Case Repository Research Articles

Conduct of Virtual Neurology DM Final Examination during COVID-19 Pandemic.

Medical training programs are witnessing immense disruptions worldwide due to the ongoing COVID-19 pandemic. Keeping in mind the trainees' future prospects, it is important to provide continuity of teaching and timely certification assessments. Overcoming the obstacles to routine functioning presented by SARS-CoV-2 spread, we recently conducted the DM Neurology exit examination in a hybrid virtual format. We created a curated case repository with history and clinical examination findings followed by structured questions that could be built upon for case discussions. The external examiners assessed the candidates virtually through a video conferencing platform. The end results were well accepted by all key stake holders. The concerns, logistics and experience of conducting the DM Neurology exit exam in a virtual format are summarized here.

Medical Teaching and Assessment in the Era of COVID-19.

The coronavirus pandemic has had a significant influence on medical education, most notably in terms of content delivery and provision of assessments. These unique times have facilitated the introduction of many new educational methods in medical schools globally each of which with potential merits and drawbacks. Importantly, the use of remote platforms to carry out online teaching has been especially vital in ensuring the continued training of doctors but other techniques such as telemedicine, online clinical case repositories and even virtual reality headsets are also being used to overcome these difficult circumstances. Some institutions also opted for open book written examinations raising issues surrounding this format’s legitimacy and potential benefits. Practical examinations are even harder to facilitate and although most were cancelled, this crisis may result in innovation which changes their future format. For example some may include audible clinical signs played online through a computer speaker to replace clinical examination. Overall, the COVID-19 pandemic has caused an overhaul of medical school orthodoxy that whilst disruptive, may serve to expose institutions to novel means of teaching and assessment which may ultimately improve medical education in future.

UTCPredictor: An uncertainty‐aware novel teaching cases predictor

AbstractTeaching cases are crucial for computer science (e.g., software testing) teaching. With the fast development of computer science, old and outdated teaching cases cannot meet the requirements of teaching. Therefore, teachers need to update teaching case repository continually and timely. However, teaching case development is an extremely time‐consuming work. Given today's complex and fast‐moving environment of computer science, teachers often feel blind about about what types of cases should be added for teaching. This paper presents UTCPredictor—an automated approach of predicting novel teaching cases from real production by identifying the most uncertain data, which are always with new features that reflect the latest developments and trends in the field. The implementation of UTCPredictor is based on the idea of interactive machine learning as well as several text mining techniques. To evaluate the effectiveness of UTCPredictor, we take bug report case building in software testing teaching as an example, using UTCPredictor to perform 10‐fold cross‐validation on an existing teaching case set. The performance in terms of indicators; Recall, Precision, and F1‐score, achieved three very competitive values—0.91, 0.94, and 0.85, respectively. We further evaluate the effectiveness of UTCPredictor through a user study and a questionnaire. The results are very positive; the user study indicates that educators can build a teaching case set from latest bug report repository by spending only 8.16%–18.11% time costs compared with traditional manual approach; the responses from 2,000 students for the questionnaire show that the teaching cases built with UTCPredictor are very popular among students.

Introduction To Case Study Development And Use For Engaged Learning

Location: JC Room B Case studies can be a powerful and effective means by which to engage students through the process of learning towards a goal or goals. Case studies provide an instructional method that further allows students to incorporate material from different parts of a course into a practical application. For some disciplines, there a large repository of cases that teachers can use. However, sometimes they are not ideal for the specific objectives of a course or, in the case of some disciplines, there is a dearth of existing case studies. The development of case studies for a course allows the teacher to focus and align material with the needs and experiences of his/her/their students, and utilization of case studies that rely on freely accessible material reduce barriers to access. Case studies in the classroom can be adapted in ways that are useful in Active Learning Classrooms or take advantage of technology. The objectives of this proposed workshop are to provide teachers with foundational knowledge about the development and use of different types of case studies in the classroom and to provide participants with an opportunity apply this knowledge to their own material. The session is suitable for teachers of undergraduate and graduate students for in-person or on-line formats that are new to developing case studies. The proposed workshop will be divided into four components: 1) theoretical foundations; 2) application; 3) discussion; and, 4) implementation. In the theoretical foundations component, the facilitator will provide an overview of different types of case studies and research-backed information about when and for whom they are most effective. Participants will have the opportunity to ask questions and the facilitator will be lead a discussion with examples. In the application stage, participants will have a period of time for independent work, following a guided worksheet, to develop an outline and strategy for developing a case study for their own course. In the discussion stage, participants will work in pairs or small groups to share their ideas and provide peer feedback. In the implementation component, participants will return to the full group to hear about tips and tricks for utilizing Blackboard to move cases into an on-line format, which can be useful for assignments or in the instruction of hybrid or fully on-line courses. As the end of the session, participants will leave with an idea and plan for incorporating a case study into one of their courses and know where they can seek additional information and resources for developing and implementing case studies. The proposed facilitator for the session has participated in case study development workshops, completed on-line course development certification, and recently re-designed GCH 762 Environmental Epidemiology with newly developed case studies to target student learning towards specific skill development and knowledge utilization. The workshop will draw upon these experiences and provide participants with theoretical foundation and practical application towards their own teaching.

Surgery at Sea: Exploring the Training Gap for Isolated Military Surgeons

Newly-graduated military general surgeons often find themselves isolated at sea, solely responsible for all surgical care of several thousand sailors, regardless of the surgical specialty training required for any individual procedure. This educational need assessment explored trends in afloat surgical care over the last 25 years, and assessed trainees' preparedness for their expected role as an isolated surgeon. A sample of deidentified US Navy Ship's Surgeon case logs were reviewed to determine afloat case load trends in 5 common afloat case categories (urologic/gynecologic, anorectal, hernia, appendectomy, and hand/orthopedic/trauma) from 1990s to 2017. Individual procedures were mapped to American College of Surgeons/Military Health System Knowledge, Skills, and Attitudes line items to ensure afloat-relevant skills were identified. Recent military resident case logs were then compared with afloat cases to evaluate relevant trainee experience. US Navy ships at sea from 1995 to 2017. US Navy afloat-deployed surgeons, totaling 1340 cases within the study period. Case log analysis of 1340 surgeries, comprising >200 months at sea, reflected 46 named procedures; 34 of 46 (74%) correlated to an intraoperative knowledge, skills, and attitudes item. The most common surgeries were vasectomy, (304 of 1340, 23%). No difference in case mix was apparent comparing pre- and post-2000 deployments (representing afloat laparoscopic integration) in 4 of 5 categories, while hernias proportionally declined. Case volume per deployment markedly declined overall (p < 0.001) and in each category. Resident case log analysis from 2012 to 2016 showed experience was limited in urologic/gynecologic, orthopedic, and open appendectomy categories. No formal case repository exists for afloat surgery, making detailed analysis problematic. Current training provides excellent surgical education but minimal exposure to rare-but-real cases expected on deployments, which may not translate to competency for the isolated, afloat surgeon. Military surgical leadership should embrace training for these cases and assertively invest in the development of the military's newest surgeons.

Use case repository framework based on machine learning algorithm to analyze the software development estimation with intelligent information systems

The success of information system process depends on accuracy of software estimation. Estimation is done at initial phase of software development. It requires a collection of all relevant required information for estimating the software effort. In this paper, a methodology is proposed to maintain a knowledgeable use case repository to store the use cases of various projects in several software project-related domains. This acts as a reference model to compare similar use cases of similar types of projects. The use case points are calculated and using this, schedule estimation and effort estimation of a project are calculated using the formulas of software engineering. These values are compared with the estimated effort and scheduled effort of a new project under development. Apart from these, the effective machine learning technique called neural network is used to measure how accurately the information is processed by use of case repository framework. The proposed machine learning-based use case repository system helps to estimate and analyze the effort using the machine learning algorithms.

Test cases for comparison of two interfacial solvers

We present novel test cases to study the effect of density ratio on free and forced capillary oscillations at an interface separating two immiscible, inviscid fluids. Using these tests, results obtained from two in-house developed, Volume of Fluid (VoF) based codes for solving the incompressible Euler equations with surface tension, are reported. The first solver (FSS: free surface solver) ignores the dynamics of the lighter phase solving only for the denser phase, explicitly accounting for free surface boundary conditions using the approach presented in Malan et al. (2015). The second is an interfacial solver which implements the one-fluid algorithm (OFS: one fluid solver) for simulating two-phase flows. We present four test cases involving inviscid, free and parametrically forced, capillary oscillations on Cartesian and circular base states. Explicit closed form analytical solutions in the linearised limit are presented for each case. It is found that for small value of the nonlinearity parameter (ϵ or ϵaz < 0.1) and with density ratio (ρr) ranging from 50−103, the FSS shows excellent agreement with linearised analytical predictions. For lower values of density ratio approaching ∼ 10 and below, the FSS results display substantial disagreement with those obtained from the OFS as well as with analytical predictions. At large density ratios ( ∼ 103) (and larger values of ϵ or ϵaz), the FSS shows better accuracy over longer times, when compared to the OFS, partly due to less numerical dissipation. The analytical results presented here add to the repository of test cases in the two-phase CFD literature and are expected to be useful for validating numerical models for surface tension. The comparison of the OFS with the FSS also provides useful rule-of-thumb estimates for choosing between speed (FSS) and accuracy (OFS) in numerical computations of capillary, interfacial flows.

Constructing Large Scale Cohort for Clinical Study on Heart Failure with Electronic Health Record in Regional Healthcare Platform: Challenges and Strategies in Data Reuse.

Regional healthcare platforms collect clinical data from hospitals in specific areas for the purpose of healthcare management. It is a common requirement to reuse the data for clinical research. However, we have to face challenges like the inconsistence of terminology in electronic health records (EHR) and the complexities in data quality and data formats in regional healthcare platform. In this paper, we propose methodology and process on constructing large scale cohorts which forms the basis of causality and comparative effectiveness relationship in epidemiology. We firstly constructed a Chinese terminology knowledge graph to deal with the diversity of vocabularies on regional platform. Secondly, we built special disease case repositories (i.e., heart failure repository) that utilize the graph to search the related patients and to normalize the data. Based on the requirements of the clinical research which aimed to explore the effectiveness of taking statin on 180-days readmission in patients with heart failure, we built a large-scale retrospective cohort with 29647 cases of heart failure patients from the heart failure repository. After the propensity score matching, the study group (n=6346) and the control group (n=6346) with parallel clinical characteristics were acquired. Logistic regression analysis showed that taking statins had a negative correlation with 180-days readmission in heart failure patients. This paper presents the workflow and application example of big data mining based on regional EHR data.

Using data-driven sublanguage pattern mining to induce knowledge models: application in medical image reports knowledge representation

BackgroundThe use of knowledge models facilitates information retrieval, knowledge base development, and therefore supports new knowledge discovery that ultimately enables decision support applications. Most existing works have employed machine learning techniques to construct a knowledge base. However, they often suffer from low precision in extracting entity and relationships. In this paper, we described a data-driven sublanguage pattern mining method that can be used to create a knowledge model. We combined natural language processing (NLP) and semantic network analysis in our model generation pipeline.MethodsAs a use case of our pipeline, we utilized data from an open source imaging case repository, Radiopaedia.org, to generate a knowledge model that represents the contents of medical imaging reports. We extracted entities and relationships using the Stanford part-of-speech parser and the “Subject:Relationship:Object” syntactic data schema. The identified noun phrases were tagged with the Unified Medical Language System (UMLS) semantic types. An evaluation was done on a dataset comprised of 83 image notes from four data sources.ResultsA semantic type network was built based on the co-occurrence of 135 UMLS semantic types in 23,410 medical image reports. By regrouping the semantic types and generalizing the semantic network, we created a knowledge model that contains 14 semantic categories. Our knowledge model was able to cover 98% of the content in the evaluation corpus and revealed 97% of the relationships. Machine annotation achieved a precision of 87%, recall of 79%, and F-score of 82%.ConclusionThe results indicated that our pipeline was able to produce a comprehensive content-based knowledge model that could represent context from various sources in the same domain.

Monitoring Anesthesia Care Delivery and Perioperative Mortality in Kenya Utilizing a Provider-driven Novel Data Collection Tool.

Perioperative mortality rate is regarded as a credible quality and safety indicator of perioperative care, but its documentation in low- and middle-income countries is poor. We developed and tested an electronic, provider report-driven method in an East African country. We deployed a data collection tool in a Kenyan tertiary referral hospital that collects case-specific perioperative data, with asynchronous automatic transmission to central servers. Cases not captured by the tool (nonobserved) were collected manually for the last two quarters of the data collection period. We created logistic regression models to analyze the impact of procedure type on mortality. Between January 2014 and September 2015, 8,419 cases out of 11,875 were captured. Quarterly data capture rates ranged from 423 (26%) to 1,663 (93%) in the last quarter. There were 93 deaths (1.53%) reported at 7 days. Compared with four deaths (0.53%) in cesarean delivery, general surgery (n = 42 [3.65%]; odds ratio = 15.80 [95% CI, 5.20 to 48.10]; P < 0.001), neurosurgery (n = 19 [2.41%]; odds ratio = 14.08 [95% CI, 4.12 to 48.10]; P < 0.001), and emergency surgery (n = 25 [3.63%]; odds ratio = 4.40 [95% CI, 2.46 to 7.86]; P < 0.001) carried higher risks of mortality. The nonobserved group did not differ from electronically captured cases in 7-day mortality (n = 1 [0.23%] vs. n = 16 [0.58%]; odds ratio =3.95 [95% CI, 0.41 to 38.20]; P = 0.24). We created a simple solution for high-volume, prospective electronic collection of perioperative data in a lower- to middle-income setting. We successfully used the tool to collect a large repository of cases from a single center in Kenya and observed mortality rate differences between surgery types.

D-COURT

A revolutionary mobile application that uses IBM’s Watson Analytics tool to help Judges to quickly deliver the right judgment. The application contains repository of cases of the past. Watson Analytics tool figures out the cases relating to an ongoing case. This also serves to be invaluable to the budding lawyers. Using this application will definitely reduce the cumbersome job of maintaining paper files, enables quick retrieval of desired information which in turn avoids a case being prolonged.

Judicial Law-Making: Unlocking the Creative Powers of Judges in Terms of Section 39(2) of the Constitution

The law-making role of judges has always been the subject of much controversy. For a good many a year and especially during the apartheid regime, the approach to statutory interpretation that dominated the South African courts was the orthodox textual position. According to the textualists, as they were referred to, the position that was adopted was that legislation was to be interpreted within the framework of the words used by the legislature. The courts were not empowered to make any modifications, alterations or additions to the legislative text, as this function was solely the responsibility of the legislature. The paradigmatic shift in emphasis since 1994 from a system of parliamentary sovereignty to constitutional supremacy changed this position significantly. The key consideration of statutory interpretation was that the aim and purpose of legislation was to be considered with the values of the Constitution forming the over-arching principle in the process of interpretation. The courts were enjoined to reconcile the purpose of the legislation with the provisions of the Constitution, and in particular, the Bill of Rights. The emerging view in support of the purposive or the teleological theory has been that judges do indeed have a law-making function in the process of interpretation. Since the early 1990's, it has been observed that the judiciary has been able to assert its influence on the development of the law and the emerging jurisprudence, as a result of the powers derived from the Constitution, and in particular section 39(2). The article examines the extent to which the judiciary can use this power in a post-democratic constitutional era, in South Africa, to achieve justice. From the repository of cases, which forms the basis of the discussion, the article proposes a set of factors that ought to be heeded by our courts in the application of section 39(2).&#x0D;

Building locally relevant ethics curricula for nursing education in Botswana

Aim The goal of this multi-institutional collaboration was to develop an innovative, locally relevant ethics curriculum for nurses in Botswana. Background Nurses in Botswana face ethical challenges that are compounded by lack of resources, pressures to handle tasks beyond training or professional levels, workplace stress and professional isolation. Capacity to teach nursing ethics in the classroom and in professional practice settings has been limited. Methods A pilot curriculum, including cases set in local contexts, was tested with nursing faculty in Botswana in 2012. Results Thirty-three per cent of the faculty members indicated they would be more comfortable teaching ethics. A substantial number of faculty members were more likely to introduce the International Council of Nurses Code of Ethics in teaching, practice and mentoring as a result of the training. Based on evaluation data, curricular materials were developed using the Code and the regulatory requirements for nursing practice in Botswana. A web-based repository of sample lectures, discussion cases and evaluation rubrics was created to support the use of the materials. Discussion A new master degree course, Nursing Ethics in Practice, has been proposed for fall 2015 at the University of Botswana. The modular nature of the materials and the availability of cases set within the context of clinical nurse practice in Botswana make them readily adaptable to various student academic levels and continuing professional development programmes. Conclusion The ICN Code of Ethics for Nursing is a valuable teaching tool in developing countries when taught using locally relevant case materials and problem-based teaching methods. Implications for Nursing The approach used in the development of a locally relevant nursing ethics curriculum in Botswana can serve as a model for nursing education and continuing professional development programmes in other sub-Saharan African countries to enhance use of the ICN Code of Ethics in nursing practice.

Regression Test Case Selection for MultiObjective Optimization Using Metaheuristics

A new heuristic algorithm is proposed by this paper, on multi-objective optimization using metaheuristics and TSP (travelling salesman problems). Basic thinking behind this algorithm is minimizing the TSP path or tour by dividing the entire tour into blocks that are overlapped to each other and then improve each individual block separately. Although it is unproven that a good solution have small improvement chances if a node moved far way to a position compared to its original solution. By intensively searching each block, further improvement is possible in TSP path or tour that never be supported in various search methods and genetic algorithm. Proposed algorithm and computational experiment performance was tested, and these tests are carried out with support of already present instances of problem. According to the results represented by paper, the computation verifies that proposed algorithm can solve TSPs efficiently. Proposed algorithm is then used for selecting optimal test cases, thousands of those test cases which are selected after confirming that they identify bugs and they itself selected from a repository of test cases; these thousand test cases are those test cases which are selected from several thousand test cases because they detect bugs. Few test cases from repository act as milestones (nodes) and having certain weight associated with each, proposed algorithm based on TSP implemented over selected result and select the optimal result or path or solution. These selected optimal test cases or selected path are further used to perform the regression testing, by applying those test cases selected by proposed algorithm in order to remove most of the faults or bugs effectively, i.e. take less time and identify almost all the bugs with few test cases. Hence this proposed algorithm assures most effective solution for regression testing test case selection.

Assessment of feasibility of running RSNA's MIRC on a Raspberry Pi: a cost-effective solution for teaching files in radiology.

The value of a teaching case repository in radiology training programs is immense. The allocation of resources for putting one together is a complex issue, given the factors that have to be coordinated: hardware, software, infrastructure, administration, and ethics. Costs may be significant and cost-effective solutions are desirable. We chose Medical Imaging Resource Center (MIRC) to build our teaching file. It is offered by RSNA for free. For the hardware, we chose the Raspberry Pi, developed by the Raspberry Foundation: a small control board developed as a low cost computer for schools also used in alternative projects such as robotics and environmental data collection. Its performance and reliability as a file server were unknown to us. For the operational system, we chose Raspbian, a variant of Debian Linux, along with Apache (web server), MySql (database server) and PHP, which enhance the functionality of the server. A USB hub and an external hard drive completed the setup. Installation of software was smooth. The Raspberry Pi was able to handle very well the task of hosting the teaching file repository for our division. Uptime was logged at 100 %, and loading times were similar to other MIRC sites available online. We setup two servers (one for backup), each costing just below $200.00 including external storage and USB hub. It is feasible to run RSNA's MIRC off a low-cost control board (Raspberry Pi). Performance and reliability are comparable to full-size servers for the intended purpose of hosting a teaching file within an intranet environment.

A systematic test case selection methodology for product lines: results and insights from an industrial case study

In the context of product lines, test case selection aims at obtaining a set of relevant test cases for a product from the entire set of test cases available for a product line. While working on a research-based innovation project on automated testing of product lines of Video Conferencing Systems (VCSs) developed by Cisco, we felt the need to devise a cost-effective way of selecting relevant test cases for a product. To fulfill such need, we propose a systematic and automated test selection methodology using: 1) Feature Model for Testing (FM_T) to capture commonalities and variabilities of a product line; 2) Component Family Model for Testing (CFM_T) to model the structure of test case repository; 3) A tool to automatically build restrictions from CFM_T to FM_T and traces from CFM_T to the actual test cases. Using our methodology, a test engineer is only required to select relevant features through FM_T at a higher level of abstraction for a product and the corresponding test cases will be obtained automatically. We evaluate our methodology by applying it to a VCS product line called Saturn with seven commercial products and the results show that our methodology can significantly reduce cost measured as test selection time and at the same time achieves higher effectiveness (feature coverage, feature pairwise coverage and fault detection) as compared with the current manual process. Moreover, we conduct a questionnaire-based study to solicit the views of test engineers who are involved in developing FM_T and CFM_T. The results show that test engineers are positive about adapting our methodology in their current practice. Finally, we present a set of lessons learnt while applying product line engineering at Cisco for test case selection.

Building locally relevant ethics curricula for nursing education in Botswana.

The goal of this multi-institutional collaboration was to develop an innovative, locally relevant ethics curriculum for nurses in Botswana. Nurses in Botswana face ethical challenges that are compounded by lack of resources, pressures to handle tasks beyond training or professional levels, workplace stress and professional isolation. Capacity to teach nursing ethics in the classroom and in professional practice settings has been limited. A pilot curriculum, including cases set in local contexts, was tested with nursing faculty in Botswana in 2012. Thirty-three per cent of the faculty members indicated they would be more comfortable teaching ethics. A substantial number of faculty members were more likely to introduce the International Council of Nurses Code of Ethics in teaching, practice and mentoring as a result of the training. Based on evaluation data, curricular materials were developed using the Code and the regulatory requirements for nursing practice in Botswana. A web-based repository of sample lectures, discussion cases and evaluation rubrics was created to support the use of the materials. A new master degree course, Nursing Ethics in Practice, has been proposed for fall 2015 at the University of Botswana. The modular nature of the materials and the availability of cases set within the context of clinical nurse practice in Botswana make them readily adaptable to various student academic levels and continuing professional development programmes. The ICN Code of Ethics for Nursing is a valuable teaching tool in developing countries when taught using locally relevant case materials and problem-based teaching methods. The approach used in the development of a locally relevant nursing ethics curriculum in Botswana can serve as a model for nursing education and continuing professional development programmes in other sub-Saharan African countries to enhance use of the ICN Code of Ethics in nursing practice.

Multilinear PageRank

In this paper, we first extend the celebrated PageRank modification to a higher-order Markov chain. Although this system has attractive theoretical properties, it is computationally intractable for many interesting problems. We next study a computationally tractable approximation to the higher-order PageRank vector that involves a system of polynomial equations called multilinear PageRank. This is motivated by a novel “spacey random surfer” model, where the surfer remembers bits and pieces of history and is influenced by this information. The underlying stochastic process is an instance of a vertex-reinforced random walk. We develop convergence theory for a simple fixed-point method, a shifted fixed-point method, and a Newton iteration in a particular parameter regime. In marked contrast to the case of the PageRank vector of a Markov chain where the solution is always unique and easy to compute, there are parameter regimes of multilinear PageRank where solutions are not unique and simple algorithms do not converge. We provide a repository of these nonconvergent cases that we encountered through exhaustive enumeration and randomly sampling that we believe is useful for future study of the problem.

Gerenciamento do Escopo em Projetos Originados por Meio de Licitação

A licitação, procedimento administrativo voltado para a aquisição de serviços e bens pelo Estado, é um tema relevante para gestores públicos, fornecedores de serviços e bens e para a sociedade em geral. O presente artigo tem como objetivo analisar o “projeto básico” ou “termo de referência”, elementos fundamentais de um edital de licitação, como instrumentos para o gerenciamento do escopo na gestão de projetos, principalmente na definição e controle do escopo. Além de trazer conceitos gerais e regulamentos sobre o tema licitação, o texto pretende esclarecer quais os objetivos e qual a importância do “projeto básico” ou do “termo de referência”, buscando mostrar até que ponto a adequada delineação do serviço ou compra pretendido por órgão da Administração Pública, ainda na fase do edital, pode contribuir para a gestão do projeto. O texto abrange o estudo dos instrumentos de definição do objeto a ser licitado desde a elaboração do edital da licitação, até a conseqüente contratação do vencedor. O trabalho é baseado principalmente em pesquisas bibliográficas sobre o tema em livros, artigos e repositórios de jurisprudência.DOI:10.5585/gep.v4i3.150

Diagnostic Imaging Learning Resources Evaluated by Students and Recent Graduates

Many learning resources can help students develop the problem-solving abilities and clinical skills required for diagnostic imaging. This study explored veterinary students' perceptions of the usefulness of a variety of learning resources. Perceived resource usefulness was measured for different levels of students and for academic versus clinical preparation. Third-year (n=139) and final (fifth) year (n=105) students and recent graduates (n=56) completed questionnaires on perceived usefulness of each resource. Resources were grouped for comparison: abstract/low complexity (e.g., notes, multimedia presentations), abstract/high complexity (e.g., Web-based and film case repositories), concrete/low complexity (e.g., large-group "clicker" workshops), and concrete/high complexity (e.g., small-group interpretation workshops). Lower-level students considered abstract/low-complexity resources more useful for academic preparation and concrete resources more useful for clinical preparation. Higher-level students/recent graduates also considered abstract/low-complexity resources more useful for academic preparation. For all levels, lecture notes were considered highly useful. Multimedia slideshows were an interactive complement to notes. The usefulness of a Web-based case repository was limited by accessibility problems and difficulty. Traditional abstract/low-complexity resources were considered useful for more levels and contexts than expected. Concrete/high-complexity resources need to better represent clinical practice to be considered more useful for clinical preparation.