintenance in the Institute

25



32

68

Green/eco-friendly campus

.319

.204

.357

.192

.262

.278

.503

.401

.314

.339

.188

.638

.710

.647

.662

.739

.686

.756

.763

.726

.755

Factor 1

.287

.360

.660

.622

.686

.701

.719

.739

.733

.791

.740

.332

.372

.144

.297

.276

.297

.318

.309

.442

.377

Factor 2

.739

.696

.275

.467

.352

.334

.285

.367

.350

.277

.243

.283

.278

0.111

.194

.247

.244

.209

.375

.258

.355

Factor 3

.166

.164

.368

.373

.443

.242

.481

.354

.269

.386

.162

.479

.336

.296

.184

.352

.460

.285

.350

.323

.348

Factor 4

.273

.216

.453

.388

.386

.250

.423

.421

.306

.348

.289

.324

.205

0.105

.175

.295

.274

.219

.338

.191

.298

Factor 5

.250

.294

.359

.302

.622

.407

.436

.433

.443

.456

.338

.377

.323

.307

.369

.370

.355

.210

.336

.265

.328

Factor 6

.334

.415

.345

.526

.339

.414

.374

.358

.386

.331

.300

.337

.340

.245

.310

.280

.234

.271

.350

.258

.291

Factor 7

Table 8

41


30

Attributes

29

Item no.

46 A.R. Sahu et al.

Items to scale loaded under different factor


Well defined long and short term goals.




Non teaching staff skill


Extension activates focus


institute brand mage creation mechanism



Continuous evaluation and feedback system

Good ambiance for effective teaching learning process.


Far compensation package

Far and transparent appraisal systems


Grievances redressal system


9

4

5

59

58

56

10

63

64

62

65

48

49

22

66

13

11

14

8

20

Attributes

Management commitments

2

Item no.

.469

.229

.271

.297

.176

.255

.447

.402

.344

.239

.319

.196

.323

.411

.452

.337

.372

.264

.350

.526

.320

.379

.334

.291

.681

.345

.420

.398

.602

.335

.373

.334

.270

.494

.473

.288

.389

.334

.291

.292

Factor 2

.282

.530

.306

.479

.317

.367

.403

.349

.327

.329

.346

.346

.315

.445

.271

.329

.285

.714

.704

.692

.701

Factor 3

.448

.304

.319

.355

.274

.391

.268

.290

.464

.324

.423

.476

.387

.708

.723

.900

.823

.424

.315

.325

.357

Factor 4

.416

.293

.181

.452

.336

.490

.333

.415

.281

.757

.782

.800

.819

.379

.348

.479

.404

.403

.264

.329

.297

Factor 5

.528

.380

.193

.331

.206

.782

.741

.813

.806

.509

.349

.379

.320

.354

.271

.394

.402

.296

.362

.443

.321

Factor 6

.680

.705

.691

.707

.725

.364

.440

.223

.456

.377

.476

.331

.307

.341

.380

.463

.342

.363

.371

.328

.517

Factor 7

Table 8

.200

.191

Factor 1


Items to scale loaded under different factor (continued)

48

A.R. Sahu et al.

Table 9

Bivariate correlations among the seven scales i/p factor1

i/p factor2

i/p factor3

i/p factor4

i/p factor5

i/p factor6

i/p factor1

1

i/p factor2

.447(**)

1

i/p factor3

.290(**)

.428(**)

1

i/p factor4

.398(**)

.436(**)

.358(**)

1

i/p factor5

.365(**)

.319(**)

.279(**)

.439(**)

1

i/p factor6

.331(**)

.506(**)

.333(**)

.338(**)

.395(**)

1

i/p factor7

.292(**)

.419(**)

.447(**)

.308(**)

.404(**)

.355(**)

i/p factor7

1

Note: **Correlation is significant at the 0.01 level (2-tailed).

5.8.3 Construct validity The construct validity measures the extent to which the items in a scale all measure the same construct. It was established through the use of principal component factor analysis. The factor matrices showed that they were uni-factorial with eigenvalues greater than the accepted criterion of 1.0 (Table 10). Moreover, the eigenvalues for the extracted factors are greater than 2, show that they are consistently larger (eigenvalues represent the amount of variance explained by the factor, or relative importance of each factor in accounting for variance associated with the set of variables being analysed). As suggested by Saraph et al. (1989) and Badri et al. (1995) the results of this study indicated good construct validity for the developed scales. Table 10 Construct

Summary of separate factor matrices for each constructs (input factors) Item loading range for Factor 1

Eigenvalue

% Variance explained by Factor 1

0.659 to 0.800

3.889

55.551

0.608 to 0.804

4.564

50.716

0.687 to 0.745

3.011

50.180

0.709 to 0.895

2.511

62.787

0.757 to 0.819

2.500

62.490

0.740 to 0.82

2.474

61.848

0.662 to 0.736

2.467

49.341

5.8.4 Convergent validity Convergent validity is the extent to which varying approaches to construct measurement yield the same results (Ahire et al., 1996). Convergent validity of scale was checked using the Bentler-Bonett coefficient or normed fit index (NFI) (Bentler and Bonett,


49

1980). Since the NFI values for all the CSF measurement scales (Table 11) were >0.95, they demonstrated strong convergent validity. Table 11

Bentler-Bonett coefficient or NFI for input scales

Sr no.

Scales

NFI

Infrastructure development (ID)

0.999

2

Capacity building initiatives (CBI)

0.998

3

Top management involvement (TMI)

0.994

4

Networking and collaboration (NC)

0.997

5

Innovation efforts (IE)

0.998

1

6

Continual improvement (CI)

0.995

7

Quality culture creation (QCC)

0.996

6

Conclusions

The present globalisation of technical education and related activities has resulted in search for new and innovative methods for managing quality issues in technical institutes. The consistent pressure of quality for achieving customer, stakeholder satisfaction are showing sustainable increase and increasingly, the local technical institutes have to compete with their international peers for technical and long term goals fulfillment. The growing importance of quality management and quality assurance internationalisation in the technical education sector has led to use of many quality methodologies (TQM, QFD, etc.) for technical institutes, which are often followed in industrial sector. As a response to these trends, technical institutes need to successfully deploy these quality methodologies and related improvement initiatives. However, many technical institutes (especially that are in developing world) are still lagging behind their western and more developed competitors in terms of their strategic commitment to quality improvement. Different approaches and methods of quality in technical education have been suggested by different authors. No previously published research has developed a comprehensive set of requirement or critical factors that spans the literature and all the literature provided very little or no information how to measure any of the proposed critical factors of quality in technical education. In this paper an attempt has been made to explore CSFs responsible for initiating quality management in technical education and author have offers a set of 07 CSFs of quality management in technical education by performing factor analysis. The measure proposed were empirically-based and shown to be reliable and valid. The reliability coefficient (alpha) of the initial selected 72 items measure 0.95 which is above 0.7 are considered adequate also the communality value for each variable is greater than 0.60 interpreted as a measure of ‘uniqueness’. . Systematic literature review and the comprehensive pre-testing helped insure that the measures have content, criteria, construct and convergent validity indicates that technical institute can used this instrument to evaluate the perception of quality education in their organisation. Hence the study results indicated that seven scales, such as Infrastructure Development, Capacity Building Initiatives, Top Management Involvement, Networking and Collaboration, Innovation Efforts, Continual Improvement and Quality Culture Creation are the most

50

A.R. Sahu et al.

important CSFs to be explored so as to achieve excellence in technical education. The proposed research instrument is expected to provide momentum for further research aimed at gaining a more comprehensive understanding of the quality related issues and implementation of TQM for achieving excellence in technical education.

Acknowledgements The authors hereby acknowledge the reviewers of this paper for sparing their valuable time and reviewing our paper and gave important suggestions to improve its quality. Special thanks also due to publisher of this journal who principally accepted our paper for publication.

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Appendix Questionnaire The initial 72 items were used for measuring the critical factors of quality management and respondent were asked to rate their opinion on 1–5 point rating scale for each of the statement. 1 No importance

2

3

Low importance

Medium importance

4

5

High importance

Very high importance

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Sr. no.

Attribute

1

Well defined mission, vision and value system

2


3

well defined organisational structure and governance system

4

Well defined long and short term goals.

5


6


7

Deployment mechanism for policies

8


9


10


11


12

Well defined rules, regulations and operating procedures

13


14


15


16

Scholarships for economically backward students

17

Discipline promotion

18

Social responsibility initiatives

19

Proactive management

20


21

Library automation, digital library

22

Good ambiance for effective teaching learning process.

23


24

Uninterrupted power supply

25

Hygiene and maintenance in the institute

26


27


28

Residential campus

29


Response

Notes: **Published extra ordinary achievements of staff and students, product development, innovation, merit position, college unique policies, fair admission and selection process, etc. ***Information regarding advance course, conference, symposium, etc.


55

(continued) Sr. no.

Attribute

30

Green/ecofriendly campus

31

24 × 7 high speed internet access

32


33

Medical facility (doctor/ambulance)

34


35

Psychological counseling

36

Active alumni association

37

Input quality of students

38

Stakeholder needs assessment

39


40

Installing corrective action mechanism for feedback

41


42


43

Entrepreneurship motivation

44

Quality management training (Six Sigma, TQM, Lean, QFD, etc.)

45

Patent information and promotion

46

Regular conduct of co-curricular and extracurricular activities

47

Institute industry interaction promotion

48


49

Continuous evaluation and feed back system

50

Teaching beyond syllabus

51

Quality faculty

52

Student faculty ratio

53

Aptitude and availability of faculty

54

Performance awards to students

55


56

Non-teaching staff skill

57


Response


56

A.R. Sahu et al.

(continued) Sr. no.

Attribute

58


59


60

Institution website (effective coverage and updating)

61

Classroom teaching learning monitoring

62

Institute brand image creation mechanism**

63

Extension activities focus***

64


65


66


67


68


69


70

Student exchange programme (national and international level)

71

PhD programme

72

Age of institute

Response
