Respondents categorised by broad ISCED field of study

Categories: Generic programmes and qualifications; Education; Arts and humanities; Social sciences, journalism, and information; Business, administration, and law; Natural sciences, mathematics, and statistics; Information and Communication Technologies (ICTs); Engineering, manufacturing, and construction; Agriculture, forestry, fisheries, and veterinary; Health and welfare; or Services

Readers interested in this aspect of the analysis are invited to view the full results, including all of the tests of statistical significance, in Appendix 4. Below is a summary of the results and an attempt to draw attention to the patterns in the results.

For Higher-Order Learning, Social sciences, journalism, and information students had statistically significantly higher indicator scores than all groups. Health and welfare students and Education students had the next highest indicator scores for this indicator.

Nearly all remaining fields of study form a cluster. Arts and humanities students and Business, administration, and law students were in the upper end of scores for the cluster, and Natural sciences, mathematics, and statistics students, ICT students, and Engineering, manufacturing, and construction students were in the lower range of scores for the cluster.

Agriculture, forestry, fisheries, and veterinary students and Services students had the lowest scores for Higher-Order Learning.

A similar pattern emerged for Reflective and Integrative Learning. Social sciences, journalism, and information students had statistically significantly higher indicator scores than all other groups.

Education students, Arts and humanities students, and Health and welfare students had the next highest indicator scores and they differed from all other fields of study.

Business, administration, and law students’ indicator scores were statistically significantly lower than this cluster, but also statistically significantly higher than Services students’ indicator scores, which in turn were statistically significantly higher than most of the remaining fields of study.

Natural sciences, mathematics, and statistics students, ICT students, Engineering, manufacturing, and construction students, Agriculture, forestry, fisheries, and veterinary students, and Services students made up the lowest-scoring cluster for this indicator.

Indicator scores differed substantially for Quantitative Reasoning.

Natural sciences, mathematics, and statistics students had the highest indicator scores, and they were statistically significantly higher than all other groups except Engineering, manufacturing, and construction students.

Engineering, manufacturing, and construction students had the second-highest indicator scores of all fields of study, and their indicator scores were statistically significantly higher than a cluster formed by Social sciences, journalism, and information students, ICT students, and Business, administration, and law students.

Services students clustered with Agriculture, forestry, fisheries, and veterinary students and Health and welfare students, as they had indicator scores in the middle of the range of indicator scores for this indicator.

Education students had lower indicator scores and they were statistically significantly lower than all other groups, with the exception of Agriculture, forestry, fisheries, and veterinary students.

Arts and humanities students had the lowest indicator scores, and they were statistically significantly lower than all other groups.

For Learning Strategies, Health and welfare students had statistically significantly higher indicator scores than nearly all groups. Education students had the next highest indicator scores.

Arts and humanities students, Social sciences, journalism, and information students, Business, administration, and law students, Natural sciences, mathematics, and statistics students, ICT students, and Agriculture, forestry, fisheries, and veterinary students clustered together and did not tend to differ statistically significantly from each other (though the indicator score for ICT students was statistically significantly lower than Social sciences, journalism, and information students and Business, administration, and law students in 2022, but hadn’t been in 2021).

For most of these fields of study, their scores were statistically significantly higher than the Engineering, manufacturing, and construction students and Services students.

For Collaborative Learning, Education students, Business, administration, and law students and Engineering, manufacturing, and construction students were the highest-scoring on this indicator and did not differ statistically significantly from each other.

While in 2021 Services students had statistically significantly higher indicator scores than nearly all groups, and in 2021 Agriculture, forestry, fisheries, and veterinary students were among the lower scoring groups, in 2022 they joined this highest-scoring cluster.

Natural sciences, mathematics, and statistics students, ICT students, and Health and welfare students all scored nearly the same, lower than the previously mentioned cluster but not always statistically significantly lower.

Arts and humanities students and Social sciences, journalism, and information students had statistically significantly lower indicator scores than nearly all other groups.

The remaining four indicators had similar response patterns by field of study group. For Student-Faculty Interaction, most fields of study clustered together, with Arts and humanities students and Health and Welfare students at the higher end of the cluster of scores and Social sciences, journalism, and information students and Natural sciences, mathematics, and statistics students at the lower end of the cluster.

The exception was the statistically significantly higher indicator scores for Services students compared to most other groups.

Similarly, for Effective Teaching Practices, all fields of study clustered together. Within the cluster, the indicator scores for Arts and humanities students and Health and Welfare students were the highest, and they were statistically significantly higher than Natural sciences, mathematics, and statistics students and Engineering, manufacturing, and construction students, whose indicator scores were in the lower range of the cluster.

For Quality of Interactions, the overall statistical significance of the analysis was being driven by small differences among the fields of study, but not by any one statistically significant difference between individual fields of study.

For Supportive Environment, nearly all fields of study clustered together. Within the cluster, the indicator scores for ICT students were at the higher end and Engineering, manufacturing, and construction students were at the lower end. Education students had the lowest indicator scores, and their scores were statistically significantly lower than the high end of the cluster (Social sciences, journalism, and information students, Business, administration, and law students, and ICT students).

For Learning, Creative and Social Skills, Social sciences, journalism, and information students and Business, administration, and law students had statistically significantly higher scores than most fields of study.

The next highest-scoring fields of study were a cluster formed by Education students, Health and welfare students, and Engineering, manufacturing, and construction students.

Services students fell in the middle of the distribution and did not differ statistically significantly from any field of study.

Finally, at the lower scoring end of the distribution was a cluster formed by Arts and humanities students, Natural sciences, mathematics, and statistics students, ICT students, and Agriculture, forestry, fisheries, and veterinary students.