Applying the Motivation, Opportunity, Ability (MOA) Model, and Self-Efficacy (S-E) to Better Understand Student Engagement on Undergraduate Event Management Programs
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Considering the motivation, opportunity, ability (MOA) model and the self-efficacy (S-E) component of the social cognitive theory (SCT), this article aims to examine through a series of four research questions whether such models can help to determine how students engage with their program of study. Furthermore, the article will determine factors that influence student engagement in event management (EM) degree programs and seek to understand how EM students engage with their reading and interact within classroom-based environments. In doing so, the article will contribute to the existing debates on inclusive teaching and learning in higher education (HE), and provide a link towards creating more professional and employable graduates. Self-efficacy refers to beliefs in one's capabilities to learn or perform at designated levels. Much research has demonstrated that self-efficacy influences academic motivation, learning, and achievement; particularly within science, technology, English, and mathematics (STEM) subjects. With this in mind, this research aims to investigate the frame conditions mentioned that surround both self and group efficacy and seeks to reveal whether the above models can be used to better understand the engagement and subsequent performance of undergraduate EM students. This analysis will enable academics to better understand the role of MOA and S-E, how these develop over a program of study, and thereby provide a boost to student self-efficacy. By doing so, the best possible educational experience and results in higher education can be achieved.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it