Adaptive Motivation and Emotion in Education: Research and Principles for Instructional Design

Students frequently experience various types of motivation and emotion that contribute to their engagement and learning. However, translating research on motivation and emotion into educational practice and policy has so far been limited. To facilitate greater synergy among research, practice, and policy, this overview addresses educationally relevant motivation and emotion. This summary discusses different forms of motivation or emotion, their relevant theoretical basis, evidence on how they relate to academic engagement and learning, and potential classroom supports for adaptive motivation and emotion. The article concludes with five instructional design principles that can guide educators and policymakers in promoting adaptive student motivation and emotion: (a) support students’ feelings of competence, (b) enhance autonomy, (c) use personally relevant and active tasks, (d) emphasize learning and de-emphasize social comparison, and (e) encourage feelings of belonging

Classification of study traits into the Jones and Gosling (2005) 7-dimension dog personality framework.

<p><i>Note:</i> ‘Multiple’ means we could not classify the study trait name in to a single dimension, so the trait composed of multiple dimensions. The trait estimate was not used in calculating the personality dimension moderator because of this.</p

A descriptive summary of the studies used in the meta-analysis.

<p><i>Note:</i> If a range of N was given, two numbers are presented, the smallest number of dogs used from one estimate and the largest number of dogs from another estimate. If authors concluded in their study that they had evidence for consistency for at least one trait, the study was given a ‘1’ for consistency; if authors concluded in their study that they lacked evidence for consistency of any trait, the study was given a ‘0’ for no consistency. Likewise, if authors concluded in their study that they had evidence for a lack of consistency for at least one trait, the study was given a ‘1’ for consistency; if authors concluded that there was at least one trait that was not consistent the study was given a ‘1’ for no consistency. In both cases (‘consistency’ or ‘no consistency’) a zero is given if the study did not report a consistent trait or a trait that was not consistent. A ‘1’ for Puppy test indicates that dogs were tested as puppies (<12 months of age) during the first test period or not (a ‘0’). A ‘1’ and a ‘0’ for Puppy test indicates studies that presented from results from both age categories of dogs. If a range for test interval was given, two numbers are presented, the shortest interval and the largest interval. The average study effect size was calculated by multiplying correlations for each subgroup by the inverse of its variance. The sum of these products was then divided by the sum of the inverses.</p

Interaction of test interval and age of dog.

+<p>p<0.10, ^*p<0.05, ^**p<0.01, k =  number of studies, r =  bivariate correlation.</p><p><i>Note:</i> Short intervals were those where both behavioral assessments were conducted less than 10 weeks of one another; medium intervals had test intervals of 10 to 24 weeks, and long test intervals were greater than 24 weeks apart.</p

Interaction of personality dimensions and age of dog.

+<p>p<0.10, ^*p<0.05, ^**p<0.01, k =  number of studies, r =  bivariate correlation, Q-within was calculated from fixed-effects models.</p

Contrasts (Q-values) for personality dimensions in puppies.

+<p><i>p</i><0.10, *<i>p</i><0.05, ** <i>p</i><0.01, all values are Q values.</p

Description of the Jones & Gosling 2005 personality framework used for meta-analysis.

<p>Description of the Jones & Gosling 2005 personality framework used for meta-analysis.</p

Unrestricted ML meta-regression for ‘time interval between tests’ moderator.

<p>Unrestricted ML meta-regression for ‘time interval between tests’ moderator.</p