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To illustrate our point, imagine an ITS with a perfect micro-adaptive module which would provide ideal scaffolding to each learner working on a particular Physics problem.
The learner working independently will use multiplication and division to solve time-and-distance equations as a homework assignment.
These elements are then combined, as in: The learner working in a small group will create a map of the school grounds in one-inch scale.
The learner working in a learning pair will write his or her own mathematics story problems that express time-and-distance equations in space-travel scenarios.
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Micro-adaptation refers to the variation in feedback and error correction as a learner works within a particular task or activity.
The study used a counterbalanced within-subject design with 34 online learners working in small groups.
Other instruments included an opinion questionnaire and observation of the learners working with a "think aloud" protocol.
According to this principle, redundant information can evoke extraneous processing and thereby tax learners' working memory capacity.
Indeed, although there may be some division of labour between learners working together, it will tend to be at low level, horizontal (across tasks), and flexible (Dillenbourg 1999).
Meanwhile, allocating grades to the individual attempts of the learners working in groups in no way offer any conflicts or contradictions with the notion of the cooperative learning environments they are engaged in since it promotes individual accountability (Johnson and Johnson, 2009).
Second, health professions students and their clinical teachers are co-learners, working together, along with patients and their families, to improve clinical outcomes and systems of care.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com