The Readiness of Academic Staff at South Valley University to Develop and Implement E-learning

1. The Readiness of Academic Staff at South Valley University to Develop and Implement E-learning استعداد أعضاء هيئة التدريس بجامعةجنوب الواديلتطوير و استخدام التعلم الإلكتروني Alaa Sadik Ph.D., University of Hull, UK Faculty of Education in Qena

2. Purposes of the Study • Provide a general overview of staff competencies, experience and attitudes towards e-learning. • Consider how support systems and procedures for staff can be further developed.

3. Purposes of the Study • Inform the e-learning components of the academic strategy for the University. • Investigate the perceived training needs of staff and their particular areas of difficulty as well as interest in the use of e-learning.

4. The Dimensions to be Evaluated Competencies • A related set of knowledge and skills that enable a person to effectively perform the activities of a given occupation in such a way that meets the standards expected in a particular profession. • Pedagogical and technical e-learning competencies are a set of teaching and technology standards that define proficiency in using e-learning in teaching.

5. E-learning Competencies The competent e-learning developer or facilitator must be able to cope with the following three questions: 1. Which learning principles are to be used? 2. How is the teaching to be organised? 3. Which ICT genres are going to work with? Anderson (1999)

6. E-learning Competencies Andresen’s FIKS-model

7. E-learning Competencies Types of competencies 1. Basic technology operation. 2. Professional use of technology tools. 3. Social, ethical and human issues. 4. Application of technology in learning. Teacher Technology Competency Committee (1998)

8. The Dimensions to be Evaluated Experience • Direct participation in events or knowledge, skill or practice derived from direct observation of or observation in event. • Often measured in terms of amount and frequency of technology use, training attended, etc.

9. The Dimensions to be Evaluated Attitudes • Used to understand and predict people’s reaction to an object or change and how their behaviour can be influenced. • Significant determinants of behaviour that may influence their success in high-levels of using technology in instruction.

10. Research Questions Do SVU staff have: 1. e-learning competencies required to develop and implement e-learning in their teaching? 2. sufficient experience to develop and implement e-learning in their teaching? 3. positive attitudes toward the development and evaluation of e-learning?

11. Research Questions 4. What are the variables influencing SVU staff’s current and future implementation of e-learning? 5. What content is appropriate and favoured to be included in future e-learning training programs for SVU staff?

12. Instrument and Sampling The development process involved four stages: 1. The delineation of relevant domains for the constructs of interest. 2. Survey assembly and pilot testing. 3. Large-scale field-testing. 4. The validation of instrument scores.

13. Instrument and Sampling 1. The delineation of relevant domains for the constructs of interest • Review of the literature and similar instruments on various aspects of e-learning. • The review revealed many aspects that feel within three domains.

14. Instrument and Sampling • Competencies Knowledge and skills that enable academics to effectively develop and implement e-learning approaches. • Experience Prior and present practices regarding e-learning. • Attitudes Feelings and opinion about the development and implementation of e-learning in university teaching.

15. Instrument and Sampling 2. Survey assembly and pilot testing • Develop from the information in phase one a multi-dimensional rating scale. • Domains were examined for comprehensiveness and items were added or deleted to ensure appropriate and logical coverage. • A panel of five content experts were consulted to review and reflect on these dimensions and items. • The resulting dimensions and items were pilot tested with as random sample of faculty members to comment on the importance, clarity and wording of items.

16. Instrument and Sampling 3. Large-scale field-testing • The readiness rating scale was field-tested with a sample of 233 academic staffat SVU. • Careful attention was given to potential differences between those academics who responded to the survey and the population of academies at the University.

17. Instrument and Sampling 4. The validation of instrument scores The psychometric characteristics of the instrument were investigated through the use of exploratory and confirmatory factor analyses and Cronbach's alpha.

20. The Psychometric Characteristics Competencies sub-scale - 19 items were retained with two independent constructs. - Two interpretable factors named pedagogical competencies (12 items) and technical competencies (7 items) were suggested accounted for 59.61% of variance. - The eigenvalues of the two factors from principle component analysis were larger than one: 6.38 and 4.95. - Cronbach’s coefficient : 0.92 for the entire scale and 0.89 and 0.87 for the two sub-scales.

21. Competencies sub-scale

22. The Psychometric Characteristics Experience sub-scale - 15 items were retained with three independent constructs. - Three interpretable factors named ‘frequency of use’ (4 items), ‘training received’ (3 items) and ‘practice’ (8 items) were suggested accounted for 58.83% of variance. - The eigenvalues of the three factors from principle component analysis were larger than one: 4.20, 2.84 and 1.73. - Cronbach’s coefficient : 0.85 for the entire scale and 0.84, 0.46 and 0.86 for the three sub-scales.

23. Experience sub-scale

24. The Psychometric Characteristics Attitude sub-scale - 32 items were retained with two independent constructs. - Four interpretable factors named ‘anxiety’(5 items), ‘confidence’ (7 items), ‘liking’ (7 items) and ‘importance’ (13 items) were suggested accounted for 48.83% of variance. - The eigenvalues of the four factors from principle component analysis were larger than one: 3.09, 3.84, 3.36 and 5.33. - Cronbach’s coefficient : 0.80 for the entire scale and 0.74, 0.83, 0.59 and 0.86 for the four sub-scales.

25. Attitude sub-scale

26. Attitude sub-scale

27. Interrelations and convergent validity Each sub-scale (competencies, experience and attitudes) correlates significantly with the other two sub-scales and the entire scale. In addition, significant relationships were observed between each sub-scale and its constructs.

28. Results Demographic profile

29. Results E-learning competencies • 28% of academics rated themselves as good or excellent in e-learning competencies. 16.6 % are technically competent(M=0.99). 88 % are pedagogically competent(M=2.11).

30. Results E-learning competencies • Academics scored significantly higher on the pedagogical competencies than the technical competencies. • Academics who have 5 to 10 years of teaching experience reported highest technical and pedagogical competencies than those who have less than 5 years or more than 10 years. • Assistant professors tend to have statistically higher scores on the technical competencies sub-scales than professors.

31. Results E-learning experience • 7.3% have adequate experience in e-learning. 25% frequently use e-learning technologies (M=1.21). 0.8% received in-service training in e-learning (M=0.53). 5.8% practised or implemented e-learning in their university teaching(M=0.008).

32. Results E-learning experience • Academics scored significantly highest on the frequency of use sub-scale and lowest in the training received sub-scale. • No significant differences exist among academics from different faculities or with different ranks in terms of frequency of use nor training received.

33. Results Attitudes to e-learning • 93.8%have strong positive attitudes towards e-learning. 89% less anxious 80% confident. 39% like e-learning. 86% appreciate its importance.

34. Results Attitudes to e-learning • Academics scored significantly lowest in the liking sub-scale. • Academics with 5-10 years of teaching experience are less anxious than those with more than 10 years of teaching experience.

35. Results Barriers to the development and implementation of e-learning • Lack of training 55% • Lack of knowledge 49% • Lack of time 35.2% • Lack the technical support 32% • Lack of equipment 26% • Heavy workload 15.9% • Other reasons 5%

36. Discussion and Conclusions • These universities should find the instrument developed in this study useful. • There is a need to staff training in using e-learning development software, managing e-courses, integrating Web resources and interacting with students via the Web. • A careful blend of intensive training, guidance and counselling is necessary to dispel academics’ fears. • E-learning knowledge, skills and experience are vital and influence the future acceptance and implementation of e-learning.

37. Implications and Recommendations • Research-based interventions are needed to help these academics to overcome barriers to use and development e-learning and keep up with technological development. • The University must plan to have competent computer academic staff to support e-learning development and use. • Academics need to adjust their attitudes to teach online, understand what qualifications are needed and know what they can do ensure the quality of e-learning.

38. Implications and Recommendations • The University should ensure adequate in-service training programmes and enhance academics' abilities to use information and communication technologies. • Faculties should be equipped with state-of-the-art hardware and software to encourage staff to learn and use e-learning approaches in their teaching. • There is a growing need for collaboration and sharing of experience and expertise in e-learning adoption among staff from different faculties in the university.

39. Thank you Alaa Sadik alaasadik@hotmail.com www.freewebs.com/alaasadik