Research on Online Scene Teaching Mode of Tobacco Picking Decision Tree Construction Process Integrating Deep Learning

2021 ◽  
Vol 7 (5) ◽  
pp. 3076-3086
Author(s):  
Zhang Shuili ◽  
Zhao Yi ◽  
Zheng Kexin ◽  
Zhang Jun ◽  
Zheng Fuchun
Keyword(s):  
Deep Learning ◽  
Decision Tree ◽  
Online Teaching ◽  
Information Gain ◽  
Teaching Evaluation ◽  
Teaching Process ◽  
Teaching Mode ◽  
Teaching Interaction ◽  
Tree Construction ◽  
Information And Communication

Objectives: In view of the characteristics of online teaching during the coronavirus pandemic and the importance of practical teaching in training students’ skills in the process of graduate education, this paper proposes an online scene teaching mode that takes projects as the carrier and integrates with deep learning. In order to meet the demand for information and communication engineering professionals in the big data context, the whole teaching process is divided into four stages: Topic selection, Teaching project setting, online teaching interaction and teaching evaluation. In the teaching process of Python Data Analysis Foundations, the project “establishment process of tobacco picking decision tree based on information gain” is taken as the teaching case. Prior knowledge and references are pushed through the cloud platform before class, and The scene of tobacco picking affected by the weather is set in the online classroom to guide students to seek solutions to problems, and the results are presented with graphics to assist students to summarize, and then reset the scene to promote knowledge transfer, so as to integrate deep learning into the teaching process, and modify the corresponding stages according to the teaching evaluation results. The content of the scene is gradually increased from easy to difficult, from simple to complex, and from least to most, gradually increasing the difficulty, which enhances students’ learning interest and sense of achievement. Meanwhile, students’ initiative to participate in curriculum research further strengthens the effectiveness of the course in serving scientific research, which has a certain value of popularization and application.

Evaluation of English online teaching based on remote supervision algorithms and deep learning

2020 ◽  
pp. 1-12
Author(s):  
Han Yongqing
Keyword(s):  
Deep Learning ◽  
Evaluation System ◽  
Online Teaching ◽  
Student Evaluation ◽  
Teaching Evaluation ◽  
System Structure ◽  
Automatic Evaluation ◽  
Teaching Process ◽  
Remote Supervision ◽  
School Teaching

The English online teaching automatic evaluation system is unstable in actual teaching evaluation. Therefore, how the automatic evaluation system can better adapt to high school teaching also needs a more in-depth theoretical and practical discussion. According to the actual needs of English online teaching, this article combines remote supervision and deep learning algorithms, builds a system structure for the English online teaching evaluation process, and simulates and analyzes the application of supervision algorithms in the teaching process. Moreover, this article evaluates the actions and status of the student’s learning process from the aspects of teacher evaluation and student evaluation, and also scores the teacher’s teaching process. In order to study the practical effect of this system in English online teaching, this paper designs experiments to evaluate the model online English teaching effect. The research results show that the model constructed in this paper has good performance.

scholarly journals Ignite the Sparks of BYOD Teaching Mode of Universities

2018 ◽  
Vol 1 (1) ◽  
pp. 16
Author(s):  
Hesong Liu
Keyword(s):  
Bring Your Own Device ◽  
Effect Evaluation ◽  
Teaching Process ◽  
Teaching Mode ◽  
Teaching Resources ◽  
Teaching Interaction ◽  
The Reformation ◽  
Educational Field ◽  
Education Field

With the constant development of the technology and the society, BYOD is an inevitable issue of the education field. Universities, as the frontier position of the educational field, properly bring the "BYOD" (Bring Your Own Device) to the class, which enriches the teaching means and further extends the teaching space. It promotes the development of the teaching mode in the reformation of teaching process of boosting the distribution and acquisition of teaching resources, teaching interaction and effect evaluation. 

scholarly journals Evaluation of Blended Oral English Teaching Based on the Mixed Model of SPOC and Deep Learning

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Yanli Hui
Keyword(s):  
Deep Learning ◽  
Online Education ◽  
Education Reform ◽  
Mixed Mode ◽  
Teaching Evaluation ◽  
University Education ◽  
Teaching Mode ◽  
English Teaching ◽  
The Impact ◽  
Blended Teaching

With the deep integration of “internet + education” and the continuous advancement of education reform, blended teaching has become the main method of university education reform. Blended education combines the advantages of traditional education and online education to complement each other. It not only takes advantage of the flexibility and autonomy of online education but also retains the benefits of emotional communication between teachers and students in offline education. With the increase in practical exploration of blended teaching in universities, teaching evaluation is an important part of teaching, and blended teaching evaluation should also attract attention. The purpose of this paper is to study the mixed oral English teaching evaluation based on the mixed mode of SPOC and deep learning. On the basis of analyzing the teaching design principles of the mixed mode of SPOC and deep learning and the principles of constructing the teaching evaluation after half a semester of teaching investigations conducted by the two classes of English majors, the impact of the SPOC and deep learning mixed teaching mode on students’ spoken English was studied through the method of covariance analysis. The experimental results show that the mixed teaching mode of SPOC and deep learning has been able to fully stimulate students’ interest in oral English learning and improve students’ oral English ability, critical thinking of students, ability to solve problems, group cooperation, and effective communication. Self-directed learning and self-reflection have all had a positive impact.

scholarly journals Project-based Learning: Connotation, Characteristics and Misunderstandings

2021 ◽  
Vol 3 (2) ◽  
pp. 22
Author(s):  
Peigeng Guo
Keyword(s):  
Deep Learning ◽  
Real World ◽  
Teaching Quality ◽  
Project Based Learning ◽  
Learning Problems ◽  
Teaching Process ◽  
Teaching Mode ◽  
Innovation Ability ◽  
Reading Teaching ◽  
Actual Teaching

As a kind of teaching mode, project-based learning starts from the driving problems in the real world, aiming to solve learning problems, improve students' innovation ability and practical ability, as well as promote students' deep learning. It makes a vital difference in solving the current difficulties in reading teaching, which is characterized by process, authenticity and development. Due to the reading teaching is still in exploration stage from the perspective of project-based learning, there are inevitable problems in the actual teaching process, including improper time arrangement and lack of planning. Besides, learning is a mere formality, lacking of effectiveness. So teachers need to be more careful to improve the teaching quality and efficiency of project-based learning.

scholarly journals Self-assessment of Teacher Competencies On The Use of Information and Communication Technologies in the Teaching Process

2021 ◽  
Vol 6 (3(16)) ◽  
pp. 505-520
Author(s):  
Selma Porobić ◽  
Senada Mujić ◽  
Edina Malkić ◽  
Maida Dedić ◽  
Ksenija Mujčević ◽  
...  
Keyword(s):  
Information And Communication Technologies ◽  
Communication Technology ◽  
Information Search ◽  
Online Teaching ◽  
Subjective Experience ◽  
Communication Technologies ◽  
Total Sample ◽  
Internet Survey ◽  
Teaching Process ◽  
Information And Communication

The COVID-19 pandemic, or better known as the coronavirus pandemic, brought many challenges in education, and one of them was the transition to online teaching, that is. use of information and communication technologies in teaching. Information technology is a term that describes parts (hardware) and programs (software) that allow access to download, organize, manipulate and present information electronically, and communication technology (CT) is a term that describes telecommunications equipment that can send, receive information, search and access them. This research aimed to examine the subjective experience of teachers about personal competencies in the use of information and communication technology in teaching. The population of this research consists of primary school teachers in the area of Tuzla Canton, and the total sample consists of 138 respondents. An anonymous internet survey was used, which is distributed with the help of social networks “Facebook” and a Facebook group called “Prosvjeta TK”, which brings together educators from the Tuzla Canton area. In this paper, we assume that teachers assess their information and communication competencies as positive and they consider themselves competent in their use in the teaching process. It also explores aspects of teachers’ digital competencies as essential competencies for 21st-century education. The paper will provide insight into the personal perception of teachers regarding ICT competence, which is included in the fund of previous knowledge and theoretical knowledge. The results of this research could help understand and analyze further practices, decide on further steps to build teachers’ ICT competencies in and for the future of the school.

scholarly journals EDUCATION MANAGEMENT AND INFORMATION AND COMMUNICATION TECHNOLOGIES

2021 ◽  
Author(s):  
Snežana Kirin ◽  
◽  
Nena A. Vasojević ◽  
Ivana Vučetić ◽  
◽  
...  
Keyword(s):  
Information And Communication Technologies ◽  
Education System ◽  
Primary Schools ◽  
Online Teaching ◽  
Communication Technologies ◽  
Teaching Staff ◽  
Teaching Process ◽  
Technology Advancement ◽  
Information And Communication

The education system is facing the permanent challenge to adapt to the constantly changing states in science, technology, and economy, and it plays an important role in the overall society development and socio-economic progress. In order to establish a high-quality, efficient education system, it is necessary to develop the teaching staff competences in accordance with the innovations in the education field. The quality of the teaching process largely depends on the extent to which modern teaching methods are applied, which are, in the contemporary context, based on the use of the information and communication technologies in the teaching process (ICT). Following the technology advancement and the information channels transformation, the role of the teacher has changed, and in this new context the teacher is assigned with a new role of the “teaching manager”, or the leader of the teaching process. This paper shows comparative analyses of the relations between the teaching stuff ICT training and the organisation of the teaching process, when observed in traditional and online teaching settings. The research was conducted in Serbia in January and February of 2021, during the Covid-19 pandemic, and included the sample of teachers who work in primary schools (N=609).

The Application of Data Mining Technology in the Teaching Evaluation in Colleges and Universities

2017 ◽  
Vol 14 (1) ◽  
pp. 7-12 ◽  
Author(s):  
Xiaoqi Liu
Keyword(s):  
Data Mining ◽  
Decision Tree ◽  
Evaluation System ◽  
Information Gain ◽  
Original Data ◽  
Teaching Evaluation ◽  
Personal Factors ◽  
Mining Technology ◽  
Id3 Algorithm ◽  
College Work

As the teaching management informationization level is higher and higher, Network based teaching evaluation system has been widely used, and a lot of evaluation of the original data has been accumulated. This research, taking recent five years teaching evaluation data of the college work for as basis, analyzes teachers’ personal factors and teaching operation factors respectively with the data mining technology of decision tree ID3 algorithm. By calculating the factors of information entropy and information gain value, the corresponding decision tree is gained. The teaching evaluation results are made use of really rather than become a mere formality, and thus provide powerful basis for the effectiveness and scientificalness of teaching evaluation.

Smart teaching mode based on particle swarm image recognition and human-computer interaction deep learning

2020 ◽  
Vol 39 (4) ◽  
pp. 5699-5711
Author(s):  
Shirong Long ◽  
Xuekong Zhao
Keyword(s):  
Feature Extraction ◽  
Particle Swarm Optimization ◽  
Deep Learning ◽  
Real Time ◽  
Image Recognition ◽  
Particle Swarm ◽  
Learning Technology ◽  
Search Performance ◽  
Swarm Optimization ◽  
Teaching Mode

The smart teaching mode overcomes the shortcomings of traditional teaching online and offline, but there are certain deficiencies in the real-time feature extraction of teachers and students. In view of this, this study uses the particle swarm image recognition and deep learning technology to process the intelligent classroom video teaching image and extracts the classroom task features in real time and sends them to the teacher. In order to overcome the shortcomings of the premature convergence of the standard particle swarm optimization algorithm, an improved strategy for multiple particle swarm optimization algorithms is proposed. In order to improve the premature problem in the search performance algorithm of PSO algorithm, this paper combines the algorithm with the useful attributes of other algorithms to improve the particle diversity in the algorithm, enhance the global search ability of the particle, and achieve effective feature extraction. The research indicates that the method proposed in this paper has certain practical effects and can provide theoretical reference for subsequent related research.

Utilizing Twitter Data Analysis and Deep Learning to Identify Drug Use (Preprint)

2019 ◽  
Author(s):  
Joseph Tassone ◽  
Peizhi Yan ◽  
Mackenzie Simpson ◽  
Chetan Mendhe ◽  
Vijay Mago ◽  
...  
Keyword(s):  
Social Media ◽  
Logistic Regression ◽  
Deep Learning ◽  
Decision Tree ◽  
Semantic Meaning ◽  
Predictive Capability ◽  
Logistic Regression Models ◽  
Twitter Data ◽  
Data Points ◽  
Positive Classification

BACKGROUND The collection and examination of social media has become a useful mechanism for studying the mental activity and behavior tendencies of users. OBJECTIVE Through the analysis of a collected set of Twitter data, a model will be developed for predicting positively referenced, drug-related tweets. From this, trends and correlations can be determined. METHODS Twitter social media tweets and attribute data were collected and processed using topic pertaining keywords, such as drug slang and use-conditions (methods of drug consumption). Potential candidates were preprocessed resulting in a dataset 3,696,150 rows. The predictive classification power of multiple methods was compared including regression, decision trees, and CNN-based classifiers. For the latter, a deep learning approach was implemented to screen and analyze the semantic meaning of the tweets. RESULTS The logistic regression and decision tree models utilized 12,142 data points for training and 1041 data points for testing. The results calculated from the logistic regression models respectively displayed an accuracy of 54.56% and 57.44%, and an AUC of 0.58. While an improvement, the decision tree concluded with an accuracy of 63.40% and an AUC of 0.68. All these values implied a low predictive capability with little to no discrimination. Conversely, the CNN-based classifiers presented a heavy improvement, between the two models tested. The first was trained with 2,661 manually labeled samples, while the other included synthetically generated tweets culminating in 12,142 samples. The accuracy scores were 76.35% and 82.31%, with an AUC of 0.90 and 0.91. Using association rule mining in conjunction with the CNN-based classifier showed a high likelihood for keywords such as “smoke”, “cocaine”, and “marijuana” triggering a drug-positive classification. CONCLUSIONS Predictive analysis without a CNN is limited and possibly fruitless. Attribute-based models presented little predictive capability and were not suitable for analyzing this type of data. The semantic meaning of the tweets needed to be utilized, giving the CNN-based classifier an advantage over other solutions. Additionally, commonly mentioned drugs had a level of correspondence with frequently used illicit substances, proving the practical usefulness of this system. Lastly, the synthetically generated set provided increased scores, improving the predictive capability. CLINICALTRIAL None

scholarly journals The Higher Education Sustainability before and during the COVID-19 Pandemic: A Spanish and Ecuadorian Case

2021 ◽  
Vol 13 (11) ◽  
pp. 6363
Author(s):  
Johanna Andrea Espinosa-Navarro ◽  
Manuel Vaquero-Abellán ◽  
Alberto-Jesús Perea-Moreno ◽  
Gerardo Pedrós-Pérez ◽  
Pilar Aparicio-Martínez ◽  
...  
Keyword(s):  
Higher Education ◽  
Information And Communication Technologies ◽  
Online Teaching ◽  
Communication Technologies ◽  
University Teachers ◽  
Qualitative Survey ◽  
Information And Communication ◽  
Older Teachers ◽  
Teachers Perspectives ◽  
The University

Information and communication technologies (ICTs) are key to create sustainable higher education institutions (HEIs). Most researchers focused on the students’ perspective, especially during the online teaching caused by COVID-19; however, university teachers are often forgotten, having their opinion missing. This study’s objective was to determine the factors that contribute to the inclusion of ICTs. The research based on a comparative study through an online qualitative survey focused on the inclusion and use of ICTs in two HEIs and two different moments (pre-and post-lockdowns). There were differences regarding country and working experience (p < 0.001), being linked to the ICTs use, evaluation of obstacles, and the role given to ICTs (p < 0.05). The COVID-19 caused modifications of the teachers’ perspectives, including an improvement of the opinion of older teachers regarding the essentialness of ICTs in the teaching process (p < 0.001) and worsening their perception about their ICTs skill (p < 0.05). Additionally, an initial model focused only on the university teachers and their use of ICTs has been proposed. In conclusion, the less experienced university teachers used more ICTs, identified more greatly the problematic factors, and considered more important the ICTs, with the perception of all teachers modified by COVID-19.

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