ERIC EJ991407: Helping Students Succeed through Using Reflective Practice to Enhance Metacognition and Create Realistic Predictions

2012·0.07 MB·English

by  ERIC

HEA STEM Conference
Helping students succeed through using
reflective practice to enhance
metacognition and create realistic
predictions
Carolyn Mair
Understanding how students can better manage their expectations has been a topic of interest in pedagogy
for some time, yet solutions remain elusive. This paper describes a recent study which aimed to help students
make more realistic predictions by increasing their metacognition. At the outset, participants completed a
metacognitive awareness inventory and were asked to predict the grade for their next assessment. They were
instructed on how to use a structured reflection spreadsheet and asked to reflect weekly for the study period.
At the end of the study, the inventory was re-administered and participants predicted the submission time and
grade for the next assessment. Although results showed a significant increase in scores in metacognition,
they did not show improved prediction accuracy. Possible reasons for the outcomes and further work are
discussed.
Keywords: Metacognition; higher education; student satisfaction; expectation; reflection.
A
N EXPECTATIONis a prediction about ratings (e.g. Moore, Moore & McDonald,
a future event or outcome. Predicting 2008). A great deal of importance is based
the future is notoriously difficult and on satisfaction ratings in higher education
in an attempt to manage the complexity of (HE) as they can affect the reputation of the
processing mental tasks, such as making Higher Education Institution (HEI), tutor
predictions, humans typically turn to heuris- (2008) and attrition rates. While it is clearly
tics (Simon, 1957). These are readily avail- in the interest of all to improve satisfaction,
able experience-based techniques which there is a paucity of research investigating
allow us to derive a satisfactory, rather than the relationship between students’ predic-
optimal, prediction. Despite evidence tion accuracy and satisfaction ratings.
suggesting heuristic-based predicted Rather, findings from studies investigating
outcomes can differ significantly from actual student satisfaction typically encourage staff
outcomes (Tversky & Kahneman, 1974), we to provide environments that surpass
tend to have high confidence in them student expectations (e.g. Ferguson DeJong,
(Fischhoff, Slovic & Lichtenstein, 1977). 2008) without investigating the bases on
Moreover, predicted outcomes are typically which the expectations were derived.
biased in one direction: towards overestima- Metacognition (Flavell, 1978) has been
tion of ability, skills and knowledge found to be a predictor of successful
(Dunning, Heath & Suls, 2004; Dunning et learning and academic performance (e.g.
al., 2003; Fischhoff et al., 1977; Buehler, Dunning et al., 2003), intelligence (e.g.
Griffin & Ross, 1994). Thus the incongru- Sternberg, 1984) and confidence (Kleitman
ence between predicted and actual & Stankov, 2007). Metacognition is the
outcomes can result in dissatisfaction which awareness, monitoring and control of one’s
in turn determines students’ satisfaction cognitive processes. Thus it follows that
42 Psychology Teaching Review Vol. 18 No. 2, Autumn 2012
© The British Psychological Society 2012
Helping students succeed through using reflective practice…
more accurate predictions, as a result of VLE (providing continuous accessibility).
more accurate self-perception, could be Moreover, to encourage disclosure, reflec-
developed through increased metacognition tions are neither read nor assessed. In a body
(Swartz & Perkins, 1989). In addition, this of work since 2009 Mair and Taylor have
would increase students’ autonomy (Boud, consistently shown improved metacognitive
1995; Livingston, 1997). However, in order awareness following use of the reflective
to become more metacognitively aware, one spreadsheet.
needs to be critically reflective (e.g. Schön, In order to help derive more realistic self-
1982; Dewey, 1939) and to learn from reflec- perceptions, the study described below
tive practice, weaknesses as well as strengths aimed to encourage students to develop
need to be scrutinised (Dewey, 1939). more realistic predictions (expectations) by
Evidence has shown that weaknesses are less enhanced metacognitive awareness devel-
considered when reflections are read or oped through online, structured, critical
assessed by a tutor as students tend to reflective practice. To determine the rela-
demonstrate knowledge and hide ignorance tionship between metacognition and predic-
(Boud, 1999; Sumsion & Fleet, 1996). There- tion accuracy, participants in the present
fore, not assessing reflections and using study were encouraged to reflect critically
information and communication technology for six weeks and to predict the outcome of
(ICT) for reflective practice could be advan- two assessments. The hypotheses were that
tageous as it is interpreted as less judge- reflective practice would lead to increased
mental, thus increasing disclosure and metacognitive awareness and there would be
honesty (Kettinger & Grover, 1997). Addi- relationships between metacognitive aware-
tional advantages such as its 24/7 accessi- ness and prediction accuracy, and among the
bility have often been cited (e.g. Barak, 2006; amount of participation and post-study
Paulus & Roberts, 2006; Aleven & Koedinger, metacognitive awareness and prediction
2002; Lin et al., 1999). accuracy.
Mair (2009) developed a structured Ethical approval was obtained from the
spreadsheet for critical reflective practice Department’s Ethics Committee prior to
situated on the university’s virtual learning commencement. Year 2 undergraduate
environment (VLE) in an attempt to move psychology students were asked to complete
from traditional learning journals which are the Metacognitive Awareness Inventory
assessed, and others which lack structure and (MAI; Schraw & Dennison, 1994) and reflect
guidance. The aim was to facilitate critical weekly on their learning via the VLE for six
reflective practice in a private, familiar and weeks as a ‘structured learning’ exercise in
accessible format. Moreover, because the part fulfillment of their coursework. Fifty-five
spreadsheet format makes previous reflec- students consented to the MAI data being
tions available while current reflections are analysed for the purposes of this study. The
being entered, the student takes part in MAI was used to measure self-reported
meta-reflection (Dewey, 1939; considering metacognitive awareness. The 52-item MAI
past as well as current reflections); reflecting measures a range of aspects of metacogni-
on and in practice (Schön, 1982) such that tion such as monitoring, planning, compre-
meaning becomes learning (Mezirow, 1991). hension using a six-point Likert scale.
In effect, when using the spreadsheet A structured spreadsheet for reflecting,
students enter, store and retrieve reflections based on Mair (2009) was used to encourage
across rows, guided by column heading and reflective practice on learning. Instructions
examples such as ‘How can I apply what were given at the outset and were available
I have learned in other contexts?’ whilst online. The study required students to: (i)
previous reflections are displayed in rows complete the MAI before and after the study;
above (providing meta-reflection) via the (ii) predict the grade for their next assess-
Psychology Teaching Review Vol. 18 No. 2, Autumn 2012 43
Carolyn Mair
ment (A1); (iii) reflect on their learning feedback on staff and increased attrition
using the structured reflection spreadsheet rates. Programmes aimed at increasing
on the VLE; and (iv) predict the grade they metacognition, such as critical reflection,
would be awarded for their next assessment can enable students to improve self-percep-
(A2). At the outset, participants were tions of knowledge and skills (e.g. Boud,
instructed on using the reflection spread- 2004) which should enable them to produce
sheet. The instructions were also available on realistic predictions.
the VLE. MAI baseline and post-study scores In the present study, an online, struc-
were compared, and students’ grades were tured reflection spreadsheet (e.g. Mair,
compared with actual grades for A1 and A2. 2012; Mair & Taylor, 2012) situated on the
Data from the 68 participants completed VLE was used to enhance metacognition
each of the required aspects of the study over a six-week period and to investigate
were included in the analyses. whether the intervention would lead to more
The MAI demonstrated high internal accurate grade predictions for two assess-
consistency both pre- and post-intervention ments (A1 predicted at baseline; A2
(Cronbach’s α=.92 and .94, respectively). predicted post-study). Metacognition, meas-
The mean MAI baseline scores increased ured at baseline and post-study using the
significantly from baseline to post-study MAI, significantly increased over the period
(t(35)=–3.58, p=.001) and demonstrated a of the study, but this did not correlate with
significant main effect (F(1,34)=10.42, improved grade prediction accuracy. We also
p=.003). There was no significant difference investigated the impact of amount of partici-
between prediction accuracy for A1 and A2 pation on metacognition and on prediction
(t(17)=-1.48, p=.16), but grade prediction accuracy. We found that although no signifi-
error was positively correlated with baseline cant difference was found between grade
MAI scores (Table 1). prediction accuracy for A1 or A2, it was
affected by amount of participation, as were
Discussion and conclusions post MAI scores. Moreover, participants with
Students arrive at university with high expec- greater prediction error for A1 reflected
tations and consequently some become fewer times over the course of the study and
dissatisfied when actual outcomes do not the lower the participation, the greater the
correspond with their expectations. Typi- difference between predicted and actual
cally, expectations are built on error-prone grade for both A1 and A2. Although MAI
heuristic-based predictions (Simon, 1957) scores could be an indicator of engagement,
which are likely to be biased towards over- there exists a problem beyond the ability to
estimation of ability (Tversky & Kahneman, accurately predict grades given the well-
1974). The resulting disappointment can documented benefits of metacognitive
lead to a sense of injustice, provision of poor awareness. Despite low prediction error in
Table 1: Mean MAI, predicted and actual grade and participation.
Baseline (mean (SD)) Post-study (mean (SD))
MAI 4.12 (0.47) 4.23 (0.48)
Predicted grade 60 (5.88) 62.83 (4.25)
Actual grade 60.86 (8.80) 60.72 (9.62)
Prediction error –0.86 (A1) +2.11 (A2)
Participation 11.21 (4.99)
44 Psychology Teaching Review Vol. 18 No. 2, Autumn 2012
Helping students succeed through using reflective practice…
this study, confidence in ability did increase tice on them. Finally, the vehicle for predic-
over the six-week period and it is unknown tion (Year 2 assessment grades) may not be
whether this trajectory would continue with the most suitable as student grades generally
continued reflection. Although confidence do not have great variability and by Year 2,
is desirable and can lead to better perform- most students can accurately predict what
ance, it can also lead to unrealistic (biased) grade they will receive. The findings raise
expectations (Kleitman & Stankov, 2007). some important questions: first, how can we
The study was limited by a small sample engage students who are low in metacogni-
and by the fact that students were required tive awareness? Second, how can we increase
to participate in part fulfillment of their metacognition while tempering confidence?
degree, but the work was not assessed. The Third, what are the most influential factors
latter point benefits disclosure, but is for student expectations.
unlikely to encourage participation for less
motivated students. In future, it would be Acknowledgement
interesting to analyse existing data on This work was supported by EPSRC Grant
student expectations to draw out the main EP/0137881/1.
factors such ‘feedback’ and ‘staff availability’
and investigate those factors at different Correspondence
times during the degree programme. For Professor Carolyn Mair
example by asking students to keep track of Southampton Solent University,
the instances these factors are encountered Southampton, SO14 0YN.
and apply sustained critical reflective prac- Email: [email protected]
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