What Is IT Doing In The Classroom?
Mr Graham McMahon BSc, Grad Dip Ed, MEd, MAIBiol
Penrhos College, Western Australia
ABSTRACT
This paper examines the relationships between technology-rich learning environments and the development of
higher order thinking skills in secondary school students. Computers first appeared in secondary classrooms
during the 1970s; their use has spread to all areas of the secondary curriculum. Initially heralded as a teachinglearning panacea, the success of the computer in education has been questioned by many authors. Arguments
supporting and disputing the potential and actual values of computers in the classroom are presented, followed
by an outline of a research thesis designed to answer the questions ‘What is the relationship between
technology-rich learning environments and the development of higher order thinking skills?’ and ‘To what
extent are higher order thinking skills demonstrated by students in a technology-rich environment?’. Based on a
PhD thesis in progress, the research will be conducted throughout the 2006 school year. Preliminary results
suggest that there is a significant correlation between the development of students’ computer skills and their
critical thinking ability. Further results will be presented at the ACEC 2006 conference.
INTRODUCTION
A search of the Internet for articles that examine the role of computers in education produces in excess
of 250 000 sites. Agnew (2002) states that researchers have tried to evaluate whether or not the use of
technology has a major impact on student learning. Agnew continues by explaining that students are
encouraged to develop higher order thinking skills, and that the results have been significant. However,
no formal statement about how the achievement of these skills have been observed or measured has
been made. Sherry and Jesse (2000) suggest that while educators seem to inherently ‘know’ that
technology increases student achievement, measuring the increase is challenging. Sherry and Jesse
suggest that we need to measure student motivation, metacognition, inquiry learning and the
application of the students’ skills.
This research will answer the following questions:
Q1 What is the relationship between technology-rich learning environments and the development of
higher order thinking skills?
Q2 To what extent are higher order thinking skills demonstrated by students in a technology-rich
environment?
THE ARGUMENTS – FOR AND AGAINST
A study of the use of web-based threaded discussion forums by students (Tay, Hooi & Chee, 2000)
reported a weak reasoning ability of students. This is ascribed to a school system that does not
satisfactorily cultivate students’ critical thinking skills.
An alternative view is provided by Swain, Greer & van Hover (2001), who argue that, when used
within a learning environment that endorses the cognitive flexibility theory, information and
communications technology (ICT) allows students to integrate concepts from seemingly unrelated
parts of the curriculum. However, teachers will need to become facilitators of learning rather than
authoritative figures. Concurrently, students will need to change from being passive recipients to
active constructors of knowledge.
Solomon (1993a) considered technology to fall into one of two groups of cognitive tools. One group
allows the more efficient processing of lower-order activities, thus allowing the user to focus on
higher-order thinking pursuits – the second group. Those who wish to utilise ICT must attain a level
of software proficiency. At a very basic level, a computer cannot help a student or teacher if neither
has the skills to operate it. The degree to which it may be useful in addressing higher order activities
will be determined by the range, and level, of technological skills.
This two-level model of technology is further developed by Jonassen (1996). Jonassen describes the
lower-order activities as being met by computer programs that he refers to as productivity tools. The
higher-order activities are addressed by software referred to as mindtools. Jonassen tends to classify
applications packages into one of these two groups based on the generalised nature of the software.
Kim and Reeves (2004) suggest that classification of software should be dependent on the purpose for
which the software is used. By this means, any computer program could be considered a productivity
tool or a mindtool when used as such. A relational database, for example, can be a low-level catalogue
of a set of music CDs, used to make the selection and location of a particular track easier to manage.
Alternatively, it could be used to generate knowledge by students developing their own search criteria,
to answer their own ‘what if?’ questions.
Jonassen (1996) did not consider word-processing to be a mindtool, regarding it more as a glorified
typewriter. However, in the same way that a spreadsheet can be used at two levels (a simple desktop
calculator or a mindtool), so can a word-processor. Sherry and Jesse (2000) described how wordprocessing activities could be used to enhance student thinking about the structure of text, and
increased collaboration between students when discussing texts, leading to the development of logical
and linguistic skills.
Passig (2001) contended that schooling needs to develop a different approach to developing cognition,
based on predicted changes to society resulting from innovations in technology. Whilst information as
an industry has grown from around 3% in 1860 to greater than 50% in 1990 (Huitt, 1995), Passig
warns us that the approaches to implementing ICT in education have made little difference to students’
cognitive skills.
Burbules and Linn (1991, in Maor & Phillips, 1996 online) have earlier agued that one of the goals of
science education is to help students to develop their thinking skills in order to generate the ability to
generate meaningful questions that can be investigated. Maor and Phillips pointed out that, while
computers and associated technology have the ability to support this goal, there is little evidence to
show that this has happened. Oppenheimer (1997) supported this argument. Furthermore, he claimed
that stakeholders, with an interest in perpetuating ICT in the classroom, produce research that
demonstrates academic improvements where no improvements have occurred. An example of this
paradox is provided by Stevenson (1999) when evaluating the effectiveness of a laptop computer
program in a school district. Students and teachers were surveyed over a three-year trial period.
Stevenson showed that activities such as note taking and writing did not change over the three years.
Simultaneously, activities such as electronic learning, cooperative learning and student use have all
decreased, and yet this report concluded that:
‘Teachers indicated that the laptop project generally had been satisfactorily implemented…’
‘…Use of the laptop computers as notebooks continues to be associated with sustained level of
academic achievement over time…’ (Stevenson, 1999, online)
When verbalising their thoughts, and reflecting on those thoughts, students have been shown to realise
that they were taking an active role in their learning (Maor & Phillips, 1996). Laurillard, (1993, in
Maor & Phillips, 2001 online) has suggested that this could be a shortcoming of computer-mediated
learning. There is no discussion or reflection between the student and the computer. Neither can the
computer intelligently analyse student’s input; the interpretation is based on preconceived, human
inputs. To accept that this argument is valid is to admit a poor understanding of the role of the
computer. Kim and Reeves (2004) claimed that this argument has arisen, and is maintained, by
regarding computers in education within a preconceived framework. Rather alarmingly Lee (2002)
reported that the main use of ICT, in subjects as diverse as Chinese and mathematics, is still
predominantly used to collect facts rather than promote higher order thinking. The move from quill to
slate, blackboard, whiteboard and computer has seen little change in pedagogy.
RESEARCH DESIGN
The research will be based within a social constructivist learning framework using a case study
approach. Sing (1999) argues that socialisation allows individuals to experience cognitive conflict, and
therefore also experience the confirmation or modification of existing beliefs. While the main interest
lies in exploring the idiosyncrasies of the social structure being examined, this does not prevent the
results being generalised. Cousin and Jenkins (2001) state that case study research supports a mix of
quantitative and qualitative methods. In doing so it supports the organisation of social data, preserving
the characteristics of the environment from which the data are gathered.
The data source will be the Year Nine student cohort in a metropolitan, independent girls’ school,
providing a sample size of approximately 150 students. This school has been implementing a notebook
computer program for eight years, in which all students in Years Five through to Year Ten use their
notebooks across all Learning Areas, every day at school. The majority of students enrol in the junior
years, although about one third of students begin in Years Seven and Eight, and approximately twelve
students enrol in Year Nine. The Year Nine cohort constitutes students that have had between one and
five years exposure to the technology-rich learning environment. Some students will buy a new
notebook computer after three years; others will economise by keeping their original notebook
computer for six years. Data about the length of enrolment at the school, and the age of their current
notebook computer, are held within the school’s database.
Teachers of the Year Nine students will also used as a data source. All staff are given a laptop
computer when they are first appointed to the school. Computer-based learning tools are developed by
staff specific to their Learning Areas to complement commercially available software. Teachers’
computers are renewed every two or three years.
Data Collection
The instruments used are the
Computer Laboratory Environment Inventory (CLEI);
Attitude towards Computers and Computer Classes (ACCC);
Australian Schools Computer Skills Competition (ASCSC);
Questionnaire on Teacher Interaction (QTI);
Ennis’ Weir Critical Thinking Essay (EWCTE);
Scientific Creativity Structure Model (SCSM); and
Level of Technology Integration (LoTi).
The first two instruments, CLEI and ACCC, are usually presented as one instrument. They were
developed within Western Australia and are designed to elicit students’ attitudes towards computers
and their learning environment. The ASCSC is an externally prepared test that students sit annually. It
is used to provide data about the students’ computer skills in Year Nine.
The QTI was originally developed in The Netherlands (Wubbels & Levy, 1993) and has been
modified within Western Australia. It has been used in many national and international studies of
learning environments (Fisher & Stolarchuk, 1998, et al) to determine the types of teacher:student
relationships that exist within a learning environment.
The EWCTE and SCSM are a part of the Year Nine students’ integrated curricula. The EWCTE
requires the student to formulate a complex argument in response to an earlier argument. In doing so
the test measures the student’s ability to analyse an argument and provide a logical, coherent response,
including creative and critical dimensions (Ennis, 1985). The SCSM is a relatively new instrument
modelled on the Torrance Tests of Creative Thinking (Hu & Adey, 2002). This test allows creative
thinking to be examined within the context of science education.
LoTi (Moersch, 1999) is an instrument designed to quantify the ‘technology-richness’ of a school. It
collates data based on classroom observations, teacher interviews and inventories of the technology
infrastructure. The results are expressed as a percentage of technology efficiency. Classroom
observations took place in classes utilising technology to achieve a subject specific learning goal.
These classes were videotaped, allowing them to be studied in greater detail when considering the
individual responses of students to set tasks, and the social interactions of the students. Data
concerning students’ length of enrolment at the school, and the age of their computers, is available
from the school’s database. Data collection will take place over three school terms.
The QTI, CLEI and ACCC provide individual students perceptions of aspects of the learning
environment measured on a five-point Lichert scale. The ICAS, EWCTE and SCSM scores are
converted to percentages. Data analysis involved the computation of Cronbach’s alpha coefficients to
determine the internal reliability of the instruments, and Spearman’s correlations of results to
determine the relationships that exist between the different learning environment factors.
PRELIMINARY RESULTS
At the time of writing (January 2005 – March 2006), the data collection is in progress. The results that
are presented below may have changed by the start of the Conference (October 2006).
Level of Technology Integration
Teachers were interviewed to ascertain their views about computers used as productivity tools and
mindtools within their Learning Areas. Responses include:
Table 1
Technology Use Across The Curriculum
Learning
Computer Use
Area
Productivity tool
Art
Net searching - masks from different
cultures, in conjunction with traditional
research
LOTE
Teacher’s & students’ voices embedded
into documents provide better access to
listening, speaking, practising LOTE in
between classes, at home etc
English
Work with paper in pen is enhanced by
technology to summarise group activities
Mathematics Skill building - elements of repetition,
explanation & non-judgemental feedback
for the students
SOSE
Apply skills learnt in technology classes
to SOSE subjects
Physical
Education
Science
Enhances students’ presentation tasks and
teacher presentations to students
to online text book allows quick gathering
of data, including sound/animation, not
available in an ordinary text book
Mindtool
Create individual artwork to publishing
standard on computer
Students become more critical of their
written & oral work.
Less formal teaching of grammar as the
students see for themselves the
connections between LOTE and English
Appears to improve logic. Essay structure
improves as students critically manipulate
text. This skill is transferred to
handwritten conditions
Students have the freedom &
responsibility to explore mathematics
Concept mapping software used to
arrange thoughts & ideas in a logical
order
Used in a metacognitive sense to
complete self-reflection on learning
Access Selecting/filtering data relevant
to a given task from the volumes of data
available
Teacher comments about the use of technology within specific learning areas include:
‘The girls are excited by the real-life context of their work, including budgeting aspects of art
production.’
‘It’s much more driven by them [students], and I find that, you know, they internalise, you know,
those areas much more quickly than what they used to before.’
‘The use of technology in the classroom requires a hell of a lot of courage given that the students
generally have greater technical skills, so they will not see you as the expert.’
‘Technology gives the flexibility to the students to ask the ‘what if’ questions – to really explore the
higher order thinking. To ask questions and to be building their own learning.’
‘Enthusiasm for technology in the classroom has increased over the years, because it allows you to go
beyond the classroom – beyond the paper and pencils.’
‘Phys Ed may be one of the areas where you would think we are not suited to technology when in fact
we make extensive use … of the technology.’
‘Computers allow students to have experiences that they couldn’t otherwise have.’
Table 2
LoTi Computer Efficiency Rating Chart
Descriptor
Level
Computer
Use %
A
B
C
Non-use
0
3
Awareness
1
6
Exploration
2
23
Infusion
3
20
Integration
4
30
Refinement
5
18
Total
100%
937.02/(291*4)= 0.805
Learner
Use %
D
100
100
100
100
100
100
No. of
computers
E
291
291
291
291
291
291
Product
B*C*D*E
F
0
17.46
133.86
174.6
349.2
261.9
937.02
Computer Efficiency Rating = 80.5%
Data in Tables One and Two suggests that the learning environment is indeed a technology-rich
environment, with a high level of computer efficiency as defined by Moersch (1999).
Critical Thinking Skills
Students’ scores from the EWTCE were correlated with their scores from the 2005 ASCSC test. The
questions within this test are divided into different skills groups. Cronbach’s alpha coefficients for the
EWCTE and ASCSC are calculated to be 0.63 and 0.61. This indicates that both instruments are
providing reliable data. Table 3 shows the degrees of correlation between the EWCTE scores and the
categories within the ASCSC.
Table 3
Correlation Coefficients For The EWCTE and ASCSC
ASCSC Hardware
Productivity Programming Software Web
Communication
Total
Tools
EWCTE 0.328* -0.045
0.125
0.254*
0.358** 0.292* 0.091
* Correlation is significant at the 0.05 level (1-tailed)
** Correlation is significant at the 0.01 level (1-tailed)
CONCLUSIONS
As this is ‘work in progress’ the conclusions are necessarily brief. Data pertaining to student
perceptions of the learning environment, teacher:student relationships, creative and critical thinking
measurements are yet to be collected and analysed. However, the preliminary results suggest that the
researched learning environment is one with a high level of technology use, and that there is a
significant correlation between students’ technology skills and their level of critical thinking, as
measured by the ASCSC and EWCTE.
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