Sentence examples for deep learner model from inspiring English sources

The design of a deep learner model should begin with an explicit hypothesis (e.g. components of motivation).

We can extend the deep learner model taxonomy by incorporating a "meta" layer corresponding to cognition, affect, motivation, and learning strategy.

'Deep learner models' section introduces the concept of a deep learner model, which is a 360° perspective of each learner based on multiple dimensions including cognition, affect, motivation, and meta-cognition.

By a Deep Learner Model (DLM) we mean extending the core learner model to track not only what a learner knows, but also what the learner knows about their knowing, how they feel about their learning, their desires and motivations, the learning strategies they employ, and how they interact socially with others.

We also assume that learner feedback is dynamically generated from multiple deep learner models.

8 See discussion of deep learner models for examples of domain independent models in the inner loop.

In Open-ACRE deep learner models can be based on very simple aggregations to sophisticated machine learning algorithms.

Drawing on the work developed by du Boulay and colleagues (2010) we can classify deep learner models in terms of the taxonomy in Table 1.

It is suggested that deep learner models will become the vehicle for incorporating theoretical and practical advances in learning science into adaptive learning systems.

As adaptive systems incorporate deep learner models, they will need to evolve architecturally from closed data islands to open systems capable of exchanging data and services residing externally to the adaptive system proper.

10 It should be noted that Bloom's theory of mastery learning anticipates the idea of deep learner models by considering two principal student characteristics: cognitive entry behaviors and affective entry characteristics.