Teaching and Learning Forum 2000 [ Proceedings Contents ] University students' perceptions of information technology Elizabeth Santhanam Centre for Staff Development University of Western Australia and Carolyn Leach Department of Genetics University of Adelaide In the present age of information explosion, more and more academics, departments, faculties and/or universities are resorting to using computers and the internet in teaching/learning activities. Use of such technology is seen by some as not only aiding the processes of teaching and learning but also as being an inevitable step in the progression of higher education. However, what do we know about students' knowledge and skills, or their perceptions, relating to computers and other forms of information technology? An investigation was carried out to survey some aspects of science students' backgrounds, including their views regarding use of computers, familiarity with software and hardware. This pilot study at the University of Adelaide produced outcomes that may surprise some academics. The results suggest a gender bias relating to students' perception of their ability to use computers. Developing confidence in the use of computers seems to be necessary for some students, particularly the female students, if universities are aiming to develop self directed learning among students by using use computers and the World Wide Web.

Introduction

While academics/departments/faculties/universities are trying to utilise computers and other information technology (IT), there are issues that require attention. One such issue is the need for higher education to be inclusive i.e. teaching should cater to all students and not just the 'privileged'. Australian universities espouse to the principles of equity in education. How inclusive is the use of computer based media for instruction? What do we know of student backgrounds in relation to computer knowledge and skills? Isn't this information necessary to facilitate student learning through computer based media, since the "design of learning material for any medium should always begin with the definition of objectives and analysis of student learning needs" (Laurillard, 1993, p. 181-182)?

Background

In a pilot study at the University of Adelaide, student backgrounds relating to computer use, knowledge and skills as well as some factors that may influence student perceptions of their ability were investigated. Student perceptions of their ability may be an indicator of their real ability, so it can be used to identify groups of students who may require special help before implementation of computer based teaching. The outcomes of this study could be useful to the University of Adelaide and to high schools preparing students for university entry. Similar outcomes could be expected in other Australian universities.

Method

Results

If data were missing, cases were excluded pair-wise in the statistical analyses. Estimation of socio-economic status (SES) was based on home postcodes and the Australian Bureau of Statistics index of education and occupation for the state. The squared values of Age of student in years and the natural logarithm values of Computer use in hours were used to obtain a better fit for the regression model. All the variables were entered in a block for the multiple regression analysis.

The independent variables in the multiple regression model explain only about a quarter of the variance in the dependent variable, so there is a large proportion of residual variance (Tables 2 & 3). This outcome is to be expected, given the low levels of correlations between variables (Table 4). The highest correlation value of 0.453 is between student rating of their ability to use computers and the natural logarithm of hours in a week spent on using computers.

Among the student background variables that were investigated, the main predictors of student rating of their ability to use computers are the time spent on using computers and gender (Table 5). The age of students and whether or not students have completed a course in information technology in schools are the next best predictors. More time spent in using computers generally increased student rating of ability to use computers; increase in time from 0 to 10 hours per week corresponded with a sharp increase in the ability rating, but further increase in time had a marginal effect on the rating. Male students tended to rate themselves higher on computing ability than female students. The highest proportion of above average ratings for computing ability was for the 19 to 25 year old group, followed by the below 19 and finally the above 25 year old groups. Students who had completed a course in IT are more likely to rate themselves above average for ability to use computers than those who had not.

Students' familiarity with computer software and hardware was also explored, and the responses are summarised in Tables 6 and 7. Almost all students who responded to this question were familiar with a Word Processor and about half of them were familiar with Spreadsheet, but few were familiar with World Wide Web (WWW) and/or Email. The most familiar computer hardware was a Personal Computer (PC).

Discussion

Although the Faculty of Science at the University of Adelaide provides opportunities for students to become familiar with some computer software, such as Word Processor and Spreadsheet packages, the need for helping students to become familiar with these packages is not as great as for some of the other packages. Email and WWW are frequently used in computer based instruction and/or assessment, and yet the outcomes of this study suggest that the majority of entry students are not familiar with such packages. Even among final year and postgraduate students, a few may be unfamiliar with Email use (Boles, 1999). Besides familiarity with the packages, lack of access may reduce the effectiveness of the medium. For instance, although the majority of students (84%, N=345) surveyed in this study had access to computers at home, only a minority (22%, N=342) had access to the Internet.

Are students disadvantaged by their inability to access and/or use computers, and if so what can be done? The answer to the above question requires further investigation into student backgrounds and the current practices at the local level. What is clearly apparent from this investigation is the diversity in student backgrounds relating to access to information technology. There also seems to be a grave need among some students for assistance to develop skills in the use of computer softwares prior to embarking on computer based instruction. Any induction programme should recognise student diversity and "should be organised primarily for students, rather than for the institution's convenience" (Billing, p. 132). If computer based instruction or computer mediated learning is to take place effectively, then access to, and familiarity in the use of, the medium is of importance.

References

Boles, W. (1999). Classroom Assessment for Improved Learning: A Case Study in Using Email and Involving Students in Preparing Assignments. Higher Education Research and Development, 18(1), 145-159.

Braswell, R. (1988). Attitudes of the Returning University Student Towards the Use of Computers. ERIC database: ED320560

Gessler, J.E. & Horridge, P. (1993). University Students' Computer Knowledge and Commitment to Learning. Journal of Research on Computing in Education, 25(3), 347-365.

Hayes, K. King, E. & Richardson, J.T.E. (1997). Mature Students in Higher Education: III. Approaches to Studying in Access Students. Studies in Higher Education, 22(1), 19-31.

Inoue, Y. (1998). The University Student's Preference for Learning by Computer-Assisted Instruction. ERIC database: ED420309.

Lafferty, G. (1996). Equity, Access and Independent Learning: Maximising the Outcomes for Mature Age Students. Australian Journal of Adult and Community Education, 36(2), 103-111.

Laurillard, D. (1993). Rethinking University Teaching: A framework for the effective use of educational technology. London: Routledge.

Lewis, R. J. & Markwood, R. (1985). Instructional Applications of Information Technologies: A Survey of Higher Education in the West. ERIC database: ED270094.

McClure, C. R. & Lopata, C. (1995). Performance Measures for the Academic Networked Environment. ERIC database: ED405867.

Meyer, J.H.F. (1995). Gender-group Differences in the Learning Behaviour of Entering First Year University Students. Higher Education, 29(2), 201-215.

Russell, S. H. et al. (1995). Study of Communications Technology in Higher Education, 1994. Final Report [and] Executive Summary. ERIC database: ED404931.

Severiens, S.E. & Ten Dam, G.T.M. (1994). Gender Differences in Learning Styles: A Narrative Review and Quantitative Meta-analysis. Higher Education, 27(4), 487-501.