Generating, weaving and curating: disciplinary processes for reading literary text

Purpose The purposes of this study is to expand on previous work in English language arts (ELA) disciplinary literacy and to unpack literary text reading processes across three different participant groups. Design/methodology/approach The authors recruited literary scholars and first-year college students to read literary texts aloud and voice their thoughts. Transcripts were collaboratively coded and analyzed using a priori and emergent coding. Findings This study presents the findings in two ways. First, this study grouped the codes into four categories, namely, background knowledge, comprehension, disciplinary knowledge and building an interpretation. This described the differences in frequencies among the participants’ strategy use. Next, to more fully describe how participants read literary texts, this study presents the data using three processes, namely, generating, weaving and curating. These findings indicate a continuum of strategies and processes used by participants. Practical implications The study suggests using the ELA heuristic for instruction, which includes moving students beyond generating and weaving by asking them to do their own interpretive work of curation. This potential roadmap for instruction avoids a deficit mindset for students by recommending low-stakes opportunities that meet students where they are as they build their capacity for interpretive moves. Originality/value The findings help the field to gain an understanding of what novices and experts do when they read literary text, including both strategies and processes. This study also provide an ELA heuristic that has instructional implications. This study adds to the body of knowledge for disciplinary literacy in ELA in both theoretical and practical ways.

Diagnostic reasoning in cardiovascular medicine

ABSTRACT Research in cognitive psychology shows that expert clinicians make a medical diagnosis through a two step process of hypothesis generation and hypothesis testing. Experts generate a list of possible diagnoses quickly and intuitively, drawing on previous experience. Experts remember specific examples of various disease categories as exemplars, which enables rapid access to diagnostic possibilities and gives them an intuitive sense of the base rates of various diagnoses. After generating diagnostic hypotheses, clinicians then test the hypotheses and subjectively estimate the probability of each diagnostic possibility by using a heuristic called anchoring and adjusting. Although both novices and experts use this two step diagnostic process, experts distinguish themselves as better diagnosticians through their ability to mobilize experiential knowledge in a manner that is content specific. Experience is clearly the best teacher, but some educational strategies have been shown to modestly improve diagnostic accuracy. Increased knowledge about the cognitive psychology of the diagnostic process and the pitfalls inherent in the process may inform clinical teachers and help learners and clinicians to improve the accuracy of diagnostic reasoning. This article reviews the literature on the cognitive psychology of diagnostic reasoning in the context of cardiovascular disease.

Caffe2Unity: Immersive Visualization and Interpretation of Deep Neural Networks

Deep neural networks (DNNs) dominate many tasks in the computer vision domain, but it is still difficult to understand and interpret the information contained within these networks. To gain better insight into how a network learns and operates, there is a strong need to visualize these complex structures, and this remains an important research direction. In this paper, we address the problem of how the interactive display of DNNs in a virtual reality (VR) setup can be used for general understanding and architectural assessment. We compiled a static library as a plugin for the Caffe framework in the Unity gaming engine. We used routines from this plugin to create and visualize a VR-based AlexNet architecture for an image classification task. Our layered interactive model allows the user to freely navigate back and forth within the network during visual exploration. To make the DNN model even more accessible, the user can select certain connections to understand the activity flow at a particular neuron. Our VR setup also allows users to hide the activation maps/filters or even interactively occlude certain features in an image in real-time. Furthermore, we added an interpretation module and reframed the Shapley values to give a deeper understanding of the different layers. Thus, this novel tool offers more direct access to network structures and results, and its immersive operation is especially instructive for both novices and experts in the field of DNNs.

Movement-level process modeling of microsurgical bimanual and unimanual tasks

Purpose Microsurgical techniques require highly skilled manual handling of specialized surgical instruments. Surgical process models are central for objective evaluation of these skills, enabling data-driven solutions that can improve intraoperative efficiency. Method We built a surgical process model, defined at movement level in terms of elementary surgical actions ($$n=4$$ n = 4 ) and targets ($$n=4$$ n = 4 ). The model also included nonproductive movements, which enabled us to evaluate suturing efficiency and bi-manual dexterity. The elementary activities were used to investigate differences between novice ($$n=5$$ n = 5 ) and expert surgeons ($$n=5$$ n = 5 ) by comparing the cosine similarity of vector representations of a microsurgical suturing training task and its different segments. Results Based on our model, the experts were significantly more efficient than the novices at using their tools individually and simultaneously. At suture level, the experts were significantly more efficient at using their left hand tool, but the differences were not significant for the right hand tool. At the level of individual suture segments, the experts had on average 21.0 % higher suturing efficiency and 48.2 % higher bi-manual efficiency, and the results varied between segments. Similarity of the manual actions showed that expert and novice surgeons could be distinguished by their movement patterns. Conclusions The surgical process model allowed us to identify differences between novices’ and experts’ movements and to evaluate their uni- and bi-manual tool use efficiency. Analyzing surgical tasks in this manner could be used to evaluate surgical skill and help surgical trainees detect problems in their performance computationally.

Harnessing the Wisdom of the Confident Crowd in Medical Image Decision-making

Improving the accuracy of medical image interpretation is critical to improving the diagnosis of many diseases. Using both novices (undergraduates) and experts (medical professionals), we investigated methods for improving the accuracy of a single decision maker and a group of decision makers by aggregating repeated decisions in different ways. Participants made classification decisions (cancerous versus non-cancerous) and confidence judgments on a series of cell images, viewing and classifying each image twice. We first examined whether it is possible to improve individual-level performance by using the maximum confidence slating algorithm (Koriat, 2012b), which leverages metacognitive ability by using the most confident response for an image as the ‘final response’. We find maximum confidence slating improves individual classification accuracy for both novices and experts. Building on these results, we show that aggregation algorithms based on confidence weighting scale to larger groups of participants, dramatically improving diagnostic accuracy, with the performance of groups of novices reaching that of individual experts. In sum, we find that repeated decision making and confidence weighting can be a valuable way to improve accuracy in medical image decision-making and that these techniques can be used in conjunction with each other.

Virtual Prospecting in Paleontology Using a Drone-Based Orthomosaic Map: An Eye Movement Analysis

Paleontological fieldwork is often a time-consuming process and resource intensive. With unexplored and remote areas, the satellite images, geology, and topography of an area are analyzed to help survey for a site. A drone-based orthomosaic map is suggested as an additional tool for virtual paleontology fossil prospecting. The use of an orthomosaic map was compared to the use of a typical satellite map when looking for fossil sites to prospect. Factors were chosen for their impact when prospecting for a fossil site and availability of data. Eye movement data were captured for a convenience sample of paleontologists from a local university. Each band within the satellite map measures 7741 × 7821 with a ground resolution of 30 m/pix, and the ground resolution of the orthomosaic map is 2.86 cm/pix with a resolution of 52,634 × 32,383. Experts displayed a gaze behavior suggestive of high analysis levels as well as being able to identify and analyze features rapidly—this is illustrated through the presence of both longer and shorter fixations. However, experts appeared to look at both maps in more detail than novices. The orthomosaic map was very successful at both attracting and keeping the attention of the map reader on certain features. It was concluded that an orthomosaic-based drone map used in conjunction with a satellite map is a useful tool for high spatial density virtual prospecting for novices and experts.

Problem Representation in Occupational Therapy

<p>Clinical reasoning is a fundamental component of occupational therapy practice. Educators, researchers and clinicians are faced with the challenge of understanding and fostering the acquisition of clinical reasoning skills. The aim of this study was to examine the internal problem representations held by students and clinicians in respect of clients they had been treating for a period of time. Such representations form the basis on which treatment is formulated so are highly influential in the clinical reasoning process. The ultimate purpose of the study was to identify educational strategies that could be used to assist students to develop clinical reasoning skills. Understandings gained from the literature and from observation, indicated that there would be differences between novices and experts and that the work setting would affect problem representation. Thus the influence of experience and location was the primary focus of the study. To place the study within the context of the occupational therapy literature, the beliefs underlying problem representation were also explored to determine whether or not these were consistent with the philosophical assumptions identified in the literature. The method of investigation was an interview with pre-determined questions. The interview was consistent with the theory base of the study (ie. information processing), but the analysis also included the investigation of qualitative aspects. To ensure a developmental perspective was gained, respondents included students on two different levels of an occupational therapy course and clinicians who were currently practicing. The total number of respondents was 67 ie. 14 stage II students, 31 stage III students (ie. in their final year) and 22 clinicians. The study illustrated that the environmental context affects problem representation in respect of both the amount of data to be considered and the nature of that data. Differences between students' and clinicians' representation of the problem were related to qualitative aspects rather than identification of the elements relevant to treatment planning. In particular, clinicians were more able to elaborate on the data, justify their responses and provide a humanistic perspective beyond the more technical aspects of knowing the clients concerns. The beliefs governing thinking about treatment, demonstrated consistency with the occupational therapy literature (apart from one assumption). A major finding of this study is that the development of schemata related to practice areas is the basis of sound reasoning and justification of treatment planning decisions. Both domain specific knowledge and an understanding of the environmental context are important to the forming of these schemata. The implication for teaching is that the wealth of experiential knowledge that is gained by students while on clinical practice should be tapped to enable them to make links with academic knowledge and thus develop a comprehensive problem representation.</p>

Problem Representation in Occupational Therapy

<p>Clinical reasoning is a fundamental component of occupational therapy practice. Educators, researchers and clinicians are faced with the challenge of understanding and fostering the acquisition of clinical reasoning skills. The aim of this study was to examine the internal problem representations held by students and clinicians in respect of clients they had been treating for a period of time. Such representations form the basis on which treatment is formulated so are highly influential in the clinical reasoning process. The ultimate purpose of the study was to identify educational strategies that could be used to assist students to develop clinical reasoning skills. Understandings gained from the literature and from observation, indicated that there would be differences between novices and experts and that the work setting would affect problem representation. Thus the influence of experience and location was the primary focus of the study. To place the study within the context of the occupational therapy literature, the beliefs underlying problem representation were also explored to determine whether or not these were consistent with the philosophical assumptions identified in the literature. The method of investigation was an interview with pre-determined questions. The interview was consistent with the theory base of the study (ie. information processing), but the analysis also included the investigation of qualitative aspects. To ensure a developmental perspective was gained, respondents included students on two different levels of an occupational therapy course and clinicians who were currently practicing. The total number of respondents was 67 ie. 14 stage II students, 31 stage III students (ie. in their final year) and 22 clinicians. The study illustrated that the environmental context affects problem representation in respect of both the amount of data to be considered and the nature of that data. Differences between students' and clinicians' representation of the problem were related to qualitative aspects rather than identification of the elements relevant to treatment planning. In particular, clinicians were more able to elaborate on the data, justify their responses and provide a humanistic perspective beyond the more technical aspects of knowing the clients concerns. The beliefs governing thinking about treatment, demonstrated consistency with the occupational therapy literature (apart from one assumption). A major finding of this study is that the development of schemata related to practice areas is the basis of sound reasoning and justification of treatment planning decisions. Both domain specific knowledge and an understanding of the environmental context are important to the forming of these schemata. The implication for teaching is that the wealth of experiential knowledge that is gained by students while on clinical practice should be tapped to enable them to make links with academic knowledge and thus develop a comprehensive problem representation.</p>

The Extended-Expert-As-Teacher (EEAT) Model

Recently, social epistemologists have sought to establish what the governing epistemic relationship should be between novices and experts. In this article, the author argues for, and expands upon, Helen De Cruz’s expert-as-teacher model. For although this model is vulnerable to significant challenges, the author proposes that a specifically extended version can sufficiently overcome these challenges (call this the “extended-expert-as-teacher” model, or the “EEAT” model). First, the author shows the respective weaknesses of three influential models in the literature. Then, he argues the expert-as-teacher model can overcome its weaknesses by adding what he calls the “Authority Clause”, “Advisor Clause”, and “Ex Post Facto Clause” of the EEAT model. After developing a robust account of these clauses, the author entertains three major objections. First, he responds to the charge that the EEAT model is little better than the expert-as-authority model. Second, he responds to a double-counting objection. Lastly, he responds to a pragmatic objection from complexity.