Background Ethical decision-making education in nursing can be taught effectively by combining different teaching models that support the visualisation of taught concepts and integrating theory into practice. Objectives The study aims to examine the effect of flipped and jigsaw learning models on ethical decision-making and ethical sensitivity in nursing. Research design We used a nested mixed design. A pretest-posttest single-group quasi-experimental design was used in the quantitative part, and a case study method was used in the qualitative part. Participants and (...) research context This study was conducted in fall semester with second-year nursing students who studied an ethics course for the first time, using two different collaborative learning models. In the quantitative part, ethical dilemma and ethical sensitivity scales were made as pre-test with 117 and post-test with 128 students. In the qualitative part, a semi-structured three focus group interviews was conducted with 16 students. Ethical considerations After obtaining the approval of the University’s ethics committee, the study was carried out after obtaining participants’ informed written and verbal consent. Findings Students’ perspectives changed positively after training. This was related to six cases in section A of the Ethical Dilemma Scale. In part B, Practical Consideration (PC) and Principled Thinking (PT) mean scores were similar, showing no significant difference. For Familiarity in section C, it was determined that 68.4% of students in the pre-test and 77.3% in the post-test were familiar with similar dilemmas. The ethical sensitivity scale’s total scores were in a similar range. In the qualitative stage, ethical decision-making, ethical sensitivity, ethical dilemma and the improvement process were obtained as a theme. Conclusions There was an increase in the level of ethical sensitivity and familiarity with ethical dilemmas of nursing students after education. Flipped and jigsaw learning models can be used for nursing ethics courses. (shrink)

Based on the conservation of resources theory, this study developed a model linking social undermining to employees helping behaviors and work role performance via expression of guilt, with religious faith possessed by employees as a first-stage moderator. We argue that individuals will feel guilty if they perceive themselves as the perpetrators of the social undermining against their coworkers. Feeling guilt can potentially trigger prosocial responses (i.e., helping coworkers) and enhance work role performance for improving the situation. We contend that religious (...) faith that commands doing good with others further provides resources for managing these negative emotions to unleash a positive side of social undermining, such that the relation of social undermining with an expression of guilt will be strengthened. A multisource (supervisor-supervisee), multi-wave, and multi-context (education, healthcare, and banking) survey involving 281 employees largely supports our study hypotheses. The results indicated that social undermining is associated with more guilt expressions amid religious individuals, revealing higher prosocial and work role performance. For business ethics research, the current study unveils an important mediator—guilt expressions about wrongdoing—via which individuals’ social undermining behaviors at work, somewhat counterintuitively, lead to boost performance outcomes, and an employee’s religious faith helps a facilitator of this relationship. (shrink)

The stability of the power grid is concernment due to the high demand and supply to smart cities, homes, factories, and so on. Different machine learning and deep learning models can be used to tackle the problem of stability prediction for the energy grid. This study elaborates on the necessity of IoT technology to make energy grid networks smart. Different prediction models, namely, logistic regression, naïve Bayes, decision tree, support vector machine, random forest, XGBoost, k-nearest neighbor, and optimized artificial neural (...) network, have been applied on openly available smart energy grid datasets to predict their stability. The present article uses metrics such as accuracy, precision, recall, f1-score, and ROC curve to compare different predictive models. Data augmentation and feature scaling have been applied to the dataset to get better results. The augmented dataset provides better results as compared with the normal dataset. This study concludes that the deep learning predictive model ANN optimized with Adam optimizer provides better results than other predictive models. The ANN model provides 97.27% accuracy, 96.79% precision, 95.67% recall, and 96.22% F1 score. (shrink)

This article analyzes the position of Ibn Hilāl, who is regarded as nāsıbī and ghālī, in the science of Shia rijāl, his reports and the validity of the accusations against him. It is found that narrators are criticized for various reasons in the science of Shiʻa rijāl. Some of them are the Shiite followers that the imams cursed and wanted to be kept away from their adherence. It is seen that the narrations reported by some of the narrators are included (...) in the main sources of Shiite hadith, albeit these narrators were cursed by the innocent imams. Ahmed Ibn Hilāl (d. 267/880) is one of these narrators cursed by the imams and his name is found in the report (the isnād) of many early narrations. Ibn Hilāl, one of the close companions of Shia's 10th imam Ali b. Muḥammed al-Hādī (d. 254/868) and 11th imam Ḥasan al-ʻAskarī (d. 260/874), was first cursed by the letter of al-Askarī allegedly sent, and the Shiite followers were ordered to move away from him. Ibn Hilāl refused to accept the ambassadoriality of Muḥammed b. Osman (d. 305/918), the ambassador of the 12th Imam. Thus, he was cursed by Muḥammad al-Mahdī as well. In later periods, Ibn Hilāl was accused of being nāsıbī and ghālī. However, there are also some Shiite scholars who supported (tavthîk) Ibn Hilāl. In the Shi'a tradition, Nāsibism indicated the meaning of hating ʻAli and Ahl al-bayt or feeling anger towards them. Later on, this meaning has been changed into a meaning including the haters of ʻAli and then the Shiʻa Nāsibism is regarded as a position towards Shiʻa outside of Shiʻa. Ghulāt is a form of a belief generally found in the Shi'a tradition. In the belief of Ghulāt, holiness is attributed to the imams. When the Shiite sources are examined, it can be seeb that Ibn Hilāl represents neither a ghālī nor a nāsıbī position. In the Shiʻa, when the narrator leaves his sect, his narrations are evaluated differently. Therefore, among Ibn Hilāl's narrations only those which narrated before he left can be accepted. The likely reason for this attitude can be those narrators such as Ibn Hilāl brought in many narrations to the Shiite hadith literature. Ibn Bābeveyh and Sheikh Sadūk reported many narrations that includes Ibn Hilāl in their report chain (the isnad). Among these narrations, they criticized only one. Again, in the 4th century of Hijrī, Numānī, al-Hazzāz, Ibn Qavlaveyh and Mufīd reported many narrations transmitted by Ibn Hilāl. However, none of them mentioned about the negative perception on Ibn Hilāl in any of these narrations. This shows that Ibn Hilāl was not regarded as nāsıbī or ghālī in the eyes of the these scholars. As regards to, Tūsī, in the 5th century after Hijra, claimed that Ibn Hilāl was a ghālī and he was accused of being an adherent to this religion. He narrated in sum fifty narrations that included Ibn Hilāl in the report chain, but Tūsī criticized only three of them because of including Ibn Hilāl. The reason why Ibn Hilāl was accused of being nāsıbī and ghālī, which Shiʻa deemed the worst, was probably related to the political conditions of that period. On the other hand, there is no report that Ibn Hilāl shared a nāsıbī and ghālī thought or had a tendency towards them. It is obvious that if Ibn Hilâl, who has an important place in the eyes of the Shiite community, does not accept the second ambassador of al-Mahdī, and that this would cause discord among the followers. This complex situation was tried to be remedied by letters alleged to have been written by the imams, cursing Ibn Hilâl and ordering them to stay away from him. Later, Ibn Hilāl was accused of being a nāsıbî or ghālī who expressed the attitudes and thoughts that Shiʻa saw the most distant from him. Sadūk first reported the narration that Ibn Hilāl was Nāsıbî. Tūsī, on the other hand, described Ibn Hilāl as ghālī in the 5th century (after hijra). This study tries to reveal that there is no explicit evidence that proves Ibn Hilāl’s nāsıbī or ghālī position. (shrink)