Increasing creative self-efficacy: Developing the confidence
of biochemistry undergraduates to innovate
Simon Mark Payne
| David Edward Whitworth
Department of Psychology, Faculty of
Earth and Life Sciences, Aberystwyth
University, Aberystwyth, Ceredigion, UK
Institute of Biological, Environmental,
and Rural Sciences, Faculty of Earth and
Life Sciences, Aberystwyth University,
Aberystwyth, Ceredigion, UK
Simon Mark Payne, Department of
Psychology, Faculty of Earth and Life
Sciences, Aberystwyth University,
Aberystwyth, Ceredigion SY23 3UX, UK.
David Edward Whitworth, Institute of
Biological, Environmental, and Rural
Sciences, Faculty of Earth and Life
Sciences, Aberystwyth University,
Aberystwyth, Ceredigion SY23 3DD, UK.
This research received no external
Biochemistry graduates need to be creative, however assessing creativity requires
the production of novelty, judged by or against that of peers. A related phenome-
non is ‘creative self-efficacy’(CSE) –one's self-belief in producing creative out-
comes. CSE is a contributor to creativity, but is more easily assessed, and thus
more amenable for targeting pedagogically. To investigate interactions between
student CSE and the learning environment,abiochemistrylaboratoryexercise
was deployed within a ‘creative’module, wherein students created their own
experimental protocols. Students completed questionnaires at the beginning and
endofthemodule.Comparedto‘control’modules lacking overtly creative activi-
ties, the creative module significantly increased students' perceptions of their
own creativity and whether their studies had increased their creativity. Students'
confidence in meeting degree learning outcomes (for instance the ability to work
productively in a laboratory), and motivation to study, were also significantly
increased. Marks attained from the creative exercise correlated with students'
CSE, but surprisingly, students' expected marks correlated negatively with their
CSE, implying they had a poor understanding of the relationship between crea-
tivity and success. Our results suggest that the learning environment can posi-
tively affect students' CSE, promoting academic attainment of learning outcomes,
motivation, and their confidence as biochemists.
creativity, employability, innovation, social scaffolding
Biochemistry educators want their graduates to be curi-
ous, critical appraisers of information, able to produce
balanced rationales for investigations. These attributes
are enhanced by creativity, which is defined as the ability
to create novel, appropriate, and useful/impactful ideas
Employers place a premium on
innovation and creativity, which is reflected by their
inclusion in employer-informed degree accreditation
criteria such as those offered by the Royal Society of Biol-
Nevertheless, arts students typically score higher
than STEM students on self-rated creativity,
STEM students can benefit from an improved apprecia-
tion of their own creativity, increasing their competitive-
ness for employment.
Received: 17 June 2021 Revised: 18 March 2022 Accepted: 29 March 2022
This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided
the original work is properly cited.
© 2022 The Authors. Biochemistry and Molecular Biology Education published by Wiley Periodicals LLC on behalf of International Union of Biochemistry and Molecular
296 Biochem Mol Biol Educ. 2022;50:296–306.
1.1 |Creative self-efficacy (CSE)
Creative self-efficacy (CSE) is defined as ‘one's perceived
ability to create novel and useful ideas and/or products’,
and is positively associated with achievement in higher
CSE differs fundamentally from creativity in
that it is the perception of one's creativity, and is thus depen-
dant on a student's beliefs about their ability to achieve
mastery of their academic activities. Demonstrating creativ-
ity requires the production of novel ideas/products, which
is challenging to assess objectively, as it must be judged by
peers, or against that of peers.
However, CSE is compara-
tively easy to quantify, for instance using a questionnaire
for students to self-report their perceived creativity.
CSE strongly influences student aspirations, motivation
and accomplishment in higher education,
and stems from
four main sources: enactive mastery experiences, vicarious
experiences, verbal persuasion, and physiological affective
Enactive mastery experiences are when a student
reflects on the results of previous attempts at creativity,
and are the most powerful source of self-efficacy.
ous experiences are when students learn about their creative
abilities indirectly, by comparing their creative outputs to
those of peers.
Verbal persuasion is another indirect way
of increasing a student's CSE, when students are encour-
aged to view a creative task as achievable.
affective states are psychosomatic phenomena and generate
CSE if a student attributes their creativity to how they were
‘feeling’at the time.
1.2 |Benefits of increasing student CSE
CSE affects the creative goals that students set for them-
selves (e.g., challenging vs. non-threatening/facile), their
performance expectations, and whether or not they put
effort into their creative tasks. These beneficial behav-
iours are reason enough to promote the development of
CSE in students, however, the importance of CSE is fur-
ther highlighted when considering student stress, affect,
and mood, with low CSE being associated with unhelpful
cognitions (thoughts), affective responses (feelings), and
Stress and affect share a complex relationship, but
often, students will experience negative affective
responses (e.g., anger, contempt, anxiety) in academic
contexts that they find chronically distressing, when
(e.g., through a lack of CSE) they perceive themselves
unable to meet the demands of the situation.
moderate stress levels can stimulate creativity, intense
stress typically prevents creative thought.
students' creative abilities are assessed, educators should
increase their CSE through structured ‘low evaluative’
activities and formative assessments that engender a
sense of control.
Ideally, teaching environments would
be designed which regularly elicit learning experiences
akin to ‘flow’and ultimately, optimize creative perfor-
mances when the stakes are highest, for instance during
‘Psychological capital’(composed of hope, optimism,
resilience, and importantly, self-efficacy), correlates posi-
tively with creativity and the motivation to achieve, while
correlating negatively with perceived stress.
positive affect –aconsistentlystrongpredictorofacademic
performance –has been shown to promote a proactive,
approach motivation, which is influential in enhancing cre-
ativity and the use of creative cognition during study.
As might be expected, creative experiences and activities
are also generally associated with health and wellbeing ben-
efits for students, in addition to their academic benefits.
1.3 |Developing student CSE
The learning environment has a considerable impact on
the development of students' CSE, and the CSE-
Behaviour is the interplay
between personal factors (e.g., CSE) and the environment
in which the behaviour is to be enacted –for example,
the extent to which creativity has been role modelled by
the lecturer, or the inclusion/omission of creativity/
innovation in a module's learning outcomes.
educators will intuitively engender supportive environ-
ments which are likely to stimulate the development of
CSE, but there are relatively few published studies in the
literature which specifically leverage the psychology of
CSE in undergraduate science education.
This literature is mostly questionnaire-based, determin-
ing the strength and direction of association between CSE
and related constructs –such as science understanding,
student-teacher trust, transformational leadership, peers'
creative abilities, intrinsic motivation, originality, creative
self-concept, and expressiveness –while also evidencing
the ability of these constructs to predict CSE.
CSE and related constructs can be directly targeted by
intervention studies, yet very few intervention studies in
higher education have been published. A few researchers
have intervened and measured creative output as an out-
come measure in a ‘snapshot’fashion, but not targeted
cognitive variables that are associated with future creativ-
ity, such as CSE. Of the few studies that intervened and
assessed the resulting effects on CSE, none involved sci-
ence undergraduates. Dewett and Gruys
‘unconventional’teaching methods in an MBA course, in
an attempt to improve creativity via increased comfort
with risk and increased CSE. The intervention increased
students' CSE, but interestingly, it did not significantly
change how important students perceived creativity to be
PAYNE AND WHITWORTH 297
in the workplace, so it is unclear how sustainable such
CSE increases are and what study/work practices they
might prompt. Robbins and Kegley
developed an online
Creative Thinking Program founded on the principle of
‘psychological safety’as a facilitator of creativity. They
saw a statistically significant (but small) increase in CSE.
Byrge and Tang
administered an ‘embodied creativity
training program’and found that CSE can be enhanced
through targeted intervention, while Mathisen and
investigated the power of creativity training
on a variety of students, worker and teachers, and found
that CSE increased and that the CSE increase persisted
beyond the training course, compared to a control group.
No studies published to date have targeted the develop-
ment of student CSE as part of the teaching of a STEM
subject, despite CSE being linked to desirable student
outcomes, such as the confidence to innovate, increased
motivation to study, aspiration to succeed and increased
academic attainment. The potential cognitive, motiva-
tional, affective, and behavioural benefits of increasing
CSE led us to test the effectiveness of a theoretically-
derived teaching intervention designed to increase the
CSE of undergraduate biochemistry students, and to
investigate how CSE relates to biochemistry students'
perceptions of their academic abilities and outcomes.
A 19 item survey (File S1) was designed to gauge students'
CSE and related aspects of their lives/studies. They were
also asked to rate their attainment of ‘degree-level’learn-
ing outcomes and asked to predict their end-of-module
mark. Survey items were derived from established theoret-
ical propositions, for example, Bandura's
the construction of self-efficacy scales. Questions required
responses in a variety of forms, including Likert scales, free
text, and yes/no binary responses.
2.2.1 | Study design and survey
Student participants were enrolled on Life Sciences BSc
degrees. Three modules spanning the same semester
were selected for inclusion: one, the ‘Intervention Mod-
ule’(BSc year 2, n=20), contains an innovative creative
element, while the other two ‘Control Modules’make no
explicit efforts to develop student CSE (BSc years 1 and
3, combined n=32). Ethical approval was obtained from
the researchers' institution, informed consent was pro-
vided by students, and ethical principles - as outlined by
the American Psychological Association and British Psy-
chological Society - were adhered to throughout the
study. Students were provided with the context for the
study and a description of the data-management plan for
the project, and consented to complete early- and late-
semester questionnaires (weeks 1 and 11 respectively).
2.2.2 | CSE intervention
The creative exercise within the intervention module has
been described previously.
In brief, the module is
practical-based, with students undertaking a weekly
series of biochemistry ‘wet lab’experiments during the
first half of the module, following staff-provided experi-
mental protocols. During the latter half of the module
the students progress to design their own step-by-step
experimental protocols (working in pairs), which they
then implement in the laboratory, to determine how
many atoms of iron there are in a molecule of hemoglo-
bin (the ‘intervention’).
Assessment of students was
through their production of written reports for each
experiment, including the experiment for which they
developed their own protocols. Their protocols (i.e., the
products of their creativity) were not assessed directly.
The protocol-design task was well-scaffolded by con-
straining the available experimental materials, and with
an engineered system of feedback and reflection. Stu-
dents were set to work on the task in pairs for a week,
after which they discussed their draft protocols with a
member of staff. One week later they brought a revised
draft to the laboratory, which was then prototyped by a
pair of peers. Feedback from peers was reciprocal, inter-
active and happened in real-time as the draft protocols
were implemented. Finally, a week later a final version of
the protocol was implemented by the protocol creators.
The ‘intervention’had been implemented for several iter-
ations before this study and the both the module and the
intervention assessment gave reproducible marks
2.2.3 | Development of CSE
The intervention's scaffolding pedagogy, social elements,
and in-class feedback targeted the sources of CSE
298 PAYNE AND WHITWORTH
described previously (e.g., enactive mastery experiences,
vicarious experiences and verbal persuasion).
student participant attended each feedback session, and
to increase treatment fidelity care was taken to ensure
each student received consistent and accurate feedback
from staff, even during the peer-prototyping sessions. The
social interaction element of the intervention aimed to
create an environment where students were inspired to
act on their strengthening perception of CSE, and
because social interactions promote academic achieve-
The ‘low evaluative’context and controllability
engendered by the intervention are associated with lower
stress and more effective creative performance than
highly evaluative and uncontrollable creative
2.3 |Data analysis
For the key study variable CSE, paired responses (begin-
ning and end of the module) were obtained from 19 stu-
dents on the intervention module, and from 31 students
on the control modules, respectively. (For some between-
group analyses the full nof 20 and 32 were available.)
Likert scale data was assumed to be a discretisation of an
underlying continuous variable. The distribution charac-
teristics of all data were evaluated using visual checks
(histograms and normal Q–Qplots), skewness and kurto-
sis calculations, and statistical tests (Kolmogorov–
Smirnov and Shapiro–Wilk). The Kolmogorov–Smirnov
and Shapiro–Wilk tests tended to suggest non-normal
distribution, which was in conflict with observations
derived from the other inspection methods. Hence, para-
metric (ttests) and non-parametric (Mann–Whitney Uor
Wilcoxon Z) tests of difference, and parametric
(Pearson's) and non-parametric (Spearman's) tests of
association (corrected for multiple tests), were conducted
to provide a comparison of outcomes. The direction,
strength, and significance of correlations were broadly
similar for the parametric and non-parametric tests, so
the parametric tests are reported. Alpha was set at
p< 0.05 for all one- and two-tailed tests of significance.
3.1 |Teaching interventions can give
targeted increases in student CSE
Table 1displays descriptive data for the study's main vari-
ables, while Table 2summarises the early-to-late-module
change score comparisons between groups. The interven-
tion group's CSE significantly increased from beginning
to end of module (t
=2.970, p< 0.01; x=3.00 to
3.53/5), whereas the control groups' CSE did not change
significantly (x=3.61 to 3.74/5). The difference between
the two groups in CSE change from pre- to post- interven-
tion (0.13 vs. 0.53) was also significant (t
tailed p=< 0.05).
When measured early and late in the semester, the
importance participants placed on the need to be creative
in their studies remained relatively constant in both
groups (control: x=4.38 and 4.59/6; intervention:
x=4.45 and 4.65/6), as did their motivation to develop
their creative abilities (control: x=4.38 and 4.31/6; inter-
vention: x=4.45 and 4.55/6). The early-to-late-module
change scores for these two variables did not differ
between the two groups (t
=0.054, p> 0.05 and
=0.426, p> 0.05, respectively). Hence, other
between-group comparisons (control vs. intervention)
can be interpreted in light of the fact that the two groups
did not differ in these underpinning variables, suggesting
that the changes observed in CSE are a true reflection of
the intervention's effectiveness and not an artefact associ-
ated with changes in the two variables above.
Interestingly, at pre-intervention, only 10% of partici-
pants believed that they would know ‘where to start if
they wanted to learn to be more creative’, but at post-
intervention this rose to 55%. Students were not explicitly
trained in how to seek out creativity-raising opportuni-
ties, so it seems that their attitude to developing their cre-
ativity had been improved by virtue of their involvement
in the CSE intervention.
3.2 |CSE increases coincide with
enhanced perceptions of course creativity
and attainment of learning outcomes
At the beginning and end of the module participants
indicated the extent to which they believed they had
developed effective creative skills on past modules during
their degree. The intervention group's scores significantly
increased on average (t
=4.344, p< 0.001; x=2.05
to 2.90/4), whereas the control groups' did not (x=2.78
to 2.88 / 4). This difference in change from pre- to post-
between the two groups (0.09 vs. 0.85) was significant
=2.729, p< 0.01) and suggests that an increase in
contemporary CSE can retrospectively increase students'
perceptions of the historical development of their
Students also rated themselves on the ability to meet
five ‘degree-level’learning outcomes related to creativity
(‘How would you rate your own ability to …produce
novel protocols for use in a laboratory’,‘generate novel
and useful experimental data’,‘analyse and interpret
PAYNE AND WHITWORTH 299
novel data in a useful manner’,‘produce a report of novel
data and its interpretation, for use by other scientists’,
and ‘step into an unfamiliar laboratory and work produc-
tively’). Between the two surveys, participants in the
control group gained a significantly improved perception
of their ability to generate novel and useful experimental
data (x=3.50 to 3.91/6; t
p< 0.05), but no other perceived abilities changed
TABLE 1 Average scores for the main study variables
Control group Intervention group
Variable & item response scale range Early Late Difference Early Late Difference
Creative self-efficacy (1–6) 3.61 3.74 +0.13 3.00 3.53 +0.53**
Creativity skills from past modules (1–4) 2.78 2.88 +0.10 2.05 2.90 +0.85***
Importance placed on creativity (1–6) 4.38 4.59 +0.21 4.45 4.65 +0.20
Strength of motivation to develop creative abilities
4.38 4.31 0.07 4.45 4.55 +0.10
Strength of motivation for university work (1–6) 4.09 3.61 0.48 4.35 4.38 +0.03
Perceived ‘riskiness’(3to+3) 1.00 0.88 0.12 0.55 0.80 +0.25
Perceived impulsiveness (1–7) 4.72 4.50 0.22 3.95 3.90 0.05
Creative STEMM abilities (1–6):
Novel protocols 3.84 4.06 +0.22 3.48 4.08 +0.60***
Novel data 3.50 3.91 +0.41*3.75 4.40 +0.65**
Novel analyses 3.78 3.95 +0.17 3.50 4.15 +0.65*
Novel report 3.45 3.90 +0.45 4.00 4.63 +0.63**
Unfamiliar lab 3.75 3.69 0.06 3.88 4.58 +0.70**
Expected module score (%) 61.3 (7.8) 63.3 (9.3) +2% 60.0 (18.0) 63.6 (6.0) +3.6%
*p< 0.05; **p< 0.01; ***p< 0.001.
TABLE 2 Average change in study variables from pre-to-post intervention
Control group Intervention group
Variable & item response scale range
Early > late
Early > late
Creative self-efficacy (1–6) +0.13 +0.53 p< 0.05
Creativity skills from past modules (1–4) +0.09 +0.85 p< 0.01
Importance placed on creativity (1–6) +0.21 +0.20
Strength of motivation to develop creative
Strength of motivation for university work
Perceived ‘riskiness’(3to+3) 0.12 +0.25
Perceived impulsivity (1–7) +0.02 0.05
Creative STEMM abilities (1–6):
Novel protocols +0.22 +0.60 p=0.051
Novel data +0.41 +0.65
Novel analyses +0.17 +0.65
Novel report +0.45 +0.63
Unfamiliar lab 0.06 +0.70
Expected module score (%) +2% +3.6%
300 PAYNE AND WHITWORTH
significantly. In contrast, and mirroring the observed
increases in their CSE, the intervention group gained a
significantly improved perception of all five abilities
(increases ranging from 0.60 to 0.70/6; all one-tailed
3.3 |Contributory factors to academic
CSE and a disparity with extra-
Participants were asked on what experiences and
thoughts their academic creative ability self-ratings were
based. When asked early in the module, students cited
previous successful experiences as the primary positive
influence, while negative perceptions were based on pre-
viously unsuccessful experiences (File S2).
Participants were also asked whether their perceived
creativity in their studies differed from other life contexts,
and if so, why. Prior to the intervention 55% of students
from the intervention module indicated that their aca-
demic CSE was relatively lacking. Example rationales are
provided in File S2. However, at post-intervention, 75%
said they would rate their CSE similarly within university
and beyond, indicating that for the intervention group,
improved academic CSE self-rating had begun to
TABLE 3 Relationships between CSE, performance expectations, and actual performance (n=14)
Performance indicators and CSE variables
Not needed Not needed 0.587 (one-tailed
For analyses related to the intervention group's performance data, five participants were removed because they did not achieve their full potential due to non-
submission of one or more coursework components; n=14.
Grey shades indicate comparisons which would be self-self.
PAYNE AND WHITWORTH 301
converge with their CSE from contexts in which they
were more comfortable/confident (File S2).
3.4 |Positive relationships between CSE,
student-predicted grades and academic
The intervention took place in a year two module of a
3 year degree program, therefore participants' year one
average scores were available to the researchers, as were
their scores from the module itself upon its completion.
At pre- and post-intervention, participants were asked to
estimate the score they expected to achieve on the mod-
ule (and what informed their estimations –see File S2).
A series of correlation tests were performed to determine
the strength and direction of relationship between actual
scores, expected scores, and CSE (Table 3).
At pre-intervention, students generally predicted that
they would achieve a statistically similar module mark to
that which they achieved overall in their first year (60%
vs. 65%, respectively). However, despite the similar
means, the correlation between the two variables was
moderately strong and negative (r=0.427, p< 0.05)
suggesting a disconnection between past experiences and
future expectations. Nevertheless, at post-intervention
the students' predicted marks had risen slightly
(x=63.6%, SD =6.0), aligning more closely to their
actual module score (x=64.7%, SD =7.0).
In terms of CSE, the relationship between pre-
intervention and post-intervention CSE was almost non-
existent (r=0.076, one-tailed p> 0.05), suggesting inde-
pendence between the two variables and further
strengthening the study's justification (Table 3). The rela-
tionship between post-intervention CSE and actual mod-
ule score was stronger but did not quite achieve
statistical significance (r=0.376, p=0.093). Neverthe-
less, CSE did demonstrate a positive relationship with
module performance, suggesting its status as a contribut-
3.5 |CSE correlates with increased
motivation to study and may also impact
on risk-taking behaviour
Students experienced some interesting and potentially
beneficial changes associated with their participation in
the CSE intervention. Control group participants'
strength of motivation for university work substantially
decreased from beginning to end of the semester
(x=4.09 to 3.61/6; t
=1.789, two-tailed p=0.083),
whereas the intervention groups' improved slightly
(x=4.35 to 4.38/6; t
=0.101, p> 0.05). Late in the
module, the intervention group's increased CSE shared a
statistically significant, strong, positive relationship
(r=0.690, two-tailed p< 0.001) with their (slightly
increased) strength of motivation for university work
(x=4.38/6). For the control group, late in the semester,
there was no relationship between their CSE and their
motivation for university work (r=0.103, p=0.581). It
seems plausible that the intervention, which required on-
going completion of a series of tasks which clearly built
on one another, stimulated students' prolonged engage-
ment (and motivation) as well as developing their CSE.
At the beginning and end of the module participants
were also asked how ‘risky’(i.e., ‘prone to take a course
of action when the outcome is far from certain’) and
impulsive (i.e., ‘prone to act before giving the conse-
quences full consideration’) they would say they were in
everyday life. Statistically, participants in the control
group maintained their perceived ‘riskiness’(x=1.00
and 0.88/3to+3) and impulsiveness (x=4.72 and 4.50
/ 7), as did the intervention group (x=0.55 and 0.80/3
to +3; x=3.95 and 3.90/7, respectively; all two-tailed
pvalues >0.05). However, decreases in the average raw
scores for riskiness and impulsiveness can be seen for the
control group but less so for the intervention group. The
intervention sought to encourage risk-taking and creative
exploration through careful scaffolding and peer-to-peer
support, and this observation is therefore noteworthy, as
students often see creativity and risk-taking as synony-
mous, preferring to play-it-safe rather than be creative/
take a risk.
4.1 |An intervention targeted to
increase student CSE
The majority of life science undergraduates we surveyed
(55%) had lower CSE in the context of their studies than
in extra-curricular contexts. However, an intervention
which targeted the development of CSE increased stu-
dents' academic CSE, bringing it more in line with their
extra-curricular CSE. Intervention module students and
control module students exhibited no significant differ-
ences prior to the intervention, and both sets of students
were ‘primed’equally. The increase in CSE of the inter-
vention module students was not due to an increased per-
ception of the importance of creativity, or the motivation
to develop creativity, as these remained stable pre- and
post-intervention (Table 1).
The intervention was designed to draw on factors
known to promote CSE, such as a classroom
302 PAYNE AND WHITWORTH
environment that was conducive to non-threatening
peer-to-peer collaboration. By scaffolding the students'
learning activities, the module provided low-stakes ‘crea-
tive space’for enactive mastery experiences to occur. This
approach was reinforced through a system of reflection
and feedback, which is a valuable contributor to students'
introspection and metacognition.
on learning and performance, integrated with feedback
from an expert, should result in lasting increases in CSE
as an indirect form of enactive mastery experience.
would therefore be interesting to investigate whether the
ability to self-reflect is a mediator of the efficacy of this
Peer-to-peer support was also integral to the interven-
tion, with classmates providing a source of CSE through
verbal persuasion. Classmates worked together to critique
their own and their peers' creative process and output,
which would be expected to facilitate positive mood
states and enactive mastery through vicarious experience
and external perspective-taking.
4.2 |Benefits associated with increases
The increased CSE resulting from the intervention was
associated with other beneficial changes in the students'
survey responses. Compared to students on the control
modules, post-intervention the intervention group
exhibited increased motivation and risk-taking, with
increased confidence in their ability to achieve learning
outcomes and to enter the workplace (Table 1).
Increases in various types of academic self-efficacy
(e.g. reading self-efficacy) have been shown to be associ-
ated with improvements in that type of academic perfor-
Unsurprisingly, CSE is a contributing factor
to creative performance, albeit the strength of that contri-
bution can increase, remain stable, or decline over
It would be interesting to test whether increases
in CSE as a result of this intervention are also associated
with, or cause, an increase in creativity. However, as self-
efficacy and performance are reciprocally deterministic, a
‘chicken-and-egg conundrum’exists, making attempts to
establish causality difficult.
Increased CSE was associated with increased motiva-
tion for study at the end of the semester (Table 1). This is
important because completion of assignments, class
attendance, hours spent studying, and final grade, are all
associated with motivation.
Motivation to study is
time-dependent, for instance, how students compare
themselves to peers is a motivational factor that evolves
All-too-often, the strength and/or quality of
student motivation is diminished from the start to the
end of a semester,
but this was not observed in the
intervention group. Potentially, the tempo of the inter-
vention, with practical tasks being completed on an
ongoing basis clearly building on one another, stimulated
the students' prolonged engagement.
4.3 |Areas for further consideration
Increases in CSE can be lasting,
and it would be inter-
esting to undertake longitudinal studies to assess the fre-
quency with which CSE-promoting interventions should
be embedded in the curriculum. Will students with
increased CSE act on their increased sense of familiarity
with the creative side of their subject to further develop
their own creativity?
It would also be interesting to explore the relationship
between CSE and perceptions of risk-taking in students.
Risk-taking is domain specific
and future research
should investigate how risk and impulsiveness as specific
to academic pursuits, relate to student perceptions of cre-
ativity and CSE. Scaffolded opportunities for creative and
innovative exploration may attenuate students' belief in
the ‘riskiness’of creative behaviours –potentially
resulting in an altered approach, from avoidance of risk
to pursuit of opportunity.
The nature of the intervention we deployed in this
study meant that our sample size nwas necessarily small,
although nwas sufficient to demonstrate some significant
differences between intervention and control groups and
between early/late or pre-/post-intervention. The conclu-
sions drawn here are therefore somewhat tentative, and
it would be useful to target further larger modules with
bespoke CSE-targeted interventions to establish the gen-
erality of our observations, which would likely extend
beyond biochemistry to other STEM subjects and/or
school education settings.
It is concerning that there was a negative correlation
between students' prior marks and the pre-intervention
prediction of their marks in the intervention module
(Table 3). It could be that students were threatened by
the creativity element of the module, and this manifested
in a pessimistic score prediction, potentially also as a pro-
tective self-presentational strategy.
Nevertheless, an increased correlation between post-
intervention predictions and marks obtained for the
intervention module (Table 3), suggest the intervention
may help students link learning activities to learning out-
comes and performance. Students performed better than
they had expected to at the start of the semester, also
supporting the intervention's effectiveness of ‘coaching
up’students' creative abilities. In our experience ‘creativ-
ity-related’terms are usually missing from marking
PAYNE AND WHITWORTH 303
criteria and learning outcomes, making it difficult for stu-
dents to reconcile creativity with scoring points for
It is also noteworthy that many students' reported
that their pessimistic predictions of module marks were
due to previous negative experiences (Supplemental File
S2). This reinforces the importance of making creative
exercises low stakes and non-threatening, otherwise crea-
tive teaching exercises could be counterproductive,
reducing students' CSE.
4.4 |Implications for practice
CSE is an important component of the student experi-
ence that can be actively enhanced by pedagogic strate-
gies, although in higher education there is often little
opportunity for the required ‘risk-taking, collaborative
exploration and autonomy’,
and creative exercises also
have to compete for time with the taught curriculum.
Pedagogic interventions aside, leader CSE has an indirect
effect on the creativity (if not the CSE) of followers,
and academics can role-model creativity, encouraging
engagement of their students with the creative process.
The teaching intervention we deployed did not
require teaching staff to have strong CSE of their own.
Instead, it included (i) learning tasks designed to increase
students' CSE as well as a mode of assessment that
inspired creative efforts, and (ii) creation of a learning
environment that provided enabling resources, opportu-
nity structures, and was intended to reciprocally benefit
students' CSE. These are relatively simple teaching inter-
ventions that are grounded in strong psychological the-
ory, that target the four key sources of CSE (enactive
mastery experiences, vicarious experiences, verbal per-
suasion, and physiological affective states).
interventions can be relatively simple and straightfor-
ward to implement. For example, by providing ‘practice
sessions’where students can access the laboratory to
informally experiment with techniques and equipment,
by facilitating discussions between students to compare
or aggregate protocols/data, or by breaking up challeng-
ing tasks into smaller sub-tasks which can then be
brought together when the individual sub-tasks have
Potentially, the composition of the peer group ele-
ment of the intervention could be manipulated to
increase beneficial outcomes. Should students be given
autonomy to choose who to team up, or should they be
placed into groups that challenge their zone of proximal
development and role model effective study habits
Composition of the peer groups also has implications for
stress levels, social anxiety, risk-taking, and engagement
and so warrants further investigation if
CSE-raising interventions are to maximise their
Many excellent resources are available to help edu-
cators promote creativity in their teaching.
tunately, teaching practices such as modelling
creativity, allowing time for creative thinking, allowing
mistakes, and rewarding creative outputs, for example,
are often forgotten by students as their deadlines loom
and they revert to marks-acquisition mode to the exclu-
sion of skill development.
Potentially, inclusion of
‘innovation’and ‘creativity’terms throughout assess-
ment marking criteria and module learning outcomes,
their marks, and the value that teaching staff and
employers place on creativity and innovation. Ideally,
teachers would also design their modes of assessment
to explicitly include some opportunity for creative
thought and expression,
harnessing the benefits of
CSE-associated study behaviours.
David Edward Whitworth https://orcid.org/0000-0002-
1. Piffer D. Can creativity be measured? An attempt to clarify the
notion of creativity and general directions for future research.
Think Skill Creat. 2012;7:258–64.
2. Sokol A, Gozdek A, Figurska I, Blaskova M. Organizational cli-
mate of higher education institutions and its implications for
the development of creativity. Procedia Soc Behav. 2015;182:
3. Royal Society of Biology. Degree accreditation programme
handbook. London, UK: Royal Society of Biology; 2019.
Accreditation. Accessed 15 April 2021.
4. Furnham A, Batey M, Booth TW, Patel V, Lozinskaya D. Indi-
vidual difference predictors of creativity in art and science stu-
dents. Think Skill Creat. 2011;6:114–21.
5. Tierney P, Farmer SM. Creative self-efficacy: its potential ante-
cedents and relationship to creative performance. Acad Man-
age J. 2002;45:1137–48.
6. Schneider M, Preckel F. Variables associated with achievement
in higher education: a systematic review of meta-analyses.
Psychol Bull. 2017;143:565–600.
7. Plucker JA, Beghetto RA, Dow GT. Why isn't creativity more
important to educational psychologists? Potentials, pitfalls, and
future directions in creativity research. Educ Psychol. 2004;39:
8. Bandura A. Perceived self-efficacy in cognitive development
and functioning. Educ Psychol. 1993;28:117–48.
9. Bandura A. Self-efficacy: toward a unifying theory of behav-
ioral change. Psychol Rev. 1977;84:191–215.
10. Bandura A. Social foundations of thought and action: a social
cognitive theory. Englewood Cliffs, N.J: Prentice-Hall; 1986.
304 PAYNE AND WHITWORTH
11. Zimmerman BJ. Self-efficacy: an essential motive to learn. Con-
temp Educ Psychol. 2000;25:82–91.
12. Bandura A. Self-efficacy: the exercise of control. New York
City, NY: Freeman; 1997.
13. Lazarus RS, Folkman S. Transactional theory and research on
emotions and coping. Eur J Personality. 1987;1:141–69.
14. Epstein R. The big book of creativity games. New York City,
NY: McGraw-Hill; 2000.
15. Byron K, Khazanchi S, Nazarian D. The relationship between
stressors and creativity: a meta-analysis examining competing
theoretical models. J Appl Psychol. 2010;95:201–12.
16. Hamilton ER. Finding creativity and flow in a high-stakes
assessment context. Irish Educ Stud. 2013;32:109–17.
17. Csikszentmihalyi M. Flow: the psychology of optimal experi-
ence. New York: Harper & Row; 1990.
18. Sarwar F, Rahman SA, Bt PA. Psychological capital, a unique
resource to develop effective managers; relationship with crea-
tivity, achievement motivation and stress. Adv Sci Lett. 2017;
19. Baas M, De Dreu CK, Nijstad BA. A meta-analysis of 25 years
of mood-creativity research: hedonic tone, activation, or regula-
tory focus? Psychol Bull. 2008;134:779–806.
20. Rogaten J, Moneta GB. Use of creative cognition and positive
affect in studying: evidence of a reciprocal relationship. Creat
Res J. 2015;27:225–31.
21. Hughes G, Wilson C. In: Reisman F, editor. Creativity.
London, England: Innovation and Wellbeing. KIE Conference
Publications; 2017. p. 23–65.
22. Marsh HW, Martin AJ, Cheng JHS. A multilevel perspective on
gender in classroom motivation and climate: potential benefits
of male teachers for boys? J Educ Psychol. 2008;100:78–95.
23. Bandura A. The changing face of psychology at the dawning of
a globalization era. Can Psychol. 2001;42:12–24.
24. Richter AW, Hirst G, van Knippenberg D, Baer M. Creative
self-efficacy and individual creativity in team contexts: cross-
level interactions with team informational resources. J Appl
25. Beghetto RA, Baxter JA. Exploring student beliefs and under-
standing in elementary science and mathematics. J Res Sci
26. Choi JN. Individual and contextual predictors of creative per-
formance: the mediating role of psychological processes. Creat
Res J. 2004;16:187–99.
27. Karwowski M. It doesn't hurt to ask…but sometimes it hurts to
believe: polish students' creative self-efficacy and its predictors.
Psychol Aesthet Creat. 2011a;5:154–64.
28. Karwowski M. Teachers' personality and perception of the climate
for creativity in a school. Int J Creat Probl Solv. 2011b;21:37–52.
29. Karwowski M. Peer effect on Students' creative self-concept.
J Creat Behav. 2015;49:211–25.
30. Karwowski M, Gralewski J, Szumski G. Teachers' effect on Stu-
dents' creative self-beliefs is moderated by Students' gender.
Learn Individ Differ. 2015;44:1–8.
31. Karwowski M, Lebuda I. The big five, the huge two, and crea-
tive self-beliefs: a meta-analysis. Psychol Aesthet Creat. 2016;
32. Lim HS, Choi JN. Testing an alternative relationship between
individual and contextual predictors of creative performance.
Soc Behav Personal. 2009;37:117–35.
33. Puente-Díaz R. Creative self-efficacy: an exploration of its ante-
cedents, consequences, and applied implications. J Psychol.
34. Putwain DW, Kearsley R, Symes W. Do creativity self-beliefs
predict literacy achievement and motivation? Learn Individ
35. Tsai KC. The value of teaching creativity in adult education.
Int J High Educ. 2012;1:84–91.
36. Dewett T, Gruys ML. Advancing the case for creativity through
graduate business education. Think Skill Creat. 2007;2:85–95.
37. Robbins TL, Kegley K. Playing with Thinkertoys to build crea-
tive abilities through online instruction. Think Skill Creat.
38. Byrge C, Tang C. Embodied creativity training: effects on crea-
tive self-efficacy and creative production. Think Skill Creat.
39. Mathisen GE, Bronnick KS. Creative self-efficacy: an interven-
tion study. Int J Educ Res. 2009;48:21–9.
40. Bandura A. Toward a psychology of human agency. Perspect
Psychol Sci. 2006;1:164–80.
41. Whitworth DE. Recasting a traditional laboratory practical as a
“design-your-own protocol”to teach a universal research skill.
Biochem Mol Biol Educ. 2016;44:377–80.
42. Sahlberg P. In: Villalba E, editor. Measuring creativity. Luxem-
burg: OPOCE; 2009. p. 337–44.
43. Unrau NJ, Rueda R, Son E, Polanin JR, Lundeen RJ,
Muraszewski AK. Can Reading self-efficacy be modified? A
meta-analysis of the impact of interventions on Reading self-
efficacy. Rev Educ Res. 2017;88:167–204.
44. Bartimote-Aufflick K, Bridgeman A, Walker R, Sharma M,
Smith L. The study, evaluation, and improvement of university
student self-efficacy. Stud High Educ. 2016;41:1918–42.
45. Bandura A. On the functional properties of self-efficacy
revisited. J Manage. 2012;38:9–44.
46. Talsma K, Schüz B, Schwarzer R, Norris K. I believe, therefore
I achieve (and vice versa): a meta-analytic cross-lagged panel
analysis of self-efficacy and academic performance. Learn
Individ Differ. 2018;61:136–50.
47. Lepper MR, Corpus JH, Iyengar SS. Intrinsic and extrinsic
motivational orientations in the classroom: age differences and
academic correlates. J Educ Psychol. 2005;97:184–96.
48. Martin AJ, Marsh HW. Academic resilience and its psychologi-
cal and educational correlates: a construct validity approach.
Psychol Schools. 2006;43:267–81.
49. Pintrich PR, Zusho A. In: Smart JC, Tierney WG, editors.
Higher education: handbook of theory and research. Volume
17. Dordrecht, Germany: Springer; 2002.
50. Bo WV, Loh EKY, Tse SK. In: Zheng B, Guo Z, editors. Acquisi-
tion, assessment and application: theory and practice of teach-
ing Chinese in higher education. London, UK: Sinolingua
London Ltd; 2016. p. 111–28.
51. Pulfrey C, Buchs C, Butera F. Why grades engender
performance-avoidance goals: the mediating role of autono-
mous motivation. J Educ Psychol. 2011;103:683–700.
52. Smith L. Changes in student motivation over the final year of
high school. J Educ Enq. 2004;5:64–85.
53. Woodrow L. In: Ushioda E, editor. International perspectives
on English language teaching. London, England: Palgrave Mac-
PAYNE AND WHITWORTH 305
54. Tyagi V, Hanoch Y, Hall SD, Runco M, Denham SL. The risky
side of creativity: domain specific risk taking in creative indi-
viduals. Front Psychol. 2017;8:1–9.
55. Bandura A, Locke E. Negative self-efficacy and goal effects
revisited. J Appl Psychol. 2003;88:87–99.
56. Kosakowska-Berezecka N, Jurek P, Besta T, Badowska S. Self-
presentation strategies, fear of success and anticipation of
future success among university and high school students.
Front Psychol. 2017;8:1884.
57. Török L, Szab
o ZP, T
oth L. A critical review of the literature on
academic self-handicapping: theory, manifestations, prevention
and measurement. Soc Psychol Educ. 2018;21:1175–202.
58. Ceci MW, Kumar VK. A correlational study of creativity, hap-
piness, motivation, and stress from creative pursuits.
J Happiness Stud. 2016;17:609–26.
59. MacLaren I. The contradictions of policy and practice: creativ-
ity in higher education. Lond Rev Educ. 2012;10:159–72.
60. Bronson P, Merryman A. The creativity crisis. New York City,
NY: Newsweek; 2010. https://www.newsweek.com/creativity-
crisis-74665. Accessed 1 July 2019.
61. Huang L, Krasikova DV, Liu D. I can do it, so can you: the role
of leader creative self-efficacy in facilitating follower creativity.
Organ Behav Hum Dec. 2016;132:49–62.
62. Zhang X, Bartol KM. The influence of creative process engage-
ment on employee creative performance and overall job perfor-
mance: a curvilinear assessment. J Appl Psychol. 2010;95:
63. Tudge J. In: Moll LC, editor. Vygotsky and education: instruc-
tional implications and applications of sociohistorical psychol-
ogy. New York City, NY: Cambridge University Press; 1992.
64. Furrer CJ, Skinner EA, Pitzer JR. The influence of teacher and
peer relationships on students' classroom engagement and
everyday motivational resilience. Natl Soc Study Educ. 2014;
65. James A, Brookfield SD. Engaging imagination: helping stu-
dents become creative and reflective thinkers. San Francisco,
CA: Jossey-Bass; 2014.
66. Sternberg RJ, Williams WM. How to develop student creativity.
Alexandria, VA: Association for Supervision and Curriculum
67. Lieberman DA, Remedios R. Do undergraduates' motives for
studying change as they progress through their degrees? Br J
Educ Psychol. 2007;77:379–95.
68. Sternberg RJ. The concept of intelligence and its role in lifelong
learning and success. Am Psychol. 1997;52:1030–7.
69. Bandura A. Social cognitive theory in cultural context. Appl
Psychol Int Rev. 2002;51:269–90.
70. Caprara GV, Fida A, Vecchionem M, Del Bove G, Vecchio GM,
Barbaranelli C, et al. Longitudinal analysis of the role of per-
ceived efficacy for self-regulated learning in academic continu-
ance and achievement. J Educ Psychol. 2008;100:525–34.
71. Zimmerman BJ, Bandura A, Martinez-Pons M. Self-motivation
for academic attainment: the role of self-efficacy beliefs and
personal goal-setting. Am Educ Res J. 1992;29:663–76.
Additional supporting information may be found in the
online version of the article at the publisher's website.
How to cite this article: Payne SM,
Whitworth DE. Increasing creative self-efficacy:
Developing the confidence of biochemistry
undergraduates to innovate. Biochem Mol Biol
Educ. 2022;50(3):296–306. https://doi.org/10.1002/
306 PAYNE AND WHITWORTH