ABSTRACT
Since the introduction of computers in music education, numerous software applications and hardware tools have been developed, leading to a variety of technology-enhanced practices to support instrumental music teaching and learning (e.g. Bauer, 2014; Brown, 2011; Dorfman, 2013; Webster, 2011). However, despite their attractiveness and their oftenproclaimed added value for music learning and teaching, educational technologies remain a topic of debate. Different scholars have problematized their design (e.g. Manzo, 2011), their reception (e.g. Addessi, Pachet, and Caterina, 2004) and their implementation within the curriculum (e.g. Beckstead, 2001; Hennessy, Ruthven, and Brindley, 2005). Himonides and Purves (2010) even question whether the role of music technology for teaching and learning is actually well understood. They argue that the critical assessment of the effectiveness of these technologies should be based on empirical work that begins with well-informed theories about the alignment of technology with learning. The crucial question is how educational technologies fit with the cognitive processes and how this can be shaped for effectiveness in music teaching and learning, rather than merely providing students with a fun experience. To tackle this question requires considering the processing components that frame the interaction with technology, such as working memory, long-term memory, schema-construction and schema-automation (see Sweller et al., 1998, for more details). These processing components define a cognitive architecture that allows humans to learn from their interaction with the environment. The effectiveness of learning can then be assessed in terms of the ease with which information may be processed by the learner’s cognitive architecture (Choi, van Merriënboer, and Paas, 2014). For music education, an assessment of the effectiveness of educational technology, viewed from the prism of a welldesigned cognitive architecture for music learning, is indeed much needed. The connection between technology and cognitive architecture may be decisive for whether technology enhances or degrades learning.
