Examining the Validity of Adaptive Comparative Judgment for Peer Evaluation in a Design Thinking Course

Adaptive comparative judgment (ACJ) is a holistic judgment approach used to evaluate the quality of something (e.g., student work) in which individuals are presented with pairs of work and select the better item from each pair. This approach has demonstrated high levels of reliability with less bias than other approaches, hence providing accurate values in summative and formative assessment in educational settings. Though ACJ itself has demonstrated significantly high reliability levels, relatively few studies have investigated the validity of peer-evaluated ACJ in the context of design thinking. This study explored peer-evaluation, facilitated through ACJ, in terms of construct validity and criterion validity (concurrent validity and predictive validity) in the context of a design thinking course. Using ACJ, undergraduate students (n = 597) who took a design thinking course during Spring 2019 were invited to evaluate design point-of-view (POV) statements written by their peers. As a result of this ACJ exercise, each POV statement attained a specific parameter value, which reflects the quality of POV statements. In order to examine the construct validity, researchers conducted a content analysis, comparing the contents of the 10 POV statements with highest scores (parameter values) and the 10 POV statements with the lowest scores (parameter values)—as derived from the ACJ session. For the criterion validity, we studied the relationship between peer-evaluated ACJ and grader’s rubric-based grading. To study the concurrent validity, we investigated the correlation between peer-evaluated ACJ parameter values and grades assigned by course instructors for the same POV writing task. Then, predictive validity was studied by exploring if peer-evaluated ACJ of POV statements were predictive of students’ grades on the final project. Results showed that the contents of the statements with the highest parameter values were of better quality compared to the statements with the lowest parameter values. Therefore, peer-evaluated ACJ showed construct validity. Also, though peer-evaluated ACJ did not show concurrent validity, it did show moderate predictive validity.

Transforming departmental culture: Empowering a department through Appreciative Inquiry

This article outlines an appreciative inquiry (AI) into a departmental professional development process and describes the resulting implementation of an appreciative peer evaluation meeting as one part of the new professional development process. Using AI, a departmental faculty development committee sought to re-envision the professional development process. Also, the authors discuss how using AI can result in positive impacts for culture change and the model for peer evaluation can promote both individual and collective development of faculty.

Effectiveness of Roleplay Video Method in Teaching Communication Skills for Undergraduate Medical Students in Pharmacology in Indian Medical School

Background Communication is an important skill to be honed and applied by Indian medical graduate, as per revised regulations on Graduate Medical Education 2019. The objective of the present study was to evaluate the effectiveness of roleplay video demonstration in teaching communication skills to students using standard pharmacology drug prescription scenarios. Materials and Methods In this study, 136 students were divided into three batches, and in each batch, they were paired as a group of one doctor and patient and were asked to perform a roleplay of doctor-patient communication to a standard drug prescription case scenario. Communication skills of the simulated doctor were assessed before and after the administration of standard roleplay video, using modified Kalamazoo consensus statement by both the patient (peer evaluation) and the doctor (self-assessment). The effectiveness of roleplay was evaluated by comparing the total score before and after the roleplay demonstration using the Wilcoxon signed rank test. The difference between the scores of self-evaluation and peer evaluation was tested using Mann–Whitney U test. Results The communication skills score of after intervention-before intervention (p = 0.001) showed 59 positive ranks and 36.64 mean rank among patient group and 61 positive ranks and 36.74 mean rank among doctors' group, indicating there was a significant improvement in communication. Conclusion Roleplay video demonstration improved the communication skills of students in the pharmacology practical class session. It helped in the active participation of the students and was appreciated by the majority of the students.

A Conundrum of Peer Evaluation of Predicting Poor Prognostic Models Affecting the Mortality Rate of Covid -19

Mankind is confronting these days a histrionic pandemic scene with the Coronavirus proliferation over all continents. The Covid-19 pandemic outbreak is as yet not very much portrayed, and numerous research teams everywhere on the world are chipping away at one or the other restorative therapeutic issues or immunization issues. The outburst of COVID-19 has constituted a danger to wellbeing of world. With the expanding number of individuals tainted, medical services frameworks, particularly those in economically emerging nations, are bearing gigantic pressing factor for the devising a prognostic model. There is a dire requirement for the analysis of COVID-19 and the anticipation of inpatients. To diminish these issues, a data statistical information driven clinical aid framework is advanced in this paper. In view of two real world datasets in Wuhan, China, the proposed framework coordinates information from various sources with tools of Machine Learning (ML) to anticipate COVID-19 tainted likelihood of suspected patients in their first visit, and afterward foresee mortality of affirmed cases. As opposed to picking an interpretable calculation, this framework isolates the clarifications from ML models. It can do help to patient triaging and give some valuable guidance to specialists and doctors. A prognosis model is in the way of extraordinary premium for specialists to adjust their consideration methodology for therapeutic or diagnosis procedure.

A Conundrum of Peer Evaluation of Predicting Poor Prognostic Models Affecting the Mortality Rate of Covid -19

Mankind is confronting these days a histrionic pandemic scene with the Coronavirus proliferation over all continents. The Covid-19 pandemic outbreak is as yet not very much portrayed, and numerous research teams everywhere on the world are chipping away at one or the other restorative therapeutic issues or immunization issues. The outburst of COVID-19 has constituted a danger to wellbeing of world. With the expanding number of individuals tainted, medical services frameworks, particularly those in economically emerging nations, are bearing gigantic pressing factor for the devising a prognostic model. There is a dire requirement for the analysis of COVID-19 and the anticipation of inpatients. To diminish these issues, a data statistical information driven clinical aid framework is advanced in this paper. In view of two real world datasets in Wuhan, China, the proposed framework coordinates information from various sources with tools of Machine Learning (ML) to anticipate COVID-19 tainted likelihood of suspected patients in their first visit, and afterward foresee mortality of affirmed cases. As opposed to picking an interpretable calculation, this framework isolates the clarifications from ML models. It can do help to patient triaging and give some valuable guidance to specialists and doctors. A prognosis model is in the way of extraordinary premium for specialists to adjust their consideration methodology for therapeutic or diagnosis procedure.