Intelligent Tutoring System Using Decision Based Learning for Thermodynamic Phase Diagrams

Students learn when they connect new information to existing understanding or when they modify existing understanding to accept new information. Most current teaching methods focus on trying to get students to solve problems in a manner identical to that of an expert. This study investigates the effectiveness of assessing student understanding related to context specific problem solving decisions, prescribing feedback based on the assessment, and improving student understanding to the point where they can make correct decisions. Students were given a refrigeration problem unlike their prior problems and were asked to draw the cycle on a T-v diagram using a tutor system. Every group tested (a total of 373 students) showed a significant improvement in their understanding (p \u3c 0.0001, Cohen’s d \u3e 0.8) using a single 40 minute tutor activit

Authoring a Thermodynamics Cycle Tutor Using GIFT

The main idea of generalized intelligent tutoring system (ITS) development tools like Generalized Intelligent Framework for Tutoring (GIFT) is to provide authors with high-level standards and a readily reusable structure within different domains. Hence, adapting such a tool could be the best way to boost an underdeveloped tutor. In this paper we propose the design for a new GIFT-based tutor for undergraduate thermodynamics. An existing Thermodynamics Cycle Tutor has been designed that is meant to facilitate problem framing for undergraduate students. We describe the advantages of integrating this tutor with GIFT to add student models. Also an approach for evaluating the pedagogical performance of the GIFT-enhanced tutor is described

Decision-based Learning for a Sophomore Level Thermodynamics Course

Decision based learning for a sophomore level thermodynamics courseAn electronic tutor was designed and used to study the effectiveness of a new pedagogy calledDecision Based Learning. Decision based learning (DBL) has similarities to existing activelearning methods, but differs in the following important ways: 1) learning consists of developinga general to specific decision set that students can use to solve novel problems 2) students practicemaking the decisions in the instructor decision set, and are given help with understanding. Thegoal of this method is to improve student understanding through the process of decision makingso that they have a better chance of solving novel or complex problems.Students were asked to draw a T-v phase diagram for a refrigeration cycle they had never seenbefore. At any point in the drawing process, students could submit their work to receive feedback.Upon submission, the tutor evaluated the student drawing to determine the most general/importantunderstanding for which the student needed help. Rather than showing the correct answer, the tutorasked additional thought questions designed with the attempt to improve the student’sunderstanding to the point where he or she could make a decision. The decision making would, inturn, advance the student toward a correct solution. Students were asked to work at least 40minutes on the activity.Students completed a pre-tutor-test and a post-tutor-test for the purpose of determining the impactof the tutor in furthering students’ understanding regarding (P,T,v) property relationships forthermodynamic components. A significant amount of learning was demonstrated using DBL assuggested by a Cohen’s d=1.77 for 88 students, where d\u3e0.8 shows a large effect. The pre-testresults indicate that on average only 25% of students were able to identify all three relations forcomponents, before the activity. Liquid gas separator, evaporator and condenser were thecomponents that were most misunderstood by students. The post activity test showed significantlearning for component relations. As an example, 58% of the students had a misconception aboutpressure for heat exchangers. This was reduced to 18% using a single activity. More detailedanalysis investigated how students learned using this activity

Suicide Screening in Primary Care: Use of an Electronic Screener to Assess Suicidality and Improve Provider Follow-Up for Adolescents

Purpose The purpose of this study was to assess the feasibility of using an existing computer decision support system to screen adolescent patients for suicidality and provide follow-up guidance to clinicians in a primary care setting. Predictors of patient endorsement of suicidality and provider documentation of follow-up were examined. Methods A prospective cohort study was conducted to examine the implementation of a CDSS that screened adolescent patients for suicidality and provided follow-up recommendations to providers. The intervention was implemented for patients aged 12–20 years in two primary care clinics in Indianapolis, Indiana. Results The sample included 2,134 adolescent patients (51% female; 60% black; mean age = 14.6 years [standard deviation = 2.1]). Just over 6% of patients screened positive for suicidality. A positive endorsement of suicidality was more common among patients who were female, depressed, and seen by an adolescent−medicine board-certified provider as opposed to general pediatric provider. Providers documented follow-up action for 83% of patients who screened positive for suicidality. Documentation of follow-up action was correlated with clinic site and Hispanic race. The majority of patients who endorsed suicidality (71%) were deemed not actively suicidal after assessment by their provider. Conclusions Incorporating adolescent suicide screening and provider follow-up guidance into an existing computer decision support system in primary care is feasible and well utilized by providers. Female gender and depressive symptoms are consistently associated with suicidality among adolescents, although not all suicidal adolescents are depressed. Universal use of a multi-item suicide screener that assesses recency might more effectively identify suicidal adolescents

A method for exploratory repeated-measures analysis applied to a breast-cancer screening study

When a model may be fitted separately to each individual statistical unit, inspection of the point estimates may help the statistician to understand between-individual variability and to identify possible relationships. However, some information will be lost in such an approach because estimation uncertainty is disregarded. We present a comparative method for exploratory repeated-measures analysis to complement the point estimates that was motivated by and is demonstrated by analysis of data from the CADET II breast-cancer screening study. The approach helped to flag up some unusual reader behavior, to assess differences in performance, and to identify potential random-effects models for further analysis.Comment: Published in at http://dx.doi.org/10.1214/11-AOAS481 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Sex, Race, and Primary Language on Opioid Prescribing In Pediatrics

Over-prescription of pain medication has led to an opioid epidemic in the United States. Many factors can contribute to the amount of pain medication prescribed to patients. The amount of pain medication prescribed to patients is affected by many factors and previous research has shown: Men are prescribed more than women Whites more than non-whites English-speaking more than non-English-speaking The goal of the study was to look at whether this held true in a pediatric orthopedic population. We also looked at the trends in opiate prescribing over time

Physician Intervention to Positive Depression Screens Among Adolescents in Primary Care

Purpose The objective of this study was to determine the effectiveness of computer-based screening and physician feedback to guide adolescent depression management within primary care. Methods We conducted a prospective cohort study within two clinics of the computer-based depression screening and physician feedback algorithm among youth aged 12–20 years between October 2014 and October 2015 in Marion County (Indianapolis), Indiana. Results Our sample included 2,038 youth (51% female; 60% black; mean age = 14.6 years [standard deviation = 2.1]). Over 20% of youth screened positive for depression on the Patient Health Questionnaire-2 and 303 youth (14.8%) screened positive on the Patient Health Questionnaire-9 (PHQ-9). The most common follow-up action by physicians was a referral to mental health services (34.2% mild, 46.8% moderate, and 72.2% severe range). Almost 11% of youth in the moderate range and 22.7% of youth in the severe range were already prescribed a selective serotonin reuptake inhibitor. When predicting mental health service referral, significant predictors in the multivariate analysis included clinic site (40.2% vs. 73.9%; p < .0001) and PHQ-9 score (severe range 77.8% vs. mild range 47.5%; p < .01). Similarly, when predicting initiation of selective serotonin reuptake inhibitors, only clinic site (28.6% vs. 6.9%; p < .01) and PHQ-9 score (severe range 46.7% vs. moderate range 10.6%; p < .001) were significant. Conclusions When a computer-based decision support system algorithm focused on adolescent depression was implemented in two primary care clinics, a majority of physicians utilized screening results to guide clinical care

Tunable Anion-Selective Transport through Monolayer Graphene and Hexagonal Boron Nitride.

Membranes that selectively filter for both anions and cations are central to technological applications from clean energy generation to desalination devices. 2D materials have immense potential as these ion-selective membranes due to their thinness, mechanical strength, and tunable surface chemistry; however, currently, only cation-selective membranes have been reported. Here we demonstrate the controllable cation and anion selectivity of both monolayer graphene and hexagonal boron nitride. In particular, we measure the ionic current through membranes grown by chemical vapor deposition containing well-known defects inherent to scalably produced and wet-transferred 2D materials. We observe a striking change from cation selectivity with monovalent ions to anion selectivity by controlling the concentration of multivalent ions and inducing charge inversion on the 2D membrane. Furthermore, we find good agreement between our experimental data and theoretical predictions from the Goldman-Hodgkin-Katz equation and use this model to extract selectivity ratios. These tunable selective membranes conduct up to 500 anions for each cation and thus show potential for osmotic power generation

Healthcare systems data in the context of clinical trials - A comparison of cardiovascular data from a clinical trial dataset with routinely collected data

BACKGROUND: Routinely-collected healthcare systems data (HSD) are proposed to improve the efficiency of clinical trials. A comparison was undertaken between cardiovascular (CVS) data from a clinical trial database with two HSD resources. METHODS: Protocol-defined and clinically reviewed CVS events (heart failure (HF), acute coronary syndrome (ACS), thromboembolic stroke, venous and arterial thromboembolism) were identified within the trial data. Data (using pre-specified codes) was obtained from NHS Hospital Episode Statistics (HES) and National Institute for Cardiovascular Outcomes Research (NICOR) HF and myocardial ischaemia audits for trial participants recruited in England between 2010 and 2018 who had provided consent. The primary comparison was trial data versus HES inpatient (APC) main diagnosis (Box-1). Correlations are presented with descriptive statistics and Venn diagrams. Reasons for non-correlation were explored. RESULTS: From 1200 eligible participants, 71 protocol-defined clinically reviewed CVS events were recorded in the trial database. 45 resulted in a hospital admission and therefore could have been recorded by either HES APC/ NICOR. Of these, 27/45 (60%) were recorded by HES inpatient (Box-1) with an additional 30 potential events also identified. HF and ACS were potentially recorded in all 3 datasets; trial data recorded 18, HES APC 29 and NICOR 24 events respectively. 12/18 (67%) of the HF/ACS events in the trial dataset were recorded by NICOR. CONCLUSION: Concordance between datasets was lower than anticipated and the HSD used could not straightforwardly replace current trial practices, nor directly identify protocol-defined CVS events. Further work is required to improve the quality of HSD and consider event definitions when designing clinical trials incorporating HSD