Introduction Methods
Introduction Methods
Self-evaluation forms an important part of medical students ’ education , as it allows them to reflect on their work , recognise their shortcomings and seek help and further training where needed . Furthermore , insight into one ’ s performance and limitations are essential in medical practice . Continuing medical education , re-licensure and clinical competence are linked to the abilities of doctors to assess their own learning needs and choose educational activities that meet these needs . However , serious questions have been raised in the literature regarding the consistency , accuracy and reliability of self-assessment of knowledge , not only among doctors ( Davis et al , 2006 ), but also doctors-to-be ( Langendyk , 2006 ; Papinczak et al , 2007 ; Machado et al , 2008 ; Blanch-Hartigan , 2011 ; Sawdon and Finn , 2013 ).
Kruger and Dunning ( 1999 ), Krueger and Mueller ( 2002 ), and Ehrlinger et al . ( 2008 ) among several other researchers , have shown that all of us , but in particular poor performers , systematically overestimate our abilities and performance . Students that overestimate their work might not be aware of their weaknesses , i . e ., their lack of metacognitive ability deprives them of the skills needed to recognise their defects . Such students not only perform poorly and overestimate their work , but are unable to realise it and make better judgements . Kruger and Dunning ( 1999 ) have argued that low-achieving students are in a paradoxical situation of “ not knowing , and not knowing that they do not know ”. Without the ability to judge their own competence accurately , students find it difficult to set appropriate goals and the means to obtain them . The same can be said , but to a much lesser extent , for high performing students . Furthermore , Burson et al . ( 2006 ) showed that although metacognitive skill may drive low performing students to make poor judgements , students ’ assessment of their performance was inversely related to the level of task difficulty .
After ethical approval ( University of Malta Research Ethics Committee , DSG / 2018-19 / 019 _ 2 ) and informed consent , students were recruited from the first to the penultimate year of medical school .
The research consisted of two separate studies . In part 1 , Years 1 to 4 participating students answered 100 best-of-four multiple choice basic and applied anatomy questions spanning all principal body regions , under examination conditions in English . They were then asked to estimate their score .
In part 2 , after completing the gastrointestinal module , Year 2 students volunteered to sit for a mock anatomy test under examination conditions . The test consisted of 100 questions divided equally between true / false questions ( negatively marked ), best-of-five multiple choice questions , extended matching questions and single phrase answers . Immediately after the test , students were asked to estimate the mark they obtained and judge which type of question they found the most challenging .
Age , gender and nationality were extracted from class registers . Exam results were categorised by nationality into local , other-European Union ( EU , mostly British , pre-Brexit ) and non-EU ( Kuwait ).
For each year and demographic sub-group , the students ' anatomy grades were compared with their self-predicted grades using an unpaired t test and ANOVA . Correlations were analysed using Pearson ' s coefficient . For all tests , a value of P < 0.05 was considered statistically significant .
The objective of this research was to evaluate the self-assessment skills of medical students in terms of accuracy of predicting how their performance in a written anatomy test compared with their perception of their scores , as the examination is objectively marked . Practical anatomy examinations have been subjected to a similar analysis ( Sawdon and Finn , 2013 ).