The 4C/ID Model Applied to the Electrical Circuits Learning

Introduction

The 4C/ID-model has been applied mostly in technical secondary education (e.g. Sarfo & Elen, 2007) and in higher education (e.g. Lim, Reiser & Olina, 2009; Lim & Park, 2012), so this study is considered an unprecedented case in applying the model in an educational context. Thus, our goal was to study the effect of using a digital learning environment designed on the principles of the 4C/ID-model on student performance, perceived mental effort and instructional efficiency of 9^th grade students in a private school of Lisbon.

The 4C/ID-model fits into a cognitive perspective of learning, based on the Information Processing approach (Miller, 1956), Sweller’s Cognitive Load Theory (Chandler & Sweller, 1991) and Mayer’s Multimedia Learning Theory (Mayer, 2014) (cf. Chapter 3).

The central idea of ​​this model is that learning tasks should encourage students to integrate knowledge, skills, and attitudes that enhance the transfer of learning acquired in problem solving that involves new or unfamiliar situations to students (van Merriënboer & Sluijsmans, 2009). It is a model mainly intended for complex learning (cf. Chapter 6). The driving force of complex learning, based on the 4C/ID-model, is real-life task-based learning tasks, so learning tasks are the first component in designing an efficient learning environment, a vision that is shared by leading and most recent instructional design theories and models (Merril, 2012).

The model calls for four interconnected components to be taken into account when designing a learning environment for the development of complex skills:

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  Learning tasks, that are characterized by bringing the student into contact with all aspects of the complex competence at work. Ideally, these learning tasks should require learners to integrate and coordinate all or almost aspects that enable them to successfully perform the task and may include problem solving strategies and more routine aspects;

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  Supporting information, supports learning, providing pointers to problem-solving and reasoning performance of learning tasks. This type of information describes how the task domain is organized and how best to address domain-specific problems, bridging students’ prior knowledge with new knowledge;

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  Procedural information, that is the prerequisite for learning and performing the most routine aspects of learning tasks. This information is organized into small units of information and is presented to students in the moment they need it;

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  Task Practice, corresponds to additional exercises for training routine aspects of learning tasks, which is associated with a high level of automaticity. This component only exists when learning tasks do not advocate sufficient training to achieve the required level of automaticity.

A key feature of the 4C/ID-model is that initial tasks should be whole and meaningful, immediately exposing the learner to a holistic view (van Merriënboer, Kester & Paas, 2006), i.e., the model adopts a whole-part approach. Van Merriënboer, Kirschner & Kester (2003) point out that part-task approach may be not effective for complex learning environments that require the integration of skills, knowledge and attitudes. Why is 4C/ID-model suitable for complex learning? For many-sided tasks and many professional real-life assignments, it is essential that learners understand and learn relevant interactions and coordination between the various sub-tasks. By learning them in a separate way, these interactions may be missed. To ensure that all of them are worked, the 4C/ID-model proposes that whole tasks should be presented initially, although in a more simplified format (to reduce the intrinsic cognitive load) before processing to full complexity.