Academic journal article Educational Technology & Society

Modelling Mathematics Teachers' Intention to Use the Dynamic Geometry Environments in Macau: An SEM Approach

Academic journal article Educational Technology & Society

Modelling Mathematics Teachers' Intention to Use the Dynamic Geometry Environments in Macau: An SEM Approach

Article excerpt


Technology is important to the process of teaching and learning of Mathematics (National Council of Teachers of Mathematics [NCTM], 2000). It increases teachers' productivity in teaching and engages students in their learning of mathematics (Pierce & Ball, 2009). Thus, calls for the integration of technology in mathematics education have been made in various educational systems as seen in their official curriculum documents (Curriculum and Development Council & Hong Kong Examination and Assessment Authority, 2007; Curriculum and Planning Division, 2012; NCTM, 2000). Thus far, educational systems in the Western nations have responded to the call more rapidly than those in the East such as Hong Kong and Mainland China (Wong, 2003). In recent years, Macau, a special administration region of China, has become active in promoting technology integration in mathematics education among schools and encouraging teachers to use technology in the classroom. Dynamic geometry environments (DGEs) emerge as a technological tool to support mathematical teaching and learning and it has been integrated in the mathematics classroom in various countries (NCTM, 2000). Given its affordances in shaping mathematics education, the sole teacher education provider in Macau, University of Macau, has recently revised its curriculum to incorporate the use of DGEs into the pre-service and in-service courses.

Dynamic Geometry Environments (DGEs)

Dynamic Geometry Environments (DGEs) are tools originally designed for learning geometry in the 1990s. Nowadays, DGE has evolved to include features that can be used in teaching various subjects such as algebra, calculus and statistics. It provides a computer-based environment in which geometric figures can be constructed and manipulated with great ease (Straesser, 2002). In DGEs, users manipulate geometric figures using a visual interface and receive constructive feedback. In addition, multiple representations of the mathematical objects could be linked dynamically (Laborde, 2007). Using DGEs, teachers could represent and manipulate mathematical objects much more easily than before. Research on DGEs provided evidence in support of its ability to transform mathematics teaching and learning. These included the ability of DGEs to facilitate discovery or inquiry-based instruction (Laborde, 2007), to scaffold geometric problem solving (Straesser, 2002), such as using an inductive approach to explore and investigate mathematical proof, which are not usually achievable within a limited time span (Laborde, 2007). In doing so, students develop their higher-order thinking.

However, the use of DGEs in teaching mathematics is not without limitations (Anthony & Clark, 2011). An example is the low adoption of DGEs among teachers. In order to integrate DGEs into the classroom effectively, teachers have to change the existing mindsets and practices. Essentially, teachers have to learn how to use a new tool, spend more time in designing technology-based tasks to engage students in learning, and revamp their assessment protocols to be compatible with existing standards (Chan, 2015). These reasons could account for the low adoption rate among teachers who would merely use the DGEs as a supplementary tool instead of exploiting its affordances to facilitate students' learning (Ruthven, Hennessy, & Deaney, 2008).

Theory of Planned Behaviour (TPB)

Many models exist that describe and predict the use of technology, such as the Technology Acceptance Model (TAM) (Davis, Bagozzi, & Warshaw, 1989) and Theory of Planned Behaviour (TPB) (Ajzen, 1991). Among these models, the TPB has been used extensively, which assumes that the decision-making process of performing behaviours in a new situation is determined by one's behavioural intentions, which in turn is affected by three major variables: attitude towards the behaviour, subjective norms, and perceived behavioural control. …

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