Although the current study provided a valuable insight into the nature and development of Australian high school students’ maths motivation, there were some limitations that will now be discussed. These related primarily to the students included in the final sample and the length of the study.
The final sample was comprised of students who fully completed the
questionnaires at both time-points. Unfortunately this excluded students who were absent on the day of testing. Although additional time was provided and the
researcher was present to assist any students with reading difficulties, the final sample only included students who completed the majority of the items. Students with
attendance problems or those who experience difficulty in completing work were unlikely to be included. This means that the final sample probably included a greater proportion of students with good attendance, literacy and concentration rates compared to the broader student population. As a result, the factor structure, nature of associations between constructs, developmental changes and gender differences were applicable to a somewhat engaged and capable student group. Therefore, the results are not necessarily reflective of students who attend maths class irregularly or who have concentration, reading or writing difficulties. This is unfortunate because it is these students especially whose maths motivation needs supporting. It would be ideal to track both students who attend class and those who regularly skip class. This would gain a more accurate picture of how maladaptive motivation develops, as the current
results may underestimate declines in adaptive motivation of the wider student population. Tracking both student groups would also identify potential differences in the nature of associations amongst constructs between the student groups, as well as gender differences that may more salient for less engaged students.
Secondly, in the ANOVA analyses, multiple comparisons were performed on each factor of maths motivation. When hypothesis testing, there is a risk that multiple comparisons can increase the chance of making a Type I error. The ANOVA analyses were partly hypothesis testing but also partly exploratory because prior research was lacking. This meant that a Bonferroni adjustment was not seen as fully applicable. Rather than solely using the significance level of the results, interpretation was guided by the assessment of effect sizes, as represented by partial eta squared. These were found to be quite small in a number of cases. This ensured that the role of the independent variables was not overemphasised. Although applying a Bonferroni adjustment can decrease the risk of Type I error, on the other hand this technique also increases the risk of Type II error, failing to reject a null hypothesis. As this is the first study to consider such a range of motivation constructs longitudinally with a sample of Australian rural high school maths students, it was considered appropriate to
recognise all significant findings at the conventional critical value (p < .05).
Another limitation of Study 1 was that it did not address maths motivation during the senior grades of high school. Although the current study intended to examine motivation across both junior and senior high school, it was not viable within the context of the participating schools’ timetables and the workload of the senior students. In NSW schools, grades 11 and 12 comprise the senior grades. Both grades were a busy and important time because these results contributed towards students’ final High School Certificate (the HSC) and score for admission to university. During the period of data collection senior students were preparing for their exams. Although not an ideal time of year, this was when the three schools had requested to participate. Due to consideration of the students’ workload and the need for maths classes to cover revision before the exams, it was inappropriate and impractical to invite Year 11 and 12 students to participate. However, the trajectory of maths motivation during
understanding of its development. These grades are when students may feel under increasing pressure to achieve and also when they make greater choices about the careers or study disciplines what they will and will not pursue post-high school. Perhaps these conditions make self-worth and fear of failure processes more salient than during previous grades. Tracking Australian high school students during this time would help us understand their experiences in more detail and potentially shed some more light on declining maths enrolments in senior grades and tertiary courses.
Although Study 1 covered two time-points, allowing motivation to be tracked across two academic years, a longer analysis of its trajectory with the same students was not possible. This means that only linear changes in maths motivation could be analysed between the two years. However, it is possible that some facets of maths motivation follow a non-linear trajectory, as the rate of change may increase, decrease, plateau or show a curvilinear trend across multiple years. At least three time-points are needed to identify the nonlinear curve in these types of changes. The current study tried to account for this by including multiple cohorts and testing differences in their rates of change. Apart from utility valuing there were no other indications of nonlinear trends. Nevertheless, following the same group of students across several years would delineate cohort versus longitudinal differences more accurately. A longer study that tracked students into their senior grades would also permit an analysis of potential nonlinear trends that arise during the crucial senior grades.