SHORT COMMUNICATION
Association Between Learning Style Preferences and Anatomy Assessment Outcomes in Graduate-Entry and Undergraduate Medical Students Siobhain M. O’Mahony,1†* Amgad Sbayeh,1,2,3† Mary Horgan,2 Siun O’Flynn,2 Colm M.P. O’Tuathaigh2 1 Department of Anatomy and Neuroscience, School of Medicine, University College Cork, Ireland 2 Medical Education Unit, School of Medicine, University College Cork, Ireland 3 Graduate Entry Medical School, University of Limerick, Ireland
An improved understanding of the relationship between anatomy learning performance and approaches to learning can lead to the development of a more tailored approach to delivering anatomy teaching to medical students. This study investigated the relationship between learning style preferences, as measured by Visual, Aural, Read/write, and Kinesthetic (VARK) inventory style questionnaire and Honey and Mumford’s learning style questionnaire (LSQ), and anatomy and clinical skills assessment performance at an Irish medical school. Additionally, mode of entry to medical school [undergraduate/direct-entry (DEM) vs. graduate-entry (GEM)], was examined in relation to individual learning style, and assessment results. The VARK and LSQ were distributed to first and second year DEM, and first year GEM students. DEM students achieved higher clinical skills marks than GEM students, but anatomy marks did not differ between each group. Several LSQ style preferences were shown to be weakly correlated with anatomy assessment performance in a program- and year-specific manner. Specifically, the “Activist” style was negatively correlated with anatomy scores in DEM Year 2 students (rs 5 20.45, P 5 0.002). The “Theorist” style demonstrated a weak correlation with anatomy performance in DEM Year 2 (rs 5 0.18, P 5 0.003). Regression analysis revealed that, among the LSQ styles, the “Activist” was associated with poorer anatomy assessment performance (P < 0.05), while improved scores were associated with students who scored highly on the VARK “Aural” modality (P < 0.05). These data support the contention that individual student learning styles contribute little to variation in academic performance in medical students. C 2016 American Association of Anatomists. Anat Sci Educ 00: 000–000. V
Key words: gross anatomy education; medical education; undergraduate medical education; graduate-entry medical education; learning styles; anatomy assessment; clinical skills assessment; VARK; Honey and Mumford’s LSQ; anatomy assessment outcomes
INTRODUCTION Competing educational theories have proposed a number of terms, often used interchangeably, to describe learning styles—
*Correspondence to: Dr. Siobhain M. O’Mahony, Department of Anatomy and Neuroscience, School of Medicine, University College Cork, Cork, Ireland. E-mail: [email protected] †
Drs. O’Mahony and Sbayeh contributed equally to this work.
Received 14 August 2015; Revised 6 January 2016; Accepted 6 January 2016. Published online 00 Month 2016 in Wiley (wileyonlinelibrary.com). DOI 10.1002/ase.1600 C 2016 American Association of Anatomists V
Anatomical Sciences Education
MONTH 2016
Online
Library
these include “learning styles,” “approaches to learning,” and “learning strategies.” The diversity of learning style models, which have attracted research interest has resulted in the generation of specific tools which assess specific skills and attributes which are hypothesized to generalize across learning contexts (Claxton and Murrell, 1987; Coffield et al., 2004; Mitchell, 2015). It has been proposed that that optimal learning occurs where the primary learning style preferences of the learner— the way he/she assimilates, processes, and recall information— are matched with course content and mode of instruction (Sadler-Smith, 1996; Pashler et al., 2008). This diversity underscores the need for educators to incorporate a variety of teaching methods, curriculum materials, and assessment techniques to foster and support the process of learning (Murphy et al., 2004). Anat Sci Educ 00:00–00 (2016)
Various models of learning styles have been grouped into four general categories: personality models, information processing models, social interaction models, and instructional preference models (Claxton and Murrell, 1987). An example of a learning style instrument based on information processing is Honey and Mumford’s Learning Style Questionnaire (LSQ), which is derived from Kolb’s experiential learning cycle (Honey and Mumford, 1986). Honey and Mumford (1986) described four learning styles: “Activists,” who excel at generating ideas and implementing major changes; “Reflectors,” who prefer to observe and review prior to action, and prefer to investigate in a pressure-free context; “Theorists,” who enjoy intellectual arguments, probing and challenging assumptions; “Pragmatists,” who prefer hands-on demonstration, learning from experience, and learning material with a practical application. The LSQ has been widely used to characterize the learning style preferences of various healthcare profession degree students (Linares, 1999; McCall et al., 2005; Fleming et al., 2011; Aziz et al., 2013). A number of studies have investigated the relationship between LSQ scores and undergraduate medical education assessment performance. Haley and Smith (2005), based on a sample of UK medical school students, reported that “Theorists” performed better in end-of-year examinations. In a more recent study, Wilkinson et al. (2014) examined the relationship between learning style, as measured by the LSQ and Kolb’s Learning Styles Inventory, and examination results in a variety of undergraduate medical subjects, including anatomy. The results revealed a weak association between LSQ style preferences and academic achievement. “Theorists” were more likely to perform well across a variety of assessments, although these correlations were generally weak. An example of an instructional preference model is the Visual, Aural, Read/write, and Kinesthetic (VARK) model and questionnaire, which is designed to identify the following sensory modalities: Visual (V), Aural (A), Read/write (R), and Kinesthetic (K) (Fleming and Mills, 1992). The Visual learner learns by looking at image intense figures, graphic and videos (Fleming, 2011; Kharb et al., 2013). Aural learners give particular attention to words delivered by teachers (Drago and Wagner, 2004; Othman and Amiruddin, 2010; Fleming, 2011). Read/write learners like lecture notes, handouts and text books (Fleming, 2011). Kinesthetic learners prefer hands on experience, practical application, use of models and real life experiences (Othman and Amiruddin, 2010; Fleming, 2011). While some learners might have a specific preference for a single modality (unimodal), others prefer to learn a combination of two (bimodal), three (trimodal), or all four modalities (quadmodal). VARK style preference has been studied in diverse student populations and countries (James et al., 2011; Alkhasawneh, 2013; Nuzhat et al., 2013; Peyman et al., 2014; Prithishkumar and Michael, 2014; Whillier et al., 2014). Several studies have failed to show any association between VARK preference and undergraduate anatomy and medical education assessment performance (Baykan and Nac¸ar, 2007; Alkhasawneh et al., 2008; Dobson, 2009, 2010; Urval et al., 2014; Farkas et al., 2016). Other studies have demonstrated that students with multiple learning preferences (i.e. multimodal), as opposed to single learning preferences (i.e., unimodal), show improved academic performance in dental education (Al-Saud, 2013) and medical education results (Nuzhat et al., 2013; Peyman et al., 2014). There is also evidence to show that VARK preferences of third level students may shift if it proves advantageous 2
in relation to academic achievement (Vorhaus, 2010; Alkhasawneh, 2013). University College Cork (UCC) offers both a four-year graduate-entry medical (GEM) course and a five-year undergraduate/direct-entry medical (DEM) course. The former spend two years in preclinical education, while DEM students spend three years in preclinical education. Research conducted in UK and Irish medical schools suggests that graduate entrants perform significantly better than their direct entrants with respect to clinical skills/practice (Dodds et al., 2010) and research-based assessments (Duggan et al., 2014). A better understanding of the relationship between anatomy learning performance and approaches to learning has the potential to inform the delivery of course content and the development of a more tailored approach to delivering anatomy teaching to medical students. However, it is unclear whether individual differences in learning styles might be of heuristic value in predicting effective and efficient strategies for learning of anatomy course content, which is typically taught and assessed using a variety of pedagogical and assessment methodologies (Samarakoon et al., 2013). Additionally, while both LSQ and VARK preferences have been examined separately in relation to undergraduate academic performance, no study to date has conducted a side-by-side comparison of both models and their respective relationship with anatomy and other medical education examination performance (Haley and Smith, 2005; Baykan and Nac¸ar, 2007; Alkhasawneh et al., 2008; Dobson, 2009, 2010; Urval et al., 2014; Wilkinson et al., 2014; Farkas et al., 2016). The aim of this study was to investigate the relationship between LSQ and VARK preferences, and both anatomy and clinical skills assessment outcomes at the School of Medicine, University College Cork, Ireland. A secondary objective was to examine the relationship between mode of entry to medical school (DEM vs. GEM), and the putative link between learning style and assessment performance during the first year of both undergraduate programs.
MATERIALS AND METHODS Study participants were students drawn from Years 1 and 2 of the DEM medical program, and Year 1 of the GEM program at UCC during the 2012–2013 academic year. Curricular frameworks for both DEM and GEM courses at UCC follow a spiral systems based structure with an emphasis on case-based learning and small-group teaching. DEM and GEM students receive conjoined teaching at many points and are merged for the last two years of the course. For DEM students, the anatomy curriculum is delivered through three modules during Year 1 (FM1010, upper and lower limbs; FM1020, thorax and the heart; FM1030, the abdomen, respiratory systems) and two modules during Year 2 (FM2101, neuroanatomy; FM2102, male/female reproductive organs and pelvis); the total number of DEM course hours devoted to anatomy is 148 hours (30% lectures, 70% laboratory practical sessions). The GEM anatomy curriculum is delivered through three modules during Year 1 (GM1001, upper and lower limbs; GM1002, cardiovascular and respiratory systems; GM1003, abdomen, male/ female reproductive organs and pelvis) and one module during Year 2 (GM2001, neuroanatomy); the total number of GEM course hours devoted to anatomy is 163 hours (30% lectures, 70% laboratory practical sessions). For both DEM and GEM students, anatomy content is delivered using a combination of lectures and cadaver-based teaching using prosection- and O’Mahony et al.
dissection-based activities, together with availability of medical imaging and multimedia resources. Summative assessments for anatomy and clinical skills modules across both the DEM and GEM programs at UCC are carried out employing a selection of different methods. For GEM Year 1 students, anatomy assessment consists of the following: written examination (70%); continuous assessment [multiple choice questions (MCQ); short answer questions (SAQ), dissecting room-based spot examination (30%)]. For both DEM Year 1 and Year 2 students, anatomy assessment consists of the following: written examination (70%); continuous assessment (extended matching questions (EMQ); MCQ; SAQ, dissecting room-based spot examination; 30%). For both DEM Year 1 and 2 and GEM Year 1 students, clinical skills content is delivered via clinical seminars, small group learning, demonstrations, workshops, real patient visits, and bedside teaching. For both DEM Year 1 and GEM Year 1, clinical skills assessment consists of the following: written examination (MCQ; 100%). For DEM Year 2 students, clinical skills assessment consists of the following: written examination (MCQ; 50%); continuous assessment (objective structured clinical examination; 50%). All students were administered the 16-item VARK questionnaire, version 7.1 (Fleming, 2011) to determine the VARK learning style preferences of the medical student sample. Based on their responses, students were grouped as either unimodal (V, A, R, and K), or multimodal based on their learning style preferences. The inventory also returned the strength of preference for each modality of each student, calculated based on the number of question responses associated with that modality; in this way, a student’s score for each of the V, A, R, and K modalities could be represented in the numerical range of 0–16 (where 16 indicated that answers given to all questions in the inventory reflected a preference for that modality). All students were also administered the Honey and Mumford LSQ (Honey and Mumford, 1986). This 80-item questionnaire consists of statements, where students are requested to indicate whether they agree or disagree with the information presented. In a non-medical learning environment, it was shown that the LSQ possessed no predictive validity, but strong test–retest reliabilities, over a two-year time period (Kappe et al., 2009). Both types of learning style survey questionnaires (LSQ, VARK) were distributed as soft copies to the students in the Facility for Learning Anatomy Morphology and Embryology (FLAME) Laboratory) in the Department of Neuroscience and Anatomy at UCC in November 2012. The total percentage results of final summative assessment marks for anatomy and clinical skills modules of GEM and DEM students in the academic year 2012–2013 were obtained from the central student examination records in the School of Medicine at UCC. All results were converted into percentages for the purpose of this study, and were coded categorically based on degree class (fail, 0–49; pass, 50–59; second class honors, 60–69; first class honors, 70–100). Mean anatomy and clinical skills marks of DEM versus GEM were compared using independent t-tests. Pearson’s chi-square was used to examine the association between mode of entry to medicine and degree class category for both anatomy and clinical skills assessments. Spearman’s rho correlation coefficient analysis was employed to measure the putative association between VARK and LSQ domain scores and anatomical and clinical assessment outcomes of DEM and GEM students. For each of the assessment outcomes-learning style correlations (16 tests per assessment), to control for familywise error rate, a Bonferroni adjusted Anatomical Sciences Education
MONTH 2016
Figure 1. Anatomy and clinical assessment marks of direct-entry (DEM) and graduateentry medical (GEM) students. Comparison of both groups is shown in relation to the mean scores, standard error of the mean (SEM), and P-values (product of independent t-test comparisons) of anatomy and clinical skills assessment marks (total percentage score); aP < 0.05.
alpha level of 0.003 per test was employed. A linear regression model was subsequently employed to examine the relationship between assessment results and potential explanatory variables. Explanatory variables comprised sex, mode of entry to medical school (DEM versus GEM), VARK modality scores (V,A,R,K), LSQ style scores (“Activist,” “Reflector,” “Theorist,” “Pragmatist”). The threshold for statistical significance was set at P < 0.05. Statistical analyses were carried out using IBM SPSS statistical package, version 20 (IBM, Armonk, NY). Ethical approval was obtained for this study from the School of Medicine Research Ethics Committee and the Research Ethics Committee of the Cork Teaching Hospitals (ECM 4(r) 07/08/2012).
RESULTS A total of 327 students completed both learning styles questionnaires, and these data were examined alongside their summative assessment scores for their anatomy and clinical skills modules. Of the total sample, 264 were DEM students, providing a response rate of 92% (264/289 for DEM Year 1 and Year 2). Sixty-three of the respondents were GEM students, providing a response rate of 90% for this group (63/70 for GEM Year 1).
Demographics and the Comparison of Summative Examination Scores Table 1 summarizes the number and percentage of total respondents of sex, country of origin, educational levels, and ages in years for all UCC medical students included in this analysis. The distribution of summative anatomy marks achieved based on degree class achieved for each program (DEM/GEM) was as follows: DEM (fail, 3%; pass, 8%; second class honors, 16%; first class honors, 73%); GEM (fail, 3%; pass, 10%; second class honors, 27%; first class honors, 60%). The distribution of clinical skills marks for each program (DEM/GEM) was 3
Table 1. Summary of Demographic and Educational Characteristics in Direct-Entry (DEM) and Graduate-Entry Medical (GEM) Students Student Group Categories
Variable
DEM n (%)
GEM n (%)
Gender
Male Female
109 (41.2) 155 (58.8)
36 (56.8) 27 (43.2)
Country of origin
Irish Non-Irish Malaysia Singapore United Kingdom Canada Other
147 (55.7) 117 (44.3) 94 (35.5) 7 (2.8) 6 (2.6) 2 (1.0) 8 (3.0)
32 (51.5) 31 (48.5) 0 0 2 (3.0) 20 (31.5) 9 (14.0)
Educational level
Secondary school Third level Bachelor degree Masters degree Professional Doctoral degree (PhD)
216 (81.8) 30 (11.3) 13 (4.9) 5 (2.0) 0 0
0 1 (1.0) 50 (80.3) 10 (16.7) 1 (1.0) 1 (1.0)
Mean age (years)
21-26 27-32 33-38 391
199 (75.6) 56 (21.3) 5 (2.0) 4 (1.5)
2 52 6 3
(3.2) (82.5) (9.5) (4.8)
DEM, direct-entry medical students (n 5 264); GEM, graduate-entry medical students (n 5 63).
as follows: DEM (fail, 1%; pass, 2%; second class honors, 16%; first class honors, 81%); GEM (fail, 2%; pass, 19%; second class honors, 44%; first class honors, 35%). Figure 1 summarizes the comparison of summative marks for clinical and anatomy modules in DEM Year 1 versus GEM Year 1, revealing a significantly increased clinical skills assessment score in DEM Year 1 (t (200) 5 6.42, P < 0.0001), but no difference in anatomy scores between both groups (t (195) 5 0.30, P 5 0.76). These data were supported by complementary chi-square analysis of the association between student group (DEM Year 1 versus GEM Year 1) and degree class achieved in both the clinical skills and anatomy examinations. DEM Year 1 achieved a significantly higher proportion of first class honors grades in the clinical examination relative to GEM Year 1 (73.9 vs. 31.67%; v2 5 34.37, P < 0.0001), but no difference was observed for the anatomy marks (v2 5 0.76, P > 0.05). In relation to the overall VARK modality profile, 57.8% of students displayed a unimodal VARK profile, and the remaining students displayed a multimodal VARK profile (bimodal – 23.5%; trimodal – 13%; quadmodal – 5.7%). No significant difference was observed in relation to the distribution of unimodal (DEM – 57%; GEM – 60.3%) and multimodal (DEM – 43%; and GEM – 39.7%) VARK preferences between both student groups (P > 0.05). Mean (6 standard error of the mean, SEM) values for each LSQ style preference for both DEM and GEM programs were as follows: “Activist” (DEM 5 9.2 60.2; GEM 5 8.8 60.4); “Reflector” (DEM 5 14.8 60.2; GEM 5 13.7 60.5); “Theorist” (DEM 5 12.8 60.2; GEM 5 12.5 60.4); “Pragmatist” (DEM 5 12.2 60.2; GEM 5 12.4 6 0.3). 4
Correlation Analysis of VARK Profiles and Anatomy and Clinical Skills Assessment Scores Table 2 describes the strength of association observed between VARK modality scores and anatomy and clinical assessment marks. No VARK modality score was significantly correlated with anatomy and clinical skills assessment marks. Univariate t-test comparisons of anatomy or clinical skills assessment marks between students with unimodal and multimodal preferences revealed no significant difference (both P > 0.05).
Correlation Analysis of LSQ Profile and Anatomy and Clinical Assessment Scores Table 3 summarizes the measure of correlation between LSQ domain scores and anatomy and clinical assessment marks. A moderate negative correlation was observed between “Activist” and anatomy scores in DEM Year 2 students (rs 5 20.45, P < 0.05). The “Theorist” learning style showed a moderate positive association with anatomy performance in DEM Year 2 students (rs 5 0.42, P < 0.05). In relation to the clinical skills mark, no statistically significant association was demonstrated (P < 0.05).
Multiple Linear Regression Analysis To clarify the factors influencing anatomy and clinical skills assessment performance, multiple regression analysis was O’Mahony et al.
Table 2. The Correlation Between VARK Scores and Anatomy and Clinical Skills Marks in University College Cork (UCC) Medical Students Clinical VARK Modes
DEM/GEM students
Visual (V)
Anatomy
n
rs
P-value
rs
P-value
UCC DEM Year 1 DEM Year 2 GEM Year 1
254 144 47 63
20.008 0.751 0 0.061
0.901
Association Between Learning Style Preferences and Anatomy Assessment Outcomes in Graduate-Entry and Undergraduate Medical Students Siobhain M. O’Mahony,1†* Amgad Sbayeh,1,2,3† Mary Horgan,2 Siun O’Flynn,2 Colm M.P. O’Tuathaigh2 1 Department of Anatomy and Neuroscience, School of Medicine, University College Cork, Ireland 2 Medical Education Unit, School of Medicine, University College Cork, Ireland 3 Graduate Entry Medical School, University of Limerick, Ireland
An improved understanding of the relationship between anatomy learning performance and approaches to learning can lead to the development of a more tailored approach to delivering anatomy teaching to medical students. This study investigated the relationship between learning style preferences, as measured by Visual, Aural, Read/write, and Kinesthetic (VARK) inventory style questionnaire and Honey and Mumford’s learning style questionnaire (LSQ), and anatomy and clinical skills assessment performance at an Irish medical school. Additionally, mode of entry to medical school [undergraduate/direct-entry (DEM) vs. graduate-entry (GEM)], was examined in relation to individual learning style, and assessment results. The VARK and LSQ were distributed to first and second year DEM, and first year GEM students. DEM students achieved higher clinical skills marks than GEM students, but anatomy marks did not differ between each group. Several LSQ style preferences were shown to be weakly correlated with anatomy assessment performance in a program- and year-specific manner. Specifically, the “Activist” style was negatively correlated with anatomy scores in DEM Year 2 students (rs 5 20.45, P 5 0.002). The “Theorist” style demonstrated a weak correlation with anatomy performance in DEM Year 2 (rs 5 0.18, P 5 0.003). Regression analysis revealed that, among the LSQ styles, the “Activist” was associated with poorer anatomy assessment performance (P < 0.05), while improved scores were associated with students who scored highly on the VARK “Aural” modality (P < 0.05). These data support the contention that individual student learning styles contribute little to variation in academic performance in medical students. C 2016 American Association of Anatomists. Anat Sci Educ 00: 000–000. V
Key words: gross anatomy education; medical education; undergraduate medical education; graduate-entry medical education; learning styles; anatomy assessment; clinical skills assessment; VARK; Honey and Mumford’s LSQ; anatomy assessment outcomes
INTRODUCTION Competing educational theories have proposed a number of terms, often used interchangeably, to describe learning styles—
*Correspondence to: Dr. Siobhain M. O’Mahony, Department of Anatomy and Neuroscience, School of Medicine, University College Cork, Cork, Ireland. E-mail: [email protected] †
Drs. O’Mahony and Sbayeh contributed equally to this work.
Received 14 August 2015; Revised 6 January 2016; Accepted 6 January 2016. Published online 00 Month 2016 in Wiley (wileyonlinelibrary.com). DOI 10.1002/ase.1600 C 2016 American Association of Anatomists V
Anatomical Sciences Education
MONTH 2016
Online
Library
these include “learning styles,” “approaches to learning,” and “learning strategies.” The diversity of learning style models, which have attracted research interest has resulted in the generation of specific tools which assess specific skills and attributes which are hypothesized to generalize across learning contexts (Claxton and Murrell, 1987; Coffield et al., 2004; Mitchell, 2015). It has been proposed that that optimal learning occurs where the primary learning style preferences of the learner— the way he/she assimilates, processes, and recall information— are matched with course content and mode of instruction (Sadler-Smith, 1996; Pashler et al., 2008). This diversity underscores the need for educators to incorporate a variety of teaching methods, curriculum materials, and assessment techniques to foster and support the process of learning (Murphy et al., 2004). Anat Sci Educ 00:00–00 (2016)
Various models of learning styles have been grouped into four general categories: personality models, information processing models, social interaction models, and instructional preference models (Claxton and Murrell, 1987). An example of a learning style instrument based on information processing is Honey and Mumford’s Learning Style Questionnaire (LSQ), which is derived from Kolb’s experiential learning cycle (Honey and Mumford, 1986). Honey and Mumford (1986) described four learning styles: “Activists,” who excel at generating ideas and implementing major changes; “Reflectors,” who prefer to observe and review prior to action, and prefer to investigate in a pressure-free context; “Theorists,” who enjoy intellectual arguments, probing and challenging assumptions; “Pragmatists,” who prefer hands-on demonstration, learning from experience, and learning material with a practical application. The LSQ has been widely used to characterize the learning style preferences of various healthcare profession degree students (Linares, 1999; McCall et al., 2005; Fleming et al., 2011; Aziz et al., 2013). A number of studies have investigated the relationship between LSQ scores and undergraduate medical education assessment performance. Haley and Smith (2005), based on a sample of UK medical school students, reported that “Theorists” performed better in end-of-year examinations. In a more recent study, Wilkinson et al. (2014) examined the relationship between learning style, as measured by the LSQ and Kolb’s Learning Styles Inventory, and examination results in a variety of undergraduate medical subjects, including anatomy. The results revealed a weak association between LSQ style preferences and academic achievement. “Theorists” were more likely to perform well across a variety of assessments, although these correlations were generally weak. An example of an instructional preference model is the Visual, Aural, Read/write, and Kinesthetic (VARK) model and questionnaire, which is designed to identify the following sensory modalities: Visual (V), Aural (A), Read/write (R), and Kinesthetic (K) (Fleming and Mills, 1992). The Visual learner learns by looking at image intense figures, graphic and videos (Fleming, 2011; Kharb et al., 2013). Aural learners give particular attention to words delivered by teachers (Drago and Wagner, 2004; Othman and Amiruddin, 2010; Fleming, 2011). Read/write learners like lecture notes, handouts and text books (Fleming, 2011). Kinesthetic learners prefer hands on experience, practical application, use of models and real life experiences (Othman and Amiruddin, 2010; Fleming, 2011). While some learners might have a specific preference for a single modality (unimodal), others prefer to learn a combination of two (bimodal), three (trimodal), or all four modalities (quadmodal). VARK style preference has been studied in diverse student populations and countries (James et al., 2011; Alkhasawneh, 2013; Nuzhat et al., 2013; Peyman et al., 2014; Prithishkumar and Michael, 2014; Whillier et al., 2014). Several studies have failed to show any association between VARK preference and undergraduate anatomy and medical education assessment performance (Baykan and Nac¸ar, 2007; Alkhasawneh et al., 2008; Dobson, 2009, 2010; Urval et al., 2014; Farkas et al., 2016). Other studies have demonstrated that students with multiple learning preferences (i.e. multimodal), as opposed to single learning preferences (i.e., unimodal), show improved academic performance in dental education (Al-Saud, 2013) and medical education results (Nuzhat et al., 2013; Peyman et al., 2014). There is also evidence to show that VARK preferences of third level students may shift if it proves advantageous 2
in relation to academic achievement (Vorhaus, 2010; Alkhasawneh, 2013). University College Cork (UCC) offers both a four-year graduate-entry medical (GEM) course and a five-year undergraduate/direct-entry medical (DEM) course. The former spend two years in preclinical education, while DEM students spend three years in preclinical education. Research conducted in UK and Irish medical schools suggests that graduate entrants perform significantly better than their direct entrants with respect to clinical skills/practice (Dodds et al., 2010) and research-based assessments (Duggan et al., 2014). A better understanding of the relationship between anatomy learning performance and approaches to learning has the potential to inform the delivery of course content and the development of a more tailored approach to delivering anatomy teaching to medical students. However, it is unclear whether individual differences in learning styles might be of heuristic value in predicting effective and efficient strategies for learning of anatomy course content, which is typically taught and assessed using a variety of pedagogical and assessment methodologies (Samarakoon et al., 2013). Additionally, while both LSQ and VARK preferences have been examined separately in relation to undergraduate academic performance, no study to date has conducted a side-by-side comparison of both models and their respective relationship with anatomy and other medical education examination performance (Haley and Smith, 2005; Baykan and Nac¸ar, 2007; Alkhasawneh et al., 2008; Dobson, 2009, 2010; Urval et al., 2014; Wilkinson et al., 2014; Farkas et al., 2016). The aim of this study was to investigate the relationship between LSQ and VARK preferences, and both anatomy and clinical skills assessment outcomes at the School of Medicine, University College Cork, Ireland. A secondary objective was to examine the relationship between mode of entry to medical school (DEM vs. GEM), and the putative link between learning style and assessment performance during the first year of both undergraduate programs.
MATERIALS AND METHODS Study participants were students drawn from Years 1 and 2 of the DEM medical program, and Year 1 of the GEM program at UCC during the 2012–2013 academic year. Curricular frameworks for both DEM and GEM courses at UCC follow a spiral systems based structure with an emphasis on case-based learning and small-group teaching. DEM and GEM students receive conjoined teaching at many points and are merged for the last two years of the course. For DEM students, the anatomy curriculum is delivered through three modules during Year 1 (FM1010, upper and lower limbs; FM1020, thorax and the heart; FM1030, the abdomen, respiratory systems) and two modules during Year 2 (FM2101, neuroanatomy; FM2102, male/female reproductive organs and pelvis); the total number of DEM course hours devoted to anatomy is 148 hours (30% lectures, 70% laboratory practical sessions). The GEM anatomy curriculum is delivered through three modules during Year 1 (GM1001, upper and lower limbs; GM1002, cardiovascular and respiratory systems; GM1003, abdomen, male/ female reproductive organs and pelvis) and one module during Year 2 (GM2001, neuroanatomy); the total number of GEM course hours devoted to anatomy is 163 hours (30% lectures, 70% laboratory practical sessions). For both DEM and GEM students, anatomy content is delivered using a combination of lectures and cadaver-based teaching using prosection- and O’Mahony et al.
dissection-based activities, together with availability of medical imaging and multimedia resources. Summative assessments for anatomy and clinical skills modules across both the DEM and GEM programs at UCC are carried out employing a selection of different methods. For GEM Year 1 students, anatomy assessment consists of the following: written examination (70%); continuous assessment [multiple choice questions (MCQ); short answer questions (SAQ), dissecting room-based spot examination (30%)]. For both DEM Year 1 and Year 2 students, anatomy assessment consists of the following: written examination (70%); continuous assessment (extended matching questions (EMQ); MCQ; SAQ, dissecting room-based spot examination; 30%). For both DEM Year 1 and 2 and GEM Year 1 students, clinical skills content is delivered via clinical seminars, small group learning, demonstrations, workshops, real patient visits, and bedside teaching. For both DEM Year 1 and GEM Year 1, clinical skills assessment consists of the following: written examination (MCQ; 100%). For DEM Year 2 students, clinical skills assessment consists of the following: written examination (MCQ; 50%); continuous assessment (objective structured clinical examination; 50%). All students were administered the 16-item VARK questionnaire, version 7.1 (Fleming, 2011) to determine the VARK learning style preferences of the medical student sample. Based on their responses, students were grouped as either unimodal (V, A, R, and K), or multimodal based on their learning style preferences. The inventory also returned the strength of preference for each modality of each student, calculated based on the number of question responses associated with that modality; in this way, a student’s score for each of the V, A, R, and K modalities could be represented in the numerical range of 0–16 (where 16 indicated that answers given to all questions in the inventory reflected a preference for that modality). All students were also administered the Honey and Mumford LSQ (Honey and Mumford, 1986). This 80-item questionnaire consists of statements, where students are requested to indicate whether they agree or disagree with the information presented. In a non-medical learning environment, it was shown that the LSQ possessed no predictive validity, but strong test–retest reliabilities, over a two-year time period (Kappe et al., 2009). Both types of learning style survey questionnaires (LSQ, VARK) were distributed as soft copies to the students in the Facility for Learning Anatomy Morphology and Embryology (FLAME) Laboratory) in the Department of Neuroscience and Anatomy at UCC in November 2012. The total percentage results of final summative assessment marks for anatomy and clinical skills modules of GEM and DEM students in the academic year 2012–2013 were obtained from the central student examination records in the School of Medicine at UCC. All results were converted into percentages for the purpose of this study, and were coded categorically based on degree class (fail, 0–49; pass, 50–59; second class honors, 60–69; first class honors, 70–100). Mean anatomy and clinical skills marks of DEM versus GEM were compared using independent t-tests. Pearson’s chi-square was used to examine the association between mode of entry to medicine and degree class category for both anatomy and clinical skills assessments. Spearman’s rho correlation coefficient analysis was employed to measure the putative association between VARK and LSQ domain scores and anatomical and clinical assessment outcomes of DEM and GEM students. For each of the assessment outcomes-learning style correlations (16 tests per assessment), to control for familywise error rate, a Bonferroni adjusted Anatomical Sciences Education
MONTH 2016
Figure 1. Anatomy and clinical assessment marks of direct-entry (DEM) and graduateentry medical (GEM) students. Comparison of both groups is shown in relation to the mean scores, standard error of the mean (SEM), and P-values (product of independent t-test comparisons) of anatomy and clinical skills assessment marks (total percentage score); aP < 0.05.
alpha level of 0.003 per test was employed. A linear regression model was subsequently employed to examine the relationship between assessment results and potential explanatory variables. Explanatory variables comprised sex, mode of entry to medical school (DEM versus GEM), VARK modality scores (V,A,R,K), LSQ style scores (“Activist,” “Reflector,” “Theorist,” “Pragmatist”). The threshold for statistical significance was set at P < 0.05. Statistical analyses were carried out using IBM SPSS statistical package, version 20 (IBM, Armonk, NY). Ethical approval was obtained for this study from the School of Medicine Research Ethics Committee and the Research Ethics Committee of the Cork Teaching Hospitals (ECM 4(r) 07/08/2012).
RESULTS A total of 327 students completed both learning styles questionnaires, and these data were examined alongside their summative assessment scores for their anatomy and clinical skills modules. Of the total sample, 264 were DEM students, providing a response rate of 92% (264/289 for DEM Year 1 and Year 2). Sixty-three of the respondents were GEM students, providing a response rate of 90% for this group (63/70 for GEM Year 1).
Demographics and the Comparison of Summative Examination Scores Table 1 summarizes the number and percentage of total respondents of sex, country of origin, educational levels, and ages in years for all UCC medical students included in this analysis. The distribution of summative anatomy marks achieved based on degree class achieved for each program (DEM/GEM) was as follows: DEM (fail, 3%; pass, 8%; second class honors, 16%; first class honors, 73%); GEM (fail, 3%; pass, 10%; second class honors, 27%; first class honors, 60%). The distribution of clinical skills marks for each program (DEM/GEM) was 3
Table 1. Summary of Demographic and Educational Characteristics in Direct-Entry (DEM) and Graduate-Entry Medical (GEM) Students Student Group Categories
Variable
DEM n (%)
GEM n (%)
Gender
Male Female
109 (41.2) 155 (58.8)
36 (56.8) 27 (43.2)
Country of origin
Irish Non-Irish Malaysia Singapore United Kingdom Canada Other
147 (55.7) 117 (44.3) 94 (35.5) 7 (2.8) 6 (2.6) 2 (1.0) 8 (3.0)
32 (51.5) 31 (48.5) 0 0 2 (3.0) 20 (31.5) 9 (14.0)
Educational level
Secondary school Third level Bachelor degree Masters degree Professional Doctoral degree (PhD)
216 (81.8) 30 (11.3) 13 (4.9) 5 (2.0) 0 0
0 1 (1.0) 50 (80.3) 10 (16.7) 1 (1.0) 1 (1.0)
Mean age (years)
21-26 27-32 33-38 391
199 (75.6) 56 (21.3) 5 (2.0) 4 (1.5)
2 52 6 3
(3.2) (82.5) (9.5) (4.8)
DEM, direct-entry medical students (n 5 264); GEM, graduate-entry medical students (n 5 63).
as follows: DEM (fail, 1%; pass, 2%; second class honors, 16%; first class honors, 81%); GEM (fail, 2%; pass, 19%; second class honors, 44%; first class honors, 35%). Figure 1 summarizes the comparison of summative marks for clinical and anatomy modules in DEM Year 1 versus GEM Year 1, revealing a significantly increased clinical skills assessment score in DEM Year 1 (t (200) 5 6.42, P < 0.0001), but no difference in anatomy scores between both groups (t (195) 5 0.30, P 5 0.76). These data were supported by complementary chi-square analysis of the association between student group (DEM Year 1 versus GEM Year 1) and degree class achieved in both the clinical skills and anatomy examinations. DEM Year 1 achieved a significantly higher proportion of first class honors grades in the clinical examination relative to GEM Year 1 (73.9 vs. 31.67%; v2 5 34.37, P < 0.0001), but no difference was observed for the anatomy marks (v2 5 0.76, P > 0.05). In relation to the overall VARK modality profile, 57.8% of students displayed a unimodal VARK profile, and the remaining students displayed a multimodal VARK profile (bimodal – 23.5%; trimodal – 13%; quadmodal – 5.7%). No significant difference was observed in relation to the distribution of unimodal (DEM – 57%; GEM – 60.3%) and multimodal (DEM – 43%; and GEM – 39.7%) VARK preferences between both student groups (P > 0.05). Mean (6 standard error of the mean, SEM) values for each LSQ style preference for both DEM and GEM programs were as follows: “Activist” (DEM 5 9.2 60.2; GEM 5 8.8 60.4); “Reflector” (DEM 5 14.8 60.2; GEM 5 13.7 60.5); “Theorist” (DEM 5 12.8 60.2; GEM 5 12.5 60.4); “Pragmatist” (DEM 5 12.2 60.2; GEM 5 12.4 6 0.3). 4
Correlation Analysis of VARK Profiles and Anatomy and Clinical Skills Assessment Scores Table 2 describes the strength of association observed between VARK modality scores and anatomy and clinical assessment marks. No VARK modality score was significantly correlated with anatomy and clinical skills assessment marks. Univariate t-test comparisons of anatomy or clinical skills assessment marks between students with unimodal and multimodal preferences revealed no significant difference (both P > 0.05).
Correlation Analysis of LSQ Profile and Anatomy and Clinical Assessment Scores Table 3 summarizes the measure of correlation between LSQ domain scores and anatomy and clinical assessment marks. A moderate negative correlation was observed between “Activist” and anatomy scores in DEM Year 2 students (rs 5 20.45, P < 0.05). The “Theorist” learning style showed a moderate positive association with anatomy performance in DEM Year 2 students (rs 5 0.42, P < 0.05). In relation to the clinical skills mark, no statistically significant association was demonstrated (P < 0.05).
Multiple Linear Regression Analysis To clarify the factors influencing anatomy and clinical skills assessment performance, multiple regression analysis was O’Mahony et al.
Table 2. The Correlation Between VARK Scores and Anatomy and Clinical Skills Marks in University College Cork (UCC) Medical Students Clinical VARK Modes
DEM/GEM students
Visual (V)
Anatomy
n
rs
P-value
rs
P-value
UCC DEM Year 1 DEM Year 2 GEM Year 1
254 144 47 63
20.008 0.751 0 0.061
0.901
