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Navigating the Transition to Digitized Teaching: Unisa Faculty ICT Experiences

Explore the ICT acceptance and experiences of Unisa staff in moving towards a digitized teaching environment. Understand the challenges and attitudes towards learning platforms/VLEs. Discover the impact of technology acceptance factors on intention to use. Gain insights into the drivers and moderating variables influencing staff behavior and attitudes.

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Navigating the Transition to Digitized Teaching: Unisa Faculty ICT Experiences

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  1. MOVING TOWARDS A MORE ‘DIGITISED’ TEACHING ENVIRONMENT: ICT ACCEPTANCE AND EXPERIENCES OF IODL STAFF Dion van Zyl & Hanlie Liebenberg

  2. Background • Revolution of ICT’s in HE over the past 20 years has contributed to the blurring of boundariesbetween distance and contact education. • Students increasingly gaining access to a range of ICTs for educational purposes. • Students’ digital fluency forms an integral part of their graduateness. • Research at Unisa over past 5 years focussed on understanding students’ ICT digital fluency/sophistication. • However, students’ ICT fluency potential can only be achieved if educators can equally deliver quality education within new ICT environments.

  3. Research Context In 2016 the Academic Planner of Unisa commissioned the Directorate Institutional Research to roll out a research project in support of understanding the transition academic staff are making to move to a more “digitised” teaching environment. To determine the ICT usage, attitudes and the challenges academic staff experience in the transitional move to a more “digitised” teaching environment… with a focus on learning platforms/VLE’s.

  4. Research aims …explore direct relationship between technology acceptance factors and intention to use amongst Unisa staff; …investigate the mediating effects of attitudes between ICT acceptance and intention to use; …investigate moderating effects of gender, age, post level and years of service on the relationship between ICT acceptance and intention to use.

  5. Conceptual model

  6. Design Survey amongst staff Sample n=310 Well balanced across colleges, academic levels and demographics

  7. What primary platform staff use… Pockets of ‘experimental’ Why not use ‘official’ platform solely? Need for ‘more’ than what is currently offered or not utlised to full potential…?

  8. Some challenges… Limitations in bandwidth capacity restricts uploading of videos, podcast, and various social media platforms to myUnisa. Blackboard and Google classroom expensive and not supported by ICT. Not an all-inclusive page that allows interaction, but it is rather fragmented; thus, students need to jump to various platforms, pages and resources to communicate and learn. myUnisa viewed as student administrative tool rather than learning platform.

  9. Use of secondary resources to enhance T&L

  10. Construct measures

  11. Performance expectancy= 81% Agree Top Box Score Degree to which users have confidence in the system that will help in attaining gains in job performance.

  12. Effort expectancy= 84% Agree Top Box Score Measures the ease associated with the use of the system.

  13. Social influence= 33% Top Box Score Agree Degree to which an individual perceives that important others believe he or she should use the new system.

  14. Facilitating conditions= 75% Agree Top Box Score Degree to which an individual believes that an organisational and technical infrastructure exists to support use of the system.

  15. Hedonic motivation= 56% Top Box Score Agree Refers to the fun or pleasure derived from using a technology.

  16. Habit= 55% Top Box Score Agree Habit is first “explained by prior behaviour” and secondly measured as the extent to which an “individual believes the behaviour to be automatic.”

  17. Behavioural intent= 87% Top Box Score Agree Defined as the intent to continue frequent use in the future.

  18. The model

  19. Drivers of use 0.286* 0.169* 0.332* Moderating variables

  20. Attitude as mediator

  21. Moderators

  22. Age L 0.456 M 0.528 Performance expectancy (gains in job performance) Behavioural intent H 0.600

  23. Age L 0.433 Behavioural intent M Habit 0.543 H 0.653

  24. Gender M 0.551 F 0.556 Performance expectancy (gains in job performance) M 0.656 Behavioural intent Effort expectancy (ease with the use) F 0.567 M 0.535 Habit F 0.558

  25. Post grade Grade L 0.705 M Effort expectancy (ease with the use) Behavioural intent 0.594 H 0.483

  26. What we take from this… Prior use of teaching platforms and tools plays a significant role in academics persisting in the use of these mediums. However, this is not necessarily based on the value of using VLEs but rather on the habit of using them. Risk of merely using teaching platforms based on habit do not open sufficient avenues for improvement…

  27. Academics need to broaden their VLE horizon – as with students they need to experience, engage and learn by using... but the institution need to support this drive. We need to be cognisant of different ‘segments’ of academics and where they are on their academic career paths. If academics are convinced of the value of using platforms (attitudes) and the benefits thereof on their job performance (effort meets performance), it would positively affect their future usage. The next-generation digital learning environments (NGDLE) place a huge responsibility not only on technological development but also on the commitment and development of academics within their specific fields.

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