Modeling Participation Intention of Adults in Continuing Education - A Behavioral Approach
Bibliographic record
Abstract
The study examined how attitudes and subjective norms could be used to predict participation intention of adults in continuing education. In this research, attitudes comprised the two variables of positive attitude and negative attitude and subjective norms included normative belief and motivation to comply. Structural equation modeling using a maximum likelihood estimator was used to test the data collected from 752 adult respondents in Hong Kong, China. The results indicated that the relationships between positive attitude, negative attitude, normative belief and participation intention were significant. The relationship between motivation to comply and participation intention was found insignificant. However the strong relationship between motivation to comply and positive attitude revealed the indirect influence of motivation to comply on participation intention through positive attitude. The result also disclosed the phenomenon that normative belief was a better predictor of participation intention in continuing education than positive and negative attitudes in this context. The Theory of Reasoned Action (Fishbein & Ajzen, 1975) was used as the basis of reference in developing the conceptual framework of this study. The revised attitudes towards continuing education scales (Blunt, 2002) were shown to have validity in terms of the direct association with the various attitudes of adults towards continuing education. It was concluded that positive attitude, negative attitude, normative belief and motivation to comply with perceived social influence provided meaningful indicators of the respondents in the sample as well as reliable predictive variables to participation intention in continuing education.
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How this classification was reachedexpand
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 | 0.002 |
| 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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".