A study of technology adoption and usage behaviour for students in Higher Education in Institutes of Technology
- 1. A STUDY OF TECHNOLOGY ADOPTION AND USAGE BEHAVIOUR FOR STUDENTS IN HIGHER EDUCATION IN INSTITUTES OF TECHNOLOGY Ms. Rosaleen McGough - Institute of Technology Tralee Mr. Andrew Shields - Institute of Technology Tralee
- 2. Aims of the research ■ To analyse student behaviour with technology ■ To analyse the impact of technology in an academic setting ■ To determine factors that influence student usage of technology ■ To establish the difficulties regarding the use of technology ■ To determine predictive behaviours through data mining
- 3. Technology Enhanced Learning ■ Technology has become one of the biggest drivers in industry today ■ Educational Institutes must prepare students to be technologically advanced for the workplace ■ Technology use in the classroom can help increase engagement but can also be a hindrance ■ More colleges are providing accredited online courses ■ It is important that educators do not presume that students who use technology for social purposes will be as comfortable with technology in an academic setting
- 4. Research Methodology ■ Based on previous research carried out in the University of Edinburg ‘A Survey of Undergraduate Technology Use and Attitudes’ (2011) ■ An online survey was used as the data collection method, using the survey from the previous research as a framework ■ 169 responses were received, just over 5% of the student population of 3,153 students from across all years of study including post graduates.
- 5. The Sample ■ The highest rate of respondents came from fourth year students 28% ■ The largest age group was 18-22 (46%) ■ The distribution of gender was Males 53% and Females 47% ■ Over 55% of responses came from students studying in the Computing department and Creative Media and Information Technology department ■ 86% of students who responded were Irish, 8% EU students and 6% International students (non EU) *results show in all charts are based on the overall sample, although some students did not provide responses to all the questions
- 6. Smartphone and laptop ownership is high amongst students 0 10 20 30 40 50 60 70 80 90 Smartphone Tablet Kindle Laptop PC Smartphone Tablet Kindle Laptop PC Percent 89.9 43.2 10.1 85.2 36.7 Student Device Ownership
- 7. Almost 40% of students spend over 5 hours a day online 0 5 10 15 20 25 30 35 40 Less than 1 hour 1-2 hours 3-4 hours 5 hours + Percent 3 18.9 34.9 39.1 % % Students time spent online
- 8. Daily use of social media channels 0 10 20 30 40 50 60 70 80 Facebook Twitter Instagram LinkedIn Pinterest Google + YouTube Facebook Twitter Instagram LinkedIn Pinterest Google + YouTube Percent 77.5 23.7 32 25.4 10.7 21.3 68.6 Social Media Daily usage
- 9. Student confidence with the use of ICT in college is positive overall 0 10 20 30 40 50 60 Very Confident Enjoy the challenge A little apprehensive Very apprehensive Very Confident Enjoy the challenge A little apprehensive Very apprehensive Percent 56.8 22.5 13.6 3 Students confidence in the ability to the use of ICT
- 10. Students have found ICT helpful in their studies 0 10 20 30 40 50 60 70 80 Very helpful Helpful Not helpful Hindrance Percent 76.9 16.6 1.2 1.2 % Perception of Helpfulness of ICT in studies
- 11. Technical competences are positively reported 0 10 20 30 40 50 60 70 80 90 Backup your work Keep antivirus updated Keep computer’s OS updated I do this type of task alone 85.8 66.9 68.6 I would need some help to do this type of task 5.3 4.1 5.7 I have never done this type of task alone 2.4 22.5 18.9 % Reported technical competences
- 12. Overall software competences is positive 0 10 20 30 40 50 60 70 80 90 100 I do this type of task alone I would need some help to do this type of task I have never don’t this type of task alone Don’t Know/Unsure I do this type of task alone I would need some help to do this type of task I have never don’t this type of task alone Don’t Know/Unsure Use the Internet to search for statistics or demographic information 82.8 7.1 0.6 1.8 Online bibliographic/library database 71.6 16 4.1 1.2 Presentation Manager e.g. PowerPoint, Prezi 86.4 5.9 0.6 0.6 Software competences of students
- 13. Regular access to web facilities is low with the exception of Student Email 0 10 20 30 40 50 60 70 80 90 Blackboard My Docs Student Email Library Catalogue On a daily basis 31.4 37.3 85.8 5.3 On a weekly basis 18.9 15.4 5.9 21.9 Regular, but less frequent 18.3 17.8 0 30.2 Rarely or Never 24.9 21.9 0.6 34.3 % Frequency of accessing Web facilities
- 14. How students are using the Internet 0 10 20 30 40 50 60 70 Academic articles found openly on the Internet Facebok for academic work related purposes Instant messenger for conversations relating to academic work Twitter for academic work related purposes Wiki for academic work related purposes On a daily basis 14.2 7.1 20.1 3.6 10.7 On a weekly basis 26.6 14.2 18.9 6.5 24.9 Regular, but less frequent 31.4 23.1 18.9 14.8 27.8 Rarely or never 19.5 48.5 34.9 68 29.6 % Frequency of accessing Internet mediums for academic purposes
- 15. Online learning 0 10 20 30 40 50 60 70 No Yes Percent 65.7 27.2 % Percentage of students who have taken a class online 0 5 10 15 20 25 30 35 40 No Not sure Yes Percent 37.9 36.7 18.3 % Does online learning offer the same value as in-class learning
- 16. Students preference for more modules offered online 0 5 10 15 20 25 30 35 40 45 50 No Not sure Yes Percent 20.1 23.1 49.7 % % of student preferences
- 17. Awareness of the college referencing policy is high 0 10 20 30 40 50 60 70 80 No Not sure Yes Percent 12.4 5.9 74.6 % % Awareness of the college referencing policy
- 18. Will the internet cause a rise in plagiarism 0 10 20 30 40 50 60 No Not sure Yes No Not sure Yes Percent 20.1 18.9 53.8 % Students perceptions
- 19. Technology in the classroom 0 10 20 30 40 50 60 70 80 90 No Yes Percent 7.1 85.8 % % students perceptions of engagement in subjects through technology 0 10 20 30 40 50 60 No Sometimes Yes Percent 50.3 30.2 12.4 % % of students perceptions on distraction of digital devices in the classroom
- 20. Data mining to predict student behaviour ■ Data mining was employed to predict behaviour outcomes based on age, gender, year of study and field of study ■ The aim was to identify and profile students who may not be aware of the college referencing policy and who do not access facilities such as Blackboard on a daily basis. ■ Decision Trees using the Classification and Regression Tree (CART) method were used
- 24. Conclusions ■ Based on the survey results and data mining methods it is important for educational institutes to recognise that not all students are comfortable and competent with ICT ■ Supports must be in place to assist students who struggle with ICT ■ Educators must enforce rules regarding BYOD in the classroom ■ Institutions must realise that technology is another medium which can enhance learning when used appropriately
- 25. ■ Results can help institutions plan for investment in technology ■ Further research must be carried out prior to investment in online learning ■ Educators must explore the mediums that help to engage students in subject material ■ Data mining can help to extract knowledge which can then be turned into meaningful information to be used in strategic planning
- 26. Thank you for your time Q&A rosaleen.mcgough2@students.ittralee.ie andrew.shields@staff.ittralee.ie