January 2012 Volume 15 Number 1 - Educational Technology ...

y personalised context examples in the CAI sessions. Generally speaking, students of middle and low
problem-solving ability had positive mathematical belief after their exposure to personalised context
examples CAI.
Frith, Jaftha and Prince (2004) found that when students used interactive spreadsheet-based computer tutorials in
a mathematical literacy course, it brought to the foreground theories relating to the role of computer technology
as a mediator for learning of mathematics. Outcomes showed that simple definitions of disadvantage were
inadequate to account for the poor performance of students in the lower quartile. Olkun, Altun and Smith (2005)
investigated the possible impacts of computers on Turkish fourth-grade students' geometry scores and further
geometric learning. The study used a pretest–intervention–posttest experimental design. Results showed that
students who did not have computers at home initially had lower geometry scores. The result suggested that at
schools, it seemed more effective to integrate mathematical content and technology in a manner that enabled
students to make playful mathematical discoveries.
Ashton, Beevers, Korabinski and Youngson (2006) indicated that in a mathematical examination on paper, partial
credit was normally awarded for an answer that was not correct but nevertheless contained some of the correct
working. Assessments on computers normally marked an incorrect answer wrong and awarded no marks. This
can lead to discrepancies between marks awarded for the same examination given in the two different media. In
light of the findings, developments to the assessment engine have been made and some questions redesigned for
use in real automated examinations. The results were obtained as part of the Project for Assessments in Scotland
using Information Technology (PASS-IT), a major collaborative programme involving the leading educational
agencies in Scotland.
Based on Polya’s four problem-solving steps (understanding the problem, devising a plan, carrying out the plan
and looking back), Ma and Wu (2000) designed a set of interesting, active learning materials for teaching.
Research outcomes indicated both students’ learning interest and achievement had improved. Chang (2004)
incorporated strategies such as key-point marking, diagram illustration and answer review in the problem-solving
process and developed a process-oriented, computer-aided mathematics problem solving system. The system was
applied mathematical questions (mainly elementary-level arithmetic computation) with fifth graders as the
subjects of the empirical study. Results showed that the system was effective in enhancing low-achievers’
problem-solving ability.
Chang et al. (2006) proposed a computer-assisted system named MathCAL, the design of which was based on the
following four problem-solving stages: (1) understanding the problem, (2) making a plan, (3) executing the plan
and (4) reviewing the solution. A sample of 130 fifth-grade students (average 11 years old) completed a range of
elementary school mathematical problems. The result showed that MathCAL was effective in improving the
performance of students with lower problem solving ability. These assistances improved students’ problemsolving
skills in each stage.
Summary of the discourse above reveals that computer-assisted mathematics-problem-solving systems have a
positive impact on children’s problem-solving ability.
System design and Framework
The system design of this study is based on the mathematical problem-solving process proposed by Polya (1945).
It guides the children to think and solve the mathematical questions by using tag questions. Graphical
representation strategy used in addition and subtraction for lower achievement children proposed by Fuson &
Willis (1989) was taken as a reference for main design of strategy guide in solving the mathematics problem. In
the study of Fuson & Willis, they found that in the situation of addition and subtraction, when the semantic
structure conflicts with the solving strategy to get the unknown value, students might feel the answer is hardly to
get. Fuson & Willis developed a schematic drawing to assist the lower achievement students to solve the problem
in addition and subtraction with single step. The questions would be divided into four types based on the
schematic drawings: (1) PUT-TOGETHER, (2) CHANGE-GET-MORE, (3) CHANGE-GET-LESS, and (4) COMPARE.
Refer to Figure 1.
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