Abstract
dc:description.abstract<p>This mixed-methods study examined the traits and engagement of five students. The students were high school boys at an independent (non-public) school. The participants’ Big Five personality traits and trait emotional intelligence were examined in depth. In addition, observation and interviews were employed to gain a deep understanding of the students’ behavioral and affective academic engagement. Many themes and subtopics were explored. The themes (and subtopics) were traits (conscientiousness, impulse control, extraversion, stress management, happiness, optimism, and self-esteem), engagement (participation, attention, effort, and perseverance), course content (general academics, English, math, history, and science), and academic tasks (in-class: passive vs. active, out-of-class: homework, reading, academic writing, and creative writing). For many of the participants, the traits of conscientiousness and impulse control were related to low engagement. Participants with these traits preferred active and group tasks to solitary, passive tasks. Some evidence also surfaced relating competence and autonomy to engagement. Participants were more likely to exhibit behavioral engagement when the academic work was free of significant challenge. Similarly, the participants showed higher levels of engagement when choice was offered. Further study is needed to explore self-efficacy, student–teacher relationships, and motivation in relation to academic engagement. </p>
Degree
thesis:*- Name thesis:degree_name
- Doctor of Education (EdD)
- Level thesis:degree_level
- Dissertation
- Discipline thesis:degree_discipline
- Education
- Year dc:date.available
- 2017
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Milliken, Michael Scott
- Contributors dc:contributor
-
- Michelle Collay
- Kim Roberts-Morandi
- Frank Doberman
Subjects
dc:subject × 3Identifiers
dc:identifier.*- Repository record dc:identifier
- https://dune.une.edu/theses/111
- OAI identifier oai:identifier
- oai:dune.une.edu:theses-1110