Update: Electrician's Cup B-question full nanny thesis finished tutorial, teaching you to complete high-quality finished products step by step
Question b this time is the questionnaire analysis question, which is one of the topics I am best at. Questionnaire analysis looks simple, but in fact it is not that simple. The test is whether we can describe the data clearly, and what is the meaning of the model? Not much, what is pursued is well-founded and clear logic.
You can look at my catalog and know that my solution to this question is very clear. I also did this question in February this year, which is the Huashu Cup b question in the scheduled document. The winning rate of the second prize is as high as 80% %, you can take a look at my previous works, which are not all kinds of water papers on the market, and even the catalog is not logical.
The complete original paper for Question B of the Electrician Cup has a total of 49 pages, and the yellow ones are diagram making instructions or other instructions.
The development of artificial intelligence has varying degrees of impact on all levels of society, and also affects the learning of college students. In order to understand the impact of artificial intelligence on college students' learning in different aspects, this paper establishes a corresponding mathematical model.
For question 1, it is first necessary to preprocess the data in Annex 2. Some papers on the market do not conduct reliability analysis directly. The problem is dealt with, or directly. The background information of the respondents is included in the reliability analysis. In fact, the reliability analysis is mainly used to analyze whether the respondents' views on the problem are normally distributed, that is to say, whether there are major conclusions. Here, I first processed the data in Appendix 2, and then removed the background information of the respondents. After removing the background information of the respondents, the calculated standardized Cronbach’s coefficient value was 0.8X, indicating that this questionnaire was once In order to better analyze the overall content of the questionnaire, the interviewees’ background information, network usage habits, learning troubles and learning software usage, as well as the views and expectations of artificial intelligence in educational applications are divided here. The framework analysis of these four modules is carried out, and the conclusion of the analysis is elaborated. Formal questionnaire analysis is all done in this way. What’s the point of analyzing the results of those correlations and difference analysis models? The core of the questionnaire analysis is to feed back the core opinions of the respondents in the questionnaire.
Aiming at problem 2, this paper is based on the principles of scientificity, reliability, operability, comprehensiveness and sustainability, and establishes an evaluation index system for the impact of initial AI on college students’ learning through literature research. After eight professionals who have been engaged in college education for many years Under the two rounds of consultation, the final indicators were screened and determined to form four types of first-level indicators and 16 second-level indicators of artificial intelligence’s impact on college students’ learning evaluation index system, and then combined with entropy weight method (matching questionnaire data) and hierarchical analysis The method (unable to match the questionnaire data) calculates the weight of the index, and then obtains the importance of the global index. I have read a lot of papers on index system modeling, and this is the normal way to do it. If the index is not screened, the analysis is of little significance. Some people may worry about the problems that will be caused by the expert survey method here. You can rest assured here, because I have used this method in several previous games, many. All of my clients have received positive feedback, showing that this approach works. Not to mention academically, it is basically in this form.
What I use here is fuzzy comprehensive evaluation. You can also use other comprehensive evaluation algorithms, such as topsis method, rsr rank sum ratio method. Through fuzzy comprehensive evaluation, I got an overall comprehensive score of more than 3 points, which belongs to the general positive
final , summarized the above analysis content, wrote an analysis report on the impact of artificial intelligence on college students' learning, and summarized the advantages and disadvantages of this article.
For question 1, we can conduct statistics and descriptive analysis on the data in appendix 2. Before analysis, we need to process the data in the questionnaire. The data here mainly needs to be processed or the questions in the multiple-choice questions are merged. We need to split the multiple-choice questions into multiple options in the form of one-hot encoding. After processing the data, we can draw histograms, histograms, pie charts and other visual charts of the data to better understand the distribution and characteristics of the data. In order to better and more comprehensively analyze the questionnaire data, we can. Divide the content of the questionnaire into several modules for systematic analysis, and the first four questions of a group of questionnaires can be divided into the analysis of the background information of the respondents and so on.
For the second question, we need to build an indicator system for the impact of artificial intelligence on college students' learning. First, we need to consider factors such as the scientific nature and operability of the indicators to ensure that the indicators can comprehensively and accurately assess the degree of impact. Some screening may be required to build the indicator system The operation can be determined through the expert survey method. After the index construction is completed, the weight of the index system needs to be analyzed. If it can correspond to the questionnaire data, the entropy weight method can be used to achieve objective weight formulation. If it cannot correspond to the questionnaire data, you can Use subjective evaluation methods for weighting, such as the analytic hierarchy process, by calculating the weight of the primary and secondary index systems, to achieve the effect of calculating the global weight.
For the third question, we can establish an evaluation model based on the global weight and index system of the third question to evaluate the impact of artificial intelligence on college students' learning. Here, fuzzy comprehensive evaluation method, topsis method and other methods can be used, and attention should be paid Yes, the data given in the question is not enough for evaluation. In the case of artificial intelligence's impact on college students' learning, some subjective data can be included to determine it.
Finally, we summarize the first three questions and give an impact analysis report to analyze the influence, positive or negative aspects, and look forward to the future development of artificial intelligence on college students' learning.
If you want to see a more detailed explanation of the finished product, you can view the detailed explanation video, and the video introduction can be used to obtain the finished product.
Question B: Evaluation of the impact of artificial intelligence on the learning of college students
Artificial intelligence, referred to as AI, was first proposed by scientists such as McCarthy and Minsky in 1956 when they held a meeting at Dartmouth College in the United States. In 2016, artificial intelligence AlphaGo defeated South Korean Go master Lee Sedol 4:1. Later, Boston Dynamics' humanoid robot Atlas also demonstrated superb perception and control capabilities. In 2022, the artificial intelligence painting "Space Opera House" won the first prize in the art competition of the Colorado State Fair. On March 16, 2023, Baidu launched a new artificial intelligence product "Wen Xin Yi Yan". In order to seize the major strategic opportunities for the development of artificial intelligence, the State Council issued the "New Generation Artificial Intelligence Development Plan" in 2017, pointing out that a technologically powerful country should give full play to the power of artificial intelligence technology, deploy and build a first-mover advantage in the development of artificial intelligence in my country, and accelerate the construction of innovative National and world technological powerhouse. The Ministry of Education released the "Education Informatization 2.0 Action Plan" in 2018, proposing an action guideline for realizing "Intelligence Leading Education Informatization", emphasizing the development of intelligent education. The development of artificial intelligence has varying degrees of impact on all levels of society, and also affects the learning of college students. In order to understand the impact of artificial intelligence on college students' learning in different aspects, we designed a questionnaire, see Appendix 1 for details, and Appendix 2 for the survey feedback results.
According to a certain aspect you are interested in, combined with the data given in Annex 1 and Annex 2, please establish a corresponding mathematical model, analyze the impact of artificial intelligence on college students' learning, and solve the following problems:
Question 1: Analyze and numerically process the data given in Annex 2, and give a processing method;
This is mainly to do data descriptive analysis and display data. This question is the most open. It can be done very simple or very complicated. The simple method is to do frequency analysis for single-choice questions and multiple-response frequency analysis for multiple-choice questions. , the complex method can be analyzed first according to the reliability. If the reliability does not meet the requirements, then it can be considered that the survey customer group cannot reflect the whole, so it needs to be changed to multiple customer group portraits for analysis, and the questionnaire can be analyzed through cluster analysis The data is divided into multiple customer groups, and the optimal number of clusters is selected through the elbow rule, and then multi-level cross-analysis is carried out for different customers.
Question 2: Select evaluation indicators based on your data analysis results, discuss their rationality in terms of priority, scientificity, and operability, and build an evaluation index system;
The second question contains a few points: 1. Construct the index system; 2. Determine the weight of the index; For the first small question, we need to list as many indicators as possible. These indicators must be able to evaluate the impact of artificial intelligence on college students’ learning These indicators are used as preliminary indicators, and then the indicators are screened according to priority, scientificity, operability, etc., until finally a stable indicator is selected. For the second small question, we need to combine the subjective In an objective way, comprehensively determine the weight of indicators, and determine the weight of each indicator
Question 3: Establish a mathematical model, evaluate the impact of artificial intelligence on college students' learning, and give clear and convincing conclusions;
The third question requires additional data collection, because the data in the questionnaire does not include attitude questions to evaluate the impact of various indicators on college students’ learning attitudes, then we can use the Delphi method to supplement the collection of attitude data to analyze and evaluate the impact of artificial intelligence on college students impact on learning.
Question 4: Based on the data of the questionnaire, combined with your understanding, cognition and judgment of artificial intelligence, and the prospect of future artificial intelligence development, write an analysis report on the impact of artificial intelligence on college students' learning, which can include but not limited to positive or negative effects.
The fourth question is the summary and requirements of the first three questions, and a separate chapter can be pulled out to summarize the above.