Intelligence Course Research Articles

Introduction Part of the Knowledge and Intelligence Course

It is necessary for students to have a deep understanding of knowledge and intelligence. We have been teaching Knowledge and Intelligence course to the students majoring in computer science and artificial intelligence at Northeastern University since 2018. This paper is about the instructional design of the introductory part of the knowledge and intelligence course. We use a question to draw out the significance of the Knowledge and Intelligence course: "When did humans part ways with other animals?" We organize students to debate whether "walking upright" or "using tools" can better distinguish humans from animals. Through the teacher's comments on the debate, students will find that both "walking upright is a sign that distinguishes humans from other animals" or "using tools is a sign that distinguishes humans from other animals" are correct. Their essence is that "knowledge is the mark that distinguishes humans from other animals." Through the exploration and inheritance of knowledge, humans gradually parted ways with other animals. Students will understand the great significance of the Knowledge and Intelligence course by this way.

Nursing students’ emotional empathy, emotional intelligence and higher education-related stress: a cross-sectional study

BackgroundNursing is one of the critically important disciplines in healthcare. Due to its complexity and specificity, nursing students often face additional higher education-related stress. However, there is less research on higher education-related stress among nursing students. Therefore, the purpose of this study was to investigate the effects of emotional empathy and emotional intelligence on the dimensions of higher education-related stress among nursing students.MethodsThis study utilized a multi-stage sampling design and was completed within the March-June 2023 period. A total of 1126 nursing students were recruited to complete the questionnaire. The self-administered questionnaire included the basic characteristics of the subjects, an emotional empathy scale, an emotional intelligence scale, and a higher education-related stress scale. One-way ANOVA/t-tests, correlation coefficients, and hierarchical linear regression analyses were used to explore the factors affecting higher education-related stress and the relationship between emotional empathy and emotional intelligence with the dimensions of higher education-related stress.ResultsThe mean (SD) scores of challenges and dissatisfaction dimensions of higher education-related stress among nursing students were 30.052 (7.466) and 8.270 (2.205), respectively. Emotional empathy was significantly and positively related to the challenges and dissatisfaction dimensions of higher education-related stress. Emotional intelligence was negatively correlated with the challenges dimension of higher education-related stress and positively correlated with the dissatisfaction dimension. Stratified multiple regression analyses revealed that nursing students' emotional empathy and emotional intelligence were significant predictors of the dimensions of higher education-related stress.ConclusionOverall, emotional empathy and emotional intelligence were significantly correlated with all dimensions of higher education-related stress. Consequently, in future interventions, the Chinese government and education sector can develop nursing students' ability to use emotional empathy and emotional intelligence rationally through emotional regulation strategies and emotional intelligence courses, to reduce the higher education-related stress they experience.

Learning with Moodle and Google Drive: instrumental conflicts in question

Learning management systems (LMSs) are still supporting artefacts by allowing higher education students to conduct learning activities using teaching resources. These artefacts are based on graphical interfaces that display modules and contents. The mediated contents force students to manage instrumental conflicts resulting of a poor integration between didactic, pedagogical and technical artefacts, during the learning activity (Marquet, 2005). This paper investigates the impact of using the LMS Moodle on the realisation of an activity carried out in this same environment, during a business intelligence (BI) course, according to the type of integration of the teaching resources used: resources integrated into the environment and resources external to the environment. After conducting a literature review on the information search task and on learning BI with LMSs, this empirical work (N = 69) examines the effects of the type of integration of said resources on the results obtained in the quiz. The results suggest that the implementation of external resources around an LMS and therefore not integrated into the environment paradoxically enables students to obtain better results on a score in a shorter time, thus improving their ability to act.

An artificial intelligence course for chemical engineers

Artificial intelligence and machine learning are revolutionising fields of science and engineering. In recent years, process engineering has widely benefited from this novel modelling and optimisation approach. The open literature can offer several examples of their applications to chemical engineering problems. Increasing investments are devoted to these techniques from different industrial areas, but insufficient information on a structured course covering these topics in a chemical engineering curriculum could be found. The course in this paper intends to reduce this gap. We introduce one of the first courses on artificial intelligence applications in a chemical engineering curriculum. The course targets Master's students with a chemical engineering background and insufficient knowledge of statistical approaches. It covers the main aspects by utilising frontal lectures and hands-on exercises with active learning methods. This paper shows the methodology we adapted to introduce students to machine learning techniques and how they responded to each class. The student performances for each test are shown, as well as the survey results based on student feedback and suggestions. This work contains essential guidelines for educators who will provide an artificial intelligence course in a chemical engineering curriculum.

An Empirical Investigation of the Impact of Artificial Intelligence on Accounting Practice in Nigeria

This study carried out an empirical investigation on the impact of artificial intelligence on accounting practice in Nigeria. The study adopted a survey research design. Data for the study were extracted from one hundred and forty-eight (148) respondents extracted from selected organizations in Abuja. A questionnaire was used as the primary instrument for data collection. The data were analyzed with the aid of frequency tables and percentages and the hypotheses were tested with probability values extracted from the regression output. The major findings of the study revealed that expert systems and neural networks contribute positively and significantly to accounting practice in Nigeria. The implication of this finding is that any accountant that does not arm their skills with the knowledge of artificial intelligence software, may become irrelevant in the nearest future. It is therefore the recommendation of this study that accountants should attend seminars and workshops on modern accounting methodical practices in order to further their knowledge of and proficiency with artificial intelligence technologies, which will increase their dynamism in functional accounting activities and secondly; to prepare upcoming accountants for what lies ahead in the business world, the government should incorporate artificial intelligence courses into accounting at the undergraduate and graduate levels in tertiary institutions.

Develop AI Teaching and Learning Resources for Compulsory Education in China

Artificial intelligence course has been required to take for compulsory education students in China. However, not all teachers and schools are fully prepared and ready. This is partially because of the lack of adequate teaching and learning resources, which requires a major expenditure of time and effort for schools and teachers to design and develop. To meet the challenge of lacking appropriate resources in teaching and learning AI from grade 1 to grade 9, we developed AI knowledge structure and instructional resources based on Chinese national curriculum for information science and technology. Our comprehensive AI syllabus contains 90 core concepts, 63 learning indicators, and 27 teaching and learning resources, which have been implemented. The resources have been taken as model courses in teacher training programs and an exemplary course has been implemented in primary schools that verified the effectiveness of our resources.

Exploring Social Biases of Large Language Models in a College Artificial Intelligence Course

Large neural network-based language models play an increasingly important role in contemporary AI. Although these models demonstrate sophisticated text generation capabilities, they have also been shown to reproduce harmful social biases contained in their training data. This paper presents a project that guides students through an exploration of social biases in large language models. As a final project for an intermediate college course in Artificial Intelligence, students developed a bias probe task for a previously-unstudied aspect of sociolinguistic or sociocultural bias they were interested in exploring. Through the process of constructing a dataset and evaluation metric to measure bias, students mastered key technical concepts, including how to run contemporary neural networks for natural language processing tasks; construct datasets and evaluation metrics; and analyze experimental results. Students reported their findings in an in-class presentation and a final report, recounting patterns of predictions that surprised, unsettled, and sparked interest in advocating for technology that reflects a more diverse set of backgrounds and experiences. Through this project, students engage with and even contribute to a growing body of scholarly work on social biases in large language models.

Implications of Pediatric Artificial Intelligence Challenges for Artificial Intelligence Education and Curriculum Development

Several radiology artificial intelligence (AI) courses are offered by a variety of institutions and educators. The major radiology societies have developed AI curricula focused on basic AI principles and practices. However, a specific AI curriculum focused on pediatric radiology is needed to offer targeted education material on AI model development and performance evaluation. There are inherent differences between pediatric and adult practice patterns, which may hinder the application of adult AI models in pediatric cohorts. Such differences include the different imaging modality utilization, imaging acquisition parameters, lower radiation doses, the rapid growth of children and changes in their body composition, and the presence of unique pathologies and diseases, which differ in prevalence from adults. Thus, to enhance radiologists’ knowledge of the applications of AI models in pediatric patients, curricula should be structured keeping in mind the unique pediatric setting and its challenges, along with methods to overcome these challenges, and pediatric-specific data governance and ethical considerations. In this report, the authors highlight the salient aspects of pediatric radiology that are necessary for AI education in the pediatric setting, including the challenges for research investigation and clinical implementation.

Research Status and Challenges on the Sustainable Development of Artificial Intelligence Courses from a Global Perspective

The widespread application of artificial intelligence technology in various fields has made the sustainable development of artificial intelligence courses an important direction in the field of artificial intelligence education and teaching. Therefore, it is particularly important to conduct an in-depth analysis of the current research status of “artificial intelligence courses” from a global perspective. Firstly, this article clarifies the three stages of slow development, rapid development, and mature development of artificial intelligence curriculum research through the number and distribution years of the literature. It also conducts a co-authorship analysis on the distribution of countries, institutions, and authors of artificial intelligence curriculum research and identifies countries, institutions, and core authors that have made greater contributions to artificial intelligence curriculum research. Secondly, due to the involvement of artificial intelligence in many different fields of knowledge, an analysis is conducted on the journals that published papers on artificial intelligence courses. Finally, based on the analysis of keyword density and time span, the current research hotspots of artificial intelligence courses are summarized: artificial intelligence technology empowerment courses, two education directions at different stages of artificial intelligence courses, and teaching forms in the field of artificial intelligence courses. The current research trend of artificial intelligence courses is analyzed from three aspects: teaching format, teaching content, and teaching objects. This article provides a theoretical reference value and practical basis for future research and development in the field of artificial intelligence courses, while also providing experience for the efficient and sustainable development of artificial intelligence courses to a certain extent.

A Review of Gamification Teaching Based on Creative Thinking Development

The development of artificial intelligence in education has ushered in a new spring as the country pays more and more attention to basic education curriculum and innovative talents. The development of innovative talents depends on the cultivation of ability, and the core of the cultivation of ability is the development of thinking, so it is especially important to cultivate students' innovative thinking for solving the problems of artificial intelligence applications in life. The artificial intelligence course is not only a technical course, but also involves several disciplines. Through the learning of artificial intelligence course, students can be exposed to more comprehensive multidisciplinary knowledge and find the optimal solution for existing problems, which can stimulate students' innovative thinking. This paper reviews the application of innovative thinking in game teaching method.

Effect of Artificial Intelligence Course in Nursing on Students' Medical Artificial Intelligence Readiness: A Comparative Quasi-Experimental Study.

It is predicted that artificial intelligence (AI) will transform nursing across all domains of nursing practice, including administration, clinical care, education, policy, and research. This study examined the impact of an AI course in the nursing curriculum on students' medical AI readiness. This comparative quasi-experimental study was conducted with a total of 300 3rd-year nursing students, 129 in the control group and 171 in the experimental group. Students in the experimental group received 28 hours of AI training. The students in the control group were not given any training. Data were collected by a socio-demographic form and the Medical Artificial Intelligence Readiness Scale. An AI course should be included in the nursing curriculum, according to 67.8% of students in the experimental group and 57.4% of students in the control group. The mean score of the experimental group on medical AI readiness was higher ( P < .05) and the effect size of the course on readiness was -0.29. An AI nursing course positively affects students' readiness for medical AI.

Exploration of the Ideological and Political Elements of Artificial Intelligence Courses under the Background of Three Comprehensive Education

“Three comprehensive education” is an important measure and mechanism to build a big ideological and political pattern, condense various educational resources, and realize the fundamental goal of morality and cultivating people under the new situation. Curriculum ideology and politics are an effective way for universities to “three comprehensive education,” combining professional construction and curriculum characteristics, grasping the law of students’ growth and talent, and clarifying the direction of education. Curriculum ideology and politics are not only the specific practice of “three comprehensive education” but also the specific embodiment of implementing the goal of morality and talent cultivation. The “three comprehensive education” and the curriculum ideology and politics are organically integrated, represent each other, and complement each other. “Three comprehensive education” grasps the direction of education from a macro perspective, and the practice the education policy from a mesoscopic perspective. The research and exploration under the pattern of “three comprehensive education” effectively promote the supply-side structural work in universities. Pertinence and effectiveness, building a macro, meso-, and micro integrated education system, provide new ideas, new ways, and new methods. In this paper, by discussing the relevant theoretical knowledge of three complete education educating people, the intelligent image recognition algorithm is used to intelligently identify the classroom behavior of teachers and students. Combining intelligent image analysis with educational scenarios not only achieves high accuracy of action recognition in classroom scenarios. According to the process of behavior and action classification and recognition, the system is divided into three steps for research: video-based motion target positioning, human behavior and action feature extraction, and human behavior and action recognition and classification.

An Exploration of How to Carry out Introductory Course Civics on Artificial Intelligence in the Construction of National First-class Major

This paper explores the integration of ideological and political education in the Introduction to Artificial Intelligence course within the context of first-class major construction. It discusses innovative teaching methods, such as case studies, teamwork, and classroom discussions, aimed at fostering students' ideological and political qualities. By analyzing teaching practices and research, the study demonstrates the unique and feasible nature of civic education innovation in applied undergraduate institutions. The findings offer valuable insights for the reform and innovation of AI introductory courses in thinking and politics education, ultimately enhancing students' comprehensive quality and meeting the demands of educational reform.

Promoting Innovation and Practice of Introduction to Artificial Intelligence Course with Curriculum Civics as a Handle

This paper discusses the construction of Civics in the Introduction to Artificial Intelligence course for computer science majors at the Zhejiang Institute of Science and Technology, taking into consideration the rapid development of AI technology and society's increasing demand for skilled computer professionals. The following suggestions are proposed: Firstly, the curriculum should be designed to strengthen the educational content of humanities and social sciences, in order to provide a well-rounded education that complements the technical skills taught in the course. Secondly, during the teaching process of the Introduction to AI course, classroom interaction should be promoted and students should be encouraged to express their personal views. Additionally, assessment of students' comprehensive ability should be emphasized since the application and development of AI technology requires individuals with high-quality comprehensive skills. Thirdly, in the assessment method, there should be a focus on students' innovation and teamwork abilities. Encouraging students to collaborate and innovate in solving practical problems is a crucial part of developing their skills in AI technology. Through the implementation of the above suggestions, students' awareness and understanding of AI technology can be improved, while also enhancing their ability to think critically and problem-solve effectively.

Research on Online and Offline Hybrid Teaching of Introduction to Artificial Intelligence

In view of the current teaching situation and challenges faced by the Introduction to Artificial Intelligence course, this paper analyzes the core teaching objectives of the course, and explores the online and offline hybrid teaching methods of it. This paper analyzes the advantages of online and offline hybrid teaching, and probes into the development mode of online and offline hybrid teaching of Introduction to Artificial Intelligence from the aspects of teaching content, teaching mode, teaching effect, examination method, etc.

Innovation and QoS Performance Evaluation Analysis of Real-Time Sharing Platform of Intelligent Courses in Colleges

With the gradual rise of online MOOC teaching platforms, real-time sharing algorithms and QoS performance evaluation systems for online intelligent courses in colleges and universities are becoming more and more important. First of all, introduce the intelligent cloud teaching method with cloud classroom app tools as the core application, and use the smart campus platform to "fancy teaching" classrooms, MOOCs, live broadcasts and other popular forms such as animations, micro-videos, WeChat and other popular forms and language communication management. Knowledge and principles, followed by autonomous and intelligent methods used in implementing QoS decision-making and control in a cognitive network environment, to solve the problems of poor adaptability and comprehensiveness of dynamic and changeable networks. It can effectively improve the utilization rate of network resources and ensure the end-to-end QoS of the network. The results show that: NET, XML and other key technologies, on this basis, the intelligent teaching platform solution of NET, the framework and overall design of the teaching platform are introduced.

Research on Teaching Reform of Artificial Intelligence Course Based on CDIO

In view of the problem of how to set up general undergraduate artificial intelligence courses, on the basis of carefully combing and summarizing years of teaching exploration and practice, it is proposed to set Artificial Intelligence (AI) courses in the lower grades of the university. Taking the teaching practice carried out by Liaoning Institute of Science and Engineering as an example, the “12365” principle is proposed based on the CDIO concept, and corresponding teaching reform and practice are carried out.

Students’ interest in knowledge acquisition in Artificial Intelligence

Some students’ expectations and points of view related to the Artificial Intelligence course are explored and analyzed in this study. We anonymous collected answers from 58 undergraduate students out of 200 enrolled in the Computer Science specialization. The answers were analysed and interpreted using thematic analysis to find out their interests and attractive and unattractive aspects related to the Artificial Intelligence study topic. We concluded that students are interested in Artificial Intelligence due to its trendiness, applicability, their passion and interest in the subject, the potential for future growth, and high salaries. However, the students’ expectations were mainly related to achieving medium knowledge in the Artificial Intelligence field, and men seem to be more interested in acquiring high-level skills than women. The most common part that wasn't enjoyed by the students was the mathematical aspect used in Artificial Intelligence. Some of them (a small group) were also aware of the Artificial Intelligence potential which could be used in an unethical manner for negative purposes. Our study also provides a short comparison to the Databases course, in which students were not that passionate or interested in achieving medium knowledge, their interest was related to DB usage and basic information.

Teaching Reform and Practice of Artificial Intelligence Course under the Background of Integration of Production and Teaching

Teaching Reform and Practice of Artificial Intelligence Course under the Background of Integration of Production and Teaching

Exploration and Reform in Teaching Business Intelligence Course under the Background of Incorporating Ideological and Political Theories into Curriculum Teaching

Exploration and Reform in Teaching Business Intelligence Course under the Background of Incorporating Ideological and Political Theories into Curriculum Teaching