Computer game technology is poised to make a significant impact on the way our youngsters will learn. Our youngsters are ‘Digital Natives’, immersed in digital technologies, especially computer games. They expect to utilize these technologies in learning contexts. This expectation, and our response as educators, may change classroom practice and inform curriculum developments. This chapter approaches these issues ‘head on’. Starting from a review of the current educational issues, an evaluation of educational theory and instructional design principles, a new theoretical approach to the construction of “Educational Immersive Environments” (EIEs) is proposed. Elements of this approach are applied to development of an EIE to support Literacy Education in UK Primary Schools. An evaluation of a trial within a UK Primary School is discussed. Conclusions from both the theoretical development and the evaluation suggest how future teacher-practitioners may embrace both the technology and our approach to develop their own learning resources.
TopBackground
Since 2002, the Laboratory of Particle Technology and Multiphase Flow at State University of Campinas have developed new learning objects, mainly simulator modules, to evaluate their limitations as educational software.
Several denominations are found in the literature about the concepts of learning objects such as: instructional object, educational object, knowledge object, intelligent object and data object (Gibbons, Nelson, & Richards, 2000). Nevertheless, it does not matter what denomination has been improved, as the object can be practically the same.
The IEEE Learning Technology Standard Committee (2002) defines learning objects “as any entity, digital or non-digital, which can be used, re-used, or referenced during technology supported learning.” Chronological and instructional texts, class activities, books and revision aids are some examples of nondigital learning objects.
However, concerning digital learning objects, the main idea is to break the contents in small pieces that can be re-used in different learning environments, following the “spirits” of oriented-objects programming (Wiley, n.d., Verbert & Duval, 2004). According to Downes (2001), the idea of object-oriented tends toward the development of real pattern that, once defined, are copied and used in a part of the software. In this way, the simulators associated with the object-oriented programming can be classified in this definition.
According to Logmire (2001), for designing and developing material to be reused as learning objects, it should consist of features such as flexibility, easy to update, search and management, customization, interoperability, facilitation of competency-based learning, and increased value of content. All these characteristics show that the learning object models can make an easier and enhanced quality of learning, providing several facility tools for professors, students and administrators.
The simulation is a learning resource that allows the students to observe the different system behaviors through mathematical graphics or symbolical modeling of the phenomenon. In this context, the simulations have an important role to minimize the problems due missing equipment and laboratories for undergraduate students.
Tannous (2005) and Rimoli, Assis, and Tannous (2006) described some of the strategies and methodologies applied to develop learning objects (simulators with or without instructional program). It is important to remark that, in general a few works are applied to chemical engineering.
TopDevelopment Of Learning Objects
SEREA (Fluidized bed reactors modules) is simulator software for undergraduate chemical engineering students. It was developed to simulate the fluid dynamics parameters of different fluidized bed reactors, being divided by behavior of particles and project of distributors. As SEREA expanded, it was split in one real time process named “slipping controls.”
The following sections cover two modules for basic parameters that consist of the determination of minimum fluidization velocity and porosity, and bed expansion. The fluidization engineering concepts are based upon Geldart (1986), Kunii and Levenspiel (1991) and Martin (1998), and are also covered in other texts (Tannous, 1993).