scholarly journals Measuring Navigational Map Reading Competencies: A Pilot Study with a location-based GeoGame

2021 ◽  
Author(s):  
Janina Bistron ◽  
Angela Schwering
Keyword(s):  
Pilot Study ◽  
Real World ◽  
General Concept ◽  
Specific Location ◽  
Related Literature ◽  
Map Reading ◽  
Test Items ◽  
Navigational Map ◽  
Test Instrument ◽  
Professional Contexts

Navigational map reading (NMR) is relevant to people’s everyday life, in professional contexts, and in school education. Being interested in fostering children’s NMR competencies implies a test instrument for measuring potential learning progress. Related literature lacks an evaluated test for children that is focused on the spatial aspects of NMR and applicable at different locations. This paper fills this gap by presenting OriGami NMR Test – a test for measuring NMR competencies in children that is implemented in a digital geogame and played with a mobile device in the real-world. In order to enable a transfer of the test to different locations, we offer the reader the general concept of the test, the geogame, as well as a script that automatically scores the participants’ test performances and evaluates the test items for the specific location. In a pilot study, we successfully realized and evaluated the test for two different locations.

Prior real-world experience influences non-linguistic statistical learning

2020 ◽  
Author(s):  
Stephen Charles Van Hedger ◽  
Ingrid Johnsrude ◽  
Laura Batterink
Keyword(s):  
Statistical Learning ◽  
Real World ◽  
Language Experience ◽  
Pitch Range ◽  
Test Items ◽  
Instrument Measuring ◽  
Statistical Regularities ◽  
Context Free ◽  
Specific Learning

Listeners are adept at extracting regularities from the environment, a process known as statistical learning (SL). SL has been generally assumed to be a form of “context-free” learning that occurs independently of prior knowledge, and SL experiments typically involve exposing participants to presumed novel regularities, such as repeating nonsense words. However, recent work has called this assumption into question, demonstrating that learners’ previous language experience can considerably influence SL performance. In the present experiment, we tested whether previous knowledge also shapes SL in a non-linguistic domain, using a paradigm that involves extracting regularities over tone sequences. Participants learned novel tone sequences, which consisted of pitch intervals not typically found in Western music. For one group of participants, the tone sequences used artificial, computerized instrument sounds. For the other group, the same tone sequences used familiar instrument sounds (piano or violin). Knowledge of the statistical regularities was assessed using both trained sounds (measuring specific learning) and sounds that differed in pitch range and/or instrument (measuring transfer learning). In a follow-up experiment, two additional testing sessions were administered to gauge retention of learning (one day and approximately one-week post-training). Compared to artificial instruments, training on sequences played by familiar instruments resulted in reduced correlations among test items, reflecting more idiosyncratic performance. Across all three testing sessions, learning of novel regularities presented with familiar instruments was worse compared to unfamiliar instruments, suggesting that prior exposure to music produced by familiar instruments interfered with new sequence learning. Overall, these results demonstrate that real-world experience influences SL in a non-linguistic domain, supporting the view that SL involves the continuous updating of existing representations, rather than the establishment of entirely novel ones.

scholarly journals Handrails through the Swamp? A Pilot to Test the Integration and Implementation Science Framework in Complex Real-World Research

2021 ◽  
Vol 13 (10) ◽  
pp. 5491
Author(s):  
Melissa Robson-Williams ◽  
Bruce Small ◽  
Roger Robson-Williams ◽  
Nick Kirk
Keyword(s):  
Pilot Study ◽  
Case Studies ◽  
Implementation Science ◽  
Real World ◽  
Environmental Problems ◽  
Environmental Research ◽  
Integrative Framework ◽  
The World ◽  
Science Framework ◽  
Real World Problems

The socio-environmental challenges the world faces are ‘swamps’: situations that are messy, complex, and uncertain. The aim of this paper is to help disciplinary scientists navigate these swamps. To achieve this, the paper evaluates an integrative framework designed for researching complex real-world problems, the Integration and Implementation Science (i2S) framework. As a pilot study, we examine seven inter and transdisciplinary agri-environmental case studies against the concepts presented in the i2S framework, and we hypothesise that considering concepts in the i2S framework during the planning and delivery of agri-environmental research will increase the usefulness of the research for next users. We found that for the types of complex, real-world research done in the case studies, increasing attention to the i2S dimensions correlated with increased usefulness for the end users. We conclude that using the i2S framework could provide handrails for researchers, to help them navigate the swamps when engaging with the complexity of socio-environmental problems.

scholarly journals Utility of routinely collected electronic health records data to support effectiveness evaluations in inflammatory bowel disease: a pilot study of tofacitinib

2021 ◽  
Vol 28 (1) ◽  
pp. e100337
Author(s):  
Vivek Ashok Rudrapatna ◽  
Benjamin Scott Glicksberg ◽  
Atul Janardhan Butte
Keyword(s):  
Inflammatory Bowel Disease ◽  
Pilot Study ◽  
Disease Activity ◽  
Real World ◽  
Bowel Disease ◽  
P Value ◽  
Health Records ◽  
Real World Evidence ◽  
Inflammatory Bowel

ObjectivesElectronic health records (EHR) are receiving growing attention from regulators, biopharmaceuticals and payors as a potential source of real-world evidence. However, their suitability for the study of diseases with complex activity measures is unclear. We sought to evaluate the use of EHR data for estimating treatment effectiveness in inflammatory bowel disease (IBD), using tofacitinib as a use case.MethodsRecords from the University of California, San Francisco (6/2012 to 4/2019) were queried to identify tofacitinib-treated IBD patients. Disease activity variables at baseline and follow-up were manually abstracted according to a preregistered protocol. The proportion of patients meeting the endpoints of recent randomised trials in ulcerative colitis (UC) and Crohn’s disease (CD) was assessed.Results86 patients initiated tofacitinib. Baseline characteristics of the real-world and trial cohorts were similar, except for universal failure of tumour necrosis factor inhibitors in the former. 54% (UC) and 62% (CD) of patients had complete capture of disease activity at baseline (month −6 to 0), while only 32% (UC) and 69% (CD) of patients had complete follow-up data (month 2 to 8). Using data imputation, we estimated the proportion achieving the trial primary endpoints as being similar to the published estimates for both UC (16%, p value=0.5) and CD (38%, p-value=0.8).Discussion/ConclusionThis pilot study reproduced trial-based estimates of tofacitinib efficacy despite its use in a different cohort but revealed substantial missingness in routinely collected data. Future work is needed to strengthen EHR data and enable real-world evidence in complex diseases like IBD.

A highly accurate delta check method using deep learning for detection of sample mix-up in the clinical laboratory

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Rui Zhou ◽  
Yu-fang Liang ◽  
Hua-Li Cheng ◽  
Wei Wang ◽  
Da-wei Huang ◽  
...  
Keyword(s):  
Deep Learning ◽  
Statistical Methods ◽  
Real World ◽  
Error Detection ◽  
Clinical Laboratory ◽  
Characteristic Curve ◽  
False Positive Rate ◽  
Absolute Difference ◽  
Test Items ◽  
Test Sets

Abstract Objectives Delta check (DC) is widely used for detecting sample mix-up. Owing to the inadequate error detection and high false-positive rate, the implementation of DC in real-world settings is labor-intensive and rarely capable of absolute detection of sample mix-ups. The aim of the study was to develop a highly accurate DC method based on designed deep learning to detect sample mix-up. Methods A total of 22 routine hematology test items were adopted for the study. The hematology test results, collected from two hospital laboratories, were independently divided into training, validation, and test sets. By selecting six mainstream algorithms, the Deep Belief Network (DBN) was able to learn error-free and artificially (intentionally) mixed sample results. The model’s analytical performance was evaluated using training and test sets. The model’s clinical validity was evaluated by comparing it with three well-recognized statistical methods. Results When the accuracy of our model in the training set reached 0.931 at the 22nd epoch, the corresponding accuracy in the validation set was equal to 0.922. The loss values for the training and validation sets showed a similar (change) trend over time. The accuracy in the test set was 0.931 and the area under the receiver operating characteristic curve was 0.977. DBN demonstrated better performance than the three comparator statistical methods. The accuracy of DBN and revised weighted delta check (RwCDI) was 0.931 and 0.909, respectively. DBN performed significantly better than RCV and EDC. Of all test items, the absolute difference of DC yielded higher accuracy than the relative difference for all methods. Conclusions The findings indicate that input of a group of hematology test items provides more comprehensive information for the accurate detection of sample mix-up by machine learning (ML) when compared with a single test item input method. The DC method based on DBN demonstrated highly effective sample mix-up identification performance in real-world clinical settings.

PanicMechanic: A Digital Therapeutic Delivering Biofeedback for Panic Attacks (Preprint)

2021 ◽  
Author(s):  
Ellen McGinnis ◽  
Aisling O'Leary ◽  
Reed Gurchiek ◽  
William Copeland ◽  
Ryan McGinnis
Keyword(s):  
Mental Health ◽  
Heart Rate ◽  
Pilot Study ◽  
Alcohol Consumption ◽  
Future Development ◽  
Real World ◽  
Panic Attack ◽  
Eating Habits ◽  
Controlled Trial ◽  
Panic Attacks

UNSTRUCTURED Panic attacks are an impairing mental health problem that affects more than 11% of adults every year. Panic attacks are episodic, and it is difficult to predict when or where they may occur, thus they are challenging to study and treat. To this end, we present PanicMechanic, a novel mobile health (mHealth) application that captures heartrate-based data and delivers biofeedback during panic attacks. We leverage this tool to capture profiles of real-world panic attacks in a largest sample to date and present results from a pilot study to assess the feasibility and usefulness of PanicMechanic as a panic attack intervention. Results demonstrate that heart rate fluctuates by about 15 beats per minute during a panic attack and takes about 30 seconds to return to baseline from peak, cycling 4 to 5 times during each attack and that anxiety ratings consistently decrease throughout the attack. Thoughts about health were the most common trigger during the observed panic attacks, and potential lifestyle contributors include slightly worse stress, sleep, and eating habits, slightly less exercise, and slightly less drug/alcohol consumption than typical. The pilot study revealed that PanicMechanic is largely feasible to use, but would be made more so with simple modifications to the app and particularly the integration of consumer wearables. Similarly, participants found PanicMechanic useful, with 94% indicating that they would recommend PanicMechanic to a friend. These results point toward the need for future development and a controlled trial to establish effectiveness of this digital therapeutic for preventing panic attacks.

scholarly journals Can an app help identify psychomotor function impairments during drinking occasions in the real world? A mixed-method pilot study

2017 ◽  
Vol 38 (4) ◽  
pp. 438-449 ◽  
Author(s):  
Brian Suffoletto ◽  
Akash Goyal ◽  
Juan Carlos Puyana ◽  
Tammy Chung
Keyword(s):  
Pilot Study ◽  
Real World ◽  
Mixed Method ◽  
Psychomotor Function ◽  
The Real

scholarly journals VR FOR ASSEMBLY TASKS IN THE MANUFACTURING INDUSTRY – INTERACTION AND BEHAVIOUR

2020 ◽  
Vol 1 ◽  
pp. 1697-1706
Author(s):  
Y. Eriksson ◽  
M. Sjölinder ◽  
A. Wallberg ◽  
J. Söderberg
Keyword(s):  
Pilot Study ◽  
Real World ◽  
Manufacturing Industry ◽  
The Real ◽  
Assembly Tasks

AbstractA testbed was developed aiming to contribute to further knowledge on what is required from a VR application in order to be useful for planning of assembly tasks. In a pilot study the testbed was tested on students. The focus of the study was to explore the users’ behaviour, and to gain a better understanding of their experience using VR. The students experienced a gap between the real world and VR, which confirms theories that VR is not a copy or twin of an object or environment.

scholarly journals Real World of Artificial Intelligence - A Review

2020 ◽  
Vol 11 (2) ◽  
pp. 41-47
Author(s):  
Amandeep Kaur ◽  
Madhu Dhiman ◽  
Mansi Tonk ◽  
Ramneet Kaur
Keyword(s):  
Artificial Intelligence ◽  
Neural Networks ◽  
Natural Language Processing ◽  
Face Recognition ◽  
Language Processing ◽  
Real World ◽  
Review Paper ◽  
General Concept ◽  
Research Trends ◽  
Human Intelligence

Artificial Intelligence is the combination of machine and human intelligence, which are in research trends from the last many years. Different Artificial Intelligence programs have become capable of challenging humans by providing Expert Systems, Neural Networks, Robotics, Natural Language Processing, Face Recognition and Speech Recognition. Artificial Intelligence brings a bright future for different technical inventions in various fields. This review paper shows the general concept of Artificial Intelligence and presents an impact of Artificial Intelligence in the present and future world.

scholarly journals Is hidrorium able to improve the students’ critical thinking skills?

2020 ◽  
Vol 8 (1) ◽  
pp. 20-28
Author(s):  
Dedy Dwi Setyawan ◽  
Ali Mustadi
Keyword(s):  
Critical Thinking ◽  
Thinking Skills ◽  
Critical Thinking Skills ◽  
Analysis Method ◽  
Test Items ◽  
High Category ◽  
Test Instrument ◽  
The Media ◽  
Very High ◽  
Passing Grade

The condition of the students’ critical thinking skills in the Kowangbinangun State Elementary School has impacted their learning results. Departing from this situation, a study for improving the students’ critical thinking skills and learning results by using hidrorium as the media should be conducted. Within the conduct of the study, the approach that had been adopted was the classroom action research. Then, the instruments that had been implemented were the test instrument, namely the test items for measuring the achievement of the students’ learning results, and the non-test instrument, namely the assignment assessment rubric for measuring the students’ critical thinking skills level. Furthermore, the data analysis method that had been adopted was the descriptive-comparativee method. Within the first cycle, 4% of the students belonged to the “Very High” category, 14% of the students belonged to the “High” category, and 82% of the students belonged to the “Low” category; as a result, 33% of the students met the passing grade while 67% of the students did not meet the passing grade. The research in the first cycle improved the students’ critical thinking skills and thus 14% of the students belonged to the “Very High” category, 57% of the students belonged to the “High” category, and 29% of the students belonged to the “Low” category. Following up the improvement, the learning results of the students showed that 64% of the students met the passing grade whereas 36% of the students did not meet the passing grade. In the second cycle, the students’ critical thinking skills also improved since 86% of the students belonged to the “Very High” category and 14% of the students belonged to the “High” category. Thus, the students’ learning results improved as well with 82% of the students met the passing grade and 18% of the students did not meet the passing grade.

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