Learning technologies in pre-service teacher education courses: concerns of students. ®

Dr Tony Jones

Graduate School of Education

La Trobe University

Bundoora Vic 2083

Australia

Fax +613 9479 3070

Email t.jones@latrobe.edu.au

Initial teacher education focuses on key learning areas and cognitive development of learners. Current teacher education students are also expected to acquire the skills and knowledge necessary to integrate uses of learning technologies into normal classroom practice. Although seen as important by prospective employers, educational applications of technology have to remain subordinate to curriculum and pedagogy in pre-service courses.

This paper discusses issues arising from the inclusion of mandatory computer-related subjects in a pre-service teacher education course. A particular emphasis is the feelings and perceptions of students about their computer efficacy. In addition, links between these perceptions and computer use during a teaching practicum are explored.

Results indicate that significant numbers of both supervising teachers and student teachers did not use computers during the teaching practicum. This phenomenon is discussed and some possible explanations are presented. Finally some implications in the area of teaching about learning technologies for pre-service teacher education programs are raised.

For many years schools and education systems focussed primarily on acquiring computer hardware and software. In recent years, possibly because computers have become common-place in schools, the focus has shifted to issues of teacher professional development and classroom use.

While there is still a need for basic computer literacy courses in pre-service teacher education courses, a significant proportion of existing classroom teachers use computers as tools in personal and professional tasks, or to assist in the teaching/learning process. As these teachers are already computer users, they require professional development assistance in order to integrate computer use into their teaching practice and to redefine the teacher's role in a technological classroom. The change of focus in teacher professional development is reflected in Rethinking learning and teaching (Department of Education, 1998) in Victoria and documents published by the Standards Council of the Teaching Profession (SCTP). The ideas contained in these documents are impacting on the content of educational computing courses for both pre-service and in-service teachers.

Several different forms of anxiety have been reported in educational research journals. For example there is an extensive body of literature and research on mathematics anxiety. Although computer use in education is a relatively recent development, studies into computer anxiety have been reported for more than two decades.

Anxiety in any area of education is an emotional state, and links have been established between anxiety and motivation, perception of content relevance, performance, and self-esteem. For example Buxton (1981) discusses these links in relation to anxiety about learning mathematics. Similarly Dyck, Gee & Smither (1998) report on computer anxiety scales and other research dating from the early 1980s. However there is no consensus and what computer anxiety is and how it can be measured. Rosen & Maguire (1990) performed a meta-analysis on quantitative research studies on computerphobia and noted that out of 81 studies analysed there were 66 different measuring instruments.

Pintrich & Schunk (1996: 7) claim that "much research shows that students' perceptions of their capabilities relate positively to motivation." Self-efficacy theory examines the role of students' perceptions of their competence. The theory has developed from social learning theory and was originally applied in health related areas rather than education. Recently educational theorists have adapted the theory and model. Pintrich & Schunk (1996: 88), cite Bandura's (1986) definition of self-efficacy as "people's judgements of their capabilities to organize and execute courses of action required to attain designated types of performances". This definition suggests that self-efficacy differs from other constructs such as task-specific self-concept and self-perceptions of competence because it is specific, "organize and execute courses of action", and it applies to particular goals, "attain designated types of performances".

Research into self-efficacy was developed and linked with educational theory by Bandura in the 1970s. Since then Bandura and other researchers have clarified the concept of self-efficacy and expanded its use into many diverse domains of educational research. An extensive body of research has been built up that reports about and analyses self-efficacy in diverse areas of education at levels from primary school through to adult.

Student perceptions are thoughts, beliefs, and feelings about persons, situations and events (Schunk & Meece 1992: ix). Researchers have identified several forms of student perceptions. Two types that relate to the Personal Computer Self-Efficacy Scale are outcome perceptions and perceived self-efficacy.

Learning styles can be defined as the various methods employed by individual learners for perceiving and processing information within the context of their environment (Kolb, 1984; Litchfield, 1993). Almost all research into preferred learning styles has been in the context of learning in traditional classrooms or lecture halls. Research in this area indicates that learning styles affect both how learners acquire information as well as how they organise it. So far there has been relatively little research into the effects of students' preferred learning styles in the context of computer-based, computer-managed, or computer-mediated delivery.

Kolb (1984) defined learning styles as an individuals preferred methods for perceiving and processing. Both Kolb's Experiential Learning Theory (ELT) and 4MAT, McCarthy's (1987) derivation from ELT, hypothesised that there were four distinct, cyclic and consecutive states of learning: concrete experience; reflective observation; abstract conceptualisation; and active experimentation. Concrete experience and abstract conceptualisation can be considered as extremes of a continuum representing the way people perceive experience and information. Similarly reflective observation and active experimentation are extremes of a continuum representing the different ways people process experience and information. The combinations formed by theses processing and perceiving techniques create four distinct but equally valuable learning styles McCarthy, 1987).

The 46 participants in this study consisted of the entire cohort of a pre-service primary teacher education course at an Australian university. The minimum academic qualification for entry into the course was a suitable undergraduate degree, although several participants had also completed an honours year or masters degree.

Only six (13%) of the participants were male. Eighteen (39%) participants gave their age as being under 25 years at the commencement of the course.

Two instruments were used to collect different forms of data. The first instrument, a Personal Computer Efficacy Questionnaire (PCEQ), was derived from the Computer Self-Efficacy Scale (CSE) developed and validated by Murphy, Coover and Owen (1989). Two of the three factors of the CSE were slightly modified for the local context. In their study the developers report that these two factors accounted for 86% of the systematic covariance among the CSE items, with alpha reliabilities of .97 and .96. The third factor, which explained only 6% of covariation, related to mainframe computing skills and was not relevant to this study. It was replaced by six items linked to generic educational software commonly used in primary schools and part of the content of the participants' course.

The aim of the PCEQ instrument was to ascertain students' perceptions of their ability to use computers. The instrument contains 34 items, all commencing with the stem, "I feel confident ...". Sixteen items are classified as relating to basic computing skills such as " ... entering and saving data into a file". A further twelve items, including " ... using a computer to organise information" and " ... understanding terms relating to computer hardware", are classified as being concerned with advanced computing skills. The final six items in this questionnaire relate to skills associated with using the Internet and multimedia software. This instrument was administered in February during the first week of classes.

The second instrument, School Computer Access Questionnaire (SCAQ), related to computer access and use in schools for teachers and students. It was administered in May immediately following a two-week teaching practicum in schools, and sought details of access and use of computers by teacher education students, supervising classroom teachers, and primary school students.

The Personal Computer Efficacy Questionnaire (PCEQ) consisted of 34 items that were scored on a 5 point Likert scale from strongly disagree to strongly agree. Because of the common positive stem all items were positive and none had to be reversed for scoring purposes. Strongly disagree responses were scored as 1, disagree as 2, and so on up to strongly agree which was scored as 5. SPSS version 8.0 for Windows was used to perform basic descriptive statistical analyses.

Among the 16 items categorised as being basic computer skills, five items had a mean greater than 4.00 and no items had a mean less than 2.70. Table 1 displays these four items with their means and standard deviations.

Table 1 Means and standard deviations of high scoring basic skill items

The item with the lowest mean (2.73) was "I feel confident copying a disk". Only two other items had a mean less than 3.00.

This analysis indicated that as a whole this group of pre-service teacher education students believed they possessed a range basic computing skills. In all four items shown in Table 1 90% or more either agreed or strongly agreed. In contrast, for the item "I feel confident copying a disk" less than 30% of the participants agreed or strongly agreed.

Analysis of the items categorised as advanced determined that the item, "I feel confident about learning to use a variety of programs" (mean = 3.63) was the only one with a mean greater than 3.00. In contrast three items had means of approximately 2.00 or less. These are set out in Table 2.

Table 2 Means and standard deviations of low scoring advanced skill items

For people who have not formally studied computing it is not surprising that these items would be rated lowly. In general it would be expected that people confident with these items would have learned to computer programming and would have extensive experience using and being around computers. Neither of these is a characteristic of the participants in this study.

The School Computer Access Questionnaire was designed to collect data on computer use and access in 46 primary classrooms over a two week period. The two most significant questions asked about the amount of computer use by both the particular teacher education student and their supervising teacher during the ten school-days of the practicum. The results from these two questions are surprising and disappointing. Surprising in light of the efforts of the Victorian Department of Education to make use of learning technologies an integral part of everyday teaching and learning in government schools. Disappointing because in spite the efforts of schools and parents in providing computer hardware and software, computer use is far from being a daily occurrence for most students and primary teachers.

Table 3 Computer use by supervisors and student teachers (percentages)

The data shows that fewer than one-third of the supervising teachers used computers more than once or twice over the 10 day period of this survey. However this information must be linked with data in Table 4, which indicates that in some schools computers were only available in specialist rooms or laboratories.

Table 4 Computer positioning in schools (percentages)

In addition to some schools only having computers in laboratories, 48.4% of the student teachers reported that someone other than the class teacher worked with the class on computers in the laboratory during the survey period. This corresponds with information that 80.6% of the schools had a computer resource person. In some cases this person was a classroom teacher who did not take other teachers' classes. In other cases the computer resource person did teach other teachers' classes on a regular basis.

At the beginning of a course data was collected about students' perceptions of their ability to use computers. Data relating to computer access and use was collected following a two-week teaching practicum in schools.

The data collection instruments used in this project did not probe computer experience prior to participants commencing their pre-service teacher education course. However the high level of self perception in their ability to perform basic computing tasks among the participants indicates considerable prior computer experience. It might well be that in future years it should be expected that all entrants into pre-service teacher education courses will have mastered these basic computing skills. This would mean that more time could be spent on developing skills and techniques directly related to classroom use of computers and other forms of learning technology.

Lack of use of the technology that already exists in primary classrooms is a much more significant problem. In this project the similarity of reported use by pre-service teachers and their supervisors suggests that classroom teachers who do not themselves use computers will not encourage teacher education students to use computers with students.

It appears likely that teachers at all levels, primary, secondary and tertiary, will continue to be expected to make increased use of computers and other learning technologies. For beginning teachers the focus has shifted away from a lack of hardware and software towards a struggle to develop and acquire the skills and techniques necessary to make effective classroom use of learning technologies.

Bandura, A. (1986). Social foundations of thought and action - a social cognitive theory. Englewood Cliffs: Prentice Hall.

Buxton, L. (1981). Do you panic about maths?: Coping with mathematics anxiety. London: Heinemann.

Department of Education (1998). Rethinking learning and teaching. Melbourne: DoE.

Dyck, J., Gee, N. & Smither, J. (1998). The changing construct of computer anxiety for younger and older adults. Computers in Human Behavior, 14(1), 61-77.

Kolb, D.(1984). Experiential learning. New Jersey: Prentice-Hall.

McCarthy, B. (1987). The 4MAT system. Barrington Hills, Il.: Excel Inc.

Murphy, C., Coover, D. & Owen, S. (1989). Development and validation of the computer self-efficacy scale. Educational and Psychological Measurement, 49, 891-899.

Pintrich, & Schunk, D. (1996). Motivation in education: Theory, research and applications. Englewood Cliffs: Prentice Hall.

Rosen, L. & Maguire, P. (1990). Myths and realities of computerphobia: A meta-analysis. Anxiety Research, 3, 231-247.

Where you live now, do you have access to a computer? YES NO

If YES, do you own this computer? YES NO

Did you use computers in your under graduate degree? YES NO

How often do you use a computer?

At home never rarely often everyday

At university [excluding this subject] never rarely often everyday

For the following questions SA means you strongly agree, A means you agree, N neither agree nor disagree, D you disagree, and SD you strongly disagree.