Does higher education foster critical and creative learners? An exploration of two universities in South Korea and the USA

This paper describes two studies that explore students' beliefs about critical and creative learning at two universities, and considers the implications of those beliefs in comparison to the universities' stated education goals. One is a mixed method study of students at a top university in Korea, and the second is a comparative study between the Korean university and a United States (US) university. The first study found that both high-achievers and the general population at a top Korean university perceived their critical and creative abilities as lower than their receptive learning abilities, and that higher achievers were neither more critical nor creative than lower achievers. The second study finds that the Korean university students, compared to US students, were more likely to rate their receptive learning ability as higher than their critical and creative learning abilities. Comparisons across year of higher education (HE) suggest that Korean students' perceptions did not significantly change with respect to year in school, while US students' perceptions of critical learning abilities significantly increased across school years. Results are discussed with respect to the impact of culture, epistemological beliefs, and HE instruction on critical and creative learning

Investigating Information Structure of Phishing Emails Based on Persuasive Communication Perspective

Current approaches of phishing filters depend on classifying messages based on textually discernable features such as IP-based URLs or domain names as those features that can be easily extracted from a given phishing message. However, in the same sense, those easily perceptible features can be easily manipulated by sophisticated phishers. Therefore, it is important that universal patterns of phishing messages should be identified for feature extraction to serve as a basis for text classification. In this paper, we demonstrate that user perception regarding phishing message can be identified in central and peripheral routes of information processing. We also present a method of formulating quantitative model that can represent persuasive information structure in phishing messages. This paper makes contribution to phishing classification research by presenting the idea of universal information structure in terms of persuasive communication theories

Weakly Supervised Semantic Parsing with Execution-based Spurious Program Filtering

The problem of spurious programs is a longstanding challenge when training a semantic parser from weak supervision. To eliminate such programs that have wrong semantics but correct denotation, existing methods focus on exploiting similarities between examples based on domain-specific knowledge. In this paper, we propose a domain-agnostic filtering mechanism based on program execution results. Specifically, for each program obtained through the search process, we first construct a representation that captures the program's semantics as execution results under various inputs. Then, we run a majority vote on these representations to identify and filter out programs with significantly different semantics from the other programs. In particular, our method is orthogonal to the program search process so that it can easily augment any of the existing weakly supervised semantic parsing frameworks. Empirical evaluations on the Natural Language Visual Reasoning and WikiTableQuestions demonstrate that applying our method to the existing semantic parsers induces significantly improved performances.Comment: EMNLP 202

Topological Structure of Dense Hadronic Matter

We present a summary of work done on dense hadronic matter, based on the Skyrme model, which provides a unified approach to high density, valid in the large $N_c$ limit. In our picture, dense hadronic matter is described by the {\em classical} soliton configuration with minimum energy for the given baryon number density. By incorporating the meson fluctuations on such ground state we obtain an effective Lagrangian for meson dynamics in a dense medium. Our starting point has been the Skyrme model defined in terms of pions, thereafter we have extended and improved the model by incorporating other degrees of freedom such as dilaton, kaons and vector mesons.Comment: 13 pages, 8 figures, Talk given at the KIAS-APCTP Symposium in Astro-Hadron Physics "Compact Stars: Quest for New States of Dense Matter", November 10-14, 2003, Seoul, Korea, published by World Scientific. Based on talk by B.-Y. Par

Model-Free Reconstruction of Capacity Degradation Trajectory of Lithium-Ion Batteries Using Early Cycle Data

Early degradation prediction of lithium-ion batteries is crucial for ensuring safety and preventing unexpected failure in manufacturing and diagnostic processes. Long-term capacity trajectory predictions can fail due to cumulative errors and noise. To address this issue, this study proposes a data-centric method that uses early single-cycle data to predict the capacity degradation trajectory of lithium-ion cells. The method involves predicting a few knots at specific retention levels using a deep learning-based model and interpolating them to reconstruct the trajectory. Two approaches are used to identify the retention levels of two to four knots: uniformly dividing the retention up to the end of life and finding optimal locations using Bayesian optimization. The proposed model is validated with experimental data from 169 cells using five-fold cross-validation. The results show that mean absolute percentage errors in trajectory prediction are less than 1.60% for all cases of knots. By predicting only the cycle numbers of at least two knots based on early single-cycle charge and discharge data, the model can directly estimate the overall capacity degradation trajectory. Further experiments suggest using three-cycle input data to achieve robust and efficient predictions, even in the presence of noise. The method is then applied to predict various shapes of capacity degradation patterns using additional experimental data from 82 cells. The study demonstrates that collecting only the cycle information of a few knots during model training and a few early cycle data points for predictions is sufficient for predicting capacity degradation. This can help establish appropriate warranties or replacement cycles in battery manufacturing and diagnosis processes

Optimal Harvesting for an Age-Spatial-Structured Population Dynamic Model with External Mortality

We study an optimal harvesting for a nonlinear age-spatial-structured population dynamic model, where the dynamic system contains an external mortality rate depending on the total population size. The total mortality consists of two types: the natural, and external mortality and the external mortality reflects the effects of external environmental causes. We prove the existence and uniqueness of solutions for the population dynamic model. We also derive a sufficient condition for optimal harvesting and some necessary conditions for optimality in an optimal control problem relating to the population dynamic model. The results may be applied to an optimal harvesting for some realistic biological models

An integrated humanities–social sciences course in health sciences education: proposed design, effectiveness, and associated factors

Previous research has not provided enough direction regarding effective content design of courses integrating the humanities and social sciences in medical and dental education. This study aims at exploring how an Integrated Medical/Dental Humanities–Social Medicine/Dentistry course may be designed; how effective it may be in terms of student growth in knowledge, attitudes, skills, and aspirations; and associated factors. The course was designed by distilling commonalities in the international standards for medical/dental education proposed by seven major health organizations. This analysis resulted in a curriculum covering nine major topics: history, professionalism, communication, ethics, management, policy, insurance, law, and research methodology. During the 2017 calendar year, data was collected and statistically analyzed from 68 third-year pre-doctoral students enrolled in the resulting MDHS 13-week course. Participants showed growth in skills, aspirations, knowledge, and attitudes, with the greatest change occurring in skills, then aspirations, knowledge, and attitudes. Knowledge growth was the only variable significantly related to student achievement of course objectives (β = 0.635, t (63) = 3.394, p = 0.001). The topics that students perceived as most critical were insurance, policy, management, and law. The perceived importance of research was most common among participants and was significantly related to all learning outcomes (For knowledge, β = 0.213, t (63) = 2.203, p = 0.031; for attitudes, β = 0.784, t (63) = 10.257, p = 0.000; for skills, β = 0.769, t (63) = 9.772, p = 0.000; and aspirations β = 0.639, t (63) = 7.595, p = 0.000). This study proposed a framework for humanities-social sciences education in health sciences education and analyzed its implementation. The empirical evaluation of its effectiveness and factors related to successful outcomes found that students perceived gains in their knowledge, attitudes, skills, and aspirations for humanistic and social aspects of dentistry/medicine. In addition, their recognition of the importance of research was associated with the greatest growth in all four learning outcomes. This study may contribute to the improved design of integrated humanities–social sciences courses.This study was supported by a National Research Foundation of Korea (NRF) grant funded by the Ministry of Science and ICT (NRF-2017R1C1B2010469) and, in part, by the Dental Research Institute of Seoul National University. The funding bodies played no role in the design of the study, the collection, analysis, and interpretation of data, or in the writing of the manuscript