Section A: Interim Summary

Given the limited opportunity to collect commencing student data, significance testing was undertaken in the pilot phase to gradually build knowledge for the working party, while being mindful that alpha variations may also represent sample variation.

To this point, the instrument’s internal consistency, which measured student connectedness, maintained an excellent reliability coefficient over time and revealed the benefit of a later collection period. Overall, the high internal consistency of the connectedness scale strongly indicated that no item modifications were required and that the connectedness component of the tool can be confidently used in future collections. The overall connectedness mean of 42.03 (out of a maximum score of 50) at Time 1, indicated a moderately-high connected population, reporting the highest means for family, personal and community with the two lowest means being reported for lecturers and other students. This result was surprising, given the broad acceptance, by most members of the working party, that regional students were less prepared or supported by their families for university. The availability of local data was certainly effective in engaging staff to share and compare existing knowledge across a variety of sectors, and for the first time this data enabled staff to represent the campus context in in a favourable light when planning for resources and priorities, which were driven primarily by the needs of larger campuses.

At Time 2, the overall connectedness scale mean decreased to 40.02 (still in top 20%) Family and community connectedness means decreased slightly but were stable over time compared to significant mean decreases represented by p values for personal (0.000), other students (0.000) and lecturers (0.002) at the 0.05 level. The broad range of standard deviations over time indicated a continuing diversity of responses, but the differences in the range barely decreased from 1.89 at Time 1 to 1.81 at Time 2. The availability of such data created confidence that the tool captured sources of difference over time. Knowledge of these significant decreases, during first semester, was another unexpected finding for the working party. Many assumed that changes would not appear until the following semester, when

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students have settle into a routine, have had time to establish friendships/networks and when they would experience a change of lecturers and class groupings.

Compared to the connectedness scales, the student behaviour subscales at Time 1 and Time 2 conveyed a variety of low, moderate and high reliability coefficients (alphas) ranging from 0.510 – 0.840; the overall behaviour subscale reliability coefficient was 0.699 at Time 1 and dropped to 0.649 at Time 2. At Time 1 the two subscales of mood (0.775) and sleep (0.742) were above the recommended alpha level of 0.07 and well-being was close behind at 0.685. At Time 2, alphas for the subscales of sleep (0.840) and mood (0.816) increased to a good levels while well-being increased (0.719), for the first time, to the recommended alpha level of 0.07, and as such, indicating the three subscales could be retained for future collections and that a later collection point may reveal additional data.

The alphas for the remaining three subscales of substance use, risk taking and academic behaviours decreased over time, and all remained below the recommended alpha level of 0.70, thus signalling the need to revise or replace the these subscales before future collections. However, a suboptimal internal consistency result for academic behaviours over time was considered important to retain as some subscale items may be more significant after the first semester; suboptimal emotional behaviour alphas will be revisited at the end of the analysis of Section B regarding what modification will be required.

As previously stated, a high mean score was a desirable outcome, while a low score consistently signalled an opportunity for intervention. The mean decrease for sleep at Time 2 represents a change in sleep quality and may reflect students sleep habits after settling into their new circumstances and routines. Mean increases for risk taking and substance abuse at Time 2 indicate reduced participation in these adverse behaviours while reduced standard deviations indicates reduced variability of responses. Decreased means for sleep and mood, while not significant at Time 2, are offset by increased standard deviations, indicating a wider range of responses at this time; decreases so early into the university journey warrant investigation over a longer period to determine if this pattern stabilises or escalates. In this instance, significant behaviour differences were restricted to wellbeing (p = 0.028), which indicated the need for activities to support student well-being over time. Although not statistically significant, a reduced mean and standard deviation, for academic behaviours at Time 2, is also important as it indicates non-progression of engagement with positive academic behaviours, otherwise considered essential signposts of student development. The

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availability of this baseline behaviour data reveals that the nature of change is complex and the interplay of behaviours signal the importance of understanding local contexts.

The consideration that support required, beyond Orientation week and a few items from activities week, was alarming. The main concerns included how and when to offer additional support for students, in light of fractional support personnel employment, and escalating workloads for regional academic staff, who had the roles of lecturer and tutor. Support staff suggested it would be helpful to work more closely with academic staff, noting that they primarily worked with individual students and small groups on tasks, but did not have a clear understanding of unit and faculty requirements across year levels. Academic staff supported working closer together, in some capacity, and identified the urgent need to obtain approval from Faculty Heads to request shared campus times to enable students to access any additional supports, as timetable planning occurred a semester in advance. Despite the lack of detail (big and small) for the ‘intended intervention’ it was essential to let all participating faculties and staff know that a space/place for support activities would be required at the start of the next academic year.

Overall, this early process was also an essential step to involve more university staff to support regional students, to challenge and share understandings of connectedness and behaviour norms, agree about what to measure, for how long, and when to trial the collection procedures. The early data about connectedness sources contributed, in part, to Phase 2 of the research process (shown in Table 4.1) and guided the development of a cross-campus intervention to identify priorities and support more students. The next section focuses on the analysis of full data for 45 student pairs at Time 1 and Time 2 to determine if similar findings can be reflected.