Dion van Zyl & Hanlie Liebenberg

Slides:



Advertisements
Similar presentations
E-learning and Libraries WSIS Forum, Geneva,11 May 2010 Tullio Basaglia, CERN Scientific Information Service, Geneva.
Advertisements

An e-Learning Strategy to promote technology enabled learning i n UCC Teaching & Learning workshop 30 October, 2012.
Role of Vendor Technologies in the Development of Network Professionals Mak Sharma and Sharon Cox School of Computing, Telecommunications and Networks.
Why don’t innovation models help with informatics implementations? Rod Ward University of the West of England Medinfo 2010.
Using technology to improve learning Stella BurtonBeaumont Community Primary school1.
Online Information Services and Social Media Social Networking.
Margaret J. Cox King’s College London
Student Engagement Survey Results and Analysis June 2011.
+ The model of using technology to foster comprehensive thinking skill. The research of study of teaching method via various application software in order.
THE INFLUENCE OF DESIGN OF A WEB-BASED EDUCATIONAL TOOL ON SATISFACTION AND LEARNING PERFORMANCE Manuel J. Sánchez-Franco Ángel F. Villarejo-Ramos Begoña.
Librarians becoming competent: Technology acceptance in the workplace Sarah-Jane Saravani LIANZA Conference, Hamilton, 22 October, 2013.
March E-Learning or E-Teaching? What’s the Difference in Practice? Linda Price and Adrian Kirkwood Programme on Learner Use of Media The Open University.
Unified Theory of Acceptance and Use of Technology and the VET sector Sarah-Jane Saravani Shar-e-Fest, Hamilton, 11 October, 2013.
TECHNOLOGY ACCEPTANCE MODEL
GGGB6022: ACADEMIC WRITING 2 PRESENTATION: 'ATTITUDES & MOTIVATION TOWARDS THE LEARNING OF L2' AISHAH BINTI ADNAN (P79048)
Support for English, maths and ESOL Module 1 Managing the transition to functional skills.
Internet Self-Efficacy Does Not Predict Student Use of Internet-Mediated Educational Technology Article By: Tom Buchanan, Sanjay Joban, and Alan Porter.
Volunteer Engagement Survey Results May 29, 2013.
Leisure and Recreation. Lesson aims – 1.1 Consider what is actually meant by leisure time. 1.2 Consider the choices individuals have about how they make.
THE INTERNET GENERATION AND ITS IMPLICATION ON HIGHER EDUCATION QUALITY MANAGEMENT (OER, MOOCS, ONLINE DISTANCE COURSES AND ASSESSMENT) Samanthi Wickramasinghe,
Making the e-strategy happen – the new role for Becta Mike Briscoe Assistant Director.
The Students’ Acceptance of Learning Management Systems in Saudi Arabia: A Case Study of King Abdulaziz University Sami Binyamin1,2 , Malcolm Rutter1,
New Survey for Congregations
What Difference Can Portfolio Make in Radiographer Work Practice
Cambridge Lower Secondary
Effects Of Internet On The Study Habits Of Students
Posted on Box.com Cone Communications Green Gap Trend Tracker Re:Thinking Consumptionhttps://pac.box.com/s/8hm52qjnhgn12paand7r.
Visible Learning Plus: an introduction
DEPARTMENT OF HUMAN AND SOCIAL CIENCES APPLIED LINGUISTICS IN ENGLISH CAREER    “THE INFLUENCE OF TEACHER’S ATTITUDES AND BELIEFS INTO TECHNOLOGY-RELATED.
Section title This presentation is designed to help you talk to key stakeholders about Drive. It is not designed to be used with young people or their.
Australian Professional Standards for Teachers Unpacking the Standards
Digital Badging Student-Curated Evidence of Learning
An introduction for parents
Talent Management in an Age of Uncertainty Workshop Introduction
Utilising Skills Competitions in Developing Vocational Education and Training (VET) to meet Future Challenges Seminars on Countries Approaches to Skills.
LogiKal Projects We will make your Project Controls work
Interact 2: Communicating
Service Failures and Recovery in Tourism and Hospitality: A Practical Manual Erdogan Koc.
Reality Check The Asset-Building Strengths
A Roadmap for Higher Education Leaders
Online Driver Education and Virtual Classroom
Teaching and Supporting Adult Learners
MYP planning: the unit planner
A closer look at the Technology Acceptance Model (TAM)
Introduction to the Capability Framework
Elizabeth Hoerath Manager FSL Policy and Implementation Unit
Role of Social Media in Learning
Unlocking Student Potential
EDUC Quiz #1 (W. Huitt) EDUC 2130 W. Huitt
Negotiating Detention: Insights From Northern Ireland
Hartnell Climate Results
How connected are you online?
Soft & Transferable Skills
Suzanne Guerin University College Dublin & ISSE Steering Committee
Identifying enablers & disablers to change
Dion van Zyl & Hanlie Liebenberg
An introduction for parents
Preparing for Adulthood
TL 1071 – Implementing Learner-centered Teaching for Student Success
Helping Young Americans Chart a Path to Career Success
The Heart of Student Success
2017 UC Staff Engagement Survey
Online Driver Education and Virtual Classroom
Lecture 10: User Acceptance
April 14, 2008 Public Presentation EPSB Board Meeting
Lead Generation Through Social Media
Didactics vs Learning to Learn: Principles and Practices
PRESENTATION AT CHANG’OMBE SECONDARY DEMONSTRATION SCHOOL
Learning analytics in Compleap
Liberian-German Cooperation in Health Strengthening Gender Equality at Liberia’s Health Training Institutions – The Gender Audit Process – 2018.
Presentation transcript:

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

Background Revolution of ICT’s in HE over the past 20 years has contributed to the blurring of boundaries between 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.

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.

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.

Conceptual model

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

What primary platform staff use… myUnisa (97%) Blackboard (12%) Google classroom (9% ) Moodle (4%) Adobe classroom (3%) WebCT (3%) Kaleidos (1%) myUnisa remain the primary platform, rightfully so… While the use of myUnisa was to be expected, it is interesting to note the other forms of VLE’s used by academics. Pockets of use and in some instances experimental. Why not stick with ‘official’ platform – either need for ‘more’ than what is currently offered or not utlised to full potential…? Fronter (0,3%) Pockets of ‘experimental’ Why not use ‘official’ platform solely? Need for ‘more’ than what is currently offered or not utlised to full potential…?

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.

Use of secondary resources to enhance T&L YouTube 46% Podcasts 27% Facebook 22% Twitter 10% Google classroom 9% Vodcasts 6% Powtoons 3%

Construct measures

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

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

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.  

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.  

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

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.”

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

The model

Drivers of use 0.286* 0.169* 0.332* Moderating variables

Attitude as mediator

Performance expectancy Use Attitude (medium effect) Performance expectancy Effort expectancy Habit

Moderators

(gains in job performance) Age L 0.456 Performance expectancy (gains in job performance) M 0.528 Behavioural intent H 0.600 Results show that age was identified as having some moderating effect on the relationship between performance expectancy and intent to use, with the strength of the relationship increasing with age. Older academics are slightly more inclined (sensitive) to use teaching platforms, if it can help them to attain gains in job performance.

Age Habit Behavioural intent 0.433 Habit M 0.543 Behavioural intent H 0.653

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

Post grade Grade L Effort Behavioural M expectancy intent H 0.705 Effort expectancy (ease with the use) M 0.594 Behavioural intent Academics that fall into the lower post grades categories P8-P10, the relationship between effort expectancy and behavioural intent were slightly stronger. Thus, the degree to which an academic (P8-P10) believes that the system teaching platforms is easy to use, and not complex in nature, will be more sensitive towards future use. Therefore, for young emerging academics starting on their career path and who finds the use of VLEs easy and understandable, effort expectancy would have the largest effect on their future intent of behaviour. H 0.483

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…

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.