The Irish survey of student engagement: A comparative analysis with international surveys of student engagement.
Bibliographic record
Abstract
According to Coates (2010), measuring engagement can provide a means to develop a fuller understanding of the student experience above and beyond that ascertained through student satisfaction surveys. To examine this topic further, this research analyses the Irish Survey of Student Engagement (ISSE) and compares it to similar surveys of student engagement from other countries. The surveys deal with student engagement, rather than satisfaction and are modelled on the first such survey used in the United States and Canada, the National Survey of Student Engagement (NSSE). The underpinning design decisions for the NSSE is based on the premise that what students do during college counts more in terms of desired outcomes than who they are or event where they go to college (Kuh, 2001). The development of the NSSE was based on Chickering and Gameson’s (1987) seven practices in undergraduate education and other instruments that measured the student experience. In Ireland, the National Strategy for Higher Education to 2030 (HEA, 2011) recommended that every Irish higher education institution should put in place a comprehensive anonymous student feedback system, coupled with structures to ensure that action is taken promptly in relation to student concerns. This brought about the Irish Survey of Student Engagement (ISSE) and the central objective of this project is to develop a valuable source of information about students’ experiences of higher education in Ireland by asking students themselves. This paper aims to address the question: how does the Irish Survey of Student Engagement compare to other such surveys and is it achieving what it set out to do? The researcher proposes recommendations for improving the Irish Survey of Student Engagement and explores alternative options to measuring student engagement. The methodology employed is secondary research of the actual surveys used elsewhere and related academic journal articles on this topic. The research explores the background and context of the surveys and provides an overview of each. Throughout the paper, the local experience at the researcher’s Irish higher education institute is considered and used to support claims made, where possible. The surveys of student engagement have immense value and encourage a participation rate that could not be replicated through qualitative means. With some more rigid approaches and a combination of other methodological possibilities, the Irish survey could be more comparable internationally, but this may not be of great importance. Of utmost importance is comparisons of institutions within a country and due to the latitude given to institutions in how they participate, this is not always possible. This merits attention and a more cohesive approach should be developed in order address the important underpinning rationale for the research, to give students a voice and to improve student engagement.
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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 | 0.018 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".