scholarly journals Alternatively Assessing Conceptual Learning in an Emergency Clinical Environment—A Mixed Methods Design

2020 ◽  
Vol 4 (2) ◽  
pp. 27
Author(s):  
Zhidong Zhang ◽  
Alice Yang Zhang
Keyword(s):  
Problem Solving ◽  
Cognitive Processes ◽  
Alternative Assessment ◽  
Assessment Tool ◽  
Cognitive Model ◽  
Clinical Problem ◽  
Assessment Model ◽  
Clinical Environment ◽  
Cognitive Content ◽  
Dynamic Learning

Modeling cognitive processes in clinical learning environments is a necessary first step towards improving learning assessment and medical practice by using an alternative assessment model. Verbal protocol and cognitive content analyses are effective methods of exploring such cognitive processes. For the purpose of simplifying the discussion, we have labeled these processes as Identification of Information, Advanced Cognition, and Medical Cognitive Action. Exploring problem solving processes with Bayesian network techniques can characterize students' dynamic learning processes quantitatively, identify differences in cognitive components at different stages of learning and better represent clinical problem solving features.We develop a hierarchical cognitive model as a cognitive assessment tool to describe the complex cognitive network relations, which can be applied to various clinical cognitive situations. The study concludes that the cognitive model was useful in identifying students' learning trajectories by representing the different cognitive features.

scholarly journals IMPLEMENTATION OF SSI CONCEPT MAPPING AS A DYNAMIC LEARNING ENVIRONMENT TO ENHANCE STUDENTS' SCIENTIFIC PERFORMANCE

2021 ◽  
Vol 20 (6) ◽  
pp. 969-982
Author(s):  
King-Dow Su
Keyword(s):  
Problem Solving ◽  
Learning Environment ◽  
Concept Mapping ◽  
Assessment Tool ◽  
Moral Dilemma ◽  
Validity And Reliability ◽  
Dynamic Learning ◽  
Scientific Performance ◽  
Context Learning ◽  
Positive Presentations

The presented research focuses on verifying the confluent application of concept mapping (CM) and socio-scientific issues (SSI) according to the value-laden and moral dilemma orientation to construct problem-solving performance. This research sets up some perspectives for all 146 participants, including 139 students and 7 experts. All findings reveal that the design of SSICM contexts includes a rebuttal process and incense claim to improve students' argument response (16.4%), to increase content knowledge and illuminate their science learning by argumentations. To develop an assessment tool with high validity and reliability (Cronbach's α > .9) and find positive presentations of all learning attitudes in the SSICM context, learning environment and results will concern the best argumentation process. Students’ interview responses and SWOT analysis of teachers indicate that SSICM's use of argument in the classroom is a real benefit. The research provided a better paradigm of attempts to combine analytical and academic hypotheses to explain literature sources by teachers, researchers, textbook developers, and editors. Keywords: concept mapping (CM), problem-solving, socio-scientific issues (SSI), SSICM contexts

scholarly journals Online and other ICT-based Training Tools for Problem-solving Skills

2016 ◽  
Vol 11 (06) ◽  
pp. 35
Author(s):  
Athanasios Drigas ◽  
Maria Karyotaki
Keyword(s):  
Problem Solving ◽  
Learning Environments ◽  
Cognitive Processes ◽  
Metacognitive Skills ◽  
Dynamic Learning ◽  
Self Monitoring ◽  
Problem Solving Skills ◽  
Social Dynamic ◽  
Key Factor ◽  
Real World Learning

Problem-solving requires creative skills, critical thinking as well the ability to implement ideas and theories in practical ways. Moreover, interactive and self-managed problem-solving experiences promote students’ motivation as expressed through the developmental progression of learners’ metacognitive skills, such as self-monitoring and self-reinforcement. Effective learning based on constructivist didactics, encompassing self-organized learning in combination with active and creative problem-solving in collaborative settings, advances students’ concomitant cognitive and meta-cognitive processes. Hence, students’ co-construction of knowledge embodied in social dynamic learning environments, such as school-based tasks leverage the semantic relationships rising from exercising, verifying and testing of knowledge through information sharing and discussion. Future studies should focus on designing interactive, adaptable, ill-defined, real-world learning environments to elicit students’ cognitive and meta-cognitive processes as a key factor for the effective training of problem-solving skills.

Cognitive Models of Design Ideation

2007 ◽  
Author(s):  
Noe Vargas Hernandez ◽  
Jami J. Shah ◽  
Steven M. Smith
Keyword(s):  
Cognitive Psychology ◽  
Problem Solving ◽  
Mental Imagery ◽  
Cognitive Processes ◽  
Cognitive Model ◽  
Cognitive Models ◽  
Visual Thinking ◽  
Human Problem ◽  
Design Ideation

The objective of this paper is to present a series of proposed cognitive models for specific components of design ideation. Each model attempts to explain specific cognitive processes occurring during ideation. Every model presented here is constructed with elements (i.e. cognitive processes) and theories available from cognitive psychology, human problem solving, mental imagery, and visual thinking. Every model in turn is an element of a higher-level cognitive model of design ideation. These models provide a better understanding of the components involved during ideation and their relationships.

Development of Core Clinical Learning Competencies for Australian Exercise Physiology Students

2020 ◽  
Vol 9 (1) ◽  
pp. 1-9
Author(s):  
Jacqueline Raymond ◽  
Rebecca Sealey ◽  
Fiona Naumann ◽  
Kieron Rooney ◽  
Timothy English ◽  
...  
Keyword(s):  
Assessment Tool ◽  
Physical Activity Intervention ◽  
Lifestyle Modification ◽  
Exercise Physiology ◽  
Clinical Learning ◽  
Clinical Environment ◽  
Clinical Placements ◽  
Entry Level ◽  
Learning Competencies ◽  
Physiology Students

ABSTRACT Background: Clinical placements and assessment are an essential part of education to become a health professional. However, quality assessment in a clinical environment is challenging without a clear representation of what constitutes competence. The aim of this study was to establish core clinical learning competencies for Australian exercise physiology students. Methods: This study used a mixed-methods, multiphase approach. The competencies were developed following electronic surveys and focus groups, with additional refinement provided by the project team. Preliminary validation was conducted via electronic survey where (i) participants rated the importance of each unit of competency for entry-level practice, and (ii) participants who had recently graduated (n = 23) rated the extent to which they perceived they were competent in each unit. Results: The competencies are described as 19 elements organized into 6 units. The units are (i) communication, (ii) professionalism, (iii) assessment and interpretation, (iv) planning and delivery of an exercise and/or physical activity intervention, (v) lifestyle modification, and (vi) risk management. Of 126 survey participants, the majority (93%–98%) considered each unit as being important for entry-level practice. The majority (78%–95%) of recent graduates considered themselves competent in each unit, suggesting the competencies are articulated around the level of a new practitioner. Conclusion: The core clinical learning competencies resulted from an extensive, iterative process involving those with expertise in the area. The competencies have a range of applications, including informing the development of a student placement assessment tool for use in a clinical placement environment.

scholarly journals Remote Virtual Simulation for Incident Commanders—Cognitive Aspects

2021 ◽  
Vol 11 (14) ◽  
pp. 6434
Author(s):  
Cecilia Hammar Wijkmark ◽  
Maria Monika Metallinou ◽  
Ilona Heldal
Keyword(s):  
Decision Making ◽  
Problem Solving ◽  
Cognitive Processes ◽  
Research Methodology ◽  
Current Knowledge ◽  
Learning Objectives ◽  
Virtual Simulation ◽  
Practical Training ◽  
Case Research ◽  
Action Case

Due to the COVID-19 restrictions, on-site Incident Commander (IC) practical training and examinations in Sweden were canceled as of March 2020. The graduation of one IC class was, however, conducted through Remote Virtual Simulation (RVS), the first such examination to our current knowledge. This paper presents the necessary enablers for setting up RVS and its influence on cognitive aspects of assessing practical competences. Data were gathered through observations, questionnaires, and interviews from students and instructors, using action-case research methodology. The results show the potential of RVS for supporting higher cognitive processes, such as recognition, comprehension, problem solving, decision making, and allowed students to demonstrate whether they had achieved the required learning objectives. Other reported benefits were the value of not gathering people (imposed by the pandemic), experiencing new, challenging incident scenarios, increased motivation for applying RVS based training both for students and instructors, and reduced traveling (corresponding to 15,400 km for a class). While further research is needed for defining how to integrate RVS in practical training and assessment for IC education and for increased generalizability, this research pinpoints current benefits and limitations, in relation to the cognitive aspects and in comparison, to previous examination formats.

scholarly journals SARS-CoV-2 Epidemics in Retirement and Nursing Homes in Italy: A New Preparedness Assessment Model after the First Epidemic Wave

2021 ◽  
Vol 18 (11) ◽  
pp. 5712
Author(s):  
Carmelo Gugliotta ◽  
Davide Gentili ◽  
Silvia Marras ◽  
Marco Dettori ◽  
Pietro Paolo Muglia ◽  
...  
Keyword(s):  
Nursing Homes ◽  
Perceived Risk ◽  
Assessment Tool ◽  
Resident Training ◽  
Assessment Model ◽  
Infection Prevention And Control ◽  
Field Assessment ◽  
Italian Context ◽  
And Control ◽  
The City

The aim of the study is to evaluate the preparedness of retirement and nursing homes in the city of Sassari at the end of the first wave of the severe acute respiratory syndrome coronavirus 2 epidemic, first by investigating the risk perception of epidemic outbreaks by the facility managers and subsequently by carrying out a field assessment of these facilities. To perform the field assessment, a checklist developed by the CDC (Infection Prevention and Control Assessment Tool for Nursing Homes Preparing for COVID-19) and adapted to the Italian context was used. Fourteen facilities took part in the survey (87.5%). The application of good practices for each survey area was expressed as a percentage with the following median values: restriction policies (87.5%), staff training (53.8%), resident training (67.6%), availability of personal protective equipment (41.7%), infection control practices (73.5%) and communication (80%). Among the facilities, considerable variability was observed in these evaluation fields: only the restriction policies and communication activities were applied uniformly. A discrepancy was found between perceived risk and real danger in the facilities, requiring targeted communication actions. At present, it is necessary to promote a new approach based on the prediction of critical events, thereby providing the means to effectively address them.

CLINICAL PROBLEM-SOLVING

Neurosurgery ◽  
2008 ◽  
Vol 62 (6) ◽  
pp. 1330-1339 ◽  
Author(s):  
Nathan J. Ranalli ◽  
David G. Kline ◽  
Michael L. McGarvey ◽  
Nicholas M. Boulis ◽  
Eric L. Zager
Keyword(s):  
Problem Solving ◽  
Clinical Problem ◽  
Clinical Problem Solving

Agreement and Reliability Analysis of Machine Learning Scaling in the Assessment of Acute Proximal Weakness by Experts and Non-Experts: Clinical Feasibility Study (Preprint)

2021 ◽  
Author(s):  
Eunjeong Park ◽  
Kijeong Lee ◽  
Taehwa Han ◽  
Hyo Suk Nam
Keyword(s):  
Machine Learning ◽  
Reliability Analysis ◽  
Gold Standard ◽  
Assessment Tool ◽  
Expert Knowledge ◽  
Hybrid Approach ◽  
Assessment Model ◽  
Lower Limbs ◽  
Neurological Deficits ◽  
Percent Agreement

BACKGROUND Assessing the symptoms of proximal weakness caused by neurological deficits requires expert knowledge and experienced neurologists. Recent advances in artificial intelligence and the Internet of Things have resulted in the development of automated systems that emulate physicians’ assessments. OBJECTIVE This study provides an agreement and reliability analysis of using an automated scoring system to evaluate proximal weakness by experts and non-experts. METHODS We collected 144 observations from acute stroke patients in a neurological intensive care unit to measure the symptom of proximal weakness of upper and lower limbs. A neurologist performed a gold standard assessment and two medical students performed identical tests as non-expert assessments for manual and machine learning-based scaling of Medical Research Council (MRC) proximal scores. The system collects signals from sensors attached on patients’ limbs and trains a machine learning assessment model using the hybrid approach of data-level and algorithm-level methods for the ordinal and imbalanced classification in multiple classes. For the agreement analysis, we investigated the percent agreement of MRC proximal scores and Bland-Altman plots of kinematic features between the expert- and non-expert scaling. In the reliability analysis, we analysed the intra-class correlation coefficients (ICCs) of kinematic features and Krippendorff’s alpha of the three observers’ scaling. RESULTS The mean percent agreement between the gold standard and the non-expert scaling was 0.542 for manual scaling and 0.708 for IoT-assisted machine learning scaling, with 30.63% enhancement. The ICCs of kinematic features measured using sensors ranged from 0.742 to 0.850, whereas the Krippendorff’s alpha of manual scaling for the three observers was 0.275. The Krippendorff’s alpha of machine learning scaling increased to 0.445, with 61.82% improvement. CONCLUSIONS Automated scaling using sensors and machine learning provided higher inter-rater agreement and reliability in assessing acute proximal weakness. The enhanced assessment supported by the proposed system can be utilized as a reliable assessment tool for non-experts in various emergent environments.

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