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The Role of Motivation and Engagement in Students’ Enjoyment and Achievement in Science
Published in The Journal of The Future Project, 5, 20-23
Andrew J. Martin1, Roger Kennett2, Marianne Mansour1, Brad Papworth1, Joel Pearson1
1University of New South Wales, Australia
2The Future Project (The King’s School), Australia
August 2018
LAYPERSON’S OVERVIEW
Boosting the science skills and knowledge that underpin research and innovation enhances a
nation’s competitiveness and its citizens’ wellbeing. Unfortunately, statistics in recent years have
shown that science in Australia is under some threat. Science enrolments for senior school students
have been in a long-term descending trend and the science achievement of Australian high school
students has declined in recent years. At the same time, high school students’ interest in and
enjoyment of science can be difficult to sustain because science is a challenging subject. Improving
students’ science motivation and engagement has been identified as part of the solution to these
troubling statistics. Thus, in this investigation, we examined students’ science motivation and
engagement—and their links to students’ enjoyment and achievement in science. Our study of 160
high school boys and girls from two schools found that there were some key motivation and
engagement factors that are significantly linked to both enjoyment of and achievement in science.
Targeting these factors in science pedagogy may be one avenue for boosting science outcomes
among Australian high school students.
ABSTRACT
In recent years, Australian students’ participation and achievement in science has been declining,
leading to calls for research to identify factors that may be targeted to redress these troubling trends.
The present study focused on students’ motivation and engagement in science as potential factors
implicated in science outcomes. Specifically, the study explored the relationship between students’
motivation and engagement in science and their enjoyment of, and achievement in, science. The
sample comprised 160 boys and girls in Years 7 to 10 from two urban Australian schools.
Correlations demonstrated that key aspects of students’ science motivation and engagement were
indeed linked to their enjoyment of and achievement in science. Findings provide insight into
motivation and engagement factors to target in educational intervention seeking to optimise science
outcomes. Discussion of findings identifies next steps in assessment of students’ science motivation
and engagement, including examination of psycho-physiological (via biometrics) and neuro-
psychological (via electroencephalography; EEG) correlates.
INTRODUCTION
Enhancing the science knowledge and skills that drive research and innovation in diverse
aspects of society will boost a nation’s competitiveness (Australian Academy of Science, 2006;
Office of the Chief Scientist, 2012, 2014). However, Australian statistics show that science
enrolments for senior school students have been in a long-term descending trend (Office of the
Chief Scientist, 2014) and the science achievement of Australian students has declined in the latest
(2016) Trends in International Mathematics and Science Study. Improving and sustaining students’
science motivation and engagement has been identified as critical to addressing these alarming
statistics and to enhance students’ enjoyment of and achievement in science (Committee for a
National Science Communications Strategy, 2010). Therefore, this investigation examined students’
science motivation and engagement—and their links to students’ enjoyment and achievement in
science.
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In this study, motivation is defined as students’ energy, inclination, and drive to learn and
achieve; engagement is defined as the behaviour following from this energy, inclination, and drive
(Martin, 2007). Motivation and engagement are multidimensional, comprising positive and negative
thoughts, emotions, and behaviours. The Motivation and Engagement Wheel (Martin, 2007) is a
multidimensional framework that articulates these positive and negative motivation and engagement
factors (see Liem & Martin, 2012 for a review of its development—and for more detail on its
motivation and engagement factors). These factors are grouped into four themes: positive
motivation, positive engagement, negative motivation, and negative engagement. Figure 1 displays
the Motivation and Engagement Wheel.
<<Insert Figure 1 about here>>
Three factors reflect students’ positive motivation in science: self-belief, valuing, and learning
focus. Positive engagement in science also comprises three factors: planning and monitoring
behaviour, task management, and persistence. Three factors are part of negative motivation:
anxiety, failure avoidance, and low control. Finally, self-sabotage and disengagement are the two
factors reflecting negative engagement.
METHODS AND MATERIALS
Participants
The study comprised 160 students in Year 7 (29%), Year 8 (27%), Year 9 (22%), and Year 10
(22%). They were from an independent single-sex boys’ school (~70% of the sample) and an
independent single-sex girls’ school (~30%) in Sydney, Australia. The average age was 13.99 (SD =
1.24) years.
Procedure
Data collection was supervised by a university research assistant and involved the following
three components: an online demographic survey, an online science motivation and engagement
survey, and a hard copy science test. Students participated in small groups of 6-10 students.
Students completed all parts of the survey and test on their own.
Materials
Motivation and engagement in science. Science motivation and engagement were measured
using the Motivation and Engagement Scale (MES; Martin, 2015). The MES item wording was
adapted to science—an adaptation that has been previously validated (Green, Martin, & Marsh,
2007). Each of the 11 parts of Wheel was assessed via 4 items (thus, a 44-item instrument in total).
To each item, students rated themselves on a scale of 1 (Strongly Disagree) to 7 (Strongly Agree).
Each student’s responses to each of the 4 items were then aggregated to generate 11 average scores
for each student (each average score corresponding to each part of the Wheel).
Science enjoyment and science achievement. Science enjoyment was assessed with four items
previously validated by Green et al. (2007). As with the MES, these items were rated by students on
a scale of 1 (Strongly Disagree) to 7 (Strongly Agree) and then aggregated to generate an average
enjoyment score for each student. Science achievement was assessed using questions from the
Australian Council for Educational Research (ACER) Progressive Achievement Tests in Science
(PAT Science; Martin, Urbach, Hudson, & Zoumboulis, 2009). The PAT Science is a validated test
assessing scientific literacy, science knowledge, and application of scientific principles from Years
3 to 10. To ensure comparability across Years 7 to 10, we standardized (M = 0, SD = 1.00) the total
raw score for each year group.
Data Analysis
Data analysis centred on bivariate Pearson product-moment correlations using SPSS for
Windows (version 24). The minimum level of statistical significance was set at p < .05 (though, for
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completeness, we also signalled where an effect was significant at p < .10), with values of p < .01
and p < .001 reflecting more stringent levels of statistical significance. We also present effect sizes
for each correlation, based on Cohen’s d-value. For each d-value we indicate its magnitude, with d
= 0.2, 0.5, and 0.8 corresponding to small, medium and large effects respectively.
RESULTS
Results are presented in Table 1. In terms of correlation between positive motivation and
engagement and students’ science enjoyment, self-belief (r = .52, p < .001), valuing (r = .68, p <
.001), learning focus (r = .53, p < .001), planning and monitoring (r = .25, p < .01), task
management (r = .29, p < .001), and persistence (r = .49, p < .001) were statistically significant—all
associated with greater science enjoyment. Of this group of motivation and engagement factors,
relatively higher effect sizes were found for self-belief (d = 1.22), valuing (d = 1.86), learning focus
(d = 1.25), and persistence (d = 1.12).
<<Insert Table 1 about here>>
Regarding the correlation between negative motivation and engagement and students’ science
enjoyment, anxiety (r = -.19, p < .05), failure avoidance (r = -.17, p < .05), low control (r = -.28, p <
.001), self-sabotage (r = -.26, p < .01), and disengagement (r = -.70, p < .001) were statistically
significant—all associated with lower science enjoyment. Of this group of motivation and
engagement factors, a relatively higher effect size was found for disengagement (d = 1.96).
In terms of the correlation between positive motivation and engagement and students’ science
achievement, self-belief (r = .25, p < .01), valuing (r = .21, p < .01), and persistence (r = .14, p <
.10) were statistically significant—all associated with greater science achievement. Of this group of
motivation and engagement factors, a relatively higher effect size was found for self-belief (d =
0.52).
Regarding the correlation between negative motivation and engagement and students’ science
achievement, anxiety (r = -.20, p < .05), low control (r = -.26, p < .01), and disengagement (r = -
.24, p < .01) were statistically significant—all associated with lower science achievement. Of this
group of motivation and engagement factors, relatively higher effect sizes were found for low
control (d = 0.54) and disengagement (d = 0.50).
DISCUSSION
The present study sought to ascertain the link between students’ motivation and engagement
in science and their enjoyment of and achievement in science. Harnessing the factors in the
Motivation and Engagement Wheel (Martin, 2007), findings showed that motivation and
engagement were significantly associated with students’ enjoyment of and achievement in science.
Notably, of the Wheel’s factors it emerged that self-belief in science, valuing of science, learning
focus in science, and persistence in science were particularly linked to higher levels of enjoyment of
science—while disengagement was particularly linked to lower levels of enjoyment in science. In
terms of science achievement, self-belief was particularly linked to higher performance—while low
control and disengagement were particularly linked to lower levels of science performance.
One aspect of our research design important to note is that all our motivation and engagement
measures were based on students’ self-report. A great deal of prior research has shown this to be a
valid approach to assessment (see Liem & Martin, 2012 for review), but there is now a need to
expand assessment of these factors by drawing on latest developments in emerging fields of
psychology. Indeed, a major project along these lines funded by the Australian Research Council in
partnership with The Future Project is in progress. In this project, researchers harness latest
developments in technology to explore (a) psycho-physiological (via biometrics) and neuro-
psychological (via electroencephalography; EEG) correlates of students’ science motivation,
engagement, and achievement. There is growing evidence that psycho-physiology and neuro-
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psychology can inform and supplement educational practice (e.g., Brookman, 2016) and we seek to
examine this in relation to science motivation, engagement, and achievement.
CONCLUSION
Motivation and engagement are vital elements of students’ experience of and achievement at
school. The present study demonstrated that science is no exception, with distinct aspects of science
motivation and engagement significantly associated with their enjoyment of and performance in
science. These findings provide direction for specific motivation and engagement factors that might
be targeted in efforts to enhance science outcomes through school—and beyond.
ACKNOWLEDGEMENTS
This research was supported in part by the Australian Research Council (Linkage Projects) and The
Future Project (and its Consortium of Partners: The King’s School, Aegros BioPharma, Quantal
Bioscience, SanguiBio, Joan Lloyd Consulting).
REFERENCES
Australian Academy of Science (2006). Mathematics and statistics: Critical skills for Australia's
future. Melbourne, Australia: Australian Academy of Science.
Brookman (2016). Learning from educational neuroscience. The Psychologist, 29, 766-769.
Committee for a National Science Communications Strategy (2010). Inspiring Australia: A national
strategy for engagement with the sciences. Canberra: CNSCS.
Green, J., Martin, A.J., & Marsh, H.W. (2007). Motivation and engagement in English,
mathematics and science high school subjects: Towards an understanding of multidimensional
domain specificity. Learning and Individual Differences, 17, 269-279.
Liem, G.A., & Martin, A.J. (2012). The Motivation and Engagement Scale: Theoretical framework,
psychometric properties, and applied yields. Australian Psychologist, 47, 3-13.
Martin, A.J. (2007). Examining a multidimensional model of student motivation and engagement
using a construct validation approach. British Journal of Educational Psychology, 77, 413-
440.
Martin, A.J. (2015). The Motivation and Engagement Scale. Sydney, Australia: Lifelong
Achievement Group. (www.lifelongachievement.com)
Martin, R., Urbach, D., Hudson, R., & Zoumboulis, S. (2009). Progressive Achievement Tests in
Science. Melbourne: Australian Council for Educational Research.
Office of the Chief Scientist (2012). Health of Australian Science. Canberra: Australian
Government.
Office of the Chief Scientist. (2014). Benchmarking Australian Science, Technology, Engineering,
and Mathematics. Canberra: Australian Government.
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Figure 1.
Motivation and Engagement Wheel (reproduced with permission from
www.lifelongachievement.com).
Self-
belief
Learning
Focus
Valuing Persistence
Planning
Task
management
Anxiety
Failure
avoidance
Low
control
Self-
sabotage
Disengagement
POSITIVE
MOTIVATION
POSITIVE
ENGAGEMENT
NEGATIVE
MOTIVATION
NEGATIVE
ENGAGEMENT
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Table 1. Bivariate correlations (and effect sizes; Cohen’s d) between motivation and engagement in
science and students’ enjoyment of and achievement in science
Enjoyment of
science: r
Cohen’s Effect Size:
d (and magnitude)
Achievement in
science: r
Cohen’s Effect Size:
d (and magnitude)
Positive motivation in science
- Self-belief
.52***
1.22 (large)
.25**
0.52 (medium)
- Valuing
.68***
1.86 (large)
.21**
0.43 (small)
- Learning focus
.53***
1.25 (large)
.06
0.12 (negligible)
Positive engagement in science
- Plan and monitor
.25**
0.52 (medium)
-.09
0.18 (negligible)
- Task management
.29***
0.61 (medium)
-.06
0.12 (negligible)
- Persistence
.49***
1.12 (large)
.14†
0.28 (small)
Negative motivation in science
- Anxiety
-.19*
0.39 (small)
-.20*
0.41 (small)
- Failure avoidance
-.17*
0.35 (small)
-.07
0.14 (negligible)
- Low control
-.28***
.58 (medium)
-.26**
0.54 (medium)
Negative engagement in science
- Self-sabotage
-.26**
0.54 (medium)
-.08
0.16 (negligible)
- Disengagement
-.70***
1.96 (large)
-.24**
0.50 (medium)
† p < .10, * p < .05, ** p < .01, *** p < .001
