CEC Faculty Proceedings, Presentations, Speeches and Lectures


Measuring technological e-learning readiness and effectiveness in the online learning environment

Event Location / Date(s)

Orlando, FL / October 10-12, 2012

Document Type

Conference Proceeding

Presentation Date


Conference Name / Publication Title

18th Annual Sloan-C International Conference on Online Learning



E-learning readiness (e-readiness) is a critical component in evaluating the effectiveness of online course delivery at the institutional level and the instructor level. To make cost-effective decisions about technology acquisition and training to support online course delivery across an institution or a consortium of institutions, institutions need to know if technology integration is at a sufficient level of perceived quality and satisfaction among online instructors. Online instructors need to gauge their technology knowledge and skills levels to determine if they are keeping current with technology trends. Online instructors need to be able to assess meaningfully the effectiveness of technology integration in online courses and what technological barriers instructors face in delivering online courses.

We propose that a critical factor of e-learning success is the e-readiness of the online instructor. According to Penna and Stara (2008), e-readiness is quantified as a single numeric measure that explains the overall success of e-learning, where a low score signifies a technology deficiency determined by corresponding low scores in one or more dimensions. Knowing the e-readiness score can help to identify a learning institution's strengths and weaknesses in technology acquisition and training to inform policy decisions, to position the institution technologically in the competitive global market, and to apply limited resources wisely across institutional boundaries. This information can be used also to address instructors' barriers to technology use.

The conference call indicates that "Ongoing issues around assessment, access, and quality all present questions that require thoughtful decision making. How will we confront these challenges?" In this presentation, we will engage the audience by asking, “Online instructors: are you "e-learning systems ready"? Is your own e-learning systems readiness score in-line with your institution's e-ready score?"


Instructors face pressures by administration, online learners and even colleagues to integrate various technology tools into their online teaching. Many instructors have not incorporated the technology as anticipated, citing adoption and integration of the technology into their teaching practices as challenging. Other issues include inadequate hardware, software, and facilities, and problems of connectivity and reliability apart from their hesitance in accepting the OLE as a valid learning medium. Widespread technology use in online learning environments (OLEs) is also hindered by online instructors' lack of awareness or lack of use of the various technology tools that can help the instructor improve engagement and learning. Online users are said to be e-ready if they had high scores in four readiness scales: academic, technical, lifestyle, and learning readiness (Holsapple & Lee-Post, 2006). A low level of e-readiness among online instructors could unknowingly impact educational institutions' successful delivery of their online programs.


A study at the University of West Indies aimed at deriving an e-readiness score of online instructors and of the institutional level. The study also assessed whether e-readiness affected instructors' perceived effectiveness of technology integration in online courses in examining three information systems stages proposed by DeLone and McLean (2004) in the e-learning environment: design, delivery, and net outcomes.

A survey was conducted in the fall of 2011 to gather data on online instructor e-readiness and instructors perceptions of six aspects of the learning environment based on the IS Success Model. The six variables examined were System Quality (stability, speed and responsiveness of the technology), Service Quality (technology training to provide adequate learner-instructor interactions), Information Quality (accuracy, clarity and formats required for fast retrieval), System Use (extent to which the technology tools are actually used), User Satisfaction (online instructors' level of satisfaction when accessing and interacting in the OLE), and Net Benefits (positive or negative aspects of online instructors' experiences with adoption, integration and dependence on technology for online teaching). The survey also captured feedback from online instructors about their level of e-readiness, including their technical competence (technical literacy, and type of computer used in the OLE), lifestyle aptitude (communication patterns and online habits), learning preference toward the OLE (learning styles and values), and academic preparedness (years teaching and prior online experience).

The online instructors for the sample (n=113) were chosen from among 144 online courses offered by the Open Campus of the University of West Indies. Courses are managed by one course coordinator and at least ten e-tutors. Aggregate ratings were used to determine the e-readiness scores of the university and the online instructors. Wang, Wang and Shee (2007), stated that a rating of four or higher on a five-point Likert-scale for each item indicates an acceptable level of e-learning systems success. Regression analysis was used to investigate relationships between instructors' e-readiness predicting each of the six variables.


Survey results revealed that the e-learning systems success score of the university was 4.07 out of 5 or 81.4%. The e-readiness score of online instructors was 4.53 or 90.6%. Linear regression analysis indicated that e-readiness was a significant and positive predictor of the system design, system delivery, and system outcome stages (proposed by DeLone and McLean model) and their associated dimensions. Multiple linear regression analysis showed that the constructs together accounted for 42.2% of the variance in Net Benefits. Of the six predictors in the model, user satisfaction provided the largest unique contribution when the other predictors were held constant. The results of this study should assist in the understanding of the technology barriers that persist, that universities engaged in online course delivery will need to address when implementing plans that require instructors to integrate various technology tools in online courses.

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