E-learning Quality Assurance Benchmarking in Higher Education

1. E-learning Quality Assurance Benchmarking in Higher Education Fatimah Alsaif Johann Bernoulli Institute of Mathematics & Computer Science University of Groningen Netherlands F.A.S.Alsaif@rug.nl ArockisamyClementking College of Computer Science King Khalid University Saudi Arabia cksami@kku.edu.sa

2. Overview • Scope • Introduction • Background of the Study • Existing Quality Assessment Approaches • Requirements of Benchmarking • Problem Statement and Possible Solutions • Existing Quality Frameworks Analysis • Discussion on Existing Quality Frameworks • Identification of Quality Indicators • Conclusion and Future Work

3. Scope • Identification of high priority quality indicators for smart learning systems through the analysis of the existing learning systems quality frameworks. • Identification • Analysis • Determination • Conversion and representation • Conclusion

4. Scope • Identification of exiting quality frameworks. • Analysis of the existing technology-based learning systems for the identification of its major indicators. • Determination of indicators. • Conversion and representation of the indicators and its models. • Conclusion of major and minor influencing learning system factors.

5. Background of the Study • The changing landscapes and its responsibility in all domains • The challenge in the re-assessing of the methods and processes utilized to assure quality and gear towards excellence or smart models • Standard processes for quality assurance as providing measures for system-improvement • Rapid growth of education programs • Appreciation of smart system in the community

6. Background of the Study • Designing a model for quality smart system in the learning domain • Identification of the measurable indicators required to form a smart model • Review of the literature and comparisons between existing recommendations and practices to assist to view expected smart model

7. Background of the Study • The outcome of this study • Identify the indicators for different quality frameworks. • Prove that quality score-carded model possesses most of the relevant features for enabling decisions. • Assess and develop a model for the overall quality of a smart education system.

8. Identification of Existing frame works • The educational– learning system domain was selected as per researcher previous work and interest. • Based on the literature, numerous points of view are available for assessing the quality of education. • Recommendations and different approaches discovered in the literature suggest guidelines to assess programs and their quality components for educational system.

9. Identification of Existing frame works • The quality process assessed through: • Benchmarking • Specification of standards • Benchmarking is the process of comparing the performance and outcomes against what was achieved by selected other programmes operating in a similar field and comparative practices.

10. Analysis • Much literature is reviewed and major four benchmarking are considered towards the analysis in addition to the 13 frame-works.

11. The reviewed frameworks to demonstrate the processes available to specify and assess quality are as follows: Analysis

12. Analysis

13. Analysis • In reality the process of benchmarking is not easy to apply in most educational domain. Mckinnon et al. (2000) • University life learning and teaching is the most difficult area to benchmark, since it is common at universities that the approach to teaching and the courses are not standard. • Courses, even professional and specialized courses leading to registration, are rarely directly comparable.

14. Analysis • Benchmarking became an increasingly and widely-utilized method to implement quality- assurance and promotion. • Benchmarking allows the choice of changes that help to improve of quality the identification of application of areas for improvement. • Moriarty (2011) illustrates this method as an example-driven technological process that works within an organization with the targets of purposely changing an existing state of affairs into an improved state of affairs.

15. Analysis • Moriarty and Smallman (2009) have further illustrated it as follows: The position of benchmarking lies between the existing states of affairs and the states of affairs sought after and participates to the transformation process that achieves these enhancements. • The European Centre for Strategic Management of Universities (ESMU) defines it as follows: Benchmarking is an internal organizational process which seeks to enhance the performance of the organization by learning about potential enhancements of its main and/or backing processes through looking at these processes in other, preferable-performing organizations.

16. Discussion on Analysis • In the literature, the major issue in assessing the quality of any information system is to determine the standards by which the quality is defined and measured. • Challenge is to transfer from traditional education systems to those which include or are entirely based on e-learning approaches. • Seddon and Yip (1992) proposed that a variety of measures of effectiveness are required for miscellaneous systems.

17. Discussion on Analysis • In 2006, Levy argued that there were no comprehensive studies exploring the actual effectiveness of e-learning systems. • Barr and Tagg (1995) argued that whenever web technology is utilized in educational environments, it is essential to think about its influence on students, faculty members, courses and institutions.

18. Selected Frameworks

19. Determination of Indicators

20. Conversion and Representation of Indicators • There are many similarities between the thirteen frameworks and studies demonstrated in this review of quality assessment for online education programs.

21. Conversion and Representation of Indicators • Main indicators to take in consideration: • The support of institution • The improvement of the course • The procedure of teaching and learning • The structure of the course • The support of student • The support of faculty and the assessment • Evaluation in assuming the quality of online learning

22. Conclusion • The evaluation of quality education is more important. • Programs keep on growing and students everywhere in the world search for quality in their degree programs. • Quality education truly matters as the eventual influence is to our students. • Higher education is in need of a new way to classify and evaluate quality within education programs. • Education online is inherently different from traditional education, therefore it requires specific benchmarks and benchmarking processes.

23. Conclusion • Business and industry have made use of quality assurance processes for numerous years to identify and quantify quality enhancement and develop strategic planning and decision-making. • Quality assessment processes are being utilized in higher education. • After looking through the literature, itis clear that the Quality Score-carded model succeeds to obtain all of the relevant features present in formerly-suggested frameworks.

24. Future Direction • In our next steps, we plan to develop a new framework based on the strengths of all surveyed ones, and in particular, the Quality Score-carded model. • The previous study indicates that the e-learning systems could be measured using the existing frameworks. For future work, the sub- indicators from these frameworks will be identified to create a Smart Learning Model.