Reducing the implementation burden of Tangible User Interfaces in education

Since Tangible User Interfaces (TUI)s were introduced as an educational technology, it has gained sustained interest from lecturers and professionals in the field due to its ability to engage students in active learning. TUIs extend the domain of reality based human computer interaction by enabling users to interact with digital data through physical objects with representational significance. A user can interact with a TUI system by applying various object manipulations such as movement and rotation. In turn, a TUI responds by giving the user visual, auditory and/or tactile feedback. This novel human computer interaction technology enables the development of a wide variety of different systems that aid lecturing and learning activities in various educational categories and levels (Terrenghi et al., 2005), (Fjeld et al., 2007).

Although positive results have been reported in literature using current TUI architectures and toolkits, the acceptance of this educational technology is still being held due to the various difficulties current toolkits present during the implementation and usage of such TUI architectures. Some of these difficulties include; the required design and creation of a TUI table, continual software and hardware calibrations, procurement expenses, the big footprint required by the complete system itself and continual on-site technical expertise.

This research presents a new TUI toolkit called TangiBoard which is specifically designed to solve these difficulties while reaching a bigger audience at the same time. The toolkit’s new marker set enables the development of vertical TUI systems using technology and hardware already available in each classroom. Apart from reducing setup costs, time and technical expertise, the proposed toolkit facilitates system calibration and integration with existing TUI applications. This is enabled by a robust computer vision application that is able to run at real-time speeds while recognizing and tracking a contributed marker set using a regular web camera or a mobile device as the main camera.

The proposed toolkit was evaluated in terms of ease of implementation, learning effectiveness and recognition performance. Learning effectiveness experiment results concluded that by using this toolkit students were better able to understand the concept being taught when compared with traditional lecture delivery methods. Ease of implementation evaluations concluded that participants with previous experience in TUIs also preferred using the proposed toolkit.