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Clinical reasoning skills of speech and language therapy students

Kirsty Hoben{, Rosemary Varley{ and Richard Cox{

{Department of Human Communication Sciences, University of Sheffield, Sheffield, UK {Department of Informatics, School of Science and Technology, University of Sussex, Falmer, Brighton, UK


Background: Difficulties experienced by novices in clinical reasoning have been well documented in many professions, especially medicine (Boshuizen and Schmidt 1992, 2000; Elstein, Shulman and Sprafka 1978; Patel and Groen 1986; Rikers, Loyens and Schmidt 2004). These studies have shown that novice clinicians have difficulties with both knowledge and strategy in clinical reasoning tasks. Speech and language therapy students must also learn to reason clinically, yet to date there is little evidence of how they learn to do so. Aims: In this paper, we report the clinical reasoning difficulties of a group of speech and language therapy students. We make a comparison of a subgroup of these with experienced speech and language therapists' reasoning and proposes some methods and materials to aid the development of clinical reasoning in speech and language therapy students. Methods & Procedures: Student diagnostic reasoning difficulties were analysed during the assessment of unseen cases on an electronic patient database, the Patient Assessment and Training System (PATSy (Lum et al. 2006). Pairs of students were videoed as they completed a one hour assessment of one of three `virtual patients'. One pair of experienced speech and language therapists, who were not part of the project team, also completed an assessment of one of these cases under the same conditions. Screen capture was used to record all on screen activity within PATSy web pages (i.e. mouse pointer position, hyperlink and button presses, page scrolling, browser navigation interactions and data entered); Verbal comments made by participants were analysed via a seven-level coding scheme that aimed to describe the events that occur in the process of diagnostic reasoning. Outcomes & Results: Students displayed a range of competence in making an accurate diagnosis. Diagnostically accurate students showed use of specific professional vocabulary, and a greater use of firm diagnostic statements. For the

Address correspondence to: Kirsty Hoben, Department of Human Communication Sciences, University of Sheffield, 31 Claremont Crescent, Sheffield S10 2TA, UK; e-mail: [email protected]

International Journal of Language & Communication Disorders ISSN 1368-2822 print/ISSN 1460-6984 online # 2007 Royal College of Speech & Language Therapists DOI: 10.1080/13682820601171530


Kirsty Hoben et al.

diagnostically inaccurate students, typical difficulties were a failure to interpret test results and video observations, difficulty in carrying out a sequence of tests consistent with a diagnostic reasoning path, and problems in recalling and using theoretical knowledge. Conclusions and Implications: We discuss how identification of student diagnostic reasoning difficulties can inform the design of learning materials intended to address these problems. Keywords: Clinical reasoning, students, speech and language therapy.

What this paper adds What is already known on this subject Studies in medicine and related fields have shown that students have difficulties with both knowledge and strategy in clinical diagnostic reasoning tasks. To date, there has been little research in this area in speech and language therapy. What this study adds Speech and language therapy students show clinical reasoning difficulties similar to those observed in medicine and other related domains. They could benefit from explicit teaching of strategies to improve their clinical reasoning and consolidate their domain knowledge.

Introduction The literature on novice and expert reasoning in medicine and other domains has identified areas of difficulty for novices in problem solving and reasoning, all of which are connected to a lack of domain knowledge, both in terms of content and structure. Novices show a difficulty in conceptualising problems at a deep, abstract level, characterized by an inability to inhibit attention to surface features, perceive abstract features or judge the relevance of findings and observations. For example, Sloutsky and Yarlas (2000) found that novices, when judging whether visually presented equations had been seen before, based their decisions on surface features such as commonality of numbers or number of addends in the equation, rather than deeper mathematical principles such as associativity. In a study of novices and experts diagnosing cases of breast pathology using microscopy, Crowley et al. (2001) found that novices had difficulty in recognising and interpreting key clinical findings, often missing the location of the lesion altogether or erroneously construing normal findings as pathological. They also found that novices tended to describe features rather than categorise them (e.g. describing what was seen as `big blue blobs', compared to a more expert classification of `central necrosis'). The process of gathering information is more effortful for novices and because they use a less accessible and structured knowledge base, recognition and interpretation of salient cues becomes difficult. Novices have also been found to have difficulty discriminating between relevant and irrelevant information. In a nursing study, Shanteau et al. (1991) found that student nurses rated 67% of items in a nursing scenario as essential in making a diagnosis, compared to expert nurses' judgement of 44% of the items as essential. Thus novices are unable to understand and select the pertinent information about a

Clinical reasoning skills of speech and language therapy students


problem and this in turn makes the data to be considered, and relationships between them, larger and more complex. Boshuizen and Schmidt (2000) argue that changes in knowledge depth and organisation facilitate changes in reasoning skill. The novice moves from individual pieces of knowledge to integration of separate facts into higher level, compiled knowledge in the form of concept clusters, which Boshuizen and Schmidt term `knowledge encapsulation'. They view the final stage of medical reasoning development to be the formation of clinical concepts, where biomedical knowledge is integrated into clinical knowledge and is no longer explicitly used in reasoning. Their experimental work reveals however, that physicians are still able to access this detailed biomedical knowledge when necessary (Boshuizen and Schmidt 1992, Van de Wiel et al. 2000). Boshuizen and Schmidt also claim that at the final stage of reasoning development, illness scripts are formed, consisting of enabling conditions, the `fault' (i.e. the pathophysiological process involved), and the consequences or signs and symptoms of the disease process. The studies of novices cited above illustrate the early stages of Boshuizen and Schmidt's model, with knowledge networks being activated but a lack of ability to extract higher level concepts from the data presented. Patel and Kaufman (2000) claim that biomedical knowledge is not as well integrated in experts as Boshuizen and others propose. Their experiments (e.g. Kaufman et al. 1996) showed that experienced clinicians were able to give accurate clinical explanations of pathophysiology but not necessarily give correct biomedical explanations of basic physiology. Their work suggests that the process of increasing clinical expertise depends on an integration of basic knowledge into clinical concepts. This makes it difficult subsequently to disentangle the basic knowledge from the particular clinical manifestations which a clinician would encounter. The teaching of biomedical sciences on medical courses with a traditional curriculum is generally done at a pre-clinical stage, which explains why first, students are unable to use it at this stage to help with diagnostic reasoning and, second, why it seems to be relearned in a different form when clinical knowledge becomes deeper. These difficulties with knowledge depth, structure and integration impact on novices' ability to reason through a problem and use effective strategies. Novices have difficulty planning a diagnostic strategy and organizing incoming information. Mavis et al. (1998) found that novice medical students had difficulty applying knowledge and strategies flexibly to a diagnostic situation, planning a focussed neurological examination but carrying out an unnecessarily comprehensive one. This unfocussed information gathering has also been shown in case history taking and hypothesis formation. Patel et al. (1997) found that medical students attempting to diagnose a complex endocrinology case were unable to develop specific hypotheses and thereby target their questioning of the patient. Instead, using a standard case history, they adopted a data gathering rather than hypothesis driven approach, and therefore generated a large amount of irrelevant information. Similarly, in scientific reasoning, Klahr (2000) found that novices begin tasks without clear goals, testing without a hypothesis, rather than starting with a hypothesis and carrying out specific tests. Problems with knowledge organization and strategy lead to difficulties in evaluating progress and interpreting findings. Hmelo-Silver et al. (2002) studied novice and expert physicians designing a trial for a new cancer drug. They found


Kirsty Hoben et al.

that novices spent a considerable amount of time monitoring their cognitive activities, through discussion of whether or not they understood all aspects of the task, but much less time than the experts evaluating their progress, for example by comparing the results of trials. Being able to evaluate progress is necessary in any activity, such as clinical reasoning, where hypotheses are formed, tested and evaluated, often in cycles. Efficient evaluation of progress has an effect on the amount of effort involved and the accuracy of the final results or diagnosis. Difficulties in evaluating progress and understanding the significance of findings were also found by Arocha and Patel (1995) in a study of novice medical diagnostic reasoning using inconsistent cases (i.e. cases where clinical findings or test results do not fit with initial information). Novices were generally unable to incorporate inconsistent data into their hypotheses. They were able to generate only a limited number of hypotheses, which in itself precludes the consideration of alternative hypotheses even if the inconsistency is perceived. McAllister and Rose (2000) acknowledge the relative paucity of research into the processes of clinical reasoning in speech and language therapy. However, there are similarities in the global characteristics of diagnostic reasoning across related professions such as medicine, physiotherapy, occupational therapy and nursing, i.e. all these professionals take a history, carry out some form of assessment or investigative testing, compare the results to known disorders and come to a diagnosis. It is likely, therefore, that speech and language therapy novices will display similar reasoning difficulties to those observed in novices from other clinical domains. Cox and Lum (2004) described a range of domain general and domain specific skills necessary in speech and language therapy. Examples of domain general skills (i.e. skills that any intelligent person could be expected to have without any specific training) include: hypothesis generation, an ability to decide how evidence supports a hypothesis and deductive reasoning ability (i.e. making a hypothesis from a piece of data and then systematically examining further data to determine whether they support or contradict the hypothesis). Examples of domain specific skills (i.e. those that relate to a specific knowledge and skill base, in this case speech and language therapy) include: knowledge of language processing models and tests and an ability to link these to observations of patients' communication impairments. The current research examined speech and language therapy students' developing diagnostic reasoning skills, using an existing database of speech and language therapy cases, the Patient Assessment and Training System (PATSy) (Lum et al. 2006). The database consists of `virtual patients', and includes video clips, medical history, assessment results and links to related publications. Students were able to `administer' tests to patients and keep a log of their findings and conclusions. Methods Participants The study recruited eight masters level and 26 undergraduate speech and language therapy students from two UK universities via posters on notice boards and email. Undergraduate students were in the penultimate year of their studies and

Clinical reasoning skills of speech and language therapy students


masters level students were in their final year. In addition, a pair of speech and language therapists experienced in aphasia but not members of the project team took part in order to provide a comparison. University ethical approval was granted for the conduct of the research and all usual ethical practices were observed. Procedure Students worked in pairs (dyad pairings were mostly self-selected). The main reason for the use of dyads was to collect verbal protocols that were more natural and less cognitively disruptive for participants to produce than think-aloud protocols from individual participants. Dyads were given one hour to undertake the diagnosis of one of three pre-selected PATSy cases; DBL, RS, both acquired cases, or JS1, a developmental case. The PATSy cases used for the study all exhibited a degree of ambiguity in their clinical presentation i.e. their behavioural profile might be consistent with a number of possible diagnoses of underlying impairment. Participants were asked to come to a consensus decision and produce a set of statements that described key impairments shown by the case, and if possible, an overall diagnostic category. The interaction of the students was video-recorded and all participants completed a learning log that is automatically generated and stored within PATSy. The learning log contained questions such as `What conclusions can you draw from what you have just seen?' and `Where do you want to go next (further test data?, introductory video?)'. A dynamic video screen capture was also performed using commercial software (CamtasiaH). Subsequently these multiple data sources were synchronized for playback and analysis using NITE tools ( NITE/), developed at the University of Edinburgh. Coding The statements made by participants in dialogue were coded for particular statement types that might occur in diagnostic reasoning. Coding was carried out directly from the combined files described above. All utterances of students relating to the diagnosis of the case were coded. The coding scheme was developed for the purposes of this study. An initial six-level scheme was devised a priori from expectations of novice difficulties in the diagnostic process by two experienced speech and language therapists on the project team with extensive experience of student clinical learning, who then independently coded the statements. Using a consensus method, they discussed codings and revised descriptors for each level. This process resulted in the original level 5 category being subdivided into two levels based on the granularity of diagnosis. After a series of iterations of the descriptors for each category, inter-rater reliability was established by the two raters independently coding a random selection of 30% of the dialogue data sample. One rater was blind to the PATSy case, participants and site at which data were collected, although occasionally the content of the discussion, particularly regarding the paediatric case, made it impossible always to be blind to the case. A Kappa score of 0.89 was achieved, indicating satisfactory inter-rater reliability. One rater then coded all spoken statements produced by the


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student dyads and the expert pair. Intra-rater reliability was assessed on codings with a time interval of 4 months between categorisations. A Kappa score of 0.97 was achieved, indicating highly satisfactory intra-rater reliability. The coding scheme contained seven categories. Other. N Level Zero: the dataAmbiguousonstatements and hypotheses that could not be tested with available the PATSy system. Level One: Reading of data. Statements that consisted of reading aloud data N without making any comment or additional interpretation. Making a concrete observation. This N Level Two:about a single piece of data and which category included statements did not use any


professional terminology. Level Three: Making a superordinate level clinical observation. Descriptive statements which used a higher level concept couched in professional register, or compared information from two or more test results. Level Four: Hypothesis. Statements that expressed a predicted causal relationship between two factors. Level Five: General diagnostic statement. Statements including or excluding a superordinate diagnostic category and of the type that might be used in a report to another, non-SLT professional. Level Six: Specific diagnostic statement. Statements in this category shared the characteristics of Level Five diagnostic statements. However, statements at this level had a greater detail of description than Level Five statements and might be used in a report to another speech and language therapist. (See appendix A for definitions and examples of each category.)

The coding categories relate to the literature reviewed earlier, for example, Level Two might be seen as attention to surface features of behaviour (Sloutsky and Yarlas 2000), Level Three could be viewed as the integration of knowledge into larger concept clusters (Boshuizen and Schmidt 2000), Level Four links to the ability to plan a diagnostic strategy (Patel et al. 1997), and Levels Five and Six could characterize the evaluation of progress through a series of assessments (Patel and Arocha 1995). Analyses Before the coding of data, student pairs were independently categorized as diagnostically accurate (DA) or inaccurate (DI) based on whether they reached a diagnosis for the case they had worked on (either DBL, RS or JS1) that was at an appropriate level for a novice/newly qualified speech and language therapist. This categorisation was carried out by experienced speech and language therapists on the project team. DA students were those that were able to report key impairments displayed by the case (e.g. type and extent of lexical retrieval deficit). Similarly, the tests selected by a pair were evaluated for relevance to the case and to the comments in dialogue and in their written log. In addition, test choices were examined for relatedness and movement along a diagnostic path. For example, a test sequence involving a switch from a picture semantics task such as Pyramids and Palm Trees (Howard and Patterson 1992) to non-word repetition in the context of discussion of written word comprehension was classed as an unrelated sequence. The

Clinical reasoning skills of speech and language therapy students


performance of a subset of student dyads who diagnosed the aphasic case DBL was compared with the dyad of experienced clinicians who diagnosed the same case. Results Eight pairs of students were categorized as being diagnostically accurate (DA). The remaining nine pairs did not produce a diagnosis that was viewed as accurate for a novice clinician and were categorised as diagnostically inaccurate (DI). The difficulties displayed by the diagnostically inaccurate subgroup were: a failure to interpret test results and video observations by assessing their relevance in relation to evidence already gathered, difficulty in carrying out a sequence of tests consistent with a diagnostic reasoning path, and problems in recalling and using theoretical knowledge.

Figure 1. Mean number of statements made by student dyads from the diagnostically accurate and diagnostically inaccurate subgroups over 1 hour and all three PATSy test cases.

Figure 1 displays the mean number of statements of each type produced by the DA and DI subgroups (17 dyads total, across all three PATSy cases). The data reveal some disparities between the groups: the DI dyads produced a greater number of Level One and Two statements, indicating more reading aloud of information on the screen without interpretation and a greater number of descriptive statements in nonspecialist register. Student use of Level Three, Four and Five, statements, that is, superordinate statements using professional terminology, statements postulating relationships between two variables, and general diagnostic statements, appeared with similar frequency in the two subgroups. The DA group produced more Level Six statements, where the diagnosis was expressed in professional terminology of fine granularity. This suggested that this subgroup could link the patterns of behaviour observed in the patient case to highly specific domain knowledge, i.e. these students could bridge the gap between theory and practice.


Kirsty Hoben et al.

Table 1. Numbers of statements at each level for experts, diagnostically accurate (DA) and diagnostically inaccurate (DI) pairs expressed as a percentage of the total for each pair for PATSy case DBL Diagnostic statement level percentage of total Participants Expert pair DA pair C DA pair F DA pair P DI pair E DI pair K DI pair M 0 0 4.16 8.33 0 3.70 13.04 6.45 1 0 0 0 9.52 7.40 4.34 29.03 2 5.26 12.5 4.16 4.76 7.40 8.69 25.80 3 60.52 41.66 54.16 23.80 37.03 34.78 25.80 4 13.15 20.83 12.5 33.33 40.74 21.73 12.90 5 7.89 12.5 4.16 4.76 0 13.04 0 6 13.15 8.33 16.66 14.28 3.70 4.34 0 Row total (%) 100 100 100 100 100 100 100

The experienced pair of therapists diagnosed case DBL and their performance was compared with the subset of students (dyads n56) who also diagnosed this case. For the purposes of making a valid comparison, we compared only those student pairs who diagnosed the same case. The results are presented in Table 1. Table 1 shows that the experienced therapists did not make Level Zero or Level One statements. They make very few Level Two statements but a greater number of Level Three statements, compared with either of the student groups. Experienced therapists also made approximately 20% firm diagnostic statements at Levels Five and Six. Student results on case DBL conform to the general pattern observed across all PATSy cases. Again, DA students made fewer Level One and Two statements and more Level Six statements. The profile of the DA students was more similar to that of experienced clinicians than to that of the DI group. DA students also made approximately 20% Level Five and Six statements, whilst the occurrence of such statements was generally lower in the DI subgroup. Further qualitative analyses of student performance revealed a number of themes indicative of problems in diagnostic reasoning. Examples are given below which are typical of students in the DI group. Students displayed few wellelaborated schemata of diagnoses, leading to difficulties in making sense of data:

`She was making errors, wasn't she, in producing words but I haven't really found any pattern yet.' `It's hard to know what to look at isn't it? What means something and what doesn't.' `I'm not entirely sure why they're (client's responses) not very appropriate.'

The high numbers of Level One and Two statements in the DI group reflect problems in this area. The patient's behaviours are noted, but the students have difficulty interpreting their significance or relationship. Some students showed difficulty in carrying out a sequence of tests consistent with a diagnostic-reasoning path. For example one dyad chose the following test sequence at the beginning of their assessment of the paediatric case JS1: a handwriting sample, a non-word reading test, followed by a word reading test and then a questionnaire on the client's social and academic functioning. They started with marginally relevant and relatively fine grained

Clinical reasoning skills of speech and language therapy students


tests before going on to look at the questionnaire. In this case, the questionnaire gave useful background information about broad areas of difficulty for the client. Evaluating this evidence would have been more useful at the beginning of their assessment as it allows the clinician to `reduce the problem space' in which they are working and to focus their diagnostic effort on areas that are more likely to be crucial to the understanding of the case. No hypotheses or specific clinical reasons for these tests were given by the students, indicating that they were not using the tests to attempt to confirm or disconfirm a hypothesis about the case they were diagnosing. Their approach was descriptive, rather than theory or hypothesis-driven. Discussion Studies of reasoning in domains related to speech and language therapy and the results of the current study provide evidence that there may be common patterns of development from novice to expert. Results from the current research show that student speech and language therapists exhibit difficulty in conceptualising problems at a deep, abstract level, planning a diagnostic strategy, organising incoming information, evaluating progress and interpreting findings, as reported by the studies in other domains. Theoretically motivated and empirically supported resources to address these issues could be developed, such as `intelligent tutors', using hypermedia support to allow novice speech and language therapy students to learn in a `virtual' situation, thus allowing them to be better prepared when interacting with real patients. The analysis of the data presented here has led to a number of ideas for enhancing students' diagnostic reasoning, which offer potential for use as formative assessment tools for educators, but also as self-assessment tools for students. For example, making students aware of the types of statement described in the coding scheme presented here could provide a structure for self-monitoring and assessment, enabling students to evaluate and develop their own diagnostic reasoning skills. A student making Level Two statements could use the descriptors in the coding scheme to develop those types of statements into Level Three statements, for example, from `Scores worse when words are involved' (Level Two) to `Worse at accessing semantic information from written form' (Level Three). Similarly, assisting students to formulate testable hypotheses can facilitate an efficient and effective assessment strategy. For example, from `I think this is quite significant, this non-word reading thing' to `Her inability to read non-words might indicate dyslexia and poor ability to translate from orthography to speech'. In addition, a resource currently under development consists of a computerbased interactive tree diagram (Figure 2) of the cognitive subprocesses associated with language comprehension and production which may be evaluated by a particular speech, language or cognitive test. Such tools enable students to understand the processes that are probed by a particular test. In turn, this could then facilitate theory and hypothesis-driven reasoning during the assessment process. The tool could also be used as part of a tutorial with questions such as: `Using the diagram, trace a description for the TROG. How might thinking about tests in this way be helpful when planning a test strategy?' Students could be prompted to make superordinate clinical observations and a tentative hypothesis early in an assessment session. After making a hypothesis,


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Figure 2. Computer-based interactive tree diagram for describing tests.

students could be prompted about a suitable test either before they had made a choice, or immediately afterwards if they chose an inappropriate test for their hypothesis. For students using PATSy, these prompts could take the form of a video showing two students discussing a relevant topic. After a series of tests, students could be prompted to attempt a firm diagnostic statement. Again, within PATSy, video clip examples of students doing this could be offered concurrently. This concept of vicarious learning (i.e. learning by observing the learning of others) is the focus of current research activity ( McAllister and Rose (2000) promote and describe curriculum interventions designed to make the diagnostic reasoning process conscious and explicit, without separating it from domain knowledge. They claim that this helps students to integrate knowledge and reasoning skills. Whilst this is not a universally shared opinion (e.g. Doyle 1995, 2000), the results described here indicate that students may benefit from explicit teaching of strategies to improve their clinical reasoning and consolidate their domain knowledge. Acknowledgements The research was funded as part of a 3-year ESRC grant, under the Teaching and Learning Research Programme (Grant No. RES139-25-0127). The authors thank Dr Julie Morris at the University of Newcastle for her advice and contributions to this paper, and colleagues at the University of Edinburgh, John Lee and Susen Rabold, The University of Newcastle, Barbara Howarth and the University of Sussex, Jianxiong Pang. References

AROCHA, J. F. and PATEL, V. L., 1995, Novice diagnostic reasoning in medicine: Accounting for clinical evidence. Journal of the Learning Sciences, 4, 355­384. BOSHUIZEN, H. P. A. and SCHMIDT, H. G., 1992, On the role of biomedical knowledge in clinical reasoning by experts, intermediates and novices. Cognitive Science, 16, 153­184. BOSHUIZEN, H. P. A. and SCHMIDT, H. G., 2000, The development of clinical reasoning expertise. In J. Higgs and M. Jones (eds), Clinical Reasoning in the Health Professions (Edinburgh: Butterworth Heinemann), pp. 15­22.

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CAMTASIAH, 2006, Techsmith Camtasia Studio Screen Recording and Presentation (available at: http:// (accessed on 1 September 2006). COX, R. and LUM, C., 2004, Case-based teaching and clinical reasoning: seeing how students think with PATSy. In S. Brumfitt (ed.), Innovations in Professional Education for Speech and Language Therapy (London: Whurr), pp. 169­196. CROWLEY, R. S., NAUS, G. J. and FRIEDMAN, C. P., 2001, Development of visual diagnostic expertise in pathology. In S. Bakken (ed.), American Medical Informatics Association Annual Symposium (Washington, DC: AMIA). DOYLE, J., 1995, Issues in teaching clinical reasoning to students of speech and hearing science. In J. Higgs and M. Jones (eds), Clinical Reasoning in the Health Professions (Edinburgh: Butterworth Heinemann), pp. 224­234. DOYLE, J., 2000, Teaching clinical reasoning to speech and hearing students. In J. Higgs and M. Jones (eds), Clinical Reasoning in the Health Professions (Edinburgh: Butterworth-Heinemann), pp. 230­235. ELSTEIN, A. S., SHULMAN, L. S. and SPRAFKA, S. A., 1978, Medical Problem Solving: An Analysis of Clinical Reasoning (Cambridge, MA: Harvard University Press). HMELO-SILVER, C., NAGARAJAN, A. and DAY, R. S., 2002, `It's harder than we thought it would be': a comparative case study of expert-novice experimentation strategies. Science Education, 86, 219­243. HOWARD, D. and PATTERSON, K., 1992, Pyramids and Palm Trees: A Test of Semantic Access from Words and Pictures (Bury St Edmunds: Thames Valley Test Co.). KAUFMAN, D. R., PATEL, V. L. and MAGDER, S. A., 1996, The explanatory role of spontaneously generated analogies in a reasoning about physiological concepts. International Journal of Science Education, 18, 369­386. KLAHR, D., 2000, Exploring Science: The Cognition and Development of Discovery Processes (Cambridge, MA: MIT Press). LANGUAGE TECHNOLOGY GROUP, UNIVERSITY of EDINBURGH, 2006, NITE XML Toolkit Homepages (available at: (accessed on 1 September 2006). LUM, C., COX, R., KILGOUR, J. and MORRIS, J., 2006, Universities of Sussex, Edinburgh and Newcastle. PATSy: A Database of Clinical Cases for Teaching and Research (available at: (accessed on 1 September 2006). MAVIS, B. E., LOVELL, K. L. and OGLE, K. S., 1998, Why Johnnie can't apply neuroscience: testing alternative hypotheses using performance-based assessment. Advances in Health Sciences Education, 3, 165­175. MCALLISTER, L. and ROSE, M., 2000, Speech­language pathology students: learning clinical reasoning. In J. Higgs and M. Jones (eds), Clinical Reasoning in the Health Professions (Edinburgh: ButterworthHeinemann), pp. 205­213. PATEL, V. L. and AROCHA, J. F., 1995, Congnitive models of clinical reasoning and conceptual representation. Methods of Information in Medicine, 34 (1), 1­10. PATEL, V. L., GROEN, G. J. and PATEL, Y. C., 1997, Cognitive aspects of clinical performance during patient workup: the role of medical expertise. Advances in Health Sciences Education, 2, 95­114. PATEL, V. L. and GROEN, G. J., 1986, Knowledge based solution strategies in medical reasoning. Cognitive Science, 10, 91­116. PATEL, V. L. and KAUFMAN, D. R., 2000, Clinical reasoning and biomedical knowledge: Implications for teaching. In J. Higgs and M. Jones (eds), Clinical Reasoning in the Health Professions (Edinburgh: Butterworth-Heinemann), pp. 33­44. RIKERS, R. M. J. P., LOYENS, S. M. M. and SCHMIDT, H. G., 2004, The role of encapsulated knowledge in clinical case representations of medical students and family doctors. Medical Education, 38, 1035­1043. SHANTEAU, J., GRIER, M., JOHNSON, J. and BERNER, E., 1991, Teaching decision-making skills to student nurses. In J. Baron and R. V. Brown (eds), Teaching Decision Making to Adolescents (Hillsdale, NJ: Lawrence Erlbaum Associates). SLOUTSKY, V. M. and YARLAS, A. S., 2000, Problem representation in experts and novices: Part 2. Underlying processing mechanisms. In L. R. Gleitman and A. K. Joshi (eds), Twenty Second Annual Conference of the Cognitive Science Society (Mahwah, NJ: Lawrence Erlbaum Associates). VAN DE WIEL, M. W. J., BOSHUIZEN, H. P. A. and SCHMIDT, H. G., 2000, Knowledge restructuring in expertise development: evidence from pathophysiological representations of clinical cases by students and physicians. European Journal of Cognitive Psychology, 12, 323­355.

134 Appendix: Seven-level coding scheme Level Zero: Other

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Statements that contain features that cross-coding categories are recorded as ambiguous. In addition, hypotheses that cannot be tested with the data available on the PATSy system, e.g. speculation about the patient's lifestyle or the patient's state of mind on a particular day, e.g. `he's had two heart attacks and he's had this parietal infarct which kind of, suggests to me ... poor lifestyle' or `Perhaps he didn't feel like doing a test that day'. Level One: Reading of data Statements that consist of reading aloud data without making any comment or additional interpretation, e.g. `Forty-six out of fifty two on Pyramids and Palm Trees picture­picture'. Level Two: Making a concrete observation Statements about a single piece of data which do not use any professional terminology (i.e. they could be made by a lay person with no domain specific knowledge). Statements at this level do make some level of comment on, or interpretation of the data, beyond simply reading it aloud, e.g. `He didn't get them all right'. Level Three: Making a superordinate level clinical observation Statements that use higher level concepts and show evidence of the use of some professional register rather than lay terms, e.g. `there were some semantic errors there'. Alternatively, statements at this level may compare information to a norm or other test result, e.g. `11 months behind but that doesn't strike me as particularly significant'. These statements can be differentiated from higher level statements because they do not make firm diagnostic statements such as `he's definitely got comprehension problems'. Similarly, they are not couched in hypothesis language, i.e. they could not trigger a specific search strategy though assessments or observations. They may make statements from the data including words such as `seems', but do not predict from the data. Level Four: Hypothesis The crucial element is the expression of a causal relationship between two factors. This may be expressed by an explicit or implicit `if ... then' structure, e.g. `If he's finding the picture­picture condition difficult, then that suggests his central semantic system is probably not intact'. Statements at this level may be phrased as a question directed at the data, e.g. `are these results saying autism?' They may be couched as a predictive statement that might trigger a search/test strategy, e.g. `he could be dyspraxic'. Level Five: Diagnostic statement Statements in this category are phrased in the language of diagnostic certainty. They may contain strong linguistic markers of certainty, such as `definitely' or `certain'.

Clinical reasoning skills of speech and language therapy students


They do not contain any indicators of uncertainty. Statements with tag questions, such as `He has an expressive language disorder, doesn't he?' are carefully evaluated, as the tags have a social function. Statements in this category consist of those which include or exclude a superordinate diagnostic category. The granularity of the statement is such that it allows broad exclusion/inclusion of diagnostic categories, e.g. language versus speech disorder. Statements in this category are likely to be found in a letter to another professional rather than a speech and language therapist, e.g. `He definitely has word finding problems'. Level Six: Diagnostic certainty Statements in this category are phrased in the language of diagnostic certainty. They may contain strong linguistic markers of certainty, such as `definitely' or `certain'. They do not contain any indicators of uncertainty. Statements in this category consist of those which include or exclude a superordinate diagnostic category. They use predominantly appropriate professional register. They are likely to be used in a report to a speech and language therapist, i.e. they use specific professional terminology. Statements at this level have a finer granularity of description than level five statements, e.g. `The patient has an impaired central semantic system'.



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