Table 2 Theoretical underpinnings of the 4C/ID model

Cognitive load theory [48, 49, 60]

Learning entails cognitively demanding processing, but people have limited processing capacity. Failure to learn can often be attributed to exceeding working memory capacity

Cognitive load management should be a significant consideration when designing instruction. The application of CLT prevents cognitive overload (e.g., by simple-to-complex sequencing of learning tasks with scaffolding) but also frees up cognitive resources (e.g., by automating skills with part-task practice) that can be allocated to learning (e.g., by increasing variability of practice)

Dual process theories (e.g., [25], [46])

Describe that cognitive processing can arise in two different ways: an implicit, automatic, unconscious process and an explicit, controlled, conscious process

The performance of complex skills is defined by a combination of controlled processes performed in a variable way across situations and automatic processes performed in a highly consistent way across situations

Reflective expertise [40, 58], Adaptive expertise [7]

A kind of expertise that entails performing familiar aspects of a task automatically so processing resources become available for dealing with unfamiliar aspects of the task

Training should facilitate the simultaneous development of domain-specific procedures for familiar, recurrent task aspects and a rich declarative knowledge base for dealing with unfamiliar, nonrecurrent aspects. Whole-task training helps learners coordinate these different task aspects

Schema theory (e.g., [2, 4])

Knowledge is organized in schemas: mental structures or frameworks that help us understand the world and allow problem-solving, decision-making, and reasoning

For nonrecurrent aspects, the development of a rich declarative knowledge base, or schema construction, is facilitated by inductive learning with learning tasks and elaboration of supportive information

ACT-R ([1])

Describes that human cognition emerges from a cognitive architecture consisting of six modules. A production system containing domain-specific IF–THEN structures interacts with declarative memory and the other modules to drive behavior

For recurrent aspects, the acquired declarative knowledge is compiled into domain-specific procedures or rules. Repetition strengthens these rules. The rule formation and strengthening processes drive the transition from controlled processing to efficient automatic performance

Cognitive flexibility theory [24, 31]

Describes that learning from case examples through different conceptual perspectives stimulates flexible interconnection of concepts in the mind

Processing information from multiple viewpoints is recommended to ensure that elaboration takes place

Deliberate practice [13, 14]

Describes expert performance as the result of individualized training by a qualified teacher who communicates the goal of the training and provides immediate feedback so that the learner can make repeated revised attempts

Deliberate practice relates to part-task practice, which allows the learner to repeatedly practice a recurrent task aspect to automate it while receiving immediate feedback