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Acceptance and Usability of OER in Indian Higher Education: An Investigation Using UTAUT Model Cover

Acceptance and Usability of OER in Indian Higher Education: An Investigation Using UTAUT Model

Open Praxis
Volume 10 (2018): Issue 1
By:   
Open Access
|Jan 2018
Figures & tables

Figures & Tables

Table 1

OER initiatives in India

OER initiativesWebsite
CSIR explorations- Open Access Repository of Indian theseshttp://eprints.csirexplorations.com/
Digital library of India-digital collection of freely accessible rare books collected from different libraries of Indiahttp://www.dli.ernet.in/
Indian National, Digital library in Engineering, sciences, and technology (INDEST)-Consortium for e resources of engineering and technological institutionshttp://paniit.iitd.ac.in/indest/
Kalasampada-Digital library: Resources of Indian cultural heritagehttp://ignca.nic.in/dgt_0001.htm
Vidyanidhi-Indian digital library of electronic theseshttp://eprints.uni-mysore.ac.in
Vigyan Prasar Digital Library- Digital library contains digital version of significant scientific workshttp://www.vigyanprasar.gov.in/digilib/
CEC Learning Object repository- The econtent and unique learning object repositories of providing higher educationhttp://cec.nic.in/e-content/Pages/default.aspx
E gyankosh- National depository of digital learning resourceshttp://egyankosh.ac.in/
National Programme on technology enhanced learning (NPTEL)- E learning platform for various courseshttps://onlinecourses.nptel.ac.in/explorer
Eklavya- E learning portalhttp://ekalavya.org/elearn/EkalavyaUser/Index.aspx
E-Grid- An online learning networkhttp://econtent.nielit.gov.in/rs/start.php
Brrihaspati- Open platform for learninghttp://digitallearning.eletsonline.com/2008/04/brihaspati-e-learning-platform/
ShodhGanga- Repository of PhD theseshttp://shodhganga.inflibnet.ac.in/
Figure 1

The UTAUT model

Source: Venkatesh et al. (2003)

Figure 2

Research model for acceptance and usability of OER in India

Adapted from: Mtebe and Raisamo (2014)

Table 2

UTAUT Constructs

Core constructsDefinition
Performance ExpectancyThe degree to which an individual believes that using the system will help him or attain gains in job performance.
Effort ExpectancyThe degree of ease associated with the use of the system.
Social InfluenceThe degree to which an individual perceives that important other believe he or she should use the new system.
Facilitating ConditionsThe degree to which an individual believes that an organizational and technical infrastructure exists to support use of the system.

[i] Source: Venkatesh et al. (2003) and Tan (2013)

Table 3

UTAUT Constructs and Hypotheses

Core ConstructsHypotheses
Performance Expectancy (PE)H1: PE has a positive impact on BI to use OER
Effort Expectancy (EE)H2: EE has a positive impact on BI to use OER
Social Influence (SI)H3: SI has a positive impact on BI to use OER
Facilitating Conditions (FC)H4: FC has a positive impact on BI to use OER
Table 4

The UTAUT Constructs and Items

ConstructItem CodeItem
Performance Expectancy (PE)PE1OER is useful in courses
PE2Using OER will enable to accomplices course development activities quickly
PE3Using OER would increase learning outcome of students
PE4OER use will allow to have access to more information
Effort Expectancy (EE)EE1Interaction with OER is clear
EE2Easy for using and integrating OER in courses
EE3OER is easy to use
EE4Learning to use OER is easy
Social Influence (SI)SI1People who influence my behaviour think that I should use OER
SI2People who are important think that I should use and integrate OER into my courses
SI3University staff are supportive in integrating OER in my course
SI4University will support the use of OER in teaching and learning
Facilitating Condition (FC)FC1I have the resources necessary to access OER
FC2I have the knowledge necessary to use and integrate OER in my course
FC3OER is similar to other course content I use for teaching
FC4Help will be available when I get problem in using and integrating OER in my course
Table 5

Descriptive analysis

  1. Type of University

    1. ODL – 6

      1. IGNOU, New Delhi, India

      2. BRAOU, Hyderabad, India

      3. VMOU, Kota, India

      4. YCMOU, Nashik, India

      5. NSOU, Kolkotta, India

      6. TNOU, Chennai, India

    2. Face to Face – 12

      1. Delhi University, Delhi, India

      2. JNU, New Delhi, India

      3. Ambedkar university, New Delhi, India

      4. Berhampur University, Odisha, India

      5. Utkal University, Bhubaneswar, India

      6. Sambalpur University, Sambalpur, India

      7. SNDT University, Mumbai, India

      8. Xaviers University, Bhubaneswar, India

      9. Mumbai University, Mumbai, India

      10. Jammu University, Jammu, India

      11. Andhra Unversity, Vizag, India

      12. TISS, Mumbai, India

    3. Dual – 4

      1. Calcutta University, Kolkotta, India

      2. Jamia Milia Islamia University, New Delhi, India

      3. University of Mysore, Mysore, India

      4. University of Pune, Pune, India

B. Response on Basics about OER
QuestionsYes (percentage)No (percentage)
Are you aware of the concept of OER?188 (93.1%)14 (6.9%)
Will you share your courses as OER?174 (86.1%)28 (13.9%)
Have you ever used OER?40 (19.8%)162 (80.2%)
Table 6

Pearson’s Correlations among four constructs and BI

BIPEEESIFC
BIPearson Correlation1.687**.698**.157*.460**
N202202202202202
PEPearson Correlation.687**1.844**.085.532**
N202202202202202
EEPearson Correlation.698**.844**1.226**.726**
N202202202202202
SIPearson Correlation.157*.085.226**1.236**
N202202202202202
FCPearson Correlation.460**.532**.726**.236**1
N202202202202202

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

* Correlation is significant at the 0.05 level (2-tailed)

Table 7

Model Summary

ModelRR SquareAdjusted R SquareStd. Error of the Estimate
1.723a.523.513.42721

a Predictors: (Constant), FC, SI, PE, EE

Table 8

Regression coefficients

ModelUnstandardized CoefficientsStandardized CoefficientstSig.
BStd. ErrorBeta
1(Constant)1.233.3343.698.000
PE.259.072.3423.581.000
EE.427.116.4343.682.000
SI.061.075.042.803.423
FC-.063.098-.047-.643.521

a Dependent Variable: BI

Table 9

Confirmation of Hypotheses

HypothesisRegression resultConfirmation
H1 : PEHighly significant (β = .342, P < .001)Yes
H2 : EEHighly significant (β = .434, P < .001)Yes
H3: SINot significant (β = .042, p < .423No
H4: FCNot significant (β = -.047, p < .521)No
Table 10

Not using OER: Key Factors

FactorsMajor Reasons as opined by respondents
a. Awareness and training

  • There is lack of awareness and also lack of knowledge and skill in how OER can be used-

  • Lot of respondents is of this view that they are not well trained to use OER.

  • Awareness is lacking on the learning and teaching side with regard to use of OER

  • Not techno- savvy, absence of proper guidance.

  • Perhaps because of problems related to access, attitude, linguistic barriers

  • Lack of knowledge of availability of such resources.

  • The faculty is not oriented about how to use OER in teaching.

  • Due to Non Awareness. The Culture of using need to be developed as it can disseminate education and promote collaborative learning

  • Lack of training to the teacher regarding OER technologies is the biggest hurdle

  • Ignorance about OER

  • Lack of awareness on uses rights (licensing) of OER material

b. Infrastructure

  • There are many factors like access, speed of Internet, economical conditions of the students, reach in rural area, etc.

  • Lack of resources / technology to access Internet.

  • Insufficient access to OER for the students.

  • Faculty does not have access to OER sites (e g, we do not have access to YouTube and FB from university). This brings in challenges in accessing

  • Shortage of multimedia based OER in Indian context,

  • Shortage of OER in vernacular languages of India

c. Policy, attitude and management

  • Lack of strong institutional policies

  • Now a days Internet in flooded with OER, there must be some mechanism to evaluate those OER and a comprehensive list can be prepared subject wise and updated regularly by bodies like UGC, AICTE, MCI, etc.

  • May be the faculty has doubts in the quality of OER as they are freely available. Also the authenticity of the material is under question.

  • Absence of proper database by Indian regulatory bodies is also a matter of concern shown by respondents problems related to access, attitude.

  • Even today, teachers and students do not use OER in regular teaching and learning. It is treated as supplementary resource. Also OER faces the problem of its authenticity. Since syllabus and evaluation pattern differs, OER available can not used as it is.

  • Cost of Use and technical illiteracy, non-support from the employer, mindset of teachers

d. Plagiarism and copyright

  • May be due to plagiarism- Respondents fear about plagiarism issues that may arise due to usage of OER.

  • Copy right issues

  • Fear because of no proper copyright guidelines.

  • Many academicians do not want to share their content or want to keep ownership with them

  • Apprehensions that the hard work of a person might just get copy pasted without his approval or knowledge.

DOI: https://doi.org/10.5944/openpraxis.10.1.623 | Journal eISSN: 2304-070X
Journal RSS Feed
Language: English
Page range: 55 - 65
Submitted on: Apr 13, 2017
Accepted on: Dec 6, 2017
Published on: Jan 1, 2018
Published by: International Council for Open and Distance Education (ICDE)
In partnership with: Paradigm Publishing Services
Keywords:
OER,
Usability,
Technology Acceptance,
UTAUT,
India

© 2018 Nayantara Padhi, published by International Council for Open and Distance Education (ICDE)
This work is licensed under the Creative Commons Attribution 4.0 License.

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