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Chapter 1 : Context for the Irish Survey of Student Engagement

Notes for interpreting the data

How is the indicator score for each indicator calculated?

Indicator scores are NOT percentages but rather represent relative performance. They are calculated scores to enable interpretation of the data at a higher level than individual questions, i.e. to act as signposts to help the reader to navigate the large data set. Responses to questions are converted to a 60-point scale, with the lowest response placed at 0 and the highest response placed at 60. If a respondent selects “Quite a bit” as their response choice, their response converts to 40.

Indicator scores are calculated for a respondent when they answer all or almost all related questions. The exact number of responses required varies according to the indicator, based on psychometric testing undertaken for the North American National Survey of Student Engagement (NSSE). All responses are required for Higher-Order LearningQuantitative ReasoningLearning StrategiesCollaborative Learning, and Student-Faculty Interaction. All responses but one are required for Reflective and Integrative LearningEffective Teaching PracticesQuality of Interactions, and Supportive Environment. The indicator score is calculated from the mean of (non-blank) responses given. Indicator scores for any particular student group – for example, the first year undergraduate cohort – are calculated as the mean of individual indicator scores.

Consequently, and crucially, indicator scores cannot be combined across indicators to calculate an average overall indicator score in any meaningful or statistically sound way.

How can I best understand indicator scores for different groups?

Indicator scores provide greatest benefit when used as signposts to explore the experiences of different groups of students – for example, first year undergraduate students and final year undergraduate students, or Irish domiciled students and internationally domiciled students. Indicator scores also provide an insight into the experiences of comparable groups over multiple datasets – for example, the experiences of 2023 first year undergraduate students relative to 2022 first year undergraduate students.

How can I best understand indicator scores for different indicators?

Different indicators should not be compared to each other. For example, there is no simple, direct link between indicator scores for Higher-Order Learning and indicator scores for Reflective and Integrative Learning. No useful interpretation can be drawn from the fact that indicator scores for Higher-Order Learning are generally higher than indicator scores for Reflective and Integrative Learning.

However, the following differences could usefully be explored: Higher-Order Learning indicator scores for final year undergraduate students are higher than Higher-Order Learning indicator scores for first year undergraduate and taught postgraduate students; Reflective and Integrative Learning indicator scores appear notably lower for first year undergraduate students than Reflective and Integrative Learning indicator scores for final year undergraduate and taught postgraduate students. 

To date, analysis of data demonstrates that greatest variation is evident within higher education institutions rather than between institutions. This has also been found to be the case in other countries that have implemented comparable surveys.

This reinforces the view that students and staff within individual higher education institutions are best placed to interrogate their local data. They best understand the local context and are well-placed to plan appropriate enhancement actions on that basis.