This study inspected the effect of Massive Open Online Course and flipped instruction on EFL learners’ foreign language speaking anxiety, foreign language learning motivation, and attitude toward English learning. To fulfill this objective, the Oxford Quick Placement Test was given to 160 Iranian EFL learners, of whom 120 upper-intermediate participants were chosen and divided into two experimental groups—MOOC and flipped —and one control group. After that, all selected participants were administered a speaking anxiety questionnaire and a motivation questionnaire as the (...) pre-test of the research. Then, one of the experimental groups received an online-based instruction via Skype: one conversation was instructed to this group online every session. The other experimental group received the treatment via flipped-based instruction. The audio files and the texts of the conversations were sent to this group via the WhatsApp application because they all had easy access to it. On the other hand, the control group did not receive any Internet-delivered treatment yet was trained through a face-to-face method. This process continued until the last session, and after the treatment period, the post-tests of speaking anxiety and motivation were given to all three groups to determine the effectiveness of the treatment. Moreover, two attitude questionnaires were administered to the experimental groups to examine their attitudes toward the MOOC and the flipped models of instructions. The findings of the One-way ANOVA test, Post-hoc Scheffe test, and paired samples t-test showed that there were significant differences between the post-test of the experimental groups and the control group. The results indicated that the experimental groups significantly outflanked the control group after the treatment. Lastly, the outcomes showed that participants in both experimental groups had positive attitudes toward technological-based instructional environments. (shrink)

From a classical perspective, multinational companies operate based on market determinants, but recent economic discussions emphasize the central role of the human cognitive system in the decision-making process, thereby giving birth to interdisciplinary fields such as behavioral economics and neuroeconomics. While neuroeconomics is still considered an emerging field, hitherto scant studies have investigated the reflection of cultural experiences on the nervous system. Moreover, the interpretation of cultural diversity in the decision-making process, especially from a neuroeconomic perspective, has not been explored. (...) In response, this study, aperspective research in nature, endeavors to research the neural responses to cultural diversity by contextualizing the neuroeconomic discussion within an MNC framework as one of the best multicultural settings. This study demonstrates that the internationalization process of MNCs is established on the cultural identity and integration of the executive. Through a neuroscientific lens, our findings prove that culture is a fundamental determinant of the cognitive makeup; therefore, cultural diversity in MNCs influences their decision-making process. Moreover, the performance of MNCs is driven by cultural harmonization at the executive level. Finally, the study reveals that the novel field of neuroeconomics is instrumental in identifying cultural intuitions on brain cells and the implications on economic decisions even at a corporate level. The main contribution of this study is the initiation of a multidisciplinary merge of the sociocultural and economic as well as neuroscientific fields, as a research center for MNCs’ decision-making processes. (shrink)

This study aims to explore effective ways to improve college students’ entrepreneurial self-efficacy and intentions through entrepreneurship education. The survey used a random sample of 804 college students in Zhejiang Province, China. The results show that: In terms of the characteristics of entrepreneurial intention, there are significant differences in gender, entrepreneurial experience, entrepreneurial competition experience, and family background of self-employment. There are significant differences in the characteristics of entrepreneurship education in gender, entrepreneurial competition experience, and the family background of self-employment. (...) In the relationship among entrepreneurship education, entrepreneurial self-efficacy, and entrepreneurial intention, entrepreneurship education is significantly and positively related to entrepreneurial self-efficacy and entrepreneurial intention. Entrepreneurial self-efficacy is significantly and positively associated with entrepreneurial intention. Entrepreneurial self-efficacy plays a complete mediating role between entrepreneurship education and entrepreneurial intention. Entrepreneurial self-efficacy also has a suppressing effect on the relationship between the two. Entrepreneurial competition experience moderates the second half of the mediating effect of entrepreneurial self-efficacy. Finally, the study offers several proposals for the teaching practice of entrepreneurship education. (shrink)

The twenty-first century is arguably the century of computing. In such a world saturated by computing, Computational Thinking is now recognized as a foundational competency for being an informed citizen and being successful in STEM work. Nevertheless, how to effectively import different types of teaching methods in university courses is subjected to further evaluation. Currently, the arguments in favor of tangible robots including high interaction, great practicality, and specific operation results make themselves to be often used as a teaching medium (...) and tool for teaching activities between teachers and students. Hence, in addition to cultivating students with computational thinking ability, this paper discussed how to integrate tangible robots into project-based learning courses of thinking skills training to improve the learning performance of the computational thinking ability. This study conducted in one semester on the 105 students from three classes. Experimental results show that the project-based learning method integrated with the teaching material of robotic visual programs approach had significantly better effectiveness in improving students' learning achievements than the traditional teaching method integrated with paper practice teaching materials approach. Analysis of the questionnaire results showed that the proposed learning approach did not increase the students' cognitive burden. In sum, the proposed approach helps students' learning achievement and cognitive load. (shrink)

Cardiovascular disease is a major complication of type 2 diabetes mellitus. In addition to traditional risk factors, psychological determinants play an important role in CVD risk. This study applied Deep Neural Network to develop a CVD risk prediction model and explored the bio-psycho-social contributors to the CVD risk among patients with T2DM. From 2017 to 2020, 834 patients with T2DM were recruited from the Department of Endocrinology, Affiliated Hospital of Harbin Medical University, China. In this cross-sectional study, the patients' bio-psycho-social (...) information was collected through clinical examinations and questionnaires. The dataset was randomly split into a 75% train set and a 25% test set. DNN was implemented at the best performance on the train set and applied on the test set. The receiver operating characteristic curve analysis was used to evaluate the model performance. Of participants, 272 were diagnosed with CVD. The developed ensemble model for CVD risk achieved an area under curve score of 0.91, accuracy of 87.50%, sensitivity of 88.06%, and specificity of 87.23%. Among patients with T2DM, the top five predictors in the CVD risk model were body mass index, anxiety, depression, total cholesterol, and systolic blood pressure. In summary, machine learning models can provide an automated identification mechanism for patients at CVD risk. Integrated treatment measures should be taken in health management, including clinical care, mental health improvement, and health behavior promotion. (shrink)

This paper studies the fixed-time trajectory tracking control problem of robot manipulators in the presence of uncertain dynamics and external disturbances. First, a novel nonsingular fixed-time sliding mode surface is presented, which can ensure that the convergence time of the suggested surface is bounded regardless of the initial states. Subsequently, a novel fast nonsingular fixed-time sliding mode control is developed so that the closed-loop system is fixed-time convergent to the equilibrium. By applying the proposed NFNFSMC method and the adaptive technique, (...) a novel adaptive nonsingular fixed-time control scheme is proposed, which can guarantee fast fixed-time convergence of the tracking errors to small regions around the origin. With the proposed control method, the lumped disturbance is compensated by the adaptive technique, whose prior information about the upper bound is not needed. The fixed-time stability of the trajectory tracking control under the proposed controller is proved by the Lyapunov stability theory. Finally, corresponding simulations are given to illustrate the validity and superiority of the proposed control approach. (shrink)