student learning preferences reflect curricular change
TRANSCRIPT
Medical Teacher, Vol. 24, No. 1, 2002
32 ISSN 0142–159X print/ISSN 1466–187X online/02/010032–09 © 2002 Taylor & Francis LtdDOI: 10.1080/00034980120103450
Student learning preferences reflect curricular change
CLARE KELL & ROBERT VAN DEURSENDepartment of Physiotherapy Education, University of Wales College of Medicine, Cardiff, UK
SUMMARY This study measured the learning preference profiledevelopment and readiness for self-directed learning over time oftwo undergraduate student cohorts experiencing different curric-ular presentations of essentially the same syllabus. The resultsfrom three measurement points are reported following eachcohort through their first half of the BSc (Honours) Physio-therapy Course, Cardiff. At intake both cohorts preferred aconcrete, fact-based learning environment, which was teacherstructured. Over time, the cohorts responded significantly differ-ently to their curricula in respect of the student-structuredlearning preference (LP) variable (p < 0.05), and displayedtrends (p < 0.1) towards response difference for the concrete,interpersonal and individual LP variables. Cohort differencesare discussed in terms of the planned curriculum changes madeduring the intervening revalidation exercise. It is suggested thatcurricula mould students’ learning profile development. Theimpact of this statement on future curriculum development isdiscussed and educational research-in-action promoted.
Introduction
Long (2000, p. 13) suggested that, for a student to beeducationally self-directed, he or she must be ‘conscious ofat least some of the important parts of the process and (be)able to apply the self (consciousness) to those elements forpurposes of controlling the process’. This ‘insider’ knowl-edge about the learning process would support thesuggestion that self-direction is ‘situational’, i.e. the abilityand confidence to be educationally self-directed is linked toa student’s familiarity and expertise within the particularfield (Grow, 1991, p. 127). A confidence to control thelearning process may explain the greater self-directiondisplayed by mature undergraduate students (Kell & vanDeursen, 2000) who are assumed to transfer skills learntfrom their personal/social self-directed environments totheir new learning situation.
Students who are self-directed in their learning are saidto exhibit initiative, independence, self-confidence andpersistence in learning, they accept responsibility for theirlearning, are comfortable with uncertainty and change andsee problems as challenges; they are skilled in criticalthinking and time management and have a goal-orientatedapproach to learning (Guglielmino, 1977; Jenner, 1992;Garrison, 1997).
The Dearing Report of 1997 charged higher education(HE) to produce graduates capable of contributingeffectively to society and achieving personal fulfilmentthroughout life (National Committee of Inquiry intoHigher Education, 1997, Section 5:11). If educatorsagree that ‘students’ approach to learning … is very exten-sively influenced by aspects of course design’ (Gibbs, 1992,
p. 164), then it should be possible to develop courses thatfacilitate these ‘self-direction-in-learning’ (Long, 2000, p.12) characteristics through their curricula. Measuring theeffectiveness of courses in achieving this aim could thenprovide evidence to support further debate and curriculumdevelopment.
The rigorous, quinquennial revalidation of undergrad-uate courses provides an excellent forum to promote theuse of evidence-based practice in course design. The revali-dation exercise of 1997 (BSc (Honours) Physiotherapy,Cardiff) facilitated many curricular changes around aconsistent syllabus. It was the intention of the course teamthat such curricular change would facilitate the students’development of problem-solving and critical thinking skillswhile encouraging deeper and more self-reliant learningstrategies.
Table 1 profiles the major Year 1 undergraduate curric-ular differences experienced by two student cohorts before(Cohort 94) and after (Cohort 98) the 1997 revalidationexercise. It is interesting to note the major changes inassessment procedures following revalidation. Cohort 98was exposed to fewer assessment points, which required agreater emphasis on application and understanding oflearning than was evident in the curriculum of Cohort 94.In response to increasing class sizes post revalidation, theacademic staff significantly altered their teaching practiceto facilitate student-learning activity both during and aftercontact time. While operating a systematic approach tocourse design (Diamond, 1998), the course revalidation of1997 acknowledged the dynamic nature of curricula in itsefforts to interrelate the components of aims, teaching,learning and assessment methods. Aware of the commongoals, staff developed a wide range of teaching and learningactivities intended to expose the undergraduates to avariety of learning environments appropriate to theirachievement of the specified aims. Supporting students inthe direction of their own learning was seen as a commongoal for Cohort 98. Group and individual learning activi-ties were included in the new curriculum in response to theassertion that self-directed learning (SDL) effectivenessrequires seeking information for learning outcome comple-tion from all useful sources, i.e. SDL is not synonymouswith learning alone (Garrison, 1997). Group and indi-vidual learning skills are also essential tools for professionalpractice where graduates will work as autonomousmembers of the multidisciplinary team.
Correspondence: Clare Kell, MSc MCSP, Department of Physiotherapy Educa-tion, University of Wales College of Medicine, Heath Park, Cardiff CF144XN, Wales, UK. Tel/fax: 029 20 742267; email: [email protected]
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Having identified the intended 1998 curricular outcomes,it was important to investigate the influence of the changeson the undergraduate students’ learning profile develop-ment. The objectives of this current study were therefore tocompare the learning profile changes of two undergraduatestudent cohorts who had experienced different curricularpresentations of essentially the same syllabus, and then tointerpret the results in terms of curriculum development.
Acknowledging the curricular changes outlined above, itwas assumed that Cohort 98’s learning profile would differfrom that of Cohort 94 over time. While perceived prefer-ence for fact- and skills-based learning would remain high(in recognition of the major skills content of the course), itwas hypothesized that Cohort 98’s preference for an envi-ronment using student-structured learning activities wouldincrease significantly over time at the expense of preferencefor teacher-structured learning environments; studentswould become flexible over time in their preferences towork in isolation or as part of a group. It was furtherhypothesized that Cohort 98 would respond to the curric-ular changes by perceiving greater personal confidence toundertake self-directed learning activities.
Methodology
Sample
With a revalidation exercise having occurred in 1997, thestudy populations were the undergraduate cohorts of 1994(n = 43; mean age = 20.7 yrs) and 1998 (n = 66; meanage = 21.1 yrs) on the BSc (Honours) Physiotherapyprogramme in Cardiff.
Measuring tools
In addition to simple demographic data, studentscompleted the 58-item Self-directed Learning ReadinessScale—A (SDLRS) designed for use with young, educatedadults (Guglielmino, 1977; Long, 1987). The question-naire was amended slightly and anglicized to helpcompletion. This self-rating inventory asks students torate their perception of their possessing the attitudes, abil-ities and personality characteristics necessary for self-direction in learning. Guglielmino (1989) reports that theSDLRS is a measure of the students’ current readiness toengage in SDL with the implication that this level isresponsive to change. With scores ranging from 58 to 290,the average mean score for this study population issuggested as 214 within an average ‘band’ of 189–240(Guglielmino, 1977).
The cohorts also completed the Rezler & French(1975) Learning Preference Inventory (LPI), which wasdesigned to measure the preference of undergraduatestudents of the healthcare professions for one learningenvironment over another. Again a self-rating question-naire, students ranked their preference for learning acrossthree dipole dimensions of learning environments as listedin Table 2. Validated for use with populations similar tothis current study (Rezler & Rezmovic, 1982; Vittetoe &Hooker, 1983), scores for each variable range from 15 to90. High and low preferences for a learning environmentare identified by scores of greater than 60 and less than 40respectively. Rezler & French (1975) suggest that studentswith a score of 50 demonstrate flexibility towards theirlearning.
Table 1. Curricular differences between Cohort 94 and Cohort 98 to Take 3
Cohort 94 Cohort 98
Cohort size: n = 43 Cohort size: n = 66Seven compulsory assignments during Year 1 Four compulsory assignments during year 112 practical skills assessed throughout Year 1 as learnt Practical skills assessed by three end-of-year examsWritten exam questions knowledge-based Written exam questions focusing on application and topic
integrationEvidence of didactic teaching Active student learning focusProblem-solving approach to learning introduced in year 2 Problem-solving approach to learning introduced from
admission
Table 2. Description of the six dimensions of learning preference
Learning preference Description
Concrete learning Preference for learning tangible, specific, practical tasks with focus on skillsAbstract learning Preference for learning theories and generating hypotheses with focus on general
principles and conceptsTeacher-structured learning Preference for learning in a well-organized, teacher-directed class, with expectations,
assignments and goals clearly identifiedStudent-structured learning Preference for learning via student-organized tasks with emphasis on autonomy and
self-directionInterpersonal learning Preference for working or learning with others, with emphasis on harmonious relations
between students and teacher and among studentsIndividual learning Preference for learning or working alone, with emphasis on self-reliance and solitary
tasks such as reading
Source: Rezler & French (1975).
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Administration points
Cohorts completed the measurement package on admis-sion to the course (i.e. before they had been exposed to thecourse but with the baggage of past experience and expec-tation), at the end of the taught part of the first year priorto their progression examinations in pre-clinical sciences,and during the second year prior to their clinical place-ments but following a term of clinical sciences. Eachadministration occurred during class time ensuringconsistent testing conditions. The administration pointswere selected in line with staff perception of potentialcurricular influences on student learning, i.e. studentsrevising for exams in large volume, fact-based subjects(Take 2) and students developing problem-solving andcritical thinking skills in preparation for clinical practice(Take 3).
Data analysis
The data analysis included complete data sets only, thus byTake 3 Cohort 94 comprised 38 students with Cohort 98continuing into Year 2 with only the 45 full-time students.In order to compare the curricular influences on thecohorts, the cohort changes were plotted and tested forsignificance using a repeated measures ANOVA wherescore change over time was tested by means of a first-orderpolynomial contrast. A difference between cohorts in scorechange over time was tested as a time change * cohortinteraction. The cohort main effect was also tested. Thesignificance level was 0.05.
Results
Cohort entry profiles
The sequence of Figures 1–4 present the entry profiles foreach of the variables considered in this study.
Figures 1–4 suggest that Cohort 94 and Cohort 98 weresimilar in their entry variable mean scores; no significantdifferences were found. The cohorts can collectively besaid to prefer a concrete, fact-based environment which isteacher-structured, reject a student-structured environ-ment and consider themselves flexible learners in abstract,interpersonal and individual learning environments. Bothcohorts display average perceived readiness for undertakingSDL.
Changes in scores over time
The change in student perception for each of the variablesover time is presented graphically in Figures 5–8. Allfigures present group mean score data and the LPI varia-bles are displayed with their dipole pair for comparison.Table 3 records the numerical mean score and standarddeviation data for each cohort’s variables acrossadministrations.
Readiness for SDL
Figure 5 illustrates a decrease in SDLRS mean scores overtime, but this change was not significant. There was nosignificant difference in cohort response, suggesting thatcurriculum change had no influence on this variable.
Figure 1. Intake Profile SDLRS.Note: Mean scores and standard deviations presented as variance from suggested population mean scores—dark horizontalline (Guglielmino, 1977).
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LPI results
Concrete and abstract learning preferences. Figure 6 demon-strates a significant increase in concrete learning preferencefor both cohorts (p < 0.05). A trend (p < 0.1) was
displayed in the different cohort responses over time,suggesting that Cohort 94 responded more strongly to theconcrete environment. The cohort mean scores for theabstract learning variable did not change significantly overtime.
Figure 2. Intake Profile Learning Preference dipole pair concrete vs. abstract learning.Note: Mean scores presented with standard deviations. The dark horizontal line corresponds to the average score of a‘flexible’ student.
Figure 3. Intake Profile Learning Preference dipole pair teacher vs. student structured learning.Note: Mean scores presented with standard deviations. The dark horizontal line corresponds to the average score of a‘flexible’ student.
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Teacher- and student-structured learning preferences. The per-sistence of both cohorts’ dipole preference over time isillustrated in Figure 7. Of note however, is the direction ofthe change in cohort mean scores over time.
Although the change and cohort response differenceswere not significant over time with respect to the teacher-structured variable, Figure 7 would suggest that a changein response direction exists between the cohorts over time.
Figure 7 also illustrates an interaction between thecohorts’ mean scores for the student-structured variable.There was a significant difference (p < 0.05) in cohortresponse with respect to the student-structured learningpreference variable. Cohort 94’s preference for learning inthis environment decreased over time (principally duringYear 1), while Cohort 98 demonstrated a slow acceptanceof the student-structured environment.
Figure 4. Intake Profile Learning Preference dipole pair interpersonal vs. individual learning.Note: Mean scores presented with standard deviations. The dark horizontal line corresponds to the average score of a‘flexible’ student.
Table 3. Change in variable mean scores over time for Cohorts 1994 and 1998
Variable Cohort 1994 Cohort 1998
SDLRS 1 209.51 ± 21.49 215.46 ± 21.472 208.85 ± 21.89 209.50 ± 19.713 207.05 ± 24.35 210.90 ± 18.37
Concrete LP 1 57.51 ± 11.94 60.95 ± 9.592 62.43 ± 12.31 61.34 ± 9.333 65.24 ± 11.34 62.40 ± 11.38
Abstract LP 1 47.60 ± 9.94 47.12 ± 7.892 48.38 ± 10.94 47.64 ± 9.113 46.55 ± 8.75 47.56 ± 8.25
Teacher-structured LP 1 60.44 ± 12.96 62.02 ± 13.252 63.45 ± 12.11 60.45 ± 12.683 62.29 ± 13.87 59.38 ± 12.33
Student-structured LP 1 45.60 ± 13.43 41.08 ± 11.692 39.68 ± 12.12 41.79 ± 11.313 39.92 ± 12.32 42.83 ± 12.30
Interpersonal LP 1 53.16 ± 13.64 58.83 ± 12.842 56.18 ± 13.00 52.64 ± 12.703 55.95 ± 14.02 55.44 ± 14.47
Individual LP 1 50.60 ± 12.39 45.02 ± 10.922 44.90 ± 12.93 50.64 ± 11.153 44.71 ± 13.66 44.98 ± 11.04
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Interpersonal and individual learning preferences. As Figure 8demonstrates, the cohorts responded differently over timefor each of the variables. There was a tendency for thecohorts to differ in their response over time with respect tothe interpersonal learning variable (IP) (p < 0.1). ForCohort 98 the perceived preference for the IP environmenttended to decrease over time. Both cohorts displayed asignificant change over time (p < 0.05) with respect to theindividual learning environment. There was a tendency forthe cohorts to differ in their change over time (p < 0.1).
Although not tested statistically, it is interesting tonote the graphical relationship between the SDLRS and
interpersonal learning preference variables over time forCohort 98.
Discussion
The results suggest that the cohorts responded significantly(p < 0.05) differently to their curricula in respect of thestudent-structured learning variable, while displayingtrends (p < 0.1) for the difference in score change over timefor the concrete, interpersonal and individual learningvariables.
Figure 5. Change over time: SDLRS.Note: The dark horizontal line indicates the mean adult score of 214 (Guglielmino, 1977).
Figure 6. Change over time—Learning Preference: concrete vs. abstract learning.Note: The dark horizontal line corresponds to the average score of a ‘flexible’ student.
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While few statistically significant changes in learningprofile development over time were uncovered in thisstudy, the results would suggest that, given the limitationsof self-report inventories, the measuring tools used herewere sensitive to the students’ perceived change. Thisobservation is expected for the SDLRS (Guglielmino,1989) and has led to its use in previous studies to evaluatecourse-specific change (e.g. Kasworm, 1983). The LPI,however, was developed to help teaching staff match theteaching environments/formats to their students’ learningpreferences (Rezler & French, 1975; Loesch & Foley,1988). Students were thought to be motivated and performbetter if they received teaching in line with their learningpreference (Cahill & Madigan, 1984; Pittman, 1983).
With the recent focus on preparation for lifelonglearning, thoughts have turned in favour of exposingstudents to different learning environments in order toextend and challenge their habitual preferences andempower students to select latent learning orientationsmore appropriate to their individual, specialized learningneeds (Kolb, 1983; Loesch & Foley, 1988). The results ofthis study would support the use of the LPI to monitorchange in perceived profile development over time.
The results support the first study hypothesis in respectof an expected increase in student preference for a concretelearning environment over time for both cohorts. At thisstage of the current study one would expect the dipole pref-erence concrete/abstract learning to persist in view of the
Figure 7. Change over time—Learning Preference: teacher vs. student structured learning.Note: The dark horizontal line corresponds to the average score of a ‘flexible’ student.
Figure 8. Change over time—Learning Preference: interpersonal vs. individual learning.Note: The dark horizontal line corresponds to the average score of a ‘flexible’ student.
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large fact and skills components of the course covered pre-clinically. As the students of Cohort 98 continue into clin-ical practice placements, it would be hoped that the deeperlearning skills facilitated in Year 1 would enable them tomake abstractions and generalizations of their concreteknowledge base to meet the individual needs of theirpatients. Helping Cohort 98 to seek out integration andrelevance from the start of the course should make thetransition to clinical practice a natural progression.
It is the change in cohort-perceived preference forteacher- and student-structured learning (Figure 7) overtime that lends moderate short-term support to our 1997curriculum development. The results suggest that Cohort98 may be moving away from a preference for a teacher-structured learning environment in favour of one in whichthey are given more control. As the cohort response for thisdipole pair was significant only in respect of the student-structured preference variable the study hypothesis shouldbe rejected, but with the acknowledgment that possiblecohort interaction is occurring over time for both variablesand should be reviewed.
The different cohort responses to the interpersonal/indi-vidual learning dipole pair (Figure 8) were expected in lightof the efforts to encourage both group work and personallearning in the students of Cohort 98 and supports therelevant study hypothesis. The slight move away from the‘flexible’ score for both dipole variables by Take 3 inCohort 98 may reflect the emphasis on group, clinicalproblem-solving tasks in Year 2. The results, however,would suggest that Cohort 98 is displaying the early signsof learning environment flexibility consistent with theirfuture professional and lifelong learning needs.
On the basis of these results the study hypothesis thatthe 1997 curricular changes would increase students’perceived readiness for self-directed learning (SDLR) overtime has to be rejected. Although no statistically significantdifferences in cohort mean scores over time were recorded,Figure 5 suggests that Year 1 had a detrimental effect onperceived SDLR for Cohort 98, and that Cohort 94 didnot perceive this change. The small increase in variablemean score noted for Cohort 98 at Take 3 mirrors thecohort’s slight increase in preference for a student-struc-tured learning environment at this time, and is thought toreflect the increased emphasis on student activity inlearning during Year 2. The course team must reflect onthe result at Take 2 and consider the possibility of incorpo-rating Year 2 learning and teaching activities into Year 1.
This study offers support for the view that curricularfactors impact on undergraduate learning profile develop-ment. By implication, it is suggested that intentionalcurricular changes could be used to mould student learningdevelopment in a specified direction. It would seem appro-priate, therefore, to focus attention on identifying any‘best-fit’ learning and teaching environments and activitiesthat facilitate development of the myriad of generic skillsidentified as ‘essential’ for graduates who contribute effec-tively to society as self-directed and lifelong learners(NCIHE, 1997). While Grow (1991) and Garrison (1997)offer user-friendly models for SDL skill development,educators should be encouraged to monitor their students’learning styles and preferences and discuss their resultsthrough the local and national learning and teaching
support networks. Collaborative identification and accept-ance of good practice could then have a major impact onwidespread curriculum development.
The possible graphical relationship between the varia-bles SDLRS and interpersonal learning in this study mayalso warrant further investigation. Does the profile suggestthat fledgling self-directed learners need to/prefer towork in group settings while they practise and developconfidence in their new learning skills?
Extending a previous study (Kell & van Deursen, 2000)to include another cohort of undergraduate students hasafforded the academic staff the opportunity to monitor theimpact of intended curricular change on certain aspects ofthe students’ learning profile development and provideduseful feedback for future curricular development. Wesuggest that the adoption of this educational research-in-action approach to curriculum development may be oneroute towards meeting the charge to produce lifelonglearners and detect any unintentional, negative influencesof our curricula on undergraduate learning development.
Practice points
Notes on contributors
CLARE KELL studied physiotherapy at Addenbrooke’s School ofPhysiotherapy, Cambridge; she worked clinically in South Wales for6 years, completed an MSc in Medical Education (UWCM) and isnow lecturer at the Department of Physiotherapy Education,University of Wales College of Medicine, Cardiff.
ROBERT VAN DEURSEN studied physiotherapy at the St. U.P.A.,Utrecht, The Netherlands. Having worked clinically for 7 years, heobtained an MSc in Human Movement Science at the Free Univer-sity, Amsterdam and a PhD in Kinaesiology at Penn StateUniversity, USA, and is now lecturer/research coordinator at theDepartment of Physiotherapy Education, University of WalesCollege of Medicine, Cardiff.
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