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"Cognitive" motivation: how can we model natural intelligence like that found in humans and other animals?
Important concepts of cognitive motivation theory include expectancy-value theory, attribution theory, cognitive dissonance, self-perception, and self-actualization.
Whereas behavioral motivation is essentially extrinsic, a reaction to positive and negative reinforcements, cognitive motivation is essentially intrinsic — based on the learner's internal drive.
The cognitive approach has proved useful in the analysis of several types of motivation, among them achievement behaviour, dissonance motivation, and self-actualization (see below Cognitive motivation).
She is coauthor of 5 intelligence tests and 2 self-report scales on academic anxiety and on cognitive motivation.
Defining autonomy as both an attitude towards learning and a capacity for independent learning, Dickinson (1995) proposes two theories of cognitive motivation: "attribution theory" and "self-determination theory".
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There are at least three main clusters that might be called the "math", "engineering", and "cognitive" motivations.
It also undertakes empirical analyses of user modeling to explore the factors influencing users׳ adoption of big data by integrating cognitive motivations as well as user values as the primary determining factors.
When facing information that corresponds with one's cognitive motivations, people accept that information happily and uncritically.
Since a participant should weigh affective and cognitive motivations before making decisions, critical decision differences can be expected between gifted and average adolescents.
The SRL dimensions that arise are: meta-cognitive regulation (commitment with the learning goal, planning and follow-up), cognition regulation (use of cognitive strategies), motivation regulation (adjustment of mood, making learning attractive), behavioural regulation (time and effort management) and environmental regulation (seeking material and social resources).
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