A Formative Analysis of How Preservice Teachers Learn to Use Technology

Abstract

A comprehensive, formal comparison of strategies used by preservice teachers to learn how to use new technology has yet to be researched. Understanding the relative strengths and weakness of learning strategies would provide useful guidance to educators and students. The purpose of the current study was to explore the effectiveness of four learning strategies: collaboration , using authentic tasks, formal instruction and exploratory learning. Seventy-four preservice teachers (25 male, 49 female) were surveyed at the beginning and end of an 8-month, consecutive, Bachelor of Education programme, with respect to their learning strategies, change in computer knowledge and use of computers in the classroom. Collaborative learning and use of authentic tasks were the most preferred strategies – formal instruction was the least preferred. A collaborative approach to learning was the best predictor of gains in computer knowledge. Authentic tasks and collaborative strategies were significant predictors of teacher use of computers in the classroom. Preference for authentic tasks was the only predictor of student use of computers. Regardless of strategy preference, selecting more than one primary learning tool was significantly correlated with amount learned and use of the computers in the classroom. Ability was not related to strategy preference. Finally, females preferred collabora-tive approach to learning, although they were significantly more open to using multiple strategies than males.

Full text

A formative analysis of how preservice teachers
learn to use technology
R. Kay
University of Ontario Institute of Technology, Oshawa, Canada
Abstract A comprehensive, formal comparison of strategies used by preservice teachers to learn how to
use new technology has yet to be researched. Understanding the relative strengths and weak-
ness of learning strategies would provide useful guidance to educators and students. The
purpose of the current study was to explore the effectiveness of four learning strategies: col-
laboration, using authentic tasks, formal instruction and exploratory learning. Seventy-four
preservice teachers (25 male, 49 female) were surveyed at the beginning and end of an 8-month,
consecutive, Bachelor of Education programme, with respect to their learning strategies,
change in computer knowledge and use of computers in the classroom. Collaborative learning
and use of authentic tasks were the most preferred strategies – formal instruction was the least
preferred. A collaborative approach to learning was the best predictor of gains in computer
knowledge. Authentic tasks and collaborative strategies were significant predictors of teacher
use of computers in the classroom. Preference for authentic tasks was the only predictor of
student use of computers. Regardless of strategy preference, selecting more than one primary
learning tool was significantly correlated with amount learned and use of the computers in the
classroom. Ability was not related to strategy preference. Finally, females preferred collabora-
tive approach to learning, although they were significantly more open to using multiple strate-
gies than males.
Keywords computer resource learning, help software, learn, preservice teachers, strategies.
Overview
Over the past 10 years, educational policy specialists
and administrators have made a concerted effort to
increase the presence of technology in classrooms, spe-
cifically focusing on increasing student–computer
ratios (US Department of Education, National Center
for Education Statistics 2002), maximizing the number
and speed of Internet connections (McRobbie et al.
2000; US Department of Education, National Center for
Education Statistics 2002; Compton & Harwood 2003;
Plante & Beattie 2004) and emphasizing technology as
a critical component of preservice teacher education
(e.g. OTA 1995; CEO Forum on Education and Tech-
nology 2000; ISTE/NCATE 2003; National Council for
Accreditation of Teacher Education 2003 – see Bennett
2001/2001 for a review). While considerable success in
improving the hardware infrastructure in schools has
been attained (McRobbie et al. 2000; US Department of
Education, National Center for Education Statistics
2002; Compton & Harwood 2003; Plante & Beattie
2004), integrating the use of technology into preservice
education has proven to be more of a challenge.
The purpose of this study was to explore and evaluate
the effectiveness of strategies used by preservice teach-
ers to learn new technology in order to gain insights on
how to design more successful technology and educa-
tion programmes. Note, for the purposes of this article,
Accepted: 15 November 2006
Correspondence: Dr Robin Kay, University of Ontario Institute of
Technology, 2000 Simcoe St. North, Oshawa, Ontario, L1H 7K4,
Canada. Email: robin.kay@uoit.ca
doi: 10.1111/j.1365-2729.2007.00222.x
Original article
366 © 2007 The Author. Journal compilation © 2007 Blackwell Publishing Ltd Journal of Computer Assisted Learning (2007), 23, 366–383

learning ‘new technology’ refers to learning ‘new soft-
ware’; however, other elements of technology come into
play like understanding how to use technology
in a classroom environment and operating digital
equipment.
Literature review
Technology and preservice teachers
Assuming that thoughtful use of technology in certain
contexts can have a significant and positive impact
on student learning (Baker et al. 1994; Kulik 1994;
Scardamalia & Bereiter 1996; Sivin-Kachala 1998;
Wenglinsky 1998; Mann et al. 1999; SIIA 2002; Kozma
2003), preservice teacher education programmes are a
reasonable place to start with respect to integrating tech-
nology into education, particularly when a strong infra-
structure that supports computer use is in place. Yet, the
evidence suggests that these programmes have not been
successful at preparing new teachers to use technology
effectively (OTA 1995; Moursund & Bielefeltdt 1999;
CEO Forum on Education and Technology 2000; US
Department of Education 2000; Yildirim 2000). A
number of obstacles that prevent successful implemen-
tation of computers include lack of time (Eifler et al.
2001; Wepner et al. 2003), teaching philosophy of
mentors and school administration (e.g. department
heads, principals, superintendents) with respect to tech-
nology (e.g. Stuhlmann & Taylor 1999; Dexter &
Riedel 2003; Doering et al. 2003), technological skill of
faculty of education members (Eifler et al. 2001;
Strudler et al. 2003; Thompson et al. 2003), fear of
technological problems (Doering et al. 2003; Bullock
2004), a clear lack of understanding about how to inte-
grate technology into teaching (Cuban 2001), and insuf-
ficient access to technology (e.g. Bartlett 2002; Brush
et al. 2003; Russell et al. 2003). Given the potential
problems, it should come as no surprise that preservice
teachers are perceived as unprepared to use technology.
A comprehensive review of strategies used to inte-
grate technology into preservice education revealed that
thoughtful technology-based programmes have been
developed, but only a handful of studies have conducted
careful and rigorous evaluations of these programmes
(Kay 2006b). Less than 8% of all studies reviewed
looked at changes in computer ability or classroom use
of computers as a result of these programmes. Clearly, a
more in-depth analysis is required.
One approach, not yet followed, is to examine actual
strategies that preservice teachers employ to learn how
to use technology. Comparing learning strategies might
provide insights into which approaches have the most
significant impact on improving computer ability and
increasing effective use of technology in the classroom.
Part of the challenge for this type of research is finding a
technology-based teacher education programme that
provides sufficient range of choices so that meaningful
comparison among strategies can be made. Kay (2006b)
noted that less than 5% of the 68 preservice programmes
examined used four or more methods of integrating
technology into preservice education.
Strategies for learning to use technology
There are four key learning strategies that have been
previously investigated including collaboration, formal
instruction (workshops, manuals, software help),
exploratory learning and completing authentic tasks.
While this is not an exhaustive list, it is largely represen-
tative of the literature on approaches used to learn new
technology. These four strategies align reasonably well
with the ten methods that emerged from Kay’s (2006b)
review including:
1collaboration among preservice teachers, mentor
teachers and faculty, focusing on education faculty,
focusing on mentor teachers (collaboration).
2delivering a single technology course, offering mini-
workshops, using multimedia (formal instruction).
3improving access to software, hardware and/or
support (time for exploratory learning).
4integrating technology in all courses, modeling how
to use technology, practising technology in the field
(completing authentic tasks).
Collaboration
While the benefits of collaborative learning are well
documented (e.g. Johnson & Johnson 1994, 1998;
Kagan 1997; Sharon 1999), no formal studies have sys-
tematically examined the effect of collaboration on
improving computer-related ability or use of technology
in the classroom. Most research in this area has looked at
the general impact of human assistance. Simmons and
Wild (1991) noted that a majority of individuals end up
asking for help from a more knowledgeable person.
Rieman (1996) also observed that asking another person
How preservice teachers learn to use technology 367
© 2007 The Author. Journal compilation © 2007 Blackwell Publishing Ltd

for help is a natural strategy but that there can be several
barriers – availability, feeling like you are bothering an
experienced user too often, time spent on finding
someone, and being too proud to ask for help. E-mailing
a person for help is rarely done because most people
need a quick answer to their problems (Rieman 1996). It
should be noted that some researchers have reported that
users would rather ask for help on an ‘as needed basis’
rather than be controlled by a tutor or trainer (Simmons
& Wild 1991; Bannert 2000).
Authentic tasks
Several prominent organizations have strongly
endorsed the use of authentic tasks as a viable method
for introducing technology to preservice teachers (see
Moursund & Bielefeltdt 1999 or ISTE/NCATE 2003).
While this approach has been successful in improving
confidence (Pope et al. 2002) and technology skills
(Vannatta & Beyerbach 2000; Pope et al. 2002; Albee
2003), its main advantage is a focus on meaningful
problem solving where preservice teachers are learning
with computers, not about them (e.g. Milbrath & Kinzie
2000; Doering et al. 2003). Disadvantages to using this
model include lack of hardware (Vannatta & Beyerbach
2000), limited faculty expertise and time (Vannatta &
Beyerbach 2000; Eifler et al. 2001; Whetstone &
Carr-Chellman 2001), and the difficulty of transferring
what is learned at school to field experience in the class-
room (Simpson et al. 1999; Eifler et al. 2001; Vrasida &
McIsaac 2001; Brush et al. 2003).
Formal instruction
In 2001, US companies spent approximately 21 billion
dollars in improving computer skills of employees. The
most typical response of institutions to the need for
Information and Communication Technology (ICT)
education is to focus on developing effective ‘stand-and-
deliver’ training programmes (Niederman & Webster
1998; Olfman et al. 2003; Mahaptra & Lai 2005);
however, there is evidence to suggest that this teaching
approach is not particularly effective (Olfman &
Bostrom 1991; Shayo & Olfamn 1993; Olfman &
Mandviwalla 1995). It has been estimated that more than
50% of the participants in software workshops fail to use
the software they were trained on (Olfman & Bostrom
1991; Olfman & Mandviwalla 1995). Other disadvan-
tages observed include learning technology skills in iso-
lation (Gunter 2001; Whetstone & Carr-Chellman 2001)
and technology skills not being used in the field
(Hargrave & Hsu 2000; Pope et al. 2002; Willis & Sujo
de Montes 2002).
Manuals can provide extensive information in the
form of task-oriented instructions, indexes, table of con-
tents, pictorial representations and specialized short-cut
guides (Rettig 1991). In spite of these advantages, most
new users, regardless of ability level, begin using new
software without reading the manual (Carroll 1990;
Rettig 1991; Simmons & Wild 1991; Taylor 2003).
Rettig (1991) refers to computer manuals as the best-
sellers that no one reads; however, Dryburg’s (2002)
extensive report on over 25 000 users noted that
manuals are used 60% of the time at some point in the
software learning process.
There is some evidence to suggest that using a manual
actually improves learning performance. For example,
Rieman (1996) noted that individuals can find out how to
do tasks without manuals, but more advanced features
remain untouched or unresolved. Bannert (2000),
though, observed that acquiring new software skills with
a manual was significantly faster and more productive
than tutor-guided instruction. However, not all manuals
are the same. Manuals that contain ample error informa-
tion (minimal manuals) help students perform better
than manuals with limited error information (Carroll
1990; Lazonder 1994; Lazonder & Van der Meij 1995;
Van der Meij & Carroll 1995). Van der Meij (2000) adds
that the most successful format of a manual is a two-
column layout with instructions and full-screen images
presented side by side.
Software help features are designed to provide hints,
instructions and immediate feedback to guide new learn-
ers (Patrick & McGurgan 1993; Draper 1999). However,
designing good help systems is not an easy task because
it requires one to anticipate the needs and behaviours of a
variety of learners (Duffy et al. 1992; Allwood & Kalen
1993; Patrick & McGurgan 1993; Lazonder & Van der
Meij 1995). Many users appear to spend little time using
software help (Aleven & Koedinger 2000; Bartholomé
et al. 2006). Nonetheless, there is some evidence to
suggest that properly designed help features can foster
learning (Wood & Wood 1999; Bartholomé et al. 2006),
particularly context-sensitive help (Patrick & McGur-
gan 1993; Bartholomé et al. 2006).
Exploratory learning
Self-regulated or exploratory learning is a common
method that many people use to acquire new software
368 R. Kay
© 2007 The Author. Journal compilation © 2007 Blackwell Publishing Ltd

skills (Bartholomé et al. 2006). In one report assessing
over 25 000 computer users, 96% of respondents
reported that they taught themselves to learn software
through trial and error (Dryburg 2002). Limited
research, though, has been performed by looking at the
effectiveness of exploratory learning. Several research-
ers have examined a ‘training wheels’approach to learn-
ing software where cognitive load is reduced by limiting
the number of functions available (Guzdial 1999;
Bannert 2000; Leutner 2000). Users who learn with a
reduced command set outperform those individuals pre-
sented with a full array of options (Leutner 2000). Other
research suggests that the successful exploration of soft-
ware depends on whether the new software is consistent
with previously learned software and how easy it is to
guess at commands (Guzdial 1999).
Comparing methods
The little evidence that has been gathered comparing the
use of resources suggests that people prefer to ‘try
things out’ (Carroll 1990, 1998; Rieman 1996; Dryburg
2002), read the manuals (Rieman 1996), ask for some
form of human assistance (Rieman 1996; Dryburg
2002) and, in some cases, consult the software help
system if they are particularly aggressive explorers
(Rieman 1996). Reimann and Neubert (2000) add that
users tend to consult a hybrid of resources while learn-
ing instead of relying on a single support tool.
Individual differences
Ability
It is reasonable to speculate that novices and experi-
enced learners have different perspectives and methods
while learning new technology (Lazonder & Van der
Meij 1995). Novices appear to be inconsistent in their
approach to learning software and using resources
(Rieman 1996). They are inefficient and often aimless
when engaging in exploratory learning (Kamouri et al.
1986; Kluwe et al. 1990; Polson & Lewis 1990;
Reimann & Neubert 2000), have difficulty controlling
their learning activities and knowing where to search for
answers (Bannert 2000; Van der Linden et al. 2001),
and scan or act upon information very quickly (Brandt
& Uden 2003).
As learners grow and develop understanding and
expertise, their need for software support and function-
ality changes (Jackson et al. 1998). More experienced
users read manuals in greater depth (Rieman 1996) and
are more proficient in selecting and executing search
strategies (Wood & Wood 1999; Lazonder 2000;
Bartholomé et al. 2006). However, domain-specific
software expertise appears to be more important than
general expertise (Draper 1999). For example, specific
knowledge of spreadsheet software would help an indi-
vidual learn a new spreadsheet software package more
than overall software expertise (Draper 1999). It is also
interesting to note that the differences between novice
and experts begin to disappear when tasks become more
complex (Lazonder 2000).
Gender
Gender differences in computer attitudes, use, ability
and behaviour (e.g. Kay 1992a, 2006a; Whitley 1997;
Sanders 2006) have consistently been reported in favour
of males. It is reasonable to speculate, then, that differ-
ences may occur with respect to the use of learning
strategies. To date, little research has been performed
on gender differences and methods to learn new
technology. In one large-scale study (Dryburg 2002),
men were more likely to use exploratory learning,
whereas women preferred facilitated methods (e.g. on
the job training, help from friends, family, coworkers).
Purpose and specific research questions
While multiple strategies used to learn technology have
been examined in previous research (Borenstein 1985;
Bannon 1986; Norman & Draper 1986; O’Malley 1986;
Carroll et al. 1987/88; Rieman 1996; Dryburg 2002), a
comprehensive, formal evaluation of the effectiveness
of a wide range of strategies has yet to be completed. A
majority of studies focus on a single approach (e.g.
Carroll 1990; Rieman 1996; Guzdial 1999; Bannert
2000; Belanger & Van Slyke 2000; Bartholomé et al.
2006).
The purpose of this article was to examine and
compare the effectiveness of four learning strategies
used by preservice teachers to learn how to use new
technology: collaboration, authentic tasks, formal
instruction and exploratory learning. The specific
research questions were as follows:
1Is there a significant difference among learning strat-
egies with respect to perceived helpfulness?
How preservice teachers learn to use technology 369
© 2007 The Author. Journal compilation © 2007 Blackwell Publishing Ltd

2Is there a significant difference among learning
strategies with respect to impact on learning new
technology?
3Is there a significant difference among learning strat-
egies with respect to predicting use of technology in
the classroom?
4Are there individual differences in the use of learning
strategies with respect to computer ability and
gender?
Method
Sample
Eighty-nine preservice teachers completed the pre-
laptop programme survey, while 74 completed the
post-laptop programme survey. Both pre- and post-test
scores were necessary; therefore, the final sample popu-
lation was 74 (83%). The sample consisted 25 males
and 49 females, from a variety of cultural backgrounds
(North America, Asia, Europe – 81% English as a first
language) ranging in age from 23 to 53 years (M =33.1,
SD =8.7). All students had at least a 4-year university
degree in their area of teaching specialty. With respect to
years of computer experience, 3% had 0–2 years, 10%
had 3–5 years, 38% had 6–10 years and 81% had 10 or
more years. It is important to note that years of com-
puter experience in this study was not necessarily
equivalent to computer knowledge. Preservice teachers’
pre-laptop scores on the computer ability survey (see
Table 2) were relatively low for 12 sub-scales except
word processing and spreadsheets.
Description of the programme
The Bachelor of Education degree at this university was
an 8-month consecutive programme, focusing on com-
puter science, math and science (physics, chemistry,
biology and general science) at the intermediate-
secondary school level (grades 7–12).All students were
required to have a BAwith five full university courses in
their first teachable area and three full university
courses in their second teachable area.
Every student in the preservice teacher education
programme was given an IBM R51 ThinkPad at the
beginning of the year loaded with a wide range of
educational and application-based programmes. All
classrooms were wired with high-speed Internet access
through cable and a wireless network. In addition, stu-
dents had access to a wireless network throughout the
university campus.
Model of technology use
An integrated model was used to incorporate technol-
ogy into the preservice education. In other words, stu-
dents used their laptop computers in all courses offered,
but did not take a stand alone course in technology use.
Mini-workshops (1–2 h) were offered throughout the
year on various software packages. Finally, there was
one support person available 8 h per week to assist stu-
dents with individual problems. All faculty members
created assignments and projects that required students
to use the computer as a tool to solve meaningful, prac-
tical and useful problems.
Data sources
Learning strategies survey
This survey consisted of 13 items based on a 5-point
Likert Scale (0 =no help, 1 =little help, 2 =some help,
3=much help, 4 =a great deal of help) focusing on
various strategies that an individual could use to learn
new technology. The items were based on the results
from a pilot study (see Kay 1993) and the literature
review (see Appendix I). The assumption is made that if
preservice candidates did not find a particular learning
strategy helpful, they probably did not use it as their
main source of guidance. Similarly, if they found a strat-
egy to be a great deal of help, they probably used it
regularly to guide learning.
A principal components analysis was performed to
explore whether certain combinations of the 13 strate-
gies examined in this article were evident. As all com-
munalities were above 0.5 (Stevens 1992), the principal
component analysis was deemed an appropriate explor-
atory method (Guadagnoli & Velicer 1988). Both
orthogonal (varimax) and oblique (direct oblimin)
rotations were used given that the correlation among
potential strategy combinations was unknown. These
rotational methods produced identical factor combina-
tions, so the results from the varimax rotation (using
Kaiser normalization) are presented because they sim-
plify the interpretation of the data (Field 2005). The
Kaiser-Meyer-Olkin measure of sampling adequacy
(0.763) and Bartlett’s test of sphericity (P<0.001)
370 R. Kay
© 2007 The Author. Journal compilation © 2007 Blackwell Publishing Ltd

indicated that while the sample size was small (n=74),
it was acceptable.
Based on the point of inflexion on the scree plot,
eigenvalues set over one, and accepting factor loadings
of 0.4 or greater, the principal components analysis
extracted four patterns of strategy use that were labeled
collaboration, formal instruction, exploratory learning
and authentic tasks (learning to use the computer by
completing a meaningful task) (Table 1).
The internal reliability estimates for the four learning
factors were moderate, but acceptable, particularly for a
formative analysis (Nunnally 1978; Kline 1999): col-
laboration (r=0.85), use of authentic tasks (r=0.75),
formal instructions (r=0.73) and exploratory learning
(r=0.78).
Computer ability
Several researchers (e.g. Kay 1989a, 1989b, 1992b,
1993; Fulton 1997) have noted that computer profi-
ciency is an evolving concept based, to a certain extent,
on who is learning and what technology is available.
Perhaps the best one can do is to examine what skills are
important in a given context. Recall that the context of
this study includes the following key elements: preser-
vice teachers (grades 7–12), a focus of mathematics and
science, ubiquitous access to a computer and the Inter-
net, and a model that focuses on integration. It is reason-
able, then, to develop a comprehensive assessment of
computer ability based on the kind of tool that would be
used in an educational setting. Therefore, a composite
survey of ten computer skills was developed from a
content analysis of instruments designed to assess com-
puter ability of beginning teachers (Fulton 1997; Gunter
2001; Bartlett 2002; Albee 2003; Bucci 2003; Seels
et al. 2003; Thompson et al. 2003; Wepner et al. 2003;
Wilkerson 2003; Collier et al. 2004). The specific skills
identified in previous research that were measured in the
current study included: operating systems, communica-
tion, World Wide Web, word processing, spreadsheet,
database, graphics, multimedia, web page creation and
programming. In addition, two new scales were created
to assess the use of educational software in math and
science. It is important to note that all scales were
designed to be education-specific. In other words,
Table 1. Varimax rotated factor loadings on strategies used to learn new technology.
Strategy Factor 1 Factor 2 Factor 3 Factor 4
Collaboration
Working with a classmate or a friend 0.86
Asking face-to-face questions 0.84
Working with a group of people 0.80
E-mailing questions to instructor or friend 0.60
Formal instruction
Using help menu offered by software package 0.84
Working through online tutorials 0.76
Attending computer workshops 0.55
Exploratory learning
Systematic, slow trial and error on my own 0.91
Random trial and error 0.83
Authentic tasks
Teaching with computers 0.80
Reading article/books 0.73
Using computers for planning/research/organizing
for teaching
0.68
Completing assignments that require me to use
the computer
0.52
FACTOR EIGENVALUE CUMULATIVE PER CENT PER CENT VARIANCE
1 4.94 37.9 38.0
2 1.59 12.2 50.2
3 1.44 11.1 61.3
4 1.23 9.4 70.7
How preservice teachers learn to use technology 371
© 2007 The Author. Journal compilation © 2007 Blackwell Publishing Ltd

survey items focused on tasks that a teacher would most
likely need for the classroom. It is also critical to recog-
nize that this was a self-assessment of computer ability
using an online survey. While there is solid evidence to
suggest that the scale was valid (Kay 2005), actually
computer behaviour was not assessed. The reliability
estimates for the computer ability skills assessed in this
study were high ranging from 0.90 to 0.98 (Table 2).
Computer use in the classroom
A composite measure of computer use was developed
based on a comprehensive review of research designed
to assess computer use in preservice teachers (Garland
1999; Halpin 1999; Wang & Holthaus 1999; Maeers
et al. 2000; Milbrath & Kinzie 2000; Vannatta &
Beyerbach 2000; Baylor & Ritchie 2002; Pope et al.
2002; Compton & Harwood 2003; Russell et al. 2003;
Thompson et al. 2003). In the classroom environment
where preservice teachers did their practice teaching
(field placement), two categories of computer use were
examined – teacher-based and student-based. The
teacher-based items consisted of tasks that directly sup-
ported the teachers (e.g. creating lesson plans, hand-
outs, PowerPoint presentations and searching the web
for teaching resources), whereas the student-based
items consisted of tasks that directly supported student
learning in class (e.g. using word processing or spread-
sheet software, creating a web page, using subject-
specific software like ChemSketch, Fathom, or
Geometer’s Sketchpad, and interacting with learning
objects).
The items from this scale were not designed to form
coherent, reliable structures. The scale was designed to
be a comprehensive checklist of technology tools that
preservice candidates could use. However, given the
wide range of tools examined and the limited time in the
field placement (6 weeks), consistent and frequent pat-
terns of use would be difficult to attain. Therefore, factor
analyses and internal reliability estimates were not
calculated.
Procedure
Subjects were told the purpose of the study and asked to
give written consent if they wished to volunteer to
participate. The survey was administered at the begin-
ning of the year (September) and at the end of the year
(April). It took 15–20 min to complete.
Results
Perceived helpfulness
Overall, preservice teachers appeared to find collabora-
tive learning strategies the most helpful (M =2.59,
SD =0.88), followed by authentic tasks (M =2.41,
Table 2. Description of survey.
Scale construct measure No. items Range Mean (SD) Type of question Internal reliability
Ability
Operating system 10 0–40 25.0 (9.8) 5 pt Likert Scale r=0.95
Communication 10 0–40 22.1 (10.1) 5 pt Likert Scale r=0.90
WWW skills 9 0–36 22.6 (7.8) 5 pt Likert Scale r=0.95
Word processing 10 0–40 31.5 (8.0) 5 pt Likert Scale r=0.98
Spreadsheet 6 0–24 17.9 (5.9) 5 pt Likert Scale r=0.97
Database 10 0–40 17.2 (10.7) 5 pt Likert Scale r=0.95
Graphics 6 0–24 10.3 (7.4) 5 pt Likert Scale r=0.94
Presentation 6 0–24 10.6 (7.3) 5 pt Likert Scale r=0.93
Create web page 10 0–40 8.1 (10.8) 5 pt Likert Scale r=0.95
Programming 10 0–40 22.9 (12.0) 5 pt Likert Scale r=0.98
Science 11 0–44 7.8 (6.3) 5 pt Likert Scale r=0.94
Math 7 0–28 5.0 (5.5) 5 pt Likert Scale r=0.98
Use
Teacher 7 0–28 N/A 5 pt Likert Scale N/A
Student 18 0–72 N/A 5 pt Likert Scale N/A
N/A, not available; WWW, World Wide Web.
372 R. Kay
© 2007 The Author. Journal compilation © 2007 Blackwell Publishing Ltd

SD =0.81), exploratory learning (M =2.37, SD =0.42)
and formal instruction (M =2.21, SD =0.70). Refer-
ring to the Likert rating scale (0 =no help, 1 =little
help, 2 =some help, 3 =much help, 4 =a great deal of
help), it appears that collaborative learning provided
‘much help’, whereas authentic tasks, exploratory
learning and formal instruction provided ‘some help’. It
is important, though, to look at the individual items
within each learning strategy category when interpret-
ing helpfulness (Table 3). With the exception of formal
instruction, all categories had at least one item that was
perceived as less helpful and one item that was per-
ceived as more helpful. For example, e-mailing ques-
tions was not perceived as helpful as the other strategies
within the collaborative learning category. Systematic
trial and error was highly rated in the exploratory cat-
egory, but random trial and error did not fair as well.
Teaching with computers and using a manual were not
well received within the authentic learning category, but
completing assignments and preparing for teaching
were. All items in the formal instruction category,
though, were consistently rated lower than most other
help strategies.
With respect to average rating of helpfulness, com-
pleting assignments, asking face-to-face questions,
working with a classmate and using computers to
prepare for teaching were rated highly. Consulting a
book and using the software help menu were
cited as the least helpful learning strategies (see
Table 3).
It is worth noting that the correlations among all four
learning strategies were moderate, positive and signifi-
cant (r=0.28 to r=0.51) except for the correlation
between formal instruction and exploratory learning
which was not significant. The correlation among per-
ceived helpfulness of collaboration and authentic task
strategies was the highest observed (Table 4).
Over 58% (n=42) of all preservice teachers pre-
ferred a single learning strategy, 25% (n=18) selected
two primary strategies, and 16% (n=12) select three or
more strategies. In other words, preservice teachers
tend to depend on a single learning approach to the
exclusion of others. Accounting for overlap, prefer-
ences for specific strategies were as follows: 38%
(n=28) for collaborative, 31% (n=22) for authentic
learning tasks, 24% (n=17) for formal instruc-
tions and 35% (n=25) for exploration. Note that the
criterion for determining a primary strategy was to
select those with an average preference rating of 3
or more.
Table 3. Mean score for strategies used to learn new technology.
Item % rated as little or no help Mean SD
Collaboration
1. Working with a classmate or a friend 10.8 2.73 1.09
2. Asking face-to-face questions 9.5 2.92 1.10
3. Working with a group of people 10.8 2.46 0.92
4. E-mailing questions to instructor or friend 17.6 2.24 1.11
Total collaboration 2.59 0.88
Formal instruction
5. Attending computer workshops 20.3 2.26 1.21
6. Using help menu offered by software package 25.7 2.12 1.17
7. Working through online tutorials 21.6 2.27 1.11
Total formal instruction 2.21 0.70
Exploratory learning
8. Systematic, slow trial and error on my own 9.5 2.55 0.89
9. Random trial and error 18.9 2.20 0.97
Total exploratory learning 2.37 0.42
Authentic tasks
10. Teaching with computers 18.9 2.27 1.06
11. Reading article/books 39.2 1.74 1.02
12. Using computers for planning/research/organizing for teaching 12.2 2.64 1.17
13. Completing assignments that require me to use the computer 6.8 3.00 1.03
Total authentic tasks 2.41 0.81
How preservice teachers learn to use technology 373
© 2007 The Author. Journal compilation © 2007 Blackwell Publishing Ltd

Learning strategies and amount learned
Correlations
At-test comparing pre- (M =178.5, SD =73.9) and
post- (M =271.3, SD =60.8) scores for total amount
learned revealed a significant increase (t=14.2, d.f.
=72, P<0.001). This change was significantly corre-
lated with perceived helpfulness of collaboration (r=
0.44; P<0.001), using authentic tasks (r=0.36; P<
0.005), and formal instruction (r=0.24; P<0.05), but
not exploratory strategies (r=0.17; ns).
An analysis of the correlations among individual
ability sub-tasks (see Table 2) and perceived helpful-
ness of learning strategies revealed a more complicated
pattern. Significant positive changes in operating
systems skills, using the World Wide Web, presentation
software and programming ability were not signifi-
cantly correlated with any of the learning strategies
examined in this article. With the exception of program-
ming, these software areas are relatively common tools
for most users. Perceived helpfulness of collaborative
learning strategies was significantly and positively cor-
related with significant increases in more advanced,
specialized software areas involving spreadsheets,
databases, graphics, web page design, science and
mathematics. Authentic tasks were also correlated with
many of the more advanced software areas with the
exception of web page design. Perceived helpfulness of
formal instruction and exploratory methods were not
correlated of with significant changes in any of the soft-
ware ability sub-tasks, with the exception of science
(see Table 5).
The number of primary learning strategies (rating of
3 or more) preferred by preservice teachers was signifi-
cantly correlated with positive gains in more advanced
software packages including spreadsheets (r=0.29;
P<0.05), databases (r=0.42; P<0.01), web page
design (r=0.32; P<0.01), science (r=0.50; P<0.01)
and math (r=0.41; P<0.01). Correlations with more
basic software packages (e.g. basic operating skills,
word processing, using the World Wide Web and
e-mail) and the number of primary learning strategies
were not significant, with the exception of presentation
software (r=0.24; P<0.05).
Table 4. Correlations among learning strategies.
Collaborative Authentic tasks Formal instruction Exploratory
Collaborative 1.00 0.51** 0.44** 0.32**
Authentic tasks 1.00 0.48** 0.28*
Formal instruction 1.00 0.21
Exploratory 1.00
*P<0.05 (two-tailed); **P<0.01 (two-tailed).
Table 5. Correlation among perceived helpfulness of learning strategies and change in amount learned.
Collaborative Authentic tasks Formal instruction Exploratory
Operating system 0.19 0.18 -0.07 0.00
Communication 0.27* 0.22 0.15 0.10
WWW skills 0.23 0.18 0.07 0.10
Word processing 0.17 0.19 0.11 0.10
Spreadsheet 0.30** 0.29* 0.07 0.18
Database 0.36** 0.21 0.08 0.20
Graphics 0.31** 0.24 0.15 -0.03
Presentation 0.20 0.21 0.17 0.07
Create web page 0.38** 0.19 -0.24 0.04
Programming 0.19 0.11 -0.23 0.27
Science 0.54** 0.53** 0.38* 0.42**
Math 0.37* 0.53** 0.21 0.21
*P<0.05 (two-tailed); **P<0.01 (two-tailed).
WWW, World Wide Web.
374 R. Kay
© 2007 The Author. Journal compilation © 2007 Blackwell Publishing Ltd

Regression analysis
A stepwise multiple regression analysis was performed
to examine the relationship among the four learning
categories (collaborative, authentic tasks, exploratory,
formal instruction) and the change in total amount
learned. The stepwise method was chosen because there
was no previous theory to guide selection of predictors.
Collaborative learning was the only significant predictor
of change in total amount learned (R=0.443, F=17.4,
P<0.001). Multicollinearity did not appear to be a
problem because no Variance Inflation Factor (VIF) was
over the acceptable level of 10 (Bowerman & O’Connell
1990; Myers 1990) and the average VIF (M =1.4)
was not substantially greater than 1 (Bowerman &
O’Connell 1990) when all variables were entered into
the equation. The Durbin-Watson test produced a value
of 1.96 indicating no problems with respect to autocor-
relation of errors (Durbin & Watson 1951).
Learning strategies and use of technology
in the classroom
Correlations
Perceived helpfulness of authentic tasks was signifi-
cantly and positively correlated with use of computers
in the classroom for teacher-related tasks (r=0.41;
P<0.001) and student-related tasks (r=0.31; P<
0.01). Perceived helpfulness of collaborative learning
was significantly and positively correlated with teacher-
related tasks only (r=0.26; P<0.05). All other correla-
tions among learning strategies and classroom use were
not significant.
The number of primary learning strategies preferred
was significantly correlated with teacher-related tasks
(r=0.26; P<0.05) and student-related tasks (r=0.31;
P<0.01). In other words, students who used multiple
learning strategies were more likely to use computers in
their classrooms for administration, preparation and
student use.
Regression analysis – teacher use
A stepwise multiple regression analysis was performed
to examine the relationship among the four learning
categories (collaborative, authentic tasks, exploratory,
formal instruction) and use of computers in the class-
room for teacher-related tasks. Perceived helpfulness of
authentic tasks was the only significant predictor of a
preservice candidate completing teacher-focused com-
puting tasks (R=0.41, F=14.1, P<0.001). Multicol-
linearity did not appear to be a problem because no VIF
was over the acceptable level of 10 (Bowerman &
O’Connell 1990; Myers 1990) and the average VIF
(M =1.4) was not substantially greater than 1 when all
variables were entered into the equation (Bowerman &
O’Connell 1990). The Durbin-Watson test produced a
value of 2.04, indicating no problem with respect to
autocorrelation of errors (Durbin & Watson 1951).
Regression analysis – student use
A stepwise multiple regression analysis was performed
to examine the relationship among the four learning
categories (collaborative, authentic tasks, exploratory,
formal instruction) and use of computers in the class-
room for student-related computer tasks. Perceived
helpfulness of authentic tasks as a learning strategy was
the only significant predictor of student-related com-
puter tasks (R=0.32, F=8.2, P<0.01). Multicol-
linearity did not appear to be a problem because no VIF
was over the acceptable level of 10 (Bowerman &
O’Connell 1990; Myers 1990) and the average VIF
(M =1.4) was not substantially greater than 1 when all
variables were entered into the equation (Bowerman &
O’Connell 1990). The Durbin-Watson test produced a
value of 1.8, indicating no problem with respect to auto-
correlation of errors (Durbin & Watson 1951).
Individual differences (ability and gender)
Ability
Total computer ability was assessed by adding up all the
ability sub-tasks score at the end of the programme
(Table 2). There were no significant correlations among
perceived helpfulness of learning strategies (collabora-
tion, authentic tasks, formal instruction, exploration)
and total computer ability. Ability level was not corre-
lated with the number of primary learning strategies
preferred either.
Gender
Males and females did not differ with respect to per-
ceived helpfulness of learning strategies with one
exception. Females perceived collaborative learning as
significantly more helpful than males (P<0.05). Note
that the probability level was adjusted to compensate for
the number of t-tests performed (see Kirk 1982, p. 102)
(Table 6).
How preservice teachers learn to use technology 375
© 2007 The Author. Journal compilation © 2007 Blackwell Publishing Ltd

At-test indicated that females (M =1.51, SD =1.1)
were significantly more likely than males (M =0.83,
SD =0.98) to use more than one primary learning strat-
egy (t=-2.44, d.f. =70, P<0.05). Over 50% (n=25)
of females used two or more strategies, whereas only
22% (n=5) of males chose this multiple methods
approach.
Discussion
The purpose of this article was to examine and compare
the effectiveness of four strategies used by preservice
teachers to learn how to use new technology: collabora-
tion, authentic tasks, formal instruction and exploratory
learning, and four research questions were asked:
1Is there a significant difference among learning strat-
egies with respect to perceived helpfulness?
2Is there a significant difference among learning
strategies with respect to impact on learning new
technology?
3Is there a significant difference among learning
strategies with respect to use of technology in the
classroom?
4Are there individual differences in the use of learning
strategies with respect to computer ability and
gender?
Perceived helpfulness of learning
strategies (question 1)
The learning strategies explored in this study appeared
to differ with respect to perceived helpfulness. Collabo-
ration was seen as the most helpful learning approach, a
result that is consistent with previous research on the
positive effects of collaborative learning in general (e.g.
Johnson & Johnson 1994, 1998; Kagan 1997; Sharon
1999). While Rieman (1996) noted that there are a
number of barriers to asking other people for help, pre-
service teachers in a laptop environment, particularly
females, appeared to overcome these challenges. The
relatively limited usefulness of e-mailing a person
for help is also consistent with Rieman’s (1996)
observations.
Authentic tasks were also rated relatively highly
with respect to perceived helpfulness. This approach
has been strongly endorsed, but not rigorously evalu-
ated by a number of previous studies (Halpin 1999;
Moursund & Bielefeltdt 1999; Milbrath & Kinzie
2000; Vannatta & Beyerbach 2000; Pope et al. 2002;
Albee 2003; Doering et al. 2003; ISTE/NCATE 2003).
It is interesting to note that reading a book or manual
was associated with authentic learning tasks, but not
highly rated. It is possible that users consulted written
guidance when they had to get a specific task per-
formed, but that they found this kind of resource not
particularly helpful. It is not surprising that books/
manuals in this study were not perceived as being
helpful given that there was no formal textbook or
resource library with well-designed print materials
(Carroll 1990; Lazonder 1994; Lazonder & Van der
Meij 1995; Van der Meij & Carroll 1995). It is also
important to note, though, that simply teaching with
computers was not rated as a particularly helpful
‘authentic task’. Subjects had to be completing assign-
ments, using the computer to organize, or planning for
a class to gain the full benefit of authentic learning.
Exploratory learning was thought to be relatively
helpful and this finding is supported by the literature
(Dryburg 2002; Bartholomé et al. 2006). Systematic,
slow exploration where user takes time to observe the
screen was rated as being reasonably helpful, whereas
Table 6. Gender differences in perceived
helpfulness of learning strategies.
Learning strategy Females Males d.f. t
MSDMSD
Collaborative 2.78 0.68 2.20 1.10 69 -2.83*
Authentic task 2.50 0.75 2.23 0.89 69 -1.39
Formal instruction 2.26 0.99 2.12 0.84 69 -0.63
Exploration 2.37 0.85 2.40 0.84 69 -0.15
*P<0.05.
Actual probability value was adjusted based on number of t-tests performed (see Kirk
1982, p. 102).
376 R. Kay
© 2007 The Author. Journal compilation © 2007 Blackwell Publishing Ltd

as more random, trial and error was not thought to be
particularly useful.
Several researchers (Simmons & Wild 1991; Bannert
2000) noted that users would rather use collaborative
methods than take formal courses to learn new software
and these findings are consistent with the results
observed in the current study. Formal instruction
received the lowest ratings with respect to perceived
helpfulness.
It is interesting to note that preservice teachers appear
to prefer a single learning strategy above all others, a
finding that was not supported by Reimann and Neubert
(2000). This is a potentially risky approach that could
limit overall learning and increase frustration.
Impact of learning strategies on learning
It is worthwhile to note that preservice teachers were
reasonably accurate with respect to their ratings of how
helpful specific strategies were. Collaboration was rated
the highest and it was significantly and positively
correlated with significant increases in higher level
technology skills. Authentic tasks were correlated with
subject-specific software skills (math and science
software). In other words, preservice teachers appeared
to prefer learning subject-specific software in context.
Exploratory learning and formal instruction approaches
were not significantly related to acquiring higher levels
of technological proficiency with the expectation of
science software. However, this connection was elimi-
nated once a regression analysis was performed. In
other words, compared with other learning strategies,
these approaches do not translate into improved
computer-related knowledge.
It is critical to note that the number of primary learn-
ing strategies was significantly correlated with positive
and significant increases in more advanced software
tools. If an individual prefers collaborative learning or
using authentic tasks, gains in amount learned may be
achieved, whereas if formal instruction or exploratory
learning is the primary learning strategy, learning could
be severely inhibited because of a reluctance to try other
methods.
Impact of learning strategies on classroom use
Preservice teachers who preferred authentic tasks were
significantly more likely to use technology to support
their teaching and their students learning in the
classroom. Students who favoured collaboration, on the
other hand, used computers for teaching-related tasks
only. This is an interesting reversal to the findings
observed for total amount of computer knowledge
learned. Collaboration appears to improve personal
gains in technology use, but preservice teachers may
need to use computers in more authentic situations if
gains in used are to be realized by the students they
instruct. One of the difficulties observed in previous
studies was that preservice teachers had difficulty trans-
lating authentic experiences in school to field experi-
ences in the classroom (Simpson et al. 1999; Eifler
et al. 2001; Vrasida & McIsaac 2001; Brush et al.
2003). Clearly, this was not the case for teachers in the
current study. The highly integrated philosophy of
incorporating technology into numerous aspects of
teacher education, coupled with ubiquitous access to
computers, may have contributed to more successful
transfer into the ‘real world’ of teaching.
Note that the number of preferred learning strategies
was significantly related to both teacher and student use
of computers in the classroom. One could speculate that
preservice teachers who are open to using more learning
strategies are more confident because they are better
able to handle challenges that could arise.
Individual differences
Ability was not significantly related to perceived useful-
ness of the four help strategies examined in this study.
This finding appears to contradict previous research,
indicating that novices differ considerably in their
choice and use of learning strategies and resources
employed to learn new software and technology
(Rieman 1996; Jackson et al. 1998; Wood & Wood
1999; Lazonder 2000; Bartholomé et al. 2006). It is also
important to note that ability was not related to the
number of learning strategies preferred. In other words,
preservice teachers do not prefer more strategies simply
because they are more able users.
While previous bias in favour of males with respect to
computer attitude, ability and computer use has been
observed in the past (e.g. Kay 1992b, 2006a; Whitley
1997; Sanders 2006), this pattern was not repeated in
this study. In fact, females preferred collaborative learn-
ing, the most influential predictor of amount learned,
significantly more than males. This result, though, was
How preservice teachers learn to use technology 377
© 2007 The Author. Journal compilation © 2007 Blackwell Publishing Ltd

partially supported by Dryburg’s (2002) observation
that females preferred facilitated methods. Males and
females did not differ significantly with respect to the
other three strategies assessed. There is some evidence
to suggest that (1) ubiquitous access to computers and
the Internet can eliminate gender differences in preser-
vice teachers ability to use computers; and (2) females
benefit from this kind of environment more than males
(Kay 2006a). It is possible that preservice female teach-
ers thrive more in a laptop teacher education pro-
gramme because it encourages collaboration. Students
can ask about a computer-related problem anytime,
anywhere. On the other hand, an exploratory approach,
preferred by males (Dryburg 2002), may not serve them
as well with respect to learning and using new
technology.
Another critical finding was that females were more
likely than males to select a hybrid of learning tools, an
approach that was significantly correlated with the
amount learned and use of the computers in the class-
room by teachers and students. This pattern is new and
has not been reported in previous literature.
Caveats
The results of this study should be interpreted with
caution for the following reasons:
1The sample size was relatively small and consisted of
Canadian preservice teachers – the results may not
generalize to different educational systems in other
countries.
2Actual use of strategies was inferred from preference
ratings, but it was never assessed.
3The teacher education programme evaluated was
unique involving ubiquitous access to computers,
integration of technology into all courses as opposed
to offering a single computer course – different envi-
ronments might yield different strategy preferences.
4There were no formal computer manuals and text-
books used in this study.Well-designed written mate-
rials might alter strategy preferences.
Suggestions for educators
The current study is a first look at the effectiveness of
strategies used by preservice teachers to learn new
technology. The results provide useful information for
integrating technology into preservice education more
successfully.
Both collaborative learning and the use of authentic
tasks should be encouraged and facilitated in order to
increase preservice computer-related knowledge and to
have that knowledge translated into the classroom. Pro-
grammes that rely solely on formal instruction in com-
puter laboratories are unlikely to be successful. In fact,
workshops and non-integrated computer courses may
inhibit the progress of female preservice teachers who
prefer collaboration. Note that if only ‘basic’ software
skills are promoted, the approach one chooses to learn
appears to be irrelevant. It is only when more advanced
and subject-specific skills are required that collabora-
tion and authentic tasks may be required.
Exploratory learning, a practice followed by a major-
ity of new learners, was not particularly useful unless it
was systematic and slow. Random searching and trial
and error should be discouraged. Using a manual and
the software help menu were the least preferred learning
approaches, so extensive efforts to buy written materials
or have students rely on software help may not be
fruitful.
Finally, and perhaps most importantly, preservice
teachers, particularly males, should be encouraged to
use more than one learning strategy. Having more
than one tactic to rely on can lead to more gains in
learning and more frequent use of computers in the
classroom.
Summary
A comparison of four strategies used by preservice
teachers to learn new technology was completed. The
scale for assessing perceived usefulness of strategies
showed construct validity and a moderate level of
reliability. Collaborative learning, authentic tasks and
exploratory learning were the most preferred strategies
– formal instruction was the least preferred. Acollabora-
tive approach to learning was the best predictor of gains
in computer knowledge. Authentic tasks and collabora-
tive strategies were significant predictors of teacher use
of computers in the classroom. Preference for authentic
tasks was the only predictor of use of computers by
students. Regardless of strategy preference, selecting
more than one primary learning tool was significantly
correlated with amount learned and use of the comput-
378 R. Kay
© 2007 The Author. Journal compilation © 2007 Blackwell Publishing Ltd

ers in the classroom. Ability was not related to strategy
preference. Finally, females preferred collaborative
approach to learning, although they were significantly
more open to using multiple strategies than males.
Appendix I
Learning strategies scale items
Collaboration
1Working with a classmate or a friend
2Asking face-to-face questions
3Working with a group of people
4E-mailing questions to instructor or friend
Formal instruction
5Attending computer workshops
6Using help menu offered by software package
7Working through online tutorials
Exploratory learning
8Systematic, slow trial and error on my own
9Random trial and error
Authentic tasks
10 Teaching with computers
11 Reading article/books assigned in class
12 Using computers for planning/research/organizing for teaching
13 Completing assignments that require me to use the computer
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