Abstract
Internet-based computer online teaching, as a new teaching method, has attracted extensive attention with the rapid development of Internet technology. The purpose is to explore the new education mode of college students’ innovation and entrepreneurship under the background of online teaching and to design and study the intelligent tutoring system (ITS). The prototype of the teaching model is constructed at the beginning. The study employed a probability model for analyzing tutoring system and entrepreneurship education in the context of online teaching. In the later stage, the main body, platform, and links in the teaching process and the connection and aggregation among them are reexamined by integrating teaching practice. The study results revealed that the proposed algorithm helps in identifying the importance and perceptions of ITS and entrepreneurship education.
1. Introduction
Computer online teaching based on the Internet, as a new teaching method, has attracted extensive attention with the rapid development of Internet technology [1]. Traditional teaching methods have many disadvantages, such as the fixation of class time and place and the simplification of class methods, which can be well solved by Internet online teaching. The computer-aided instruction software has undergone great changes from the simple teaching machine to the application of intelligent tutoring systems (ITS) [2]. The development of intelligent technology has brought earth-shaking changes to society. The current educational methods and modes are also in a period of great change, and the educational model begins to change from offline to online. The computer online teaching method based on the Internet begins to show a strong development trend and broad development prospects [3]. The campus network environment of domestic colleges also provides the necessary hardware foundation for network teaching. The existing network teaching system still has great defects, mainly as follows: poor intelligence; unable to adjust teaching strategies independently; lack of sharing and cooperation mechanism, which is not conducive to knowledge sharing and production; and lack of effective evaluation of students’ learning progress, learning process, and learning effect. Hence, further exploring the intelligent network tutoring mode under the network teaching environment has become a crucial content of the research on the ITS [4].
A lot of progress has been made on the research of entrepreneurship education of college students. Among them, American society focuses more on the relevant education of citizens’ innovation and entrepreneurship [5]. Since the middle of the 20th century, a series of relevant laws and regulations on entrepreneurship have been promulgated, shaping a typical model of entrepreneurship education from primary school to college and even lifelong [6]. Germany focuses on the innovation and entrepreneurship education of applied talents, and students’ entrepreneurial thinking has been well developed through a lot of practice. Japan’s classified education system makes entrepreneurship education present the characteristics of classified systematization according to regional resources and personal needs [7]. In short, compared with the domestic innovative education concept, the foreign innovative education system is complete and can basically cover students for life. China’s entrepreneurship education starts late and has been in the process of both exploration and practical development. At present, the typical institutions with better implementation of innovation education are Tsinghua University and Peking University. Tsinghua University has opened relevant courses since 2016 and began to integrate innovation and entrepreneurship education with the student training system [8]. Peking University has also begun to form a complete ecosystem of innovation and entrepreneurship education and talent training. However, the implementation level of entrepreneurship education is uneven in many colleges in China, and the teaching mode and system of innovation and entrepreneurship education cannot be well applied and popularized [9].
To sum up, the past methods of entrepreneurship education for college students were relatively traditional, which could not arouse students’ interest in learning, and it was difficult to promote the reform of innovation and entrepreneurship education for college students. The research innovation is to combine the entrepreneurship education of college students with the new teaching method of Internet online teaching [10]. Based on the constructivist learning theory, artificial intelligence technology, data mining technology, network technology, and component technology are taken as the technical background, so as to provide students with a learning environment, which is independent, intelligent, personalized, and conducive to students’ meaning construction. It will effectively promote the continuous development and progress of intelligent teaching and related disciplines and has profound theoretical and practical significance [11].
The development trend of auxiliary teaching systems is networking and intelligence, which is not only the inevitable trend of educational informatization in China but also the new development trend of college students’ entrepreneurship education [12]. In the early 1970s, the SCHOLAR system developed by Bolt Beranek and Newman Technology Company for geography teaching in South America was considered to be the earliest ITS [13]. The system at this stage only had a simple student model and knowledge representation. In the 1980s, pattern tracking had become the main module of the tutoring system. The system gave feedback to learners’ behavior through case analysis. Since the 1990s, the improvement of computer performance in all aspects has made it possible to deal with a wider range of problems [14]. The theme of its design changed to the design of the learning environment and the knowledge representation of the learning process. At present, the state’s in-depth research on ITS system is based on the establishment of a better student model, teacher strategy model, and cooperative and interactive learning method, which is aimed at further improving the intelligence and practicability of the system and making the ITS system play the teaching function of teaching students according to their aptitude [15].
In the era of intelligent digitization, ITS integrates the knowledge of computer technology, artificial intelligence, pedagogy, psychology, and other disciplines. It makes the computer system have the intelligence to realize the function of human teachers and complete the education of students by giving computer intelligence [16]. The tutoring system can change the traditional teaching mode, fully mobilize students’ enthusiasm with open interactive thinking, and realize personalized optimal teaching by means of online teaching, so it has become a crucial carrier tool to assist traditional teaching. Regarding the intelligence of the current tutoring system, the system can record the characteristic information of learners to distinguish learning styles and cognitive characteristics and realize learners’ personalized teaching [17].
The realization of ITS needs the comprehensive technology of pedagogy, psychology, computer technology, artificial intelligence technology, and so on. The traditional behaviorism learning theory holds that learning is a passive response to external stimuli and takes learners as the object of knowledge indoctrination [18]. This theory is gradually replaced by cognitive learning theory with the development of the times. Cognitive learning theory attaches importance to the internal psychological process of cognitive subjects and regards learners as the subjects of knowledge and information processing. As a crucial branch of cognitive learning theory, constructivism learning theory holds that learning is the active processing and learning of knowledge and information by learners under the guidance of teachers, which requires teachers to stimulate students’ interest in learning and help students form learning motivation [19]. When students enter the tutoring system for the first time, they need to register their personal information such as age, gender, and online learning time. They can choose two learning methods after logging into the system. One is independent learning, which will not be controlled by teaching strategies. Students can independently choose the relevant contents about innovation and entrepreneurship that need to be learned. The other is navigational learning. The system will provide teaching strategies and relevant suggestions for entrepreneurship education to guide students to complete the learning of entrepreneurship education courses [20]. Students can study personalized courses in the learning interface and then conduct course tests. The test results will be analyzed by the system. Finally, teachers make decisions to determine students’ next learning. ITS not only is a teaching tool but also has the ability of systematic induction. It can analyze students’ learning ability through different students’ respective characteristics and task completion and feed back the results to teachers, so that teachers can adopt different teaching strategies in the classroom [21]. In the tutoring system, students can review and test in the system after learning the course content. The mastery of the learned content can be determined according to the test results, and the next stage of learning can be performed on time. To achieve these functions, ITS should achieve the following construction objectives [22]: adjusting the learning progress according to the students’ level and learning situation; diagnosing and evaluating students’ learning; providing teachers with good test content and maintenance interface; and timely answering questions about the teaching content after class [23]. This study is aimed at determining the effect and design of intelligent tutoring system and entrepreneurship education through mobile learning.
2. Methods and Data
The teaching mode of the intelligent teaching platform is mainly divided into two links: online learning and project practice. In the process of carrying out the links, innovation and entrepreneurship learning is carried out in a process. Online learning and assessment are realized by integrating online and offline learning environments, and entrepreneurial projects are practiced and incubated [24]. The links among students, teachers, and system managers of the tutoring system are reanalyzed through continuous practice in the later stage. The four learning platforms of testing and learning, project team management, interactive Q and A, and information resource sharing have been opened up, running through three links: sharing and self-study, cooperation and communication, and connectivity and interaction, so as to build an organic learning ecosystem of multiple subject management and interaction.
Figure 1 represents the proposed architecture of the study. Social innovation and entrepreneurship education consists of student, staff, and trainer. They can have access to the entrepreneurial ecosystem with the inclusion of university, government, and industry. Under the multidisciplines, the four significant aspects like organization, process, facilities, and people are involved. These disciplines must adhere to higher education principles.
The Standard Office of the Central Committee issued execution opinions on developing innovation and entrepreneurship education policy in institutions of higher learning in order to encourage mass innovation and entrepreneurship. According to the state organization’s guidance for innovation and entrepreneurship, higher education institutions should assemble students’ entrepreneurship needs with society’s inventive needs. These needs can be achieved by establishing educational goals based on the school’s attitude and carrying out new educational activities with innovation and innovation as a theme, predicated on “Internet’s” entire social knowledge and different features of the time of the following equation: where and are the sets of class; is protected online class at time, respectively; subscripts and are used to express the number of infected and protected online class until time : time “” is just for notational simplicity.
To estimate the source , Equation (2) is considered. where () is from Bayes’ rule and is the probability that the realizations and occur, given an information source and the protector . Therefore, equivalent tois assumed to be uniform over. It detects for the probability which is given in the following equation: where is the set of all possible propagation sequences given and .
Then, under regular , the same approach is used for the number of possible propagation sequences where
This assumption is for the number of possible propagation sequence node in both information at the same time forand.
It is called forandin the propagation center.
Let be the number of nodes.
Letwhenis the information source.
and are two nodes that want to communicate entrepreneurship and innovation (EI).
Put in the center of the coordination system.
Let be the set of nodes in the network.
Thevertical and horizontal road might be fractious with each other at the connection. The mobile nodes are believed to move in front;turn left or turn right with assured possibility on the connection, where
If be less than zero, it means that the node is affected with deacceleration (negative acceleration).
Residual battery energy () and consumed energy () of a node at time are shown in equations (9) and (10) below.
If the current speed of the node is less than the minimum allowed velocity for its lane, the current speed increases to Smin as in Equations (11) and (12).
At long last, distinction of their speed is tolerable with respect to their positions and heading as in the following equation:
is an all-out number of students.
The distinction between the learner’s cognitive stage and the level of difficulty in the learning materials is represented bythe student’s language level objective of the following equation:
The relatively small a distinction, the more closely the learning resource’s expertise points matchthe learner’s knowledge points as in the following equation:
The overall spending information among teaching material is represented by the optimization problem of expenditure with both educational materials.
The primary function learning period goals highlight the differences between of learning time needed to complete the educational materials and also the learning detection time as in the following equation:
The learner’s total optimization performance and alsothe learning route are created by the comment section function via recalculating coefficients, as expressed by Equation (18), which is a functional illustration of the personalized learning route optimization method.
3. Results and Discussion
The common goal of ITSs is to enable effective and meaningful learning through the use of a variety of technology applications. Intelligent tutoring systems (ITSs) seem to be computer learning conditions intended to facilitate students in mastering complex skills and knowledge. This learning can be achieved by implementing powerful, sophisticated algorithms that adjust to a learning process at a perfect level and initialize complex instructional methods. Intelligent tutoring systems (ITSs) are computational models that are aimed at providing personalized instructional support to users, often using AI systems but without the assistance of a teacher in the classroom. Because of their capabilities to have each education system, ITSs have attracted a lot of attention.
The ITS will apply the principle of artificial intelligence to realize three aspects: reasoning method, knowledge representation, and natural language processing such as reasoning method mainly refer to solving students’ questions by concluding reasoning research of relevant knowledge in the knowledge base; knowledge representation is adopted to establish a domain knowledge base in ITS; natural language understanding enables the tutoring system to have an interactive dialogue with the computer, and the computer will give necessary feedback according to the students’ conversation. The data has been analyzed in this section (Figure 2).
From primary training to better schooling, instructors in any respect levels normally adopt the teaching mode of information transmission with the help of blackboard writing and courseware clarification that is the modern-day situation of the domestic schooling quarter. The content material of expert courses in Chinese universities is enormously massive and complex, requiring teachers to spend dozens of hours on explanation. Based on the background of “Internet+,” this paper proposes three academic modes integrating coaching assets. The first mode of training is to combine the coaching assets of path recording. The cloud era of the Internet is used to build a huge-scale record middle, which could manipulate and label the video direction resources recorded and uploaded by way of schools and universities, listing the call of publications, instructors, and carriers of course resources, direction potential, coaching time, and other records. On the premise of network connection, college students can log in and go to the record center to retrieve route video resources, for you to recognise online vod of video assets of university innovation and entrepreneurship education and coaching underneath the promoting of “Internet +” era. The second mode of schooling is the combination of actual-time online teaching resources (Table 1).
The college department can deploy audio and video record acquisition system consisting of microphone and Dataset.csv within the lecture room to seize the coaching state of affairs of instructors in real time and add it to the community server (Figure 3). The community server will dock the received statistics and upload the scene and channel call. Users who get admission to the web server can retrieve effective audio and video statistics via channels to finish online coaching of innovation and entrepreneurship. The third mode of training is the coaching aid that integrates literature and educational information. With “Internet+” technology to create the cloud offerings Dataset.csv, faculties and universities, and the facts of related expert understanding innovative challenge statistics uploaded to the database, the user can carry on the retrieval facts that have been marked, setting the search keywords across the call of the record content material, statistics, data capacity, and records which include the scope of application of the essential statistics. College students can get admission to the database online to gain professional expertise associated with innovation and entrepreneurship (Figure 4).
Relying on the development blessings of the “Internet+” era, colleges and universities have begun to discover actively and construct a scientific and affordable education model. This model will stimulate the initiative and enthusiasm of college students to grasp innovation and entrepreneurship skills. Some of the skills include know-how, selling the improvement of university students’ expert capacity and total fine, and helping university students begin their businesses, choose jobs, and acquire employment. Generally speaking, openness, integrity, and adapting to the mainstream fashion of the instances are the simple necessities for colleges and universities to establish an innovative and entrepreneurial training model. Innovate educational theories and plan lengthy-term improvement strategies (Table 2).
The speedy development of the network statistics era in China calls for schools and universities is to ideal the concept of innovation and entrepreneurship education, replace the teaching methods of innovation and entrepreneurship, and encourage instructors and college students to broaden remarkable Internet questioning conduct. Innovation and entrepreneurship education sports for university college students are aimed toward improving students’ innovation and entrepreneurship, enriching students’ knowledge of innovation and entrepreneurship, improving college students’ abilities of innovation and entrepreneurship, and actively transforming relevant theories into sensible movements of innovation and entrepreneurship. It is of first-rate sensible importance for colleges and universities to establish a systematic theoretical model of coaching and research on innovation and entrepreneurship training to guide college students to mix principle with practice and plan lengthy-time period innovation and entrepreneurship development strategies (Figure 5).
With the growing technology level and continuous improvement of network generation, enriching the content material of creative education, realizing the coaching mode of advancing with the times and innovation, as well as the education teaching device of the mixing, standardization, and scientification; cultivating college students’ innovative questioning; and toughening university college students’ entrepreneurial capability are the inevitable requirement of generation development. The colleges and universities will actively promote the aggregate of online teaching and offline coaching; increase lecture room exercise link, to provide college students greater questioning time and internships, and the use of the “Internet+” technology organization immersion mastering sports; enhance the complete practical ability of university college students, use the “class” and “MOOC lesson” and other kinds; and optimize students’ gaining knowledge (Table 3).
It is highly suggested to introduce organization experts to enhance the crew’s school. Many university instructors only have theoretical expertise, and hence, lag in the organizational work is revealed. Therefore, it is challenging for them to understand the task-related vacancy and marketplace demand for skills. Considering the agency professionals have collected more incredible revel in realistic sports, college-business enterprise cooperation in walking a college can provide more significant entrepreneurial opportunities for college students. Colleges and universities can lease or invite agency specialists to participate inside the schooling and coaching of innovation and entrepreneurship within the shape of taking the rate of practical schooling courses and organizing special lectures and impart and proportion modern-day technologies, successful stories, and social hot spots, as a way to improve college students’ cognition of innovation and stimulate their enthusiasm for entrepreneurs.
The teaching process automatically generates the evaluation of students’ learning achievements and cognitive ability and gives the knowledge points that students should master. The proposed model has been compared with the existing method. The study results proved that the proposed model has obtained an accuracy of 95.98% (refer to Table 4).
4. Conclusions
Based on the detailed study of the development status of distance learning, an intelligent tutoring system for the teaching environment is proposed. The system’s research direction and development trend are analyzed, and a system based on a general intelligent remote guidance system is proposed and implemented. The system applies artificial intelligence, data mining, network, and component technology to ITS based on constructivism learning theory. It can fully tap the potential information, adjust the teaching strategies, and enable learners to obtain personalized education according to their own learning needs and each student’s interests. The teaching process automatically generates the evaluation of students’ learning achievements and cognitive ability and gives the knowledge points that students should master and the teaching suggestions developed by teachers’ inference engine to simulate the teaching process. The comprehensive analysis suggests that the system has been running well since it is put into operation, can realize all functions, and has good system security and stability. When the system runs on the server of the experimental school, it assists college students’ innovation and entrepreneurship education through LAN, creates a digital learning environment for teachers and students, improves classroom teaching efficiency, and effectively reduces the burden of teachers. However, ITS research still has some defects, mainly reflected in the design of some functional modules. The development of ITS involves computer science, pedagogy, cognitive science, artificial intelligence, and many other disciplines. In future research, the application of natural language processing technology can be strengthened, the intelligence level of the system can be improved, and interactive learning and autonomous and active learning can be strengthened and can provide a practical and effective way to enhance students’ learning practice.
Data Availability
The data used to support the findings of this study are available from the corresponding author upon request.
Conflicts of Interest
The author declares that there are no conflicts of interest.